Alteration of diffusion-tensor MRI measures in brain regions involved in early stages of Parkinson's disease.

PubMed

Chen, Nan-Kuei; Chou, Ying-Hui; Sundman, Mark; Hickey, Patrick; Kasoff, Willard S; Bernstein, Adam; Trouard, Theodore P; Lin, Tanya; Rapcsak, Steven Z; Sherman, Scott J; Weingarten, Carol

2018-06-07

Many non-motor symptoms (e.g., hyposmia) appear years before the cardinal motor features of Parkinson's disease (PD). It is thus desirable to be able to use noninvasive brain imaging methods, such as magnetic resonance imaging (MRI), to detect brain abnormalities in early PD stages. Among the MRI modalities, diffusion tensor imaging (DTI) is suitable for detecting changes of brain tissue structure due to neurological diseases. The main purpose of this study was to investigate whether DTI signals measured from brain regions involved in early stages of PD differ from those of healthy controls. To answer this question, we analyzed whole-brain DTI data of 30 early-stage PD patients and 30 controls using improved ROI based analysis methods. Results showed that 1) the fractional anisotropy (FA) values in the olfactory tract (connected with the olfactory bulb: one of the first structures affected by PD) are lower in PD patients than healthy controls; 2) FA values are higher in PD patients than healthy controls in the following brain regions: corticospinal tract, cingulum (near hippocampus), and superior longitudinal fasciculus (temporal part). Experimental results suggest that the tissue property, measured by FA, in olfactory regions is structurally modulated by PD with a mechanism that is different from other brain regions.

Investigation of brain structure in the 1-month infant.

PubMed

Dean, Douglas C; Planalp, E M; Wooten, W; Schmidt, C K; Kecskemeti, S R; Frye, C; Schmidt, N L; Goldsmith, H H; Alexander, A L; Davidson, R J

2018-05-01

The developing brain undergoes systematic changes that occur at successive stages of maturation. Deviations from the typical neurodevelopmental trajectory are hypothesized to underlie many early childhood disorders; thus, characterizing the earliest patterns of normative brain development is essential. Recent neuroimaging research provides insight into brain structure during late childhood and adolescence; however, few studies have examined the infant brain, particularly in infants under 3 months of age. Using high-resolution structural MRI, we measured subcortical gray and white matter brain volumes in a cohort (N = 143) of 1-month infants and examined characteristics of these volumetric measures throughout this early period of neurodevelopment. We show that brain volumes undergo age-related changes during the first month of life, with the corresponding patterns of regional asymmetry and sexual dimorphism. Specifically, males have larger total brain volume and volumes differ by sex in regionally specific brain regions, after correcting for total brain volume. Consistent with findings from studies of later childhood and adolescence, subcortical regions appear more rightward asymmetric. Neither sex differences nor regional asymmetries changed with gestation-corrected age. Our results complement a growing body of work investigating the earliest neurobiological changes associated with development and suggest that asymmetry and sexual dimorphism are present at birth.

Brain structure, executive function and appetitive traits in adolescent obesity.

PubMed

de Groot, C J; van den Akker, E L T; Rings, E H H M; Delemarre-van de Waal, H A; van der Grond, J

2017-08-01

Children with obesity show differences in brain structure, executive function and appetitive traits when compared with lean peers. Little is known on the relationship between brain structure and these traits. To investigate the relationship between differences in brain structure and executive function and appetitive traits, in obese and lean adolescents. MRI was used to measure cortical thickness and subcortical volumes. Executive function was measured by a Stop Signal-and a Choice Delay Task. Appetitive traits were measured using the Child Eating Behaviour Questionnaire. Adolescents with obesity had greater volumes of the pallidum; 1.78 mL (SE 0.03, p=0.014), when compared with controls; 1.65 mL (SE 0.02). In the group with obesity, greater pallidum volume was positively associated with the ability to delay reward in the Choice Delay Task (p=0.012). The association between pallidum volumes and Choice Delay Task in obese adolescents supports the hypothesis that the pallidum plays an important role in executive dysfunction in obese children. © 2016 World Obesity Federation.

Associations between education and brain structure at age 73 years, adjusted for age 11 IQ

PubMed Central

Dickie, David Alexander; Ritchie, Stuart J.; Karama, Sherif; Pattie, Alison; Royle, Natalie A.; Corley, Janie; Aribisala, Benjamin S.; Valdés Hernández, Maria; Muñoz Maniega, Susana; Starr, John M.; Bastin, Mark E.; Evans, Alan C.; Wardlaw, Joanna M.; Deary, Ian J.

2016-01-01

Objective: To investigate how associations between education and brain structure in older age were affected by adjusting for IQ measured at age 11. Methods: We analyzed years of full-time education and measures from an MRI brain scan at age 73 in 617 community-dwelling adults born in 1936. In addition to average and vertex-wise cortical thickness, we measured total brain atrophy and white matter tract fractional anisotropy. Associations between brain structure and education were tested, covarying for sex and vascular health; a second model also covaried for age 11 IQ. Results: The significant relationship between education and average cortical thickness (β = 0.124, p = 0.004) was reduced by 23% when age 11 IQ was included (β = 0.096, p = 0.041). Initial associations between longer education and greater vertex-wise cortical thickness were significant in bilateral temporal, medial-frontal, parietal, sensory, and motor cortices. Accounting for childhood intelligence reduced the number of significant vertices by >90%; only bilateral anterior temporal associations remained. Neither education nor age 11 IQ was significantly associated with total brain atrophy or tract-averaged fractional anisotropy. Conclusions: The association between years of education and brain structure ≈60 years later was restricted to cortical thickness in this sample; however, the previously reported associations between longer education and a thicker cortex are likely to be overestimates in terms of both magnitude and distribution. This finding has implications for understanding, and possibly ameliorating, life-course brain health. PMID:27664981

Associations between education and brain structure at age 73 years, adjusted for age 11 IQ.

PubMed

Cox, Simon R; Dickie, David Alexander; Ritchie, Stuart J; Karama, Sherif; Pattie, Alison; Royle, Natalie A; Corley, Janie; Aribisala, Benjamin S; Valdés Hernández, Maria; Muñoz Maniega, Susana; Starr, John M; Bastin, Mark E; Evans, Alan C; Wardlaw, Joanna M; Deary, Ian J

2016-10-25

To investigate how associations between education and brain structure in older age were affected by adjusting for IQ measured at age 11. We analyzed years of full-time education and measures from an MRI brain scan at age 73 in 617 community-dwelling adults born in 1936. In addition to average and vertex-wise cortical thickness, we measured total brain atrophy and white matter tract fractional anisotropy. Associations between brain structure and education were tested, covarying for sex and vascular health; a second model also covaried for age 11 IQ. The significant relationship between education and average cortical thickness (β = 0.124, p = 0.004) was reduced by 23% when age 11 IQ was included (β = 0.096, p = 0.041). Initial associations between longer education and greater vertex-wise cortical thickness were significant in bilateral temporal, medial-frontal, parietal, sensory, and motor cortices. Accounting for childhood intelligence reduced the number of significant vertices by >90%; only bilateral anterior temporal associations remained. Neither education nor age 11 IQ was significantly associated with total brain atrophy or tract-averaged fractional anisotropy. The association between years of education and brain structure ≈60 years later was restricted to cortical thickness in this sample; however, the previously reported associations between longer education and a thicker cortex are likely to be overestimates in terms of both magnitude and distribution. This finding has implications for understanding, and possibly ameliorating, life-course brain health. © 2016 American Academy of Neurology.

Analyzing and Assessing Brain Structure with Graph Connectivity Measures

DTIC Science & Technology

2014-05-09

structural brain networks, i.e. determining which regions of the brain are physically connected. Meanwhile, functional MRI ( fMRI ) yields an image of...produced by fMRI is a map of which parts are of the brain are active and which are not at a given time. In creating functional networks, regions of...the brain which often activitate together, i.e., often show up on fMRI as deoxygenated regions together, are considered connected. DTI allows the

Reading skill and structural brain development

PubMed Central

Houston, S.M.; Lebel, C.; Katzir, T.; Manis, F.R.; Kan, E.; Rodriguez, G.R.; Sowell, E.R.

2014-01-01

Reading is a learned skill that is likely influenced by both brain maturation and experience. Functional imaging studies have identified brain regions important for skilled reading, but the structural brain changes that co-occur with reading acquisition remain largely unknown. We investigated maturational volume changes in brain reading regions and their association with performance on reading measures. Sixteen typically developing children (5-15 years old, 8 male, mean age of sample=10.06 ±3.29) received two magnetic resonance imaging (MRI) scans, (mean inter-scan interval =2.19 years), and were administered a battery of cognitive measures. Volume changes between time points in five bilateral cortical regions of interest were measured, and assessed for relationships to three measures of reading. Better baseline performances on measures of word reading, fluency and rapid naming, independent of age and total cortical gray matter volume change, were associated with volume decrease in the left inferior parietal cortex. Better baseline performance on a rapid naming measure was associated with volume decrease in the left inferior frontal region. These results suggest that children who are better readers, and who perhaps read more than less skilled readers, exhibit different development trajectories in brain reading regions. Understanding relationships between reading performance, reading experience and brain maturation trajectories may help with the development and evaluation of targeted interventions. PMID:24407200

Cortical brain connectivity evaluated by graph theory in dementia: a correlation study between functional and structural data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Curcio, Giuseppe; Altavilla, Riccardo; Scrascia, Federica; Giambattistelli, Federica; Quattrocchi, Carlo Cosimo; Bramanti, Placido; Vernieri, Fabrizio; Rossini, Paolo Maria

2015-01-01

A relatively new approach to brain function in neuroscience is the "functional connectivity", namely the synchrony in time of activity in anatomically-distinct but functionally-collaborating brain regions. On the other hand, diffusion tensor imaging (DTI) is a recently developed magnetic resonance imaging (MRI)-based technique with the capability to detect brain structural connection with fractional anisotropy (FA) identification. FA decrease has been observed in the corpus callosum of subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI, an AD prodromal stage). Corpus callosum splenium DTI abnormalities are thought to be associated with functional disconnections among cortical areas. This study aimed to investigate possible correlations between structural damage, measured by MRI-DTI, and functional abnormalities of brain integration, measured by characteristic path length detected in resting state EEG source activity (40 participants: 9 healthy controls, 10 MCI, 10 mild AD, 11 moderate AD). For each subject, undirected and weighted brain network was built to evaluate graph core measures. eLORETA lagged linear connectivity values were used as weight of the edges of the network. Results showed that callosal FA reduction is associated to a loss of brain interhemispheric functional connectivity characterized by increased delta and decreased alpha path length. These findings suggest that "global" (average network shortest path length representing an index of how efficient is the information transfer between two parts of the network) functional measure can reflect the reduction of fiber connecting the two hemispheres as revealed by DTI analysis and also anticipate in time this structural loss.

Brain structural changes following adaptive cognitive training assessed by Tensor-Based Morphometry (TBM)

PubMed Central

Colom, Roberto; Hua, Xue; Martínez, Kenia; Burgaleta, Miguel; Román, Francisco J.; Gunter, Jeffrey L.; Carmona, Susanna; Jaeggi, Susanne M.; Thompson, Paul M.

2016-01-01

Tensor-Based Morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training. PMID:27477628

The structure of creative cognition in the human brain

PubMed Central

Jung, Rex E.; Mead, Brittany S.; Carrasco, Jessica; Flores, Ranee A.

2013-01-01

Creativity is a vast construct, seemingly intractable to scientific inquiry—perhaps due to the vague concepts applied to the field of research. One attempt to limit the purview of creative cognition formulates the construct in terms of evolutionary constraints, namely that of blind variation and selective retention (BVSR). Behaviorally, one can limit the “blind variation” component to idea generation tests as manifested by measures of divergent thinking. The “selective retention” component can be represented by measures of convergent thinking, as represented by measures of remote associates. We summarize results from measures of creative cognition, correlated with structural neuroimaging measures including structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS). We also review lesion studies, considered to be the “gold standard” of brain-behavioral studies. What emerges is a picture consistent with theories of disinhibitory brain features subserving creative cognition, as described previously (Martindale, 1981). We provide a perspective, involving aspects of the default mode network (DMN), which might provide a “first approximation” regarding how creative cognition might map on to the human brain. PMID:23847503

A Factor Analysis of Functional Independence and Functional Assessment Measure Scores Among Focal and Diffuse Brain Injury Patients: The Importance of Bifactor Models.

PubMed

Gunn, Sarah; Burgess, Gerald H; Maltby, John

2018-04-30

To explore the factor structure of the UK Functional Independence Measure and Functional Assessment Measure (FIM+FAM) among focal and diffuse acquired brain injury patients. Criterion standard. A National Health Service acute acquired brain injury inpatient rehabilitation hospital. Referred sample of N=447 adults admitted for inpatient treatment following an acquired brain injury significant enough to justify intensive inpatient neurorehabilitation INTERVENTION: Not applicable. Functional Independence Measure and Functional Assessment Measure. Exploratory factor analysis suggested a 2-factor structure to FIM+FAM scores, among both focal-proximate and diffuse-proximate acquired brain injury aetiologies. Confirmatory factor analysis suggested a 3-factor bifactor structure presented the best fit of the FIM+FAM score data across both aetiologies. However, across both analyses, a convergence was found towards a general factor, demonstrated by high correlations between factors in the exploratory factor analysis, and by a general factor explaining the majority of the variance in scores on confirmatory factor analysis. Our findings suggested that although factors describing specific functional domains can be derived from FIM+FAM item scores, there is a convergence towards a single factor describing overall functioning. This single factor informs the specific group factors (eg, motor, psychosocial, and communication function) after brain injury. Further research into the comparative value of the general and group factors as evaluative/prognostic measures is indicated. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Fractal dimension brain morphometry: a novel approach to quantify white matter in traumatic brain injury.

PubMed

Rajagopalan, Venkateswaran; Das, Abhijit; Zhang, Luduan; Hillary, Frank; Wylie, Glenn R; Yue, Guang H

2018-06-16

Traumatic brain injury (TBI) is the main cause of disability in people younger than 35 in the United States. The mechanisms of TBI are complex resulting in both focal and diffuse brain damage. Fractal dimension (FD) is a measure that can characterize morphometric complexity and variability of brain structure especially white matter (WM) structure and may provide novel insights into the injuries evident following TBI. FD-based brain morphometry may provide information on WM structural changes after TBI that is more sensitive to subtle structural changes post injury compared to conventional MRI measurements. Anatomical and diffusion tensor imaging (DTI) data were obtained using a 3 T MRI scanner in subjects with moderate to severe TBI and in healthy controls (HC). Whole brain WM volume, grey matter volume, cortical thickness, cortical area, FD and DTI metrics were evaluated globally and for the left and right hemispheres separately. A neuropsychological test battery sensitive to cognitive impairment associated with traumatic brain injury was performed. TBI group showed lower structural complexity (FD) bilaterally (p < 0.05). No significant difference in either grey matter volume, cortical thickness or cortical area was observed in any of the brain regions between TBI and healthy controls. No significant differences in whole brain WM volume or DTI metrics between TBI and HC groups were observed. Behavioral data analysis revealed that WM FD accounted for a significant amount of variance in executive functioning and processing speed beyond demographic and DTI variables. FD therefore, may serve as a sensitive marker of injury and may play a role in outcome prediction in TBI.

Brain structure and executive functions in children with cerebral palsy: a systematic review.

PubMed

Weierink, Lonneke; Vermeulen, R Jeroen; Boyd, Roslyn N

2013-05-01

This systematic review aimed to establish the current knowledge about brain structure and executive function (EF) in children with cerebral palsy (CP). Five databases were searched (up till July 2012). Six articles met the inclusion criteria, all included structural brain imaging though no functional brain imaging. Study quality was assessed using the STROBE checklist. All articles scored between 58.7% and 70.5% for quality (100% is the maximum score). The included studies all reported poorer performance on EF tasks for children with CP compared to children without CP. For the selected EF measures non-significant effect sizes were found for the CP group compared to a semi-control group (children without cognitive deficits but not included in a control group). This could be due to the small sample sizes, group heterogeneity and lack of comparison of the CP group to typically developing children. The included studies did not consider specific brain areas associated with EF performance. To conclude, there is a paucity of brain imaging studies focused on EF in children with CP, especially of studies that include functional brain imaging. Outcomes of the present studies are difficult to compare as each study included different EF measures and cortical abnormality measures. Copyright © 2013 Elsevier Ltd. All rights reserved.

Only Time Will Tell: Cross-Sectional Studies Offer No Solution to the Age-Brain-Cognition Triangle--Comment on Salthouse (2011)

ERIC Educational Resources Information Center

Raz, Naftali; Lindenberger, Ulman

2011-01-01

Salthouse (2011) critically reviewed cross-sectional and longitudinal relations among adult age, brain structure, and cognition (ABC) and identified problems in interpretation of the extant literature. His review, however, missed several important points. First, there is enough disparity among the measures of brain structure and cognitive…

Reprint of "Does Functional Neuroimaging Solve the Questions of Neurolinguistics?" [Brain and Language 98 (2006) 276-290

ERIC Educational Resources Information Center

Van Lancker Sidtis, Diana

2007-01-01

Neurolinguistic research has been engaged in evaluating models of language using measures from brain structure and function, and/or in investigating brain structure and function with respect to language representation using proposed models of language. While the aphasiological strategy, which classifies aphasias based on performance modality and a…

Brain Structure-function Couplings (FY11)

DTIC Science & Technology

2012-01-01

influence time-evolving models of global brain function and dynamic changes in cognitive performance. Both structural and functional connections change on...Artifact Resistant Measure to Detect Cognitive EEG Activity During Locomotion. Journal of NeuroEngineering and Rehabilitation, submitted. 10...Specifically, identifying the communication between brain regions that occurs during tasks may provide information regarding the cognitive processes involved in

In Vivo Characterization of Traumatic Brain Injury Neuropathology with Structural and Functional Neuroimaging

PubMed Central

LEVINE, BRIAN; FUJIWARA, ESTHER; O’CONNOR, CHARLENE; RICHARD, NADINE; KOVACEVIC, NATASA; MANDIC, MARINA; RESTAGNO, ADRIANA; EASDON, CRAIG; ROBERTSON, IAN H.; GRAHAM, SIMON J.; CHEUNG, GORDON; GAO, FUQIANG; SCHWARTZ, MICHAEL L.; BLACK, SANDRA E.

2007-01-01

Quantitative neuroimaging is increasingly used to study the effects of traumatic brain injury (TBI) on brain structure and function. This paper reviews quantitative structural and functional neuroimaging studies of patients with TBI, with an emphasis on the effects of diffuse axonal injury (DAI), the primary neuropathology in TBI. Quantitative structural neuroimaging has evolved from simple planometric measurements through targeted region-of-interest analyses to whole-brain analysis of quantified tissue compartments. Recent studies converge to indicate widespread volume loss of both gray and white matter in patients with moderate-to-severe TBI. These changes can be documented even when patients with focal lesions are excluded. Broadly speaking, performance on standard neuropsychological tests of speeded information processing are related to these changes, but demonstration of specific brain-behavior relationships requires more refined experimental behavioral measures. The functional consequences of these structural changes can be imaged with activation functional neuroimaging. Although this line of research is at an early stage, results indicate that TBI causes a more widely dispersed activation in frontal and posterior cortices. Further progress in analysis of the consequences of TBI on neural structure and function will require control of variability in neuropathology and behavior. PMID:17020478

Brain Regions Associated With Internalizing and Externalizing Psychiatric Symptoms in Patients With Penetrating Traumatic Brain Injury.

PubMed

Huey, Edward D; Lee, Seonjoo; Lieberman, Jeffrey A; Devanand, D P; Brickman, Adam M; Raymont, Vanessa; Krueger, Frank; Grafman, Jordan

2016-01-01

A factor structure underlying DSM-IV diagnoses has been previously reported in neurologically intact patients. The authors determined the brain regions associated with factors underlying DSM-IV diagnoses and compared the ability of DSM-IV diagnoses, factor scores, and self-report measures to account for the neuroanatomical findings in patients with penetrating brain injuries. This prospective cohort study included 254 Vietnam War veterans: 199 with penetrating brain injuries and 55 matched control participants. Measures include DSM-IV diagnoses (from a Structured Clinical Interview for DSM), self-report measures of depression and anxiety, and CT scans. Factors underlying DSM-IV diagnoses were determined using an exploratory factor analysis and correlated with percent of brain regions affected. The ability of the factor scores, DSM-IV diagnoses, and the self-report psychiatric measures to account for the anatomical variance was compared with multiple regressions. Internalizing and externalizing factors were identified in these brain-injured patients. Damage to the left amygdala and bilateral basal ganglia was associated with lower internalizing factor scores, and damage to the left medial orbitofrontal cortex (OFC) with higher, and bilateral hippocampi with lower, externalizing factor scores. Factor scores best predicted left amygdala and bilateral hippocampal involvement, whereas DSM-IV diagnoses best predicted bilateral basal ganglia and left OFC involvement. Damage to the limbic areas involved in the processing of emotional and reward information, including structures involved in the National Institute of Mental Health's Research Domain Criteria Negative Valence Domain, influences the development of internalizing and externalizing psychiatric symptoms. Self-report measures underperformed DSM-IV and factor scores in predicting neuroanatomical findings.

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

PubMed Central

Tadić, Bosiljka; Andjelković, Miroslav; Boshkoska, Biljana Mileva; Levnajić, Zoran

2016-01-01

Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listener’s concentration to the story, confirmed by self-rating, and closeness to the speaker’s brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listener’s group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listener’s rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures (besides standard graph measures) for characterising functional brain networks under different stimuli. PMID:27880802

Brain structural changes following adaptive cognitive training assessed by Tensor-Based Morphometry (TBM).

PubMed

Colom, Roberto; Hua, Xue; Martínez, Kenia; Burgaleta, Miguel; Román, Francisco J; Gunter, Jeffrey L; Carmona, Susanna; Jaeggi, Susanne M; Thompson, Paul M

2016-10-01

Tensor-Based Morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training. Copyright © 2016 Elsevier Ltd. All rights reserved.

Synaptogenesis and heritable aspects of executive attention.

PubMed

Fossella, John A; Sommer, Tobias; Fan, Jin; Pfaff, Don; Posner, Michael I

2003-01-01

In humans, changes in brain structure and function can be measured non-invasively during postnatal development. In animals, advanced optical imaging measures can track the formation of synapses during learning and behavior. With the recent progress in these technologies, it is appropriate to begin to assess how the physiological processes of synapse, circuit, and neural network formation relate to the process of cognitive development. Of particular interest is the development of executive function, which develops more gradually in humans. One approach that has shown promise is molecular genetics. The completion of the human genome project and the human genome diversity project make it straightforward to ask whether variation in a particular gene correlates with variation in behavior, brain structure, brain activity, or all of the above. Strategies that unify the wealth of biochemical knowledge pertaining to synapse formation with the functional measures of brain structure and activity may lead to new insights in developmental cognitive psychology. Copyright 2003 Wiley-Liss, Inc.

Are there differences in brain morphometry between twins and unrelated singletons? A pediatric MRI study.

PubMed

Ordaz, S J; Lenroot, R K; Wallace, G L; Clasen, L S; Blumenthal, J D; Schmitt, J E; Giedd, J N

2010-04-01

Twins provide a unique capacity to explore relative genetic and environmental contributions to brain development, but results are applicable to non-twin populations only to the extent that twin and singleton brains are alike. A reason to suspect differences is that as a group twins are more likely than singletons to experience adverse prenatal and perinatal events that may affect brain development. We sought to assess whether this increased risk leads to differences in child or adolescent brain anatomy in twins who do not experience behavioral or neurological sequelae during the perinatal period. Brain MRI scans of 185 healthy pediatric twins (mean age = 11.0, SD = 3.6) were compared to scans of 167 age- and sex-matched unrelated singletons on brain structures measured, which included gray and white matter lobar volumes, ventricular volume, and area of the corpus callosum. There were no significant differences between groups for any structure, despite sufficient power for low type II (i.e. false negative) error. The implications of these results are twofold: (1) within this age range and for these measures, it is appropriate to include healthy twins in studies of typical brain development, and (2) findings regarding heritability of brain structures obtained from twin studies can be generalized to non-twin populations.

Risk and protective factors for structural brain ageing in the eighth decade of life.

PubMed

Ritchie, Stuart J; Tucker-Drob, Elliot M; Cox, Simon R; Dickie, David Alexander; Del C Valdés Hernández, Maria; Corley, Janie; Royle, Natalie A; Redmond, Paul; Muñoz Maniega, Susana; Pattie, Alison; Aribisala, Benjamin S; Taylor, Adele M; Clarke, Toni-Kim; Gow, Alan J; Starr, John M; Bastin, Mark E; Wardlaw, Joanna M; Deary, Ian J

2017-11-01

Individuals differ markedly in brain structure, and in how this structure degenerates during ageing. In a large sample of human participants (baseline n = 731 at age 73 years; follow-up n = 488 at age 76 years), we estimated the magnitude of mean change and variability in changes in MRI measures of brain macrostructure (grey matter, white matter, and white matter hyperintensity volumes) and microstructure (fractional anisotropy and mean diffusivity from diffusion tensor MRI). All indices showed significant average change with age, with considerable heterogeneity in those changes. We then tested eleven socioeconomic, physical, health, cognitive, allostatic (inflammatory and metabolic), and genetic variables for their value in predicting these differences in changes. Many of these variables were significantly correlated with baseline brain structure, but few could account for significant portions of the heterogeneity in subsequent brain change. Physical fitness was an exception, being correlated both with brain level and changes. The results suggest that only a subset of correlates of brain structure are also predictive of differences in brain ageing.

On the role of general system theory for functional neuroimaging.

PubMed

Stephan, Klaas Enno

2004-12-01

One of the most important goals of neuroscience is to establish precise structure-function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure-function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure-function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples.

Problematic internet use is associated with structural alterations in the brain reward system in females.

PubMed

Altbäcker, Anna; Plózer, Enikő; Darnai, Gergely; Perlaki, Gábor; Horváth, Réka; Orsi, Gergely; Nagy, Szilvia Anett; Bogner, Péter; Schwarcz, Attila; Kovács, Norbert; Komoly, Sámuel; Clemens, Zsófia; Janszky, József

2016-12-01

Neuroimaging findings suggest that excessive Internet use shows functional and structural brain changes similar to substance addiction. Even though it is still under debate whether there are gender differences in case of problematic use, previous studies by-passed this question by focusing on males only or by using gender matched approach without controlling for potential gender effects. We designed our study to find out whether there are structural correlates in the brain reward system of problematic Internet use in habitual Internet user females. T1-weighted Magnetic Resonance (MR) images were collected in 82 healthy habitual Internet user females. Structural brain measures were investigated using both automated MR volumetry and voxel based morphometry (VBM). Self-reported measures of problematic Internet use and hours spent online were also assessed. According to MR volumetry, problematic Internet use was associated with increased grey matter volume of bilateral putamen and right nucleus accumbens while decreased grey matter volume of orbitofrontal cortex (OFC). Similarly, VBM analysis revealed a significant negative association between the absolute amount of grey matter OFC and problematic Internet use. Our findings suggest structural brain alterations in the reward system usually related to addictions are present in problematic Internet use.

Structural imaging of the brain reveals decreased total brain and total gray matter volumes in obese but not in lean women with polycystic ovary syndrome compared to body mass index-matched counterparts.

PubMed

Ozgen Saydam, Basak; Has, Arzu Ceylan; Bozdag, Gurkan; Oguz, Kader Karli; Yildiz, Bulent Okan

2017-07-01

To detect differences in global brain volumes and identify relations between brain volume and appetite-related hormones in women with polycystic ovary syndrome (PCOS) compared to body mass index-matched controls. Forty subjects participated in this study. Cranial magnetic resonance imaging and measurements of fasting ghrelin, leptin and glucagon-like peptide 1 (GLP-1), as well as GLP-1 levels during mixed-meal tolerance test (MTT), were performed. Total brain volume and total gray matter volume (GMV) were decreased in obese PCOS compared to obese controls (p < 0.05 for both) whereas lean PCOS and controls did not show a significant difference. Secondary analyses of regional brain volumes showed decreases in GMV of the caudate nucleus, ventral diencephalon and hippocampus in obese PCOS compared to obese controls (p < 0.05 for all), whereas lean patients with PCOS had lower GMV in the amygdala than lean controls (p < 0.05). No significant relations were detected between structural differences and measured hormone levels at baseline or during MTT. This study, investigating structural brain alterations in PCOS, suggests volumetric reductions in global brain areas in obese women with PCOS. Functional studies with larger sample size are needed to determine physiopathological roles of these changes and potential effects of long-term medical management on brain structure of PCOS.

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

Apolipoprotein epsilon 4 allele modifies waist-to-hip ratio effects on cognition and brain structure.

PubMed

Zade, David; Beiser, Alexa; McGlinchey, Regina; Au, Rhoda; Seshadri, Sudha; Palumbo, Carole; Wolf, Philip A; DeCarli, Charles; Milberg, William

2013-02-01

This study aimed to determine whether relationships between obesity, as measured by waist-to-hip ratio (WHR), and cognition and brain structure were modified by the apolipoprotein epsilon 4 allele (apoE4). The sample included 1969 stroke- and dementia-free participants from the Framingham Offspring Cohort who underwent neuropsychological (NP) testing and structural magnetic resonance imaging (MRI) between 1999 and 2002. WHR was categorized into sex-specific quartiles with those in Q4 representing central obesity. Multivariate linear regression estimated the relationships between Q4-WHR, cognitive, and MRI measures; interaction terms examined modification of these relationships by the presence of apoE4. All analyses were cross sectional. ApoE4 status significantly modified a number of associations. Specifically, we observed a significant negative relationship between Q4-WHR and a measure of executive function in the apoE4(+) group but not in the apoE4(-) group. Similarly, we observed a stronger negative relationship between Q4-WHR and a measure of memory function for those in the apoE4(+) group compared to those in the apoE4(-) group. In addition, apoE4 status modified the relationship between Q4-WHR and 2 measures of structural brain integrity. First, a paradoxical finding of a negative association between WHR and frontal brain volume that was significant only for those in the apoE4(-) group, and a second finding that WHR was significantly associated with greater white matter hyperintensity volume only in the apoE4(+) group. These findings suggest that associations between central adiposity and both neuropsychological performance and underlying brain structure are highly complex and must be considered in the context of possible modifying genetic influences. Published by Elsevier Inc.

Population differences in brain morphology: Need for population specific brain template.

PubMed

Rao, Naren P; Jeelani, Haris; Achalia, Rashmin; Achalia, Garima; Jacob, Arpitha; Bharath, Rose Dawn; Varambally, Shivarama; Venkatasubramanian, Ganesan; K Yalavarthy, Phaneendra

2017-07-30

Brain templates provide a standard anatomical platform for population based morphometric assessments. Typically, standard brain templates for such assessments are created using Caucasian brains, which may not be ideal to analyze brains from other ethnicities. To effectively demonstrate this, we compared brain morphometric differences between T1 weighted structural MRI images of 27 healthy Indian and Caucasian subjects of similar age and same sex ratio. Furthermore, a population specific brain template was created from MRI images of healthy Indian subjects and compared with standard Montreal Neurological Institute (MNI-152) template. We also examined the accuracy of registration of by acquiring a different T1 weighted MRI data set and registering them to newly created Indian template and MNI-152 template. The statistical analysis indicates significant difference in global brain measures and regional brain structures of Indian and Caucasian subjects. Specifically, the global brain measurements of the Indian brain template were smaller than that of the MNI template. Also, Indian brain images were better realigned to the newly created template than to the MNI-152 template. The notable variations in Indian and Caucasian brains convey the need to build a population specific Indian brain template and atlas. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Catecholamines and cognition after traumatic brain injury

PubMed Central

Jenkins, Peter O.; Mehta, Mitul A.

2016-01-01

Abstract Cognitive problems are one of the main causes of ongoing disability after traumatic brain injury. The heterogeneity of the injuries sustained and the variability of the resulting cognitive deficits makes treating these problems difficult. Identifying the underlying pathology allows a targeted treatment approach aimed at cognitive enhancement. For example, damage to neuromodulatory neurotransmitter systems is common after traumatic brain injury and is an important cause of cognitive impairment. Here, we discuss the evidence implicating disruption of the catecholamines (dopamine and noradrenaline) and review the efficacy of catecholaminergic drugs in treating post-traumatic brain injury cognitive impairments. The response to these therapies is often variable, a likely consequence of the heterogeneous patterns of injury as well as a non-linear relationship between catecholamine levels and cognitive functions. This individual variability means that measuring the structure and function of a person’s catecholaminergic systems is likely to allow more refined therapy. Advanced structural and molecular imaging techniques offer the potential to identify disruption to the catecholaminergic systems and to provide a direct measure of catecholamine levels. In addition, measures of structural and functional connectivity can be used to identify common patterns of injury and to measure the functioning of brain ‘networks’ that are important for normal cognitive functioning. As the catecholamine systems modulate these cognitive networks, these measures could potentially be used to stratify treatment selection and monitor response to treatment in a more sophisticated manner. PMID:27256296

Differences in gut microbial composition correlate with regional brain volumes in irritable bowel syndrome.

PubMed

Labus, Jennifer S; Hollister, Emily B; Jacobs, Jonathan; Kirbach, Kyleigh; Oezguen, Numan; Gupta, Arpana; Acosta, Jonathan; Luna, Ruth Ann; Aagaard, Kjersti; Versalovic, James; Savidge, Tor; Hsiao, Elaine; Tillisch, Kirsten; Mayer, Emeran A

2017-05-01

Preclinical and clinical evidence supports the concept of bidirectional brain-gut microbiome interactions. We aimed to determine if subgroups of irritable bowel syndrome (IBS) subjects can be identified based on differences in gut microbial composition, and if there are correlations between gut microbial measures and structural brain signatures in IBS. Behavioral measures, stool samples, and structural brain images were collected from 29 adult IBS and 23 healthy control subjects (HCs). 16S ribosomal RNA (rRNA) gene sequencing was used to profile stool microbial communities, and various multivariate analysis approaches were used to quantitate microbial composition, abundance, and diversity. The metagenomic content of samples was inferred from 16S rRNA gene sequence data using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). T1-weighted brain images were acquired on a Siemens Allegra 3T scanner, and morphological measures were computed for 165 brain regions. Using unweighted Unifrac distances with hierarchical clustering on microbial data, samples were clustered into two IBS subgroups within the IBS population (IBS1 (n = 13) and HC-like IBS (n = 16)) and HCs (n = 23) (AUROC = 0.96, sensitivity 0.95, specificity 0.67). A Random Forest classifier provided further support for the differentiation of IBS1 and HC groups. Microbes belonging to the genera Faecalibacterium, Blautia, and Bacteroides contributed to this subclassification. Clinical features distinguishing the groups included a history of early life trauma and duration of symptoms (greater in IBS1), but not self-reported bowel habits, anxiety, depression, or medication use. Gut microbial composition correlated with structural measures of brain regions including sensory- and salience-related regions, and with a history of early life trauma. The results confirm previous reports of gut microbiome-based IBS subgroups and identify for the first time brain structural alterations associated with these subgroups. They provide preliminary evidence for the involvement of specific microbes and their predicted metabolites in these correlations.

Circulating inflammatory biomarkers in relation to brain structural measurements in a non-demented elderly population.

PubMed

Gu, Yian; Vorburger, Robert; Scarmeas, Nikolaos; Luchsinger, José A; Manly, Jennifer J; Schupf, Nicole; Mayeux, Richard; Brickman, Adam M

2017-10-01

The aim of this investigation was to determine whether circulating inflammatory biomarkers c-reactive protein (CRP), interleukin-6 (IL6), and alpha 1-antichymotrypsin (ACT) were related to structural brain measures assessed by magnetic resonance imaging (MRI). High-resolution structural MRI was collected on 680 non-demented elderly (mean age 80.1years) participants of a community-based, multiethnic cohort. Approximately three quarters of these participants also had peripheral inflammatory biomarkers (CRP, IL6, and ACT) measured using ELISA. Structural measures including brain volumes and cortical thickness (with both global and regional measures) were derived from MRI scans, and repeated MRI measures were obtained after 4.5years. Mean fractional anisotropy was used as the indicator of white matter integrity assessed with diffusion tensor imaging. We examined the association of inflammatory biomarkers with brain volume, cortical thickness, and white matter integrity using regression models adjusted for age, gender, ethnicity, education, APOE genotype, and intracranial volume. A doubling in CRP (b=-2.48, p=0.002) was associated with a smaller total gray matter volume, equivalent to approximately 1.5years of aging. A doubling in IL6 was associated with smaller total brain volume (b=-14.96, p<0.0001), equivalent to approximately 9years of aging. Higher IL6 was also associated with smaller gray matter (b=-6.52, p=0.002) and white matter volumes (b=-7.47, p=0.004). The volumes of most cortical regions including frontal, occipital, parietal, temporal, as well as subcortical regions including pallidum and thalamus were associated with IL6. In a model additionally adjusted for depression, vascular factors, BMI, and smoking status, the association between IL6 and brain volumes remained, and a doubling in ACT was marginally associated with 0.054 (p=0.001) millimeter thinner mean cortical thickness, equivalent to that of approximately 2.7years of aging. None of the biomarkers was associated with mean fractional anisotropy or longitudinal change of brain volumes and thickness. Among older adults, increased circulating inflammatory biomarkers were associated with smaller brain volume and cortical thickness but not the white matter tract integrity. Our preliminary findings suggest that peripheral inflammatory processes may be involved in the brain atrophy in the elderly. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain Imaging and Human Nutrition: Which Measures to Use in Intervention Studies?12

PubMed Central

Sizonenko, Stéphane V.; Babiloni, Claudio; Sijben, John W.; Walhovd, Kristine B.

2013-01-01

Throughout the life span, the brain is a metabolically highly active organ that uses a large proportion of total nutrient and energy intake. Furthermore, the development and repair of neural tissue depend on the proper intake of essential structural nutrients, minerals, and vitamins. Therefore, what we eat, or refrain from eating, may have an important impact on our cognitive ability and mental performance. Two of the key areas in which diet is thought to play an important role are in optimizing neurodevelopment in children and in preventing neurodegeneration and cognitive decline during aging. From early development to aging, brain imaging can detect structural, functional, and metabolic changes in humans and modifications due to altered nutrition or to additional nutritional supplementation. Inclusion of imaging measures in clinical studies can increase understanding with regard to the modification of brain structure, metabolism, and functional endpoints and may provide early sensitive measures of long-term effects. In this symposium, the utility of existing brain imaging technologies to assess the effects of nutritional intervention in humans is described. Examples of current research showing the utility of these markers are reviewed. PMID:24038255

Abdominal fat distribution and its relationship to brain changes: the differential effects of age on cerebellar structure and function: a cross-sectional, exploratory study

PubMed Central

Raschpichler, Matthias; Straatman, Kees; Schroeter, Matthias Leopold; Arelin, Katrin; Schlögl, Haiko; Fritzsch, Dominik; Mende, Meinhard; Pampel, André; Böttcher, Yvonne; Stumvoll, Michael; Villringer, Arno; Mueller, Karsten

2013-01-01

Objectives To investigate whether the metabolically important visceral adipose tissue (VAT) relates differently to structural and functional brain changes in comparison with body weight measured as body mass index (BMI). Moreover, we aimed to investigate whether these effects change with age. Design Cross-sectional, exploratory. Setting University Clinic, Integrative Research and Treatment Centre. Participants We included 100 (mean BMI=26.0 kg/m², 42 women) out of 202 volunteers randomly invited by the city's registration office, subdivided into two age groups: young-to-mid-age (n=51, 20–45 years of age, mean BMI=24.9, 24 women) versus old (n=49, 65–70 years of age, mean BMI=27.0, 18 women). Main outcome measures VAT, BMI, subcutaneous abdominal adipose tissue, brain structure (grey matter density), functional brain architecture (eigenvector centrality, EC). Results We discovered a loss of cerebellar structure with increasing VAT in the younger participants, most significantly in regions involved in motor processing. This negative correlation disappeared in the elderly. Investigating functional brain architecture showed again inverse VAT–cerebellum correlations, whereas now regions involved in cognitive and emotional processing were significant. Although we detected similar results for EC using BMI, significant age interaction for both brain structure and functional architecture was only found using VAT. Conclusions Visceral adiposity is associated with cerebellar changes of both structure and function, whereas the regions involved contribute to motor, cognitive and emotional processes. Furthermore, these associations seem to be age dependent, with younger adults’ brains being adversely affected. PMID:23355665

Complex network analysis of resting-state fMRI of the brain.

PubMed

Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

2016-08-01

Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

NASA Astrophysics Data System (ADS)

Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.

2017-04-01

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

BrainMap VBM: An environment for structural meta-analysis.

PubMed

Vanasse, Thomas J; Fox, P Mickle; Barron, Daniel S; Robertson, Michaela; Eickhoff, Simon B; Lancaster, Jack L; Fox, Peter T

2018-05-02

The BrainMap database is a community resource that curates peer-reviewed, coordinate-based human neuroimaging literature. By pairing the results of neuroimaging studies with their relevant meta-data, BrainMap facilitates coordinate-based meta-analysis (CBMA) of the neuroimaging literature en masse or at the level of experimental paradigm, clinical disease, or anatomic location. Initially dedicated to the functional, task-activation literature, BrainMap is now expanding to include voxel-based morphometry (VBM) studies in a separate sector, titled: BrainMap VBM. VBM is a whole-brain, voxel-wise method that measures significant structural differences between or within groups which are reported as standardized, peak x-y-z coordinates. Here we describe BrainMap VBM, including the meta-data structure, current data volume, and automated reverse inference functions (region-to-disease profile) of this new community resource. CBMA offers a robust methodology for retaining true-positive and excluding false-positive findings across studies in the VBM literature. As with BrainMap's functional database, BrainMap VBM may be synthesized en masse or at the level of clinical disease or anatomic location. As a use-case scenario for BrainMap VBM, we illustrate a trans-diagnostic data-mining procedure wherein we explore the underlying network structure of 2,002 experiments representing over 53,000 subjects through independent components analysis (ICA). To reduce data-redundancy effects inherent to any database, we demonstrate two data-filtering approaches that proved helpful to ICA. Finally, we apply hierarchical clustering analysis (HCA) to measure network- and disease-specificity. This procedure distinguished psychiatric from neurological diseases. We invite the neuroscientific community to further exploit BrainMap VBM with other modeling approaches. © 2018 Wiley Periodicals, Inc.

A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Cognitive Abilities Independent of IQ Correlate with Regional Brain Structure

ERIC Educational Resources Information Center

Johnson, Wendy; Jung, Rex E.; Colom, Roberto; Haier, Richard J.

2008-01-01

There is increasing evidence relating psychometric measures of general intelligence and reasoning to regional brain structure and function assessed with a variety of neuroimaging techniques. Cognitive dimensions independent of general intelligence can also be identified psychometrically and studied for any neuroanatomical correlates. Here we…

COBRA: A prospective multimodal imaging study of dopamine, brain structure and function, and cognition.

PubMed

Nevalainen, N; Riklund, K; Andersson, M; Axelsson, J; Ögren, M; Lövdén, M; Lindenberger, U; Bäckman, L; Nyberg, L

2015-07-01

Cognitive decline is a characteristic feature of normal human aging. Previous work has demonstrated marked interindividual variability in onset and rate of decline. Such variability has been linked to factors such as maintenance of functional and structural brain integrity, genetics, and lifestyle. Still, few, if any, studies have combined a longitudinal design with repeated multimodal imaging and a comprehensive assessment of cognition as well as genetic and lifestyle factors. The present paper introduces the Cognition, Brain, and Aging (COBRA) study, in which cognitive performance and brain structure and function are measured in a cohort of 181 older adults aged 64 to 68 years at baseline. Participants will be followed longitudinally over a 10-year period, resulting in a total of three equally spaced measurement occasions. The measurement protocol at each occasion comprises a comprehensive set of behavioral and imaging measures. Cognitive performance is evaluated via computerized testing of working memory, episodic memory, perceptual speed, motor speed, implicit sequence learning, and vocabulary. Brain imaging is performed using positron emission tomography with [(11)C]-raclopride to assess dopamine D2/D3 receptor availability. Structural magnetic resonance imaging (MRI) is used for assessment of white and gray-matter integrity and cerebrovascular perfusion, and functional MRI maps brain activation during rest and active task conditions. Lifestyle descriptives are collected, and blood samples are obtained and stored for future evaluation. Here, we present selected results from the baseline assessment along with a discussion of sample characteristics and methodological considerations that determined the design of the study. This article is part of a Special Issue entitled SI: Memory & Aging. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Does Functional Neuroimaging Solve the Questions of Neurolinguistics?

ERIC Educational Resources Information Center

Sidtis, Diana Van Lancker

2006-01-01

Neurolinguistic research has been engaged in evaluating models of language using measures from brain structure and function, and/or in investigating brain structure and function with respect to language representation using proposed models of language. While the aphasiological strategy, which classifies aphasias based on performance modality and a…

Brain structural correlates of reward sensitivity and impulsivity in adolescents with normal and excess weight.

PubMed

Moreno-López, Laura; Soriano-Mas, Carles; Delgado-Rico, Elena; Rio-Valle, Jacqueline S; Verdejo-García, Antonio

2012-01-01

Neuroscience evidence suggests that adolescent obesity is linked to brain dysfunctions associated with enhanced reward and somatosensory processing and reduced impulse control during food processing. Comparatively less is known about the role of more stable brain structural measures and their link to personality traits and neuropsychological factors on the presentation of adolescent obesity. Here we aimed to investigate regional brain anatomy in adolescents with excess weight vs. lean controls. We also aimed to contrast the associations between brain structure and personality and cognitive measures in both groups. Fifty-two adolescents (16 with normal weight and 36 with excess weight) were scanned using magnetic resonance imaging and completed the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ), the UPPS-P scale, and the Stroop task. Voxel-based morphometry (VBM) was used to assess possible between-group differences in regional gray matter (GM) and to measure the putative differences in the way reward and punishment sensitivity, impulsivity and inhibitory control relate to regional GM volumes, which were analyzed using both region of interest (ROI) and whole brain analyses. The ROIs included areas involved in reward/somatosensory processing (striatum, somatosensory cortices) and motivation/impulse control (hippocampus, prefrontal cortex). Excess weight adolescents showed increased GM volume in the right hippocampus. Voxel-wise volumes of the second somatosensory cortex (SII) were correlated with reward sensitivity and positive urgency in lean controls, but this association was missed in excess weight adolescents. Moreover, Stroop performance correlated with dorsolateral prefrontal cortex volumes in controls but not in excess weight adolescents. Adolescents with excess weight have structural abnormalities in brain regions associated with somatosensory processing and motivation.

TSPO Expression and Brain Structure in the Psychosis Spectrum.

PubMed

Hafizi, Sina; Guma, Elisa; Koppel, Alex; Da Silva, Tania; Kiang, Michael; Houle, Sylvain; Wilson, Alan A; Rusjan, Pablo M; Chakravarty, M Mallar; Mizrahi, Romina

2018-06-12

Psychosis is associated with abnormal structural changes in the brain including decreased regional brain volumes and abnormal brain morphology. However, the underlying causes of these structural abnormalities are less understood. The immune system, including microglial activation, has been implicated in the pathophysiology of psychosis. Although previous studies have suggested a connection between peripheral proinflammatory cytokines and structural brain abnormalities in schizophrenia, no in-vivo studies have investigated whether microglial activation is also linked to brain structure alterations previously observed in schizophrenia and its putative prodrome. In this study, we investigated the link between mitochondrial 18kDa translocator protein (TSPO) and structural brain characteristics (i.e. regional brain volume, cortical thickness, and hippocampal shape) in key brain regions such as dorsolateral prefrontal cortex and hippocampus of a large group of participants (N = 90) including individuals at clinical high risk (CHR) for psychosis, first-episode psychosis (mostly antipsychotic naïve) patients, and healthy volunteers. The participants underwent structural brain MRI scan and [ 18 F]FEPPA positron emission tomography (PET) targeting TSPO. A significant [ 18 F]FEPPA binding-by-group interaction was observed in morphological measures across the left hippocampus. In first-episode psychosis, we observed associations between [ 18 F]FEPPA V T (total volume of distribution) and outward and inward morphological alterations, respectively, in the dorsal and ventro-medial portions of the left hippocampus. These associations were not significant in CHR or healthy volunteers. There was no association between [ 18 F]FEPPA V T and other structural brain characteristics. Our findings suggest a link between TSPO expression and alterations in hippocampal morphology in first-episode psychosis. Copyright © 2018. Published by Elsevier Inc.

Causal Structure of Brain Physiology after Brain Injury from Subarachnoid Hemorrhage.

PubMed

Claassen, Jan; Rahman, Shah Atiqur; Huang, Yuxiao; Frey, Hans-Peter; Schmidt, J Michael; Albers, David; Falo, Cristina Maria; Park, Soojin; Agarwal, Sachin; Connolly, E Sander; Kleinberg, Samantha

2016-01-01

High frequency physiologic data are routinely generated for intensive care patients. While massive amounts of data make it difficult for clinicians to extract meaningful signals, these data could provide insight into the state of critically ill patients and guide interventions. We develop uniquely customized computational methods to uncover the causal structure within systemic and brain physiologic measures recorded in a neurological intensive care unit after subarachnoid hemorrhage. While the data have many missing values, poor signal-to-noise ratio, and are composed from a heterogeneous patient population, our advanced imputation and causal inference techniques enable physiologic models to be learned for individuals. Our analyses confirm that complex physiologic relationships including demand and supply of oxygen underlie brain oxygen measurements and that mechanisms for brain swelling early after injury may differ from those that develop in a delayed fashion. These inference methods will enable wider use of ICU data to understand patient physiology.

Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance.

PubMed

Verghese, Ashika; Garner, K G; Mattingley, Jason B; Dux, Paul E

2016-03-02

The ability to perform multiple, concurrent tasks efficiently is a much-desired cognitive skill, but one that remains elusive due to the brain's inherent information-processing limitations. Multitasking performance can, however, be greatly improved through cognitive training (Van Selst et al., 1999, Dux et al., 2009). Previous studies have examined how patterns of brain activity change following training (for review, see Kelly and Garavan, 2005). Here, in a large-scale human behavioral and imaging study of 100 healthy adults, we tested whether multitasking training benefits, assessed using a standard dual-task paradigm, are associated with variability in brain structure. We found that the volume of the rostral part of the left dorsolateral prefrontal cortex (DLPFC) predicted an individual's response to training. Critically, this association was observed exclusively in a task-specific training group, and not in an active-training control group. Our findings reveal a link between DLPFC structure and an individual's propensity to gain from training on a task that taps the limits of cognitive control. Cognitive "brain" training is a rapidly growing, multibillion dollar industry (Hayden, 2012) that has been touted as the panacea for a variety of disorders that result in cognitive decline. A key process targeted by such training is "cognitive control." Here, we combined an established cognitive control measure, multitasking ability, with structural brain imaging in a sample of 100 participants. Our goal was to determine whether individual differences in brain structure predict the extent to which people derive measurable benefits from a cognitive training regime. Ours is the first study to identify a structural brain marker-volume of left hemisphere dorsolateral prefrontal cortex-associated with the magnitude of multitasking performance benefits induced by training at an individual level. Copyright © 2016 the authors 0270-6474/16/362638-08$15.00/0.

The neural processing of hierarchical structure in music and speech at different timescales.

PubMed

Farbood, Morwaread M; Heeger, David J; Marcus, Gary; Hasson, Uri; Lerner, Yulia

2015-01-01

Music, like speech, is a complex auditory signal that contains structures at multiple timescales, and as such is a potentially powerful entry point into the question of how the brain integrates complex streams of information. Using an experimental design modeled after previous studies that used scrambled versions of a spoken story (Lerner et al., 2011) and a silent movie (Hasson et al., 2008), we investigate whether listeners perceive hierarchical structure in music beyond short (~6 s) time windows and whether there is cortical overlap between music and language processing at multiple timescales. Experienced pianists were presented with an extended musical excerpt scrambled at multiple timescales-by measure, phrase, and section-while measuring brain activity with functional magnetic resonance imaging (fMRI). The reliability of evoked activity, as quantified by inter-subject correlation of the fMRI responses, was measured. We found that response reliability depended systematically on musical structure coherence, revealing a topographically organized hierarchy of processing timescales. Early auditory areas (at the bottom of the hierarchy) responded reliably in all conditions. For brain areas at the top of the hierarchy, the original (unscrambled) excerpt evoked more reliable responses than any of the scrambled excerpts, indicating that these brain areas process long-timescale musical structures, on the order of minutes. The topography of processing timescales was analogous with that reported previously for speech, but the timescale gradients for music and speech overlapped with one another only partially, suggesting that temporally analogous structures-words/measures, sentences/musical phrases, paragraph/sections-are processed separately.

Structural network efficiency is associated with cognitive impairment in small-vessel disease.

PubMed

Lawrence, Andrew J; Chung, Ai Wern; Morris, Robin G; Markus, Hugh S; Barrick, Thomas R

2014-07-22

To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. © 2014 American Academy of Neurology.

Structural network efficiency is associated with cognitive impairment in small-vessel disease

PubMed Central

Chung, Ai Wern; Morris, Robin G.; Markus, Hugh S.; Barrick, Thomas R.

2014-01-01

Objective: To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. Methods: A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Results: Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Conclusions: Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. PMID:24951477

N-terminal pro–brain natriuretic peptide and abnormal brain aging

PubMed Central

Sabayan, Behnam; van Buchem, Mark A.; de Craen, Anton J.M.; Sigurdsson, Sigurdur; Zhang, Qian; Harris, Tamara B.; Gudnason, Vilmundur; Arai, Andrew E.

2015-01-01

Objective: To investigate the independent association of serum N-terminal fragment of the prohormone natriuretic peptide (NT-proBNP) with structural and functional features of abnormal brain aging in older individuals. Methods: In this cross-sectional study based on the Age, Gene/Environment Susceptibility (AGES)–Reykjavik Study, we included 4,029 older community-dwelling individuals (born 1907 to 1935) with a measured serum level of NT-proBNP. Outcomes included parenchymal brain volumes estimated from brain MRI, cognitive function measured by tests of memory, processing speed, and executive functioning, and presence of depressive symptoms measured using the Geriatric Depression Scale. In a substudy, cardiac output of 857 participants was assessed using cardiac MRI. Results: In multivariate analyses, adjusted for sociodemographic and cardiovascular factors, higher levels of NT-proBNP were independently associated with lower total (p < 0.001), gray matter (p < 0.001), and white matter (p = 0.001) brain volumes. Likewise, in multivariate analyses, higher levels of NT-proBNP were associated with worse scores in memory (p = 0.005), processing speed (p = 0.001), executive functioning (p < 0.001), and more depressive symptoms (p = 0.002). In the substudy, the associations of higher NT-proBNP with lower brain parenchymal volumes, impaired executive function and processing speed, and higher depressive symptoms were independent of the level of cardiac output. Conclusions: Higher serum levels of NT-proBNP, independent of cardiovascular risk factors and a measure of cardiac function, are linked with alterations in brain structure and function. Roles of natriuretic peptides in the process of brain aging need to be further elucidated. PMID:26231259

Inattention and Reaction Time Variability Are Linked to Ventromedial Prefrontal Volume in Adolescents.

PubMed

Albaugh, Matthew D; Orr, Catherine; Chaarani, Bader; Althoff, Robert R; Allgaier, Nicholas; D'Alberto, Nicholas; Hudson, Kelsey; Mackey, Scott; Spechler, Philip A; Banaschewski, Tobias; Brühl, Rüdiger; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Cattrell, Anna; Conrod, Patricia J; Desrivières, Sylvane; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Goodman, Robert; Gowland, Penny; Grimmer, Yvonne; Heinz, Andreas; Kappel, Viola; Martinot, Jean-Luc; Paillère Martinot, Marie-Laure; Nees, Frauke; Orfanos, Dimitri Papadopoulos; Penttila, Jani; Poustka, Luise; Paus, Tomáš; Smolka, Michael N; Struve, Maren; Walter, Henrik; Whelan, Robert; Schumann, Gunter; Garavan, Hugh; Potter, Alexandra S

2017-11-01

Neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) have most commonly reported volumetric abnormalities in the basal ganglia, cerebellum, and prefrontal cortices. Few studies have examined the relationship between ADHD symptomatology and brain structure in population-based samples. We investigated the relationship between dimensional measures of ADHD symptomatology, brain structure, and reaction time variability-an index of lapses in attention. We also tested for associations between brain structural correlates of ADHD symptomatology and maps of dopaminergic gene expression. Psychopathology and imaging data were available for 1538 youths. Parent ratings of ADHD symptoms were obtained using the Development and Well-Being Assessment and the Strengths and Difficulties Questionnaire (SDQ). Self-reports of ADHD symptoms were assessed using the youth version of the SDQ. Reaction time variability was available in a subset of participants. For each measure, whole-brain voxelwise regressions with gray matter volume were calculated. Parent ratings of ADHD symptoms (Development and Well-Being Assessment and SDQ), adolescent self-reports of ADHD symptoms on the SDQ, and reaction time variability were each negatively associated with gray matter volume in an overlapping region of the ventromedial prefrontal cortex. Maps of DRD1 and DRD2 gene expression were associated with brain structural correlates of ADHD symptomatology. This is the first study to reveal relationships between ventromedial prefrontal cortex structure and multi-informant measures of ADHD symptoms in a large population-based sample of adolescents. Our results indicate that ventromedial prefrontal cortex structure is a biomarker for ADHD symptomatology. These findings extend previous research implicating the default mode network and dopaminergic dysfunction in ADHD. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Opposing Brain Differences in 16p11.2 Deletion and Duplication Carriers

PubMed Central

Qureshi, Abid Y.; Mueller, Sophia; Snyder, Abraham Z.; Mukherjee, Pratik; Berman, Jeffrey I.; Roberts, Timothy P.L.; Nagarajan, Srikantan S.; Spiro, John E.; Chung, Wendy K.; Sherr, Elliott H.

2014-01-01

Deletions and duplications of the recurrent ∼600 kb chromosomal BP4–BP5 region of 16p11.2 are associated with a broad variety of neurodevelopmental outcomes including autism spectrum disorder. A clue to the pathogenesis of the copy number variant (CNV)'s effect on the brain is that the deletion is associated with a head size increase, whereas the duplication is associated with a decrease. Here we analyzed brain structure in a clinically ascertained group of human deletion (N = 25) and duplication (N = 17) carriers from the Simons Variation in Individuals Project compared with age-matched controls (N = 29 and 33, respectively). Multiple brain measures showed increased size in deletion carriers and reduced size in duplication carriers. The effects spanned global measures of intracranial volume, brain size, compartmental measures of gray matter and white matter, subcortical structures, and the cerebellum. Quantitatively, the largest effect was on the thalamus, but the collective results suggest a pervasive rather than a selective effect on the brain. Detailed analysis of cortical gray matter revealed that cortical surface area displays a strong dose-dependent effect of CNV (deletion > control > duplication), whereas average cortical thickness is less affected. These results suggest that the CNV may exert its opposing influences through mechanisms that influence early stages of embryonic brain development. PMID:25143601

The social network-network: size is predicted by brain structure and function in the amygdala and paralimbic regions

PubMed Central

Von Der Heide, Rebecca; Vyas, Govinda

2014-01-01

The social brain hypothesis proposes that the large size of the primate neocortex evolved to support complex and demanding social interactions. Accordingly, recent studies have reported correlations between the size of an individual’s social network and the density of gray matter (GM) in regions of the brain implicated in social cognition. However, the reported relationships between GM density and social group size are somewhat inconsistent with studies reporting correlations in different brain regions. One factor that might account for these discrepancies is the use of different measures of social network size (SNS). This study used several measures of SNS to assess the relationships SNS and GM density. The second goal of this study was to test the relationship between social network measures and functional brain activity. Participants performed a social closeness task using photos of their friends and unknown people. Across the VBM and functional magnetic resonance imaging analyses, individual differences in SNS were consistently related to structural and functional differences in three regions: the left amygdala, right amygdala and the right entorhinal/ventral anterior temporal cortex. PMID:24493846

Brain surface temperature under a craniotomy

PubMed Central

Kalmbach, Abigail S.

2012-01-01

Many neuroscientists access surface brain structures via a small cranial window, opened in the bone above the brain region of interest. Unfortunately this methodology has the potential to perturb the structure and function of the underlying brain tissue. One potential perturbation is heat loss from the brain surface, which may result in local dysregulation of brain temperature. Here, we demonstrate that heat loss is a significant problem in a cranial window preparation in common use for electrical recording and imaging studies in mice. In the absence of corrective measures, the exposed surface of the neocortex was at ∼28°C, ∼10°C below core body temperature, and a standing temperature gradient existed, with tissue below the core temperature even several millimeters into the brain. Cooling affected cellular and network function in neocortex and resulted principally from increased heat loss due to convection and radiation through the skull and cranial window. We demonstrate that constant perfusion of solution, warmed to 37°C, over the brain surface readily corrects the brain temperature, resulting in a stable temperature of 36–38°C at all depths. Our results indicate that temperature dysregulation may be common in cranial window preparations that are in widespread use in neuroscience, underlining the need to take measures to maintain the brain temperature in many physiology experiments. PMID:22972953

Patterns of Individual Variation in Visual Pathway Structure and Function in the Sighted and Blind

PubMed Central

Datta, Ritobrato; Benson, Noah C.; Prasad, Sashank; Jacobson, Samuel G.; Cideciyan, Artur V.; Bridge, Holly; Watkins, Kate E.; Butt, Omar H.; Dain, Aleksandra S.; Brandes, Lauren; Gennatas, Efstathios D.

2016-01-01

Many structural and functional brain alterations accompany blindness, with substantial individual variation in these effects. In normally sighted people, there is correlated individual variation in some visual pathway structures. Here we examined if the changes in brain anatomy produced by blindness alter the patterns of anatomical variation found in the sighted. We derived eight measures of central visual pathway anatomy from a structural image of the brain from 59 sighted and 53 blind people. These measures showed highly significant differences in mean size between the sighted and blind cohorts. When we examined the measurements across individuals within each group we found three clusters of correlated variation, with V1 surface area and pericalcarine volume linked, and independent of the thickness of V1 cortex. These two clusters were in turn relatively independent of the volumes of the optic chiasm and lateral geniculate nucleus. This same pattern of variation in visual pathway anatomy was found in the sighted and the blind. Anatomical changes within these clusters were graded by the timing of onset of blindness, with those subjects with a post-natal onset of blindness having alterations in brain anatomy that were intermediate to those seen in the sighted and congenitally blind. Many of the blind and sighted subjects also contributed functional MRI measures of cross-modal responses within visual cortex, and a diffusion tensor imaging measure of fractional anisotropy within the optic radiations and the splenium of the corpus callosum. We again found group differences between the blind and sighted in these measures. The previously identified clusters of anatomical variation were also found to be differentially related to these additional measures: across subjects, V1 cortical thickness was related to cross-modal activation, and the volume of the optic chiasm and lateral geniculate was related to fractional anisotropy in the visual pathway. Our findings show that several of the structural and functional effects of blindness may be reduced to a smaller set of dimensions. It also seems that the changes in the brain that accompany blindness are on a continuum with normal variation found in the sighted. PMID:27812129

Brain structure differences between Chinese and Caucasian cohorts: A comprehensive morphometry study.

PubMed

Tang, Yuchun; Zhao, Lu; Lou, Yunxia; Shi, Yonggang; Fang, Rui; Lin, Xiangtao; Liu, Shuwei; Toga, Arthur

2018-05-01

Numerous behavioral observations and brain function studies have demonstrated that neurological differences exist between East Asians and Westerners. However, the extent to which these factors relate to differences in brain structure is still not clear. As the basis of brain functions, the anatomical differences in brain structure play a primary and critical role in the origination of functional and behavior differences. To investigate the underlying differences in brain structure between the two cultural/ethnic groups, we conducted a comparative study on education-matched right-handed young male adults (age = 22-29 years) from two cohorts, Han Chinese (n = 45) and Caucasians (n = 45), using high-dimensional structural magnetic resonance imaging (MRI) data. Using two well-validated imaging analysis techniques, surface-based morphometry (SBM) and voxel-based morphometry (VBM), we performed a comprehensive vertex-wise morphometric analysis of the brain structures between Chinese and Caucasian cohorts. We identified consistent significant between-group differences in cortical thickness, volume, and surface area in the frontal, temporal, parietal, occipital, and insular lobes as well as the cingulate cortices. The SBM analyses revealed that compared with Caucasians, the Chinese population showed larger cortical structures in the temporal and cingulate regions, and smaller structural measures in the frontal and parietal cortices. The VBM data of the same sample was well-aligned with the SBM findings. Our findings systematically revealed comprehensive brain structural differences between young male Chinese and Caucasians, and provided new neuroanatomical insights to the behavioral and functional distinctions in the two cultural/ethnic populations. © 2018 Wiley Periodicals, Inc.

Individual differences in human brain development.

PubMed

Brown, Timothy T

2017-01-01

This article discusses recent scientific advances in the study of individual differences in human brain development. Focusing on structural neuroimaging measures of brain morphology and tissue properties, two kinds of variability are related and explored: differences across individuals of the same age and differences across age as a result of development. A recent multidimensional modeling study is explained, which was able to use brain measures to predict an individual's chronological age within about one year on average, in children, adolescents, and young adults between 3 and 20 years old. These findings reveal great regularity in the sequence of the aggregate brain state across different ages and phases of development, despite the pronounced individual differences people show on any single brain measure at any given age. Future research is suggested, incorporating additional measures of brain activity and function. WIREs Cogn Sci 2017, 8:e1389. doi: 10.1002/wcs.1389 For further resources related to this article, please visit the WIREs website. © 2016 The Authors. WIREs Cognitive Science published by Wiley Periodicals, Inc.

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.

PubMed

Yee, Yohan; Fernandes, Darren J; French, Leon; Ellegood, Jacob; Cahill, Lindsay S; Vousden, Dulcie A; Spencer Noakes, Leigh; Scholz, Jan; van Eede, Matthijs C; Nieman, Brian J; Sled, John G; Lerch, Jason P

2018-05-18

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance. Copyright © 2018. Published by Elsevier Inc.

Exposure to Severe Urban Air Pollution Influences Cognitive Outcomes, Brain Volume and Systemic Inflammation in Clinically Healthy Children

ERIC Educational Resources Information Center

Calderon-Garciduenas, Lilian; Engle, Randall; Mora-Tiscareno, Antonieta; Styner, Martin; Gomez-Garza, Gilberto; Zhu, Hongtu; Jewells, Valerie; Torres-Jardon, Ricardo; Romero, Lina; Monroy-Acosta, Maria E.; Bryant, Christopher; Gonzalez-Gonzalez, Luis Oscar; Medina-Cortina, Humberto; D'Angiulli, Amedeo

2011-01-01

Exposure to severe air pollution produces neuroinflammation and structural brain alterations in children. We tested whether patterns of brain growth, cognitive deficits and white matter hyperintensities (WMH) are associated with exposures to severe air pollution. Baseline and 1 year follow-up measurements of global and regional brain MRI volumes,…

Brain composition and olfactory learning in honey bees

PubMed Central

Gronenberg, Wulfila; Couvillon, Margaret J.

2015-01-01

Correlations between brain or brain component size and behavioral measures are frequently studied by comparing different animal species, which sometimes introduces variables that complicate interpretation in terms of brain function. Here, we have analyzed the brain composition of honey bees (Apis mellifera) that have been individually tested in an olfactory learning paradigm. We found that the total brain size correlated with the bees’ learning performance. Among different brain components, only the mushroom body, a structure known to be involved in learning and memory, showed a positive correlation with learning performance. In contrast, visual neuropils were relatively smaller in bees that performed better in the olfactory learning task, suggesting modality-specific behavioral specialization of individual bees. This idea is also supported by inter-individual differences in brain composition. Some slight yet statistically significant differences in the brain composition of European and Africanized honey bees are reported. Larger bees had larger brains, and by comparing brains of different sizes, we report isometric correlations for all brain components except for a small structure, the central body. PMID:20060918

Gestational Age is Dimensionally Associated with Structural Brain Network Abnormalities Across Development.

PubMed

Nassar, Rula; Kaczkurkin, Antonia N; Xia, Cedric Huchuan; Sotiras, Aristeidis; Pehlivanova, Marieta; Moore, Tyler M; Garcia de La Garza, Angel; Roalf, David R; Rosen, Adon F G; Lorch, Scott A; Ruparel, Kosha; Shinohara, Russell T; Davatzikos, Christos; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D

2018-04-21

Prematurity is associated with diverse developmental abnormalities, yet few studies relate cognitive and neurostructural deficits to a dimensional measure of prematurity. Leveraging a large sample of children, adolescents, and young adults (age 8-22 years) studied as part of the Philadelphia Neurodevelopmental Cohort, we examined how variation in gestational age impacted cognition and brain structure later in development. Participants included 72 preterm youth born before 37 weeks' gestation and 206 youth who were born at term (37 weeks or later). Using a previously-validated factor analysis, cognitive performance was assessed in three domains: (1) executive function and complex reasoning, (2) social cognition, and (3) episodic memory. All participants completed T1-weighted neuroimaging at 3 T to measure brain volume. Structural covariance networks were delineated using non-negative matrix factorization, an advanced multivariate analysis technique. Lower gestational age was associated with both deficits in executive function and reduced volume within 11 of 26 structural covariance networks, which included orbitofrontal, temporal, and parietal cortices as well as subcortical regions including the hippocampus. Notably, the relationship between lower gestational age and executive dysfunction was accounted for in part by structural network deficits. Together, these findings emphasize the durable impact of prematurity on cognition and brain structure, which persists across development.

Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures

PubMed Central

Holmes, Avram J.; Hollinshead, Marisa O.; O’Keefe, Timothy M.; Petrov, Victor I.; Fariello, Gabriele R.; Wald, Lawrence L.; Fischl, Bruce; Rosen, Bruce R.; Mair, Ross W.; Roffman, Joshua L.; Smoller, Jordan W.; Buckner, Randy L.

2015-01-01

The goal of the Brain Genomics Superstruct Project (GSP) is to enable large-scale exploration of the links between brain function, behavior, and ultimately genetic variation. To provide the broader scientific community data to probe these associations, a repository of structural and functional magnetic resonance imaging (MRI) scans linked to genetic information was constructed from a sample of healthy individuals. The initial release, detailed in the present manuscript, encompasses quality screened cross-sectional data from 1,570 participants ages 18 to 35 years who were scanned with MRI and completed demographic and health questionnaires. Personality and cognitive measures were obtained on a subset of participants. Each dataset contains a T1-weighted structural MRI scan and either one (n=1,570) or two (n=1,139) resting state functional MRI scans. Test-retest reliability datasets are included from 69 participants scanned within six months of their initial visit. For the majority of participants self-report behavioral and cognitive measures are included (n=926 and n=892 respectively). Analyses of data quality, structure, function, personality, and cognition are presented to demonstrate the dataset’s utility. PMID:26175908

Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures.

PubMed

Holmes, Avram J; Hollinshead, Marisa O; O'Keefe, Timothy M; Petrov, Victor I; Fariello, Gabriele R; Wald, Lawrence L; Fischl, Bruce; Rosen, Bruce R; Mair, Ross W; Roffman, Joshua L; Smoller, Jordan W; Buckner, Randy L

2015-01-01

The goal of the Brain Genomics Superstruct Project (GSP) is to enable large-scale exploration of the links between brain function, behavior, and ultimately genetic variation. To provide the broader scientific community data to probe these associations, a repository of structural and functional magnetic resonance imaging (MRI) scans linked to genetic information was constructed from a sample of healthy individuals. The initial release, detailed in the present manuscript, encompasses quality screened cross-sectional data from 1,570 participants ages 18 to 35 years who were scanned with MRI and completed demographic and health questionnaires. Personality and cognitive measures were obtained on a subset of participants. Each dataset contains a T1-weighted structural MRI scan and either one (n=1,570) or two (n=1,139) resting state functional MRI scans. Test-retest reliability datasets are included from 69 participants scanned within six months of their initial visit. For the majority of participants self-report behavioral and cognitive measures are included (n=926 and n=892 respectively). Analyses of data quality, structure, function, personality, and cognition are presented to demonstrate the dataset's utility.

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

PubMed Central

Savalia, Neil K.; Agres, Phillip F.; Chan, Micaela Y.; Feczko, Eric J.; Kennedy, Kristen M.

2016-01-01

Abstract Motion‐contaminated T1‐weighted (T1w) magnetic resonance imaging (MRI) results in misestimates of brain structure. Because conventional T1w scans are not collected with direct measures of head motion, a practical alternative is needed to identify potential motion‐induced bias in measures of brain anatomy. Head movements during functional MRI (fMRI) scanning of 266 healthy adults (20–89 years) were analyzed to reveal stable features of in‐scanner head motion. The magnitude of head motion increased with age and exhibited within‐participant stability across different fMRI scans. fMRI head motion was then related to measurements of both quality control (QC) and brain anatomy derived from a T1w structural image from the same scan session. A procedure was adopted to “flag” individuals exhibiting excessive head movement during fMRI or poor T1w quality rating. The flagging procedure reliably reduced the influence of head motion on estimates of gray matter thickness across the cortical surface. Moreover, T1w images from flagged participants exhibited reduced estimates of gray matter thickness and volume in comparison to age‐ and gender‐matched samples, resulting in inflated effect sizes in the relationships between regional anatomical measures and age. Gray matter thickness differences were noted in numerous regions previously reported to undergo prominent atrophy with age. Recommendations are provided for mitigating this potential confound, and highlight how the procedure may lead to more accurate measurement and comparison of anatomical features. Hum Brain Mapp 38:472–492, 2017. © 2016 Wiley Periodicals, Inc. PMID:27634551

Cardiorespiratory fitness, cognition and brain structure after TIA or minor ischemic stroke.

PubMed

Boss, H Myrthe; Van Schaik, Sander M; Witkamp, Theo D; Geerlings, Mirjam I; Weinstein, Henry C; Van den Berg-Vos, Renske M

2017-10-01

Background It is not known whether cardiorespiratory fitness is associated with better cognitive performance and brain structure in patients with a TIA or minor ischemic stroke. Aims To examine the association between cardiorespiratory fitness, cognition and brain structure in patients with a TIA and minor stroke. Methods The study population consisted of patients with a TIA or minor stroke with a baseline measurement of the peak oxygen consumption, a MRI scan of brain and neuropsychological assessment. Composite z-scores were calculated for the cognitive domains attention, memory and executive functioning. White matter hyperintensities, microbleeds and lacunes were rated visually. The mean apparent diffusion coefficient was measured in regions of interest in frontal and occipital white matter and in the centrum semiovale as a marker of white matter structure. Normalized brain volumes were estimated by use of Statistical Parametric Mapping. Results In 84 included patients, linear regression analysis adjusted for age, sex and education showed that a higher peak oxygen consumption was associated with higher cognitive z-scores, a larger grey matter volume (B = 0.15 (95% CI 0.05; 0.26)) and a lower mean apparent diffusion coefficient (B = -.004 (95% CI -.007; -.001)). We found no association between the peak oxygen consumption and severe white matter hyperintensities, microbleeds, lacunes and total brain volume. Conclusions These data suggest that cardiorespiratory fitness is associated with better cognitive performance, greater grey matter volume and greater integrity of the white matter in patients with a TIA or minor ischemic stroke. Further prospective trials are necessary to define the effect of cardiorespiratory fitness on cognition and brain structure in patients with TIA or minor stroke.

Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging.

PubMed

Thomas, Cibu; Sadeghi, Neda; Nayak, Amrita; Trefler, Aaron; Sarlls, Joelle; Baker, Chris I; Pierpaoli, Carlo

2018-06-01

Diurnal fluctuations in MRI measures of structural and functional properties of the brain have been reported recently. These fluctuations may have a physiological origin, since they have been detected using different MRI modalities, and cannot be explained by factors that are typically known to confound MRI measures. While preliminary evidence suggests that measures of structural properties of the brain based on diffusion tensor imaging (DTI) fluctuate as a function of time-of-day (TOD), the underlying mechanism has not been investigated. Here, we used a longitudinal within-subjects design to investigate the impact of time-of-day on DTI measures. In addition to using the conventional monoexponential tensor model to assess TOD-related fluctuations, we used a dual compartment tensor model that allowed us to directly assess if any change in DTI measures is due to an increase in CSF/free-water volume fraction or due to an increase in water diffusivity within the parenchyma. Our results show that Trace or mean diffusivity, as measured using the conventional monoexponential tensor model tends to increase systematically from morning to afternoon scans at the interface of grey matter/CSF, most prominently in the major fissures and the sulci of the brain. Interestingly, in a recent study of the glymphatic system, these same regions were found to show late enhancement after intrathecal injection of a CSF contrast agent. The increase in Trace also impacts DTI measures of diffusivity such as radial and axial diffusivity, but does not affect fractional anisotropy. The dual compartment analysis revealed that the increase in diffusivity measures from PM to AM was driven by an increase in the volume fraction of CSF-like free-water. Taken together, our findings provide important insight into the likely physiological origins of diurnal fluctuations in MRI measurements of structural properties of the brain. Published by Elsevier Inc.

The neural processing of hierarchical structure in music and speech at different timescales

PubMed Central

Farbood, Morwaread M.; Heeger, David J.; Marcus, Gary; Hasson, Uri; Lerner, Yulia

2015-01-01

Music, like speech, is a complex auditory signal that contains structures at multiple timescales, and as such is a potentially powerful entry point into the question of how the brain integrates complex streams of information. Using an experimental design modeled after previous studies that used scrambled versions of a spoken story (Lerner et al., 2011) and a silent movie (Hasson et al., 2008), we investigate whether listeners perceive hierarchical structure in music beyond short (~6 s) time windows and whether there is cortical overlap between music and language processing at multiple timescales. Experienced pianists were presented with an extended musical excerpt scrambled at multiple timescales—by measure, phrase, and section—while measuring brain activity with functional magnetic resonance imaging (fMRI). The reliability of evoked activity, as quantified by inter-subject correlation of the fMRI responses, was measured. We found that response reliability depended systematically on musical structure coherence, revealing a topographically organized hierarchy of processing timescales. Early auditory areas (at the bottom of the hierarchy) responded reliably in all conditions. For brain areas at the top of the hierarchy, the original (unscrambled) excerpt evoked more reliable responses than any of the scrambled excerpts, indicating that these brain areas process long-timescale musical structures, on the order of minutes. The topography of processing timescales was analogous with that reported previously for speech, but the timescale gradients for music and speech overlapped with one another only partially, suggesting that temporally analogous structures—words/measures, sentences/musical phrases, paragraph/sections—are processed separately. PMID:26029037

Neuronal correlates of the five factor model (FFM) of human personality: Multimodal imaging in a large healthy sample.

PubMed

Bjørnebekk, Astrid; Fjell, Anders M; Walhovd, Kristine B; Grydeland, Håkon; Torgersen, Svenn; Westlye, Lars T

2013-01-15

Advances in neuroimaging techniques have recently provided glimpse into the neurobiology of complex traits of human personality. Whereas some intriguing findings have connected aspects of personality to variations in brain morphology, the relations are complex and our current understanding is incomplete. Therefore, we aimed to provide a comprehensive investigation of brain-personality relations using a multimodal neuroimaging approach in a large sample comprising 265 healthy individuals. The NEO Personality Inventory was used to provide measures of core aspects of human personality, and imaging phenotypes included measures of total and regional brain volumes, regional cortical thickness and arealization, and diffusion tensor imaging indices of white matter (WM) microstructure. Neuroticism was the trait most clearly linked to brain structure. Higher neuroticism including facets reflecting anxiety, depression and vulnerability to stress was associated with smaller total brain volume, widespread decrease in WM microstructure, and smaller frontotemporal surface area. Higher scores on extraversion were associated with thinner inferior frontal gyrus, and conscientiousness was negatively associated with arealization of the temporoparietal junction. No reliable associations between brain structure and agreeableness and openness, respectively, were found. The results provide novel evidence of the associations between brain structure and variations in human personality, and corroborate previous findings of a consistent neuroanatomical basis of negative emotionality. Copyright © 2012 Elsevier Inc. All rights reserved.

Long-term exposure to fine particulate matter, residential proximity to major roads and measures of brain structure.

PubMed

Wilker, Elissa H; Preis, Sarah R; Beiser, Alexa S; Wolf, Philip A; Au, Rhoda; Kloog, Itai; Li, Wenyuan; Schwartz, Joel; Koutrakis, Petros; DeCarli, Charles; Seshadri, Sudha; Mittleman, Murray A

2015-05-01

Long-term exposure to ambient air pollution is associated with cerebrovascular disease and cognitive impairment, but whether it is related to structural changes in the brain is not clear. We examined the associations between residential long-term exposure to ambient air pollution and markers of brain aging using magnetic resonance imaging. Framingham Offspring Study participants who attended the seventh examination were at least 60 years old and free of dementia and stroke were included. We evaluated associations between exposures (fine particulate matter [PM2.5] and residential proximity to major roadways) and measures of total cerebral brain volume, hippocampal volume, white matter hyperintensity volume (log-transformed and extensive white matter hyperintensity volume for age), and covert brain infarcts. Models were adjusted for age, clinical covariates, indicators of socioeconomic position, and temporal trends. A 2-μg/m(3) increase in PM2.5 was associated with -0.32% (95% confidence interval, -0.59 to -0.05) smaller total cerebral brain volume and 1.46 (95% confidence interval, 1.10 to 1.94) higher odds of covert brain infarcts. Living further away from a major roadway was associated with 0.10 (95% confidence interval, 0.01 to 0.19) greater log-transformed white matter hyperintensity volume for an interquartile range difference in distance, but no clear pattern of association was observed for extensive white matter. Exposure to elevated levels of PM2.5 was associated with smaller total cerebral brain volume, a marker of age-associated brain atrophy, and with higher odds of covert brain infarcts. These findings suggest that air pollution is associated with insidious effects on structural brain aging even in dementia- and stroke-free persons. © 2015 American Heart Association, Inc.

MRI as a tool to study brain structure from mouse models for mental retardation

NASA Astrophysics Data System (ADS)

Verhoye, Marleen; Sijbers, Jan; Kooy, R. F.; Reyniers, E.; Fransen, E.; Oostra, B. A.; Willems, Peter; Van der Linden, Anne-Marie

1998-07-01

Nowadays, transgenic mice are a common tool to study brain abnormalities in neurological disorders. These studies usually rely on neuropathological examinations, which have a number of drawbacks, including the risk of artefacts introduced by fixation and dehydration procedures. Here we present 3D Fast Spin Echo Magnetic Resonance Imaging (MRI) in combination with 2D and 3D segmentation techniques as a powerful tool to study brain anatomy. We set up MRI of the brain in mouse models for the fragile X syndrome (FMR1 knockout) and Corpus callosum hypoplasia, mental Retardation, Adducted thumbs, Spastic paraplegia and Hydrocephalus (CRASH) syndrome (L1CAM knockout). Our major goal was to determine qualitative and quantitative differences in specific brain structures. MRI of the brain of fragile X and CRASH patients has revealed alterations in the size of specific brain structures, including the cerebellar vermis and the ventricular system. In the present MRI study of the brain from fragile X knockout mice, we have measured the size of the brain, cerebellum and 4th ventricle, which were reported as abnormal in human fragile X patients, but found no evidence for altered brain regions in the mouse model. In CRASH syndrome, the most specific brain abnormalities are vermis hypoplasia and abnormalities of the ventricular system with some degree of hydrocephalus. With the MRI study of L1CAM knockout mice we found vermis hypoplasia, abnormalities of the ventricular system including dilatation of the lateral and the 4th ventricles. These subtle abnormalities were not detected upon standard neuropathological examination. Here we proved that this sensitive MRI technique allows to measure small differences which can not always be detected by means of pathology.

Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis.

PubMed

Zhou, Fuqing; Zhuang, Ying; Gong, Honghan; Zhan, Jie; Grossman, Murray; Wang, Ze

2016-01-01

Brain entropy (BEN) mapping provides a novel approach to characterize brain temporal dynamics, a key feature of human brain. Using resting state functional magnetic resonance imaging (rsfMRI), reliable and spatially distributed BEN patterns have been identified in normal brain, suggesting a potential use in clinical populations since temporal brain dynamics and entropy may be altered in disease conditions. The purpose of this study was to characterize BEN in multiple sclerosis (MS), a neurodegenerative disease that affects millions of people. Since currently there is no cure for MS, developing treatment or medication that can slow down its progression represents a high research priority, for which validating a brain marker sensitive to disease and the related functional impairments is essential. Because MS can start long time before any measurable symptoms and structural deficits, assessing the dynamic brain activity and correspondingly BEN may provide a critical way to study MS and its progression. Because BEN is new to MS, we aimed to assess BEN alterations in the relapsing-remitting MS (RRMS) patients using a patient versus control design, to examine the correlation of BEN to clinical measurements, and to check the correlation of BEN to structural brain measures which have been more often used in MS studies. As compared to controls, RRMS patients showed increased BEN in motor areas, executive control area, spatial coordinating area, and memory system. Increased BEN was related to greater disease severity as measured by the expanded disability status scale (EDSS) and greater tissue damage as indicated by the mean diffusivity. Patients also showed decreased BEN in other places, which was associated with less disability or fatigue, indicating a disease-related BEN re-distribution. Our results suggest BEN as a novel and useful tool for characterizing RRMS.

N-terminal pro-brain natriuretic peptide and abnormal brain aging: The AGES-Reykjavik Study.

PubMed

Sabayan, Behnam; van Buchem, Mark A; de Craen, Anton J M; Sigurdsson, Sigurdur; Zhang, Qian; Harris, Tamara B; Gudnason, Vilmundur; Arai, Andrew E; Launer, Lenore J

2015-09-01

To investigate the independent association of serum N-terminal fragment of the prohormone natriuretic peptide (NT-proBNP) with structural and functional features of abnormal brain aging in older individuals. In this cross-sectional study based on the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study, we included 4,029 older community-dwelling individuals (born 1907 to 1935) with a measured serum level of NT-proBNP. Outcomes included parenchymal brain volumes estimated from brain MRI, cognitive function measured by tests of memory, processing speed, and executive functioning, and presence of depressive symptoms measured using the Geriatric Depression Scale. In a substudy, cardiac output of 857 participants was assessed using cardiac MRI. In multivariate analyses, adjusted for sociodemographic and cardiovascular factors, higher levels of NT-proBNP were independently associated with lower total (p < 0.001), gray matter (p < 0.001), and white matter (p = 0.001) brain volumes. Likewise, in multivariate analyses, higher levels of NT-proBNP were associated with worse scores in memory (p = 0.005), processing speed (p = 0.001), executive functioning (p < 0.001), and more depressive symptoms (p = 0.002). In the substudy, the associations of higher NT-proBNP with lower brain parenchymal volumes, impaired executive function and processing speed, and higher depressive symptoms were independent of the level of cardiac output. Higher serum levels of NT-proBNP, independent of cardiovascular risk factors and a measure of cardiac function, are linked with alterations in brain structure and function. Roles of natriuretic peptides in the process of brain aging need to be further elucidated. © 2015 American Academy of Neurology.

Hemispheric lateralization of topological organization in structural brain networks.

PubMed

Caeyenberghs, Karen; Leemans, Alexander

2014-09-01

The study on structural brain asymmetries in healthy individuals plays an important role in our understanding of the factors that modulate cognitive specialization in the brain. Here, we used fiber tractography to reconstruct the left and right hemispheric networks of a large cohort of 346 healthy participants (20-86 years) and performed a graph theoretical analysis to investigate this brain laterality from a network perspective. Findings revealed that the left hemisphere is significantly more "efficient" than the right hemisphere, whereas the right hemisphere showed higher values of "betweenness centrality" and "small-worldness." In particular, left-hemispheric networks displayed increased nodal efficiency in brain regions related to language and motor actions, whereas the right hemisphere showed an increase in nodal efficiency in brain regions involved in memory and visuospatial attention. In addition, we found that hemispheric networks decrease in efficiency with age. Finally, we observed significant gender differences in measures of global connectivity. By analyzing the structural hemispheric brain networks, we have provided new insights into understanding the neuroanatomical basis of lateralized brain functions. Copyright © 2014 Wiley Periodicals, Inc.

Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children's Numerical Abilities.

PubMed

Evans, Tanya M; Kochalka, John; Ngoon, Tricia J; Wu, Sarah S; Qin, Shaozheng; Battista, Christian; Menon, Vinod

2015-08-19

Early numerical proficiency lays the foundation for acquiring quantitative skills essential in today's technological society. Identification of cognitive and brain markers associated with long-term growth of children's basic numerical computation abilities is therefore of utmost importance. Previous attempts to relate brain structure and function to numerical competency have focused on behavioral measures from a single time point. Thus, little is known about the brain predictors of individual differences in growth trajectories of numerical abilities. Using a longitudinal design, with multimodal imaging and machine-learning algorithms, we investigated whether brain structure and intrinsic connectivity in early childhood are predictive of 6 year outcomes in numerical abilities spanning childhood and adolescence. Gray matter volume at age 8 in distributed brain regions, including the ventrotemporal occipital cortex (VTOC), the posterior parietal cortex, and the prefrontal cortex, predicted longitudinal gains in numerical, but not reading, abilities. Remarkably, intrinsic connectivity analysis revealed that the strength of functional coupling among these regions also predicted gains in numerical abilities, providing novel evidence for a network of brain regions that works in concert to promote numerical skill acquisition. VTOC connectivity with posterior parietal, anterior temporal, and dorsolateral prefrontal cortices emerged as the most extensive network predicting individual gains in numerical abilities. Crucially, behavioral measures of mathematics, IQ, working memory, and reading did not predict children's gains in numerical abilities. Our study identifies, for the first time, functional circuits in the human brain that scaffold the development of numerical skills, and highlights potential biomarkers for identifying children at risk for learning difficulties. Children show substantial individual differences in math abilities and ease of math learning. Early numerical abilities provide the foundation for future academic and professional success in an increasingly technological society. Understanding the early identification of poor math skills has therefore taken on great significance. This work provides important new insights into brain structure and connectivity measures that can predict longitudinal growth of children's math skills over a 6 year period, and may eventually aid in the early identification of children who might benefit from targeted interventions. Copyright © 2015 the authors 0270-6474/15/3511743-08$15.00/0.

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy.

PubMed

Wirsich, Jonathan; Perry, Alistair; Ridley, Ben; Proix, Timothée; Golos, Mathieu; Bénar, Christian; Ranjeva, Jean-Philippe; Bartolomei, Fabrice; Breakspear, Michael; Jirsa, Viktor; Guye, Maxime

2016-01-01

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain. We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome. In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

Relations between volumetric measures of brain structure and attentional function in spina bifida: utilization of robust statistical approaches.

PubMed

Kulesz, Paulina A; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M; Francis, David J

2015-03-01

Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product-moment correlation was compared with 4 robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator. All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PsycINFO Database Record (c) 2015 APA, all rights reserved.

A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity.

PubMed

Huang, Lijie; Huang, Taicheng; Zhen, Zonglei; Liu, Jia

2016-03-15

We present a test-retest dataset for evaluation of long-term reliability of measures from structural and resting-state functional magnetic resonance imaging (sMRI and rfMRI) scans. The repeated scan dataset was collected from 61 healthy adults in two sessions using highly similar imaging parameters at an interval of 103-189 days. However, as the imaging parameters were not completely identical, the reliability estimated from this dataset shall reflect the lower bounds of the true reliability of sMRI/rfMRI measures. Furthermore, in conjunction with other test-retest datasets, our dataset may help explore the impact of different imaging parameters on reliability of sMRI/rfMRI measures, which is especially critical for assessing datasets collected from multiple centers. In addition, intelligence quotient (IQ) was measured for each participant using Raven's Advanced Progressive Matrices. The data can thus be used for purposes other than assessing reliability of sMRI/rfMRI alone. For example, data from each single session could be used to associate structural and functional measures of the brain with the IQ metrics to explore brain-IQ association.

Fronto-Parietal gray matter and white matter efficiency differentially predict intelligence in males and females.

PubMed

Ryman, Sephira G; Yeo, Ronald A; Witkiewitz, Katie; Vakhtin, Andrei A; van den Heuvel, Martijn; de Reus, Marcel; Flores, Ranee A; Wertz, Christopher R; Jung, Rex E

2016-11-01

While there are minimal sex differences in overall intelligence, males, on average, have larger total brain volume and corresponding regional brain volumes compared to females, measures that are consistently related to intelligence. Limited research has examined which other brain characteristics may differentially contribute to intelligence in females to facilitate equal performance on intelligence measures. Recent reports of sex differences in the neural characteristics of the brain further highlight the need to differentiate how the structural neural characteristics relate to intellectual ability in males and females. The current study utilized a graph network approach in conjunction with structural equation modeling to examine potential sex differences in the relationship between white matter efficiency, fronto-parietal gray matter volume, and general cognitive ability (GCA). Participants were healthy adults (n = 244) who completed a battery of cognitive testing and underwent structural neuroimaging. Results indicated that in males, a latent factor of fronto-parietal gray matter was significantly related to GCA when controlling for total gray matter volume. In females, white matter efficiency and total gray matter volume were significantly related to GCA, with no specificity of the fronto-parietal gray matter factor over and above total gray matter volume. This work highlights that different neural characteristics across males and females may contribute to performance on intelligence measures. Hum Brain Mapp 37:4006-4016, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The Use of Computers and Video Games in Brain Damage Therapy.

ERIC Educational Resources Information Center

Lorimer, David

The use of computer assisted therapy (CAT) in the rehabilitation of individuals with brain damage is examined. Hardware considerations are explored, and the variety of software programs available for brain injury rehabilitation is discussed. Structured testing and treatment programs in time measurement, memory, and direction finding are described,…

Does MRI scan acceleration affect power to track brain change?

PubMed

Ching, Christopher R K; Hua, Xue; Hibar, Derrek P; Ward, Chadwick P; Gunter, Jeffrey L; Bernstein, Matt A; Jack, Clifford R; Weiner, Michael W; Thompson, Paul M

2015-01-01

The Alzheimer's Disease Neuroimaging Initiative recently implemented accelerated T1-weighted structural imaging to reduce scan times. Faster scans may reduce study costs and patient attrition by accommodating people who cannot tolerate long scan sessions. However, little is known about how scan acceleration affects the power to detect longitudinal brain change. Using tensor-based morphometry, no significant difference was detected in numerical summaries of atrophy rates from accelerated and nonaccelerated scans in subgroups of patients with Alzheimer's disease, early or late mild cognitive impairment, or healthy controls over a 6- and 12-month scan interval. Whole-brain voxelwise mapping analyses revealed some apparent regional differences in 6-month atrophy rates when comparing all subjects irrespective of diagnosis (n = 345). No such whole-brain difference was detected for the 12-month scan interval (n = 156). Effect sizes for structural brain changes were not detectably different in accelerated versus nonaccelerated data. Scan acceleration may influence brain measures but has minimal effects on tensor-based morphometry-derived atrophy measures, at least over the 6- and 12-month intervals examined here. Copyright © 2015 Elsevier Inc. All rights reserved.

Sex differences and structural brain maturation from childhood to early adulthood.

PubMed

Koolschijn, P Cédric M P; Crone, Eveline A

2013-07-01

Recent advances in structural brain imaging have demonstrated that brain development continues through childhood and adolescence. In the present cross-sectional study, structural MRI data from 442 typically developing individuals (range 8-30) were analyzed to examine and replicate the relationship between age, sex, brain volumes, cortical thickness and surface area. Our findings show differential patterns for subcortical and cortical areas. Analysis of subcortical volumes showed that putamen volume decreased with age and thalamus volume increased with age. Independent of age, males demonstrated larger amygdala and thalamus volumes compared to females. Cerebral white matter increased linearly with age, at a faster pace for females than males. Gray matter showed nonlinear decreases with age. Sex-by-age interactions were primarily found in lobar surface area measurements, with males demonstrating a larger cortical surface up to age 15, while cortical surface in females remained relatively stable with increasing age. The current findings replicate some, but not all prior reports on structural brain development, which calls for more studies with large samples, replications, and specific tests for brain structural changes. In addition, the results point toward an important role for sex differences in brain development, specifically during the heterogeneous developmental phase of puberty. Copyright © 2013 Elsevier Ltd. All rights reserved.

Opposing brain differences in 16p11.2 deletion and duplication carriers.

PubMed

Qureshi, Abid Y; Mueller, Sophia; Snyder, Abraham Z; Mukherjee, Pratik; Berman, Jeffrey I; Roberts, Timothy P L; Nagarajan, Srikantan S; Spiro, John E; Chung, Wendy K; Sherr, Elliott H; Buckner, Randy L

2014-08-20

Deletions and duplications of the recurrent ~600 kb chromosomal BP4-BP5 region of 16p11.2 are associated with a broad variety of neurodevelopmental outcomes including autism spectrum disorder. A clue to the pathogenesis of the copy number variant (CNV)'s effect on the brain is that the deletion is associated with a head size increase, whereas the duplication is associated with a decrease. Here we analyzed brain structure in a clinically ascertained group of human deletion (N = 25) and duplication (N = 17) carriers from the Simons Variation in Individuals Project compared with age-matched controls (N = 29 and 33, respectively). Multiple brain measures showed increased size in deletion carriers and reduced size in duplication carriers. The effects spanned global measures of intracranial volume, brain size, compartmental measures of gray matter and white matter, subcortical structures, and the cerebellum. Quantitatively, the largest effect was on the thalamus, but the collective results suggest a pervasive rather than a selective effect on the brain. Detailed analysis of cortical gray matter revealed that cortical surface area displays a strong dose-dependent effect of CNV (deletion > control > duplication), whereas average cortical thickness is less affected. These results suggest that the CNV may exert its opposing influences through mechanisms that influence early stages of embryonic brain development. Copyright © 2014 the authors 0270-6474/14/3411199-13$15.00/0.

Physical fitness and shapes of subcortical brain structures in children.

PubMed

Ortega, Francisco B; Campos, Daniel; Cadenas-Sanchez, Cristina; Altmäe, Signe; Martínez-Zaldívar, Cristina; Martín-Matillas, Miguel; Catena, Andrés; Campoy, Cristina

2017-03-27

A few studies have recently reported that higher cardiorespiratory fitness is associated with higher volumes of subcortical brain structures in children. It is, however, unknown how different fitness measures relate to shapes of subcortical brain nuclei. We aimed to examine the association of the main health-related physical fitness components with shapes of subcortical brain structures in a sample of forty-four Spanish children aged 9·7 (sd 0·2) years from the NUtraceuticals for a HEALthier life project. Cardiorespiratory fitness, muscular strength and speed agility were assessed using valid and reliable tests (ALPHA-fitness test battery). Shape of the subcortical brain structures was assessed by MRI, and its relationship with fitness was examined after controlling for a set of potential confounders using a partial correlation permutation approach. Our results showed that all physical fitness components studied were significantly related to the shapes of subcortical brain nuclei. These associations were both positive and negative, indicating that a higher level of fitness in childhood is related to both expansions and contractions in certain regions of the accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus. Cardiorespiratory fitness was mainly associated with expansions, whereas handgrip was mostly associated with contractions in the structures studied. Future randomised-controlled trials will confirm or contrast our findings, demonstrating whether changes in fitness modify the shapes of brain structures and the extent to which those changes influence cognitive function.

Structural Imaging Measures of Brain Aging

PubMed Central

Lockhart, Samuel N.

2014-01-01

During the course of normal aging, biological changes occur in the brain that are associated with changes in cognitive ability. This review presents data from neuroimaging studies of primarily “normal” or healthy brain aging. As such, we focus on research in unimpaired or nondemented older adults, but also include findings from lifespan studies that include younger and middle aged individuals as well as from populations with prodromal or clinically symptomatic disease such as cerebrovascular or Alzheimer’s disease. This review predominantly addresses structural MRI biomarkers, such as volumetric or thickness measures from anatomical images, and measures of white matter injury and integrity respectively from FLAIR or DTI, and includes complementary data from PET and cognitive or clinical testing as appropriate. The findings reveal highly consistent age-related differences in brain structure, particularly frontal lobe and medial temporal regions that are also accompanied by age-related differences in frontal and medial temporal lobe mediated cognitive abilities. Newer findings also suggest that degeneration of specific white matter tracts such as those passing through the genu and splenium of the corpus callosum may also be related to age-related differences in cognitive performance. Interpretation of these findings, however, must be tempered by the fact that comorbid diseases such as cerebrovascular and Alzheimer’s disease also increase in prevalence with advancing age. As such, this review discusses challenges related to interpretation of current theories of cognitive aging in light of the common occurrence of these later-life diseases. Understanding the differences between “Normal” and “Healthy” brain aging and identifying potential modifiable risk factors for brain aging is critical to inform potential treatments to stall or reverse the effects of brain aging and possibly extend cognitive health for our aging society. PMID:25146995

Structural imaging measures of brain aging.

PubMed

Lockhart, Samuel N; DeCarli, Charles

2014-09-01

During the course of normal aging, biological changes occur in the brain that are associated with changes in cognitive ability. This review presents data from neuroimaging studies of primarily "normal" or healthy brain aging. As such, we focus on research in unimpaired or nondemented older adults, but also include findings from lifespan studies that include younger and middle aged individuals as well as from populations with prodromal or clinically symptomatic disease such as cerebrovascular or Alzheimer's disease. This review predominantly addresses structural MRI biomarkers, such as volumetric or thickness measures from anatomical images, and measures of white matter injury and integrity respectively from FLAIR or DTI, and includes complementary data from PET and cognitive or clinical testing as appropriate. The findings reveal highly consistent age-related differences in brain structure, particularly frontal lobe and medial temporal regions that are also accompanied by age-related differences in frontal and medial temporal lobe mediated cognitive abilities. Newer findings also suggest that degeneration of specific white matter tracts such as those passing through the genu and splenium of the corpus callosum may also be related to age-related differences in cognitive performance. Interpretation of these findings, however, must be tempered by the fact that comorbid diseases such as cerebrovascular and Alzheimer's disease also increase in prevalence with advancing age. As such, this review discusses challenges related to interpretation of current theories of cognitive aging in light of the common occurrence of these later-life diseases. Understanding the differences between "Normal" and "Healthy" brain aging and identifying potential modifiable risk factors for brain aging is critical to inform potential treatments to stall or reverse the effects of brain aging and possibly extend cognitive health for our aging society.

Characterizing Brain Structures and Remodeling after TBI Based on Information Content, Diffusion Entropy

PubMed Central

Fozouni, Niloufar; Chopp, Michael; Nejad-Davarani, Siamak P.; Zhang, Zheng Gang; Lehman, Norman L.; Gu, Steven; Ueno, Yuji; Lu, Mei; Ding, Guangliang; Li, Lian; Hu, Jiani; Bagher-Ebadian, Hassan; Hearshen, David; Jiang, Quan

2013-01-01

Background To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat. Methods Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining. Results Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining. Conclusions Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease. PMID:24143186

Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.

PubMed

Fozouni, Niloufar; Chopp, Michael; Nejad-Davarani, Siamak P; Zhang, Zheng Gang; Lehman, Norman L; Gu, Steven; Ueno, Yuji; Lu, Mei; Ding, Guangliang; Li, Lian; Hu, Jiani; Bagher-Ebadian, Hassan; Hearshen, David; Jiang, Quan

2013-01-01

To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat. Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining. Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining. Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease.

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

PubMed

Adhikari, Mohit H; Hacker, Carl D; Siegel, Josh S; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo; Corbetta, Maurizio

2017-04-01

While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Brain tissues volume measurements from 2D MRI using parametric approach

NASA Astrophysics Data System (ADS)

L'vov, A. A.; Toropova, O. A.; Litovka, Yu. V.

2018-04-01

The purpose of the paper is to propose a fully automated method of volume assessment of structures within human brain. Our statistical approach uses maximum interdependency principle for decision making process of measurements consistency and unequal observations. Detecting outliers performed using maximum normalized residual test. We propose a statistical model which utilizes knowledge of tissues distribution in human brain and applies partial data restoration for precision improvement. The approach proposes completed computationally efficient and independent from segmentation algorithm used in the application.

Sulci segmentation using geometric active contours

NASA Astrophysics Data System (ADS)

Torkaman, Mahsa; Zhu, Liangjia; Karasev, Peter; Tannenbaum, Allen

2017-02-01

Sulci are groove-like regions lying in the depth of the cerebral cortex between gyri, which together, form a folded appearance in human and mammalian brains. Sulci play an important role in the structural analysis of the brain, morphometry (i.e., the measurement of brain structures), anatomical labeling and landmark-based registration.1 Moreover, sulcal morphological changes are related to cortical thickness, whose measurement may provide useful information for studying variety of psychiatric disorders. Manually extracting sulci requires complying with complex protocols, which make the procedure both tedious and error prone.2 In this paper, we describe an automatic procedure, employing geometric active contours, which extract the sulci. Sulcal boundaries are obtained by minimizing a certain energy functional whose minimum is attained at the boundary of the given sulci.

Cognitive Flexibility through Metastable Neural Dynamics Is Disrupted by Damage to the Structural Connectome.

PubMed

Hellyer, Peter J; Scott, Gregory; Shanahan, Murray; Sharp, David J; Leech, Robert

2015-06-17

Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome. Copyright © 2015 the authors 0270-6474/15/359050-14$15.00/0.

Estimated maximal and current brain volume predict cognitive ability in old age

PubMed Central

Royle, Natalie A.; Booth, Tom; Valdés Hernández, Maria C.; Penke, Lars; Murray, Catherine; Gow, Alan J.; Maniega, Susana Muñoz; Starr, John; Bastin, Mark E.; Deary, Ian J.; Wardlaw, Joanna M.

2013-01-01

Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging. PMID:23850342

Segmentation of human brain using structural MRI.

PubMed

Helms, Gunther

2016-04-01

Segmentation of human brain using structural MRI is a key step of processing in imaging neuroscience. The methods have undergone a rapid development in the past two decades and are now widely available. This non-technical review aims at providing an overview and basic understanding of the most common software. Starting with the basis of structural MRI contrast in brain and imaging protocols, the concepts of voxel-based and surface-based segmentation are discussed. Special emphasis is given to the typical contrast features and morphological constraints of cortical and sub-cortical grey matter. In addition to the use for voxel-based morphometry, basic applications in quantitative MRI, cortical thickness estimations, and atrophy measurements as well as assignment of cortical regions and deep brain nuclei are briefly discussed. Finally, some fields for clinical applications are given.

Investigating dynamical information transfer in the brain following a TMS pulse: Insights from structural architecture.

PubMed

Amico, Enrico; Van Mierlo, Pieter; Marinazzo, Daniele; Laureys, Steven

2015-01-01

Transcranial magnetic stimulation (TMS) has been used for more than 20 years to investigate connectivity and plasticity in the human cortex. By combining TMS with high-density electroencephalography (hd-EEG), one can stimulate any cortical area and measure the effects produced by this perturbation in the rest of the cerebral cortex. The purpose of this paper is to investigate changes of information flow in the brain after TMS from a functional and structural perspective, using multimodal modeling of source reconstructed TMS/hd-EEG recordings and DTI tractography. We prove how brain dynamics induced by TMS is constrained and driven by its structure, at different spatial and temporal scales, especially when considering cross-frequency interactions. These results shed light on the function-structure organization of the brain network at the global level, and on the huge variety of information contained in it.

Evaluation of five diffeomorphic image registration algorithms for mouse brain magnetic resonance microscopy.

PubMed

Fu, Zhenrong; Lin, Lan; Tian, Miao; Wang, Jingxuan; Zhang, Baiwen; Chu, Pingping; Li, Shaowu; Pathan, Muhammad Mohsin; Deng, Yulin; Wu, Shuicai

2017-11-01

The development of genetically engineered mouse models for neuronal diseases and behavioural disorders have generated a growing need for small animal imaging. High-resolution magnetic resonance microscopy (MRM) provides powerful capabilities for noninvasive studies of mouse brains, while avoiding some limits associated with the histological procedures. Quantitative comparison of structural images is a critical step in brain imaging analysis, which highly relies on the performance of image registration techniques. Nowadays, there is a mushrooming growth of human brain registration algorithms, while fine-tuning of those algorithms for mouse brain MRMs is rarely addressed. Because of their topology preservation property and outstanding performance in human studies, diffeomorphic transformations have become popular in computational anatomy. In this study, we specially tuned five diffeomorphic image registration algorithms [DARTEL, geodesic shooting, diffeo-demons, SyN (Greedy-SyN and geodesic-SyN)] for mouse brain MRMs and evaluated their performance using three measures [volume overlap percentage (VOP), residual intensity error (RIE) and surface concordance ratio (SCR)]. Geodesic-SyN performed significantly better than the other methods according to all three different measures. These findings are important for the studies on structural brain changes that may occur in wild-type and transgenic mouse brains. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Eye tracking detects disconjugate eye movements associated with structural traumatic brain injury and concussion.

PubMed

Samadani, Uzma; Ritlop, Robert; Reyes, Marleen; Nehrbass, Elena; Li, Meng; Lamm, Elizabeth; Schneider, Julia; Shimunov, David; Sava, Maria; Kolecki, Radek; Burris, Paige; Altomare, Lindsey; Mehmood, Talha; Smith, Theodore; Huang, Jason H; McStay, Christopher; Todd, S Rob; Qian, Meng; Kondziolka, Douglas; Wall, Stephen; Huang, Paul

2015-04-15

Disconjugate eye movements have been associated with traumatic brain injury since ancient times. Ocular motility dysfunction may be present in up to 90% of patients with concussion or blast injury. We developed an algorithm for eye tracking in which the Cartesian coordinates of the right and left pupils are tracked over 200 sec and compared to each other as a subject watches a short film clip moving inside an aperture on a computer screen. We prospectively eye tracked 64 normal healthy noninjured control subjects and compared findings to 75 trauma subjects with either a positive head computed tomography (CT) scan (n=13), negative head CT (n=39), or nonhead injury (n=23) to determine whether eye tracking would reveal the disconjugate gaze associated with both structural brain injury and concussion. Tracking metrics were then correlated to the clinical concussion measure Sport Concussion Assessment Tool 3 (SCAT3) in trauma patients. Five out of five measures of horizontal disconjugacy were increased in positive and negative head CT patients relative to noninjured control subjects. Only one of five vertical disconjugacy measures was significantly increased in brain-injured patients relative to controls. Linear regression analysis of all 75 trauma patients demonstrated that three metrics for horizontal disconjugacy negatively correlated with SCAT3 symptom severity score and positively correlated with total Standardized Assessment of Concussion score. Abnormal eye-tracking metrics improved over time toward baseline in brain-injured subjects observed in follow-up. Eye tracking may help quantify the severity of ocular motility disruption associated with concussion and structural brain injury.

Eye Tracking Detects Disconjugate Eye Movements Associated with Structural Traumatic Brain Injury and Concussion

PubMed Central

Ritlop, Robert; Reyes, Marleen; Nehrbass, Elena; Li, Meng; Lamm, Elizabeth; Schneider, Julia; Shimunov, David; Sava, Maria; Kolecki, Radek; Burris, Paige; Altomare, Lindsey; Mehmood, Talha; Smith, Theodore; Huang, Jason H.; McStay, Christopher; Todd, S. Rob; Qian, Meng; Kondziolka, Douglas; Wall, Stephen; Huang, Paul

2015-01-01

Abstract Disconjugate eye movements have been associated with traumatic brain injury since ancient times. Ocular motility dysfunction may be present in up to 90% of patients with concussion or blast injury. We developed an algorithm for eye tracking in which the Cartesian coordinates of the right and left pupils are tracked over 200 sec and compared to each other as a subject watches a short film clip moving inside an aperture on a computer screen. We prospectively eye tracked 64 normal healthy noninjured control subjects and compared findings to 75 trauma subjects with either a positive head computed tomography (CT) scan (n=13), negative head CT (n=39), or nonhead injury (n=23) to determine whether eye tracking would reveal the disconjugate gaze associated with both structural brain injury and concussion. Tracking metrics were then correlated to the clinical concussion measure Sport Concussion Assessment Tool 3 (SCAT3) in trauma patients. Five out of five measures of horizontal disconjugacy were increased in positive and negative head CT patients relative to noninjured control subjects. Only one of five vertical disconjugacy measures was significantly increased in brain-injured patients relative to controls. Linear regression analysis of all 75 trauma patients demonstrated that three metrics for horizontal disconjugacy negatively correlated with SCAT3 symptom severity score and positively correlated with total Standardized Assessment of Concussion score. Abnormal eye-tracking metrics improved over time toward baseline in brain-injured subjects observed in follow-up. Eye tracking may help quantify the severity of ocular motility disruption associated with concussion and structural brain injury. PMID:25582436

Brain white matter structure and information processing speed in healthy older age.

PubMed

Kuznetsova, Ksenia A; Maniega, Susana Muñoz; Ritchie, Stuart J; Cox, Simon R; Storkey, Amos J; Starr, John M; Wardlaw, Joanna M; Deary, Ian J; Bastin, Mark E

2016-07-01

Cognitive decline, especially the slowing of information processing speed, is associated with normal ageing. This decline may be due to brain cortico-cortical disconnection caused by age-related white matter deterioration. We present results from a large, narrow age range cohort of generally healthy, community-dwelling subjects in their seventies who also had their cognitive ability tested in youth (age 11 years). We investigate associations between older age brain white matter structure, several measures of information processing speed and childhood cognitive ability in 581 subjects. Analysis of diffusion tensor MRI data using Tract-based Spatial Statistics (TBSS) showed that all measures of information processing speed, as well as a general speed factor composed from these tests (g speed), were significantly associated with fractional anisotropy (FA) across the white matter skeleton rather than in specific tracts. Cognitive ability measured at age 11 years was not associated with older age white matter FA, except for the g speed-independent components of several individual processing speed tests. These results indicate that quicker and more efficient information processing requires global connectivity in older age, and that associations between white matter FA and information processing speed (both individual test scores and g speed), unlike some other aspects of later life brain structure, are generally not accounted for by cognitive ability measured in youth.

Neuroanatomical correlates of personality in the elderly.

PubMed

Wright, Christopher I; Feczko, Eric; Dickerson, Bradford; Williams, Danielle

2007-03-01

Extraversion and neuroticism are two important and frequently studied dimensions of human personality. They describe individual differences in emotional responding that are quite stable across the adult lifespan. Neuroimaging research has begun to provide evidence that neuroticism and extraversion have specific neuroanatomical correlates within the cerebral cortex and amygdala of young adults. However, these brain areas undergo alterations in size with aging, which may influence the nature of these personality factor-brain structure associations in the elderly. One study in the elderly demonstrated associations between perisylvian cortex structure and measures of self transcendence [Kaasinen, V., Maguire, R.P., Kurki, T., Bruck, A., Rinne, J.O., 2005. Mapping brain structure and personality in late adulthood. NeuroImage 24, 315-322], but the neuroanatomical correlates of extraversion and neuroticism, or other measures of the Five Factor Model of personality have not been explored. The purpose of the present study was to investigate the structural correlates of neuroticism and extraversion in healthy elderly subjects (n=29) using neuroanatomic measures of the cerebral cortex and amygdala. We observed that the thickness of specific lateral prefrontal cortex (PFC) regions, but not amygdala volume, correlates with measures of extraversion and neuroticism. The results suggest differences in the regional neuroanatomic correlates of specific personality traits with aging. We speculate that this relates to the influences of age-related structural changes in the PFC.

Structure-Function Network Mapping and Its Assessment via Persistent Homology

PubMed Central

2017-01-01

Understanding the relationship between brain structure and function is a fundamental problem in network neuroscience. This work deals with the general method of structure-function mapping at the whole-brain level. We formulate the problem as a topological mapping of structure-function connectivity via matrix function, and find a stable solution by exploiting a regularization procedure to cope with large matrices. We introduce a novel measure of network similarity based on persistent homology for assessing the quality of the network mapping, which enables a detailed comparison of network topological changes across all possible thresholds, rather than just at a single, arbitrary threshold that may not be optimal. We demonstrate that our approach can uncover the direct and indirect structural paths for predicting functional connectivity, and our network similarity measure outperforms other currently available methods. We systematically validate our approach with (1) a comparison of regularized vs. non-regularized procedures, (2) a null model of the degree-preserving random rewired structural matrix, (3) different network types (binary vs. weighted matrices), and (4) different brain parcellation schemes (low vs. high resolutions). Finally, we evaluate the scalability of our method with relatively large matrices (2514x2514) of structural and functional connectivity obtained from 12 healthy human subjects measured non-invasively while at rest. Our results reveal a nonlinear structure-function relationship, suggesting that the resting-state functional connectivity depends on direct structural connections, as well as relatively parsimonious indirect connections via polysynaptic pathways. PMID:28046127

Prediction of brain-computer interface aptitude from individual brain structure.

PubMed

Halder, S; Varkuti, B; Bogdan, M; Kübler, A; Rosenstiel, W; Sitaram, R; Birbaumer, N

2013-01-01

Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. This confirms that structural brain traits contribute to individual performance in BCI use.

Prediction of brain-computer interface aptitude from individual brain structure

PubMed Central

Halder, S.; Varkuti, B.; Bogdan, M.; Kübler, A.; Rosenstiel, W.; Sitaram, R.; Birbaumer, N.

2013-01-01

Objective: Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. Methods: We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Results: Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Conclusions: Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. Significance: This confirms that structural brain traits contribute to individual performance in BCI use. PMID:23565083

Finding the "g"-Factor in Brain Structure Using the Method of Correlated Vectors

ERIC Educational Resources Information Center

Colom, Roberto; Jung, Rex E.; Haier, Richard J.

2006-01-01

It is unclear whether brain mechanisms underlying human intelligence are distributed throughout the brain or mainly concentrated in the frontal lobes. Data are inconsistent possibly due, at least in part, to the different ways the construct of intelligence is measured. Here we apply the method of correlated vectors to determine how the general…

Structural imaging in premanifest and manifest Huntington disease.

PubMed

Scahill, Rachael I; Andre, Ralph; Tabrizi, Sarah J; Aylward, Elizabeth H

2017-01-01

Huntington disease (HD) neuropathology has a devastating effect on brain structure and consequently brain function; neuroimaging provides a means to assess these effects in gene carriers. In this chapter we first outline the unique utility of structural imaging in understanding HD and discuss some of the acquisition and analysis techniques currently available. We review the existing literature to summarize what we know so far about structural brain changes across the spectrum of disease from premanifest through to manifest disease. We then consider how these neuroimaging findings relate to patient function and nonimaging biomarkers, and can be used to predict disease onset. Finally we review the utility of imaging measures for assessment of treatment efficacy in clinical trials. Copyright © 2017 Elsevier B.V. All rights reserved.

Does white matter structure or hippocampal volume mediate associations between cortisol and cognitive ageing?

PubMed Central

Cox, Simon R.; MacPherson, Sarah E.; Ferguson, Karen J.; Royle, Natalie A.; Maniega, Susana Muñoz; Hernández, Maria del C. Valdés; Bastin, Mark E.; MacLullich, Alasdair M.J.; Wardlaw, Joanna M.; Deary, Ian J.

2015-01-01

Elevated glucocorticoid (GC) levels putatively damage specific brain regions, which in turn may accelerate cognitive ageing. However, many studies are cross-sectional or have relatively short follow-up periods, making it difficult to relate GCs directly to changes in cognitive ability with increasing age. Moreover, studies combining endocrine, MRI and cognitive variables are scarce, measurement methods vary considerably, and formal tests of the underlying causal hypothesis (cortisol → brain → cognition) are absent. In this study, 90 men, aged 73 years, provided measures of fluid intelligence, processing speed and memory, diurnal and reactive salivary cortisol and two measures of white matter (WM) structure (WM hyperintensity volume from structural MRI and mean diffusivity averaged across 12 major tracts from diffusion tensor MRI), hippocampal volume, and also cognitive ability at age 11. We tested whether negative relationships between cognitive ageing differences (over more than 60 years) and salivary cortisol were significantly mediated by WM and hippocampal volume. Significant associations between reactive cortisol at 73 and cognitive ageing differences between 11 and 73 (r = −.28 to −.36, p < .05) were partially mediated by both WM structural measures, but not hippocampal volume. Cortisol-WM relationships were modest, as was the degree to which WM structure attenuated cortisol–cognition associations (<15%). These data support the hypothesis that GCs contribute to cognitive ageing differences from childhood to the early 70s, partly via brain WM structure. PMID:26298692

Diffusion and related transport mechanisms in brain tissue

NASA Astrophysics Data System (ADS)

Nicholson, Charles

2001-07-01

Diffusion plays a crucial role in brain function. The spaces between cells can be likened to the water phase of a foam and many substances move within this complicated region. Diffusion in this interstitial space can be accurately modelled with appropriate modifications of classical equations and quantified from measurements based on novel micro-techniques. Besides delivering glucose and oxygen from the vascular system to brain cells, diffusion also moves informational substances between cells, a process known as volume transmission. Deviations from expected results reveal how local uptake, degradation or bulk flow may modify the transport of molecules. Diffusion is also essential to many therapies that deliver drugs to the brain. The diffusion-generated concentration distributions of well-chosen molecules also reveal the structure of brain tissue. This structure is represented by the volume fraction (void space) and the tortuosity (hindrance to diffusion imposed by local boundaries or local viscosity). Analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. Theoretical and experimental approaches borrow from classical diffusion theory and from porous media concepts. Earlier studies were based on radiotracers but the recent methods use a point-source paradigm coupled with micro-sensors or optical imaging of macromolecules labelled with fluorescent tags. These concepts and methods are likely to be applicable elsewhere to measure diffusion properties in very small volumes of highly structured but delicate material.

Sexual dimorphism of volume reduction but not cognitive deficit in fetal alcohol spectrum disorders: A combined diffusion tensor imaging, cortical thickness and brain volume study.

PubMed

Treit, Sarah; Chen, Zhang; Zhou, Dongming; Baugh, Lauren; Rasmussen, Carmen; Andrew, Gail; Pei, Jacqueline; Beaulieu, Christian

2017-01-01

Quantitative magnetic resonance imaging (MRI) has revealed abnormalities in brain volumes, cortical thickness and white matter microstructure in fetal alcohol spectrum disorders (FASD); however, no study has reported all three measures within the same cohort to assess the relative magnitude of deficits, and few studies have examined sex differences. Participants with FASD (n = 70; 30 females; 5-32 years) and healthy controls (n = 74; 35 females; 5-32 years) underwent cognitive testing and MRI to assess cortical thickness, regional brain volumes and fractional anisotropy (FA)/mean diffusivity (MD) of white matter tracts. A significant effect of group, age-by-group, or sex-by-group was found for 9/9 volumes, 7/39 cortical thickness regions, 3/9 white matter tracts, and 9/10 cognitive tests, indicating group differences that in some cases differ by age or sex. Volume reductions for several structures were larger in males than females, despite similar deficits of cognition in both sexes. Correlations between brain structure and cognitive scores were found in females of both groups, but were notably absent in males. Correlations within a given MRI modality (e.g. total brain volume and caudate volume) were prevalent in both the control and FASD groups, and were more numerous than correlations between measurement types (e.g. volumes and diffusion tensor imaging) in either cohort. This multi-modal MRI study finds widespread differences of brain structure in participants with prenatal alcohol exposure, and to a greater extent in males than females which may suggest attenuation of the expected process of sexual dimorphism of brain structure during typical development.

When brain neuroscience meets hydrology: timeseries analysis methods for capturing structural and functional aspects of hydrologic connectivity

NASA Astrophysics Data System (ADS)

Ali, G.; Rinderer, M.

2016-12-01

In hydrology, several connectivity definitions exist that hinder intercomparison between different studies. Yet, consensus exists on the distinction between structural connectivity (i.e., physical adjacency of landscape elements that is thought to influence material transfer) and functional or effective connectivity (i.e., interaction or causality between spatial adjacency characteristics and temporally varying factors, leading to the connected flow of material). While hydrologists have succeeded in deriving measures of structural connectivity (SC), the quantification of functional (FC) or effective connectivity (EC) is elusive. Here we borrowed timeseries analysis methods from brain neuroscience to quantify EC and FC among groundwater (n = 34) and stream discharge (n = 1) monitoring sites in a 20-ha Swiss catchment where topography is assumed to be a major driver of connectivity. Influence maps created from elevation data were used to assess SC. FC was assessed by cross-correlation, total and partial mutual information and EC quantified via total and partial entropy, Granger causality and a phase slope index. Results show that generally, a fair percentage of structural connections were also expressed as functional or effective connections. Some FC and EC measures had clear advantages over others, for instance in terms of making a distinction between Darcian fluxes of water and pressure wave-driven processes. False-positive estimations, i.e., the detection of FC and EC despite the absence of SC, were also encountered and used to invalidate the applicability of some brain-connectivity measures in a hydrological context. While our goal was not to identify the best measure of FC or EC, our study showed that the application of brain neuroscience methods for assessing FC and EC in hydrology was possible as long as SC measures were used as constraints for (or prior beliefs about) the establishment of FC and EC.

Brain morphology in school-aged children with prenatal opioid exposure: A structural MRI study.

PubMed

Sirnes, Eivind; Oltedal, Leif; Bartsch, Hauke; Eide, Geir Egil; Elgen, Irene B; Aukland, Stein Magnus

Both animal and human studies have suggested that prenatal opioid exposure may be detrimental to the developing fetal brain. However, results are somewhat conflicting. Structural brain changes in children with prenatal opioid exposure have been reported in a few studies, and such changes may contribute to neuropsychological impairments observed in exposed children. To investigate the association between prenatal opioid exposure and brain morphology in school-aged children. A cross-sectional magnetic resonance imaging (MRI) study of prenatally opioid-exposed children and matched controls. A hospital-based sample (n=16) of children aged 10-14years with prenatal exposure to opioids and 1:1 sex- and age-matched unexposed controls. Automated brain volume measures obtained from T1-weighted MRI scans using FreeSurfer. Volumes of the basal ganglia, thalamus, and cerebellar white matter were reduced in the opioid-exposed group, whereas there were no statistically significant differences in global brain measures (total brain, cerebral cortex, and cerebral white matter volumes). In line with the limited findings reported in the literature to date, our study showed an association between prenatal opioid exposure and reduced regional brain volumes. Adverse effects of opioids on the developing fetal brain may explain this association. However, further research is needed to explore the causal nature and functional consequences of these findings. Copyright © 2017 Elsevier B.V. All rights reserved.

Infant fMRI: A Model System for Cognitive Neuroscience.

PubMed

Ellis, Cameron T; Turk-Browne, Nicholas B

2018-05-01

Our understanding of the typical human brain has benefitted greatly from studying different kinds of brains and their associated behavioral repertoires, including animal models and neuropsychological patients. This same comparative perspective can be applied to early development - the environment, behavior, and brains of infants provide a model system for understanding how the mature brain works. This approach requires noninvasive methods for measuring brain function in awake, behaving infants. fMRI is becoming increasingly viable for this purpose, with the unique ability to precisely measure the entire brain, including both cortical and subcortical structures. Here we discuss potential lessons from infant fMRI for several domains of adult cognition and consider the challenges of conducting such research and how they might be mitigated. Copyright © 2018 Elsevier Ltd. All rights reserved.

Increased densities of monocarboxylate transport protein MCT1 after chronic administration of nicotine in rat brain.

PubMed

Canis, Martin; Mack, Brigitte; Gires, Olivier; Maurer, Martin H; Kuschinsky, Wolfgang; Duembgen, Lutz; Duelli, Roman

2009-08-01

Chronic administration of nicotine is followed by a general stimulation of brain metabolism that results in a distinct increase of glucose transport protein densities for Glut1 and Glu3, and local cerebral glucose utilization (LCGU). This increase of LCGU might be paralleled by an enhanced production of lactate. Therefore, the question arose as to whether chronic nicotine infusion is accompanied by increased local densities of monocarboxylate transporter MCT1 in the brain. Secondly, we inquired whether LCGU might be correlated with local densities of MCT1 during normal conditions and after chronic nicotine infusion. Nicotine was given subcutaneously for 1 week by osmotic mini-pumps and local densities of MCT1 were measured by immunoautoradiographic methods in cryosections of rat brains. MCT1 density was significantly increased in 21 of 32 brain structures investigated (median increase 15.0+/-3.6%). Immunohistochemical stainings of these substructures revealed an over-expression of MCT1 within endothelial cells and astrocytes of treated animals. A comparison of 23 MCT1 densities with LCGU measured in the same structures in a previous study revealed a partial correlation between both parameters under control conditions and after chronic nicotine infusion. 10 out of 23 brain areas, which showed a significant increase of MCT1 density due to chronic nicotine infusion, also showed a significant increase of LCGU. In summary, our data show that chronic nicotine infusion induces a moderate increase of local and global density of MCT1 in defined brain structures. However, in terms of brain topologies and substructures this phenomenon did partially match with increased LCGU. It is concluded that MCT1 transporters were upregulated during chronic nicotine infusion at the level of brain substructures and, at least partially, independently of LCGU.

The impact of brain size on pilot performance varies with aviation training and years of education

PubMed Central

Adamson, Maheen M.; Samarina, Viktoriya; Xiangyan, Xu; Huynh, Virginia; Kennedy, Quinn; Weiner, Michael; Yesavage, Jerome; Taylor, Joy L.

2010-01-01

Previous studies have consistently reported age-related changes in cognitive abilities and brain structure. Previous studies also suggest compensatory roles for specialized training, skill, and years of education in the age-related decline of cognitive function. The Stanford/VA Aviation Study examines the influence of specialized training and skill level (expertise) on age-related changes in cognition and brain structure. This preliminary report examines the effect of aviation expertise, years of education, age, and brain size on flight simulator performance in pilots aged 45–68 years. Fifty-one pilots were studied with structural magnetic resonance imaging, flight simulator, and processing speed tasks. There were significant main effects of age (p < .01) and expertise (p < .01), but not of whole brain size (p > .1) or education (p > .1), on flight simulator performance. However, even though age and brain size were correlated (r = −0.41), age differences in flight simulator performance were not explained by brain size. Both aviation expertise and education were involved in an interaction with brain size in predicting flight simulator performance (p < .05). These results point to the importance of examining measures of expertise and their interactions to assess age-related cognitive changes. PMID:20193103

Mechanical properties of the in vivo adolescent human brain.

PubMed

McIlvain, Grace; Schwarb, Hillary; Cohen, Neal J; Telzer, Eva H; Johnson, Curtis L

2018-06-10

Viscoelastic mechanical properties of the in vivo human brain, measured noninvasively with magnetic resonance elastography (MRE), have recently been shown to be affected by aging and neurological disease, as well as relate to performance on cognitive tasks in adults. The demonstrated sensitivity of brain mechanical properties to neural tissue integrity make them an attractive target for examining the developing brain; however, to date, MRE studies on children are lacking. In this work, we characterized global and regional brain stiffness and damping ratio in a sample of 40 adolescents aged 12-14 years, including the lobes of the cerebrum and subcortical gray matter structures. We also compared the properties of the adolescent brain to the healthy adult brain. Temporal and parietal cerebral lobes were softer in adolescents compared to adults. We found that of subcortical gray matter structures, the caudate and the putamen were significantly stiffer in adolescents, and that the hippocampus and amygdala were significantly less stiff than all other subcortical structures. This study provides the first detailed characterization of adolescent brain viscoelasticity and provides baseline data to be used in studying development and pathophysiology. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

All brains are made of this: a fundamental building block of brain matter with matching neuronal and glial masses.

PubMed

Mota, Bruno; Herculano-Houzel, Suzana

2014-01-01

How does the size of the glial and neuronal cells that compose brain tissue vary across brain structures and species? Our previous studies indicate that average neuronal size is highly variable, while average glial cell size is more constant. Measuring whole cell sizes in vivo, however, is a daunting task. Here we use chi-square minimization of the relationship between measured neuronal and glial cell densities in the cerebral cortex, cerebellum, and rest of brain in 27 mammalian species to model neuronal and glial cell mass, as well as the neuronal mass fraction of the tissue (the fraction of tissue mass composed by neurons). Our model shows that while average neuronal cell mass varies by over 500-fold across brain structures and species, average glial cell mass varies only 1.4-fold. Neuronal mass fraction varies typically between 0.6 and 0.8 in all structures. Remarkably, we show that two fundamental, universal relationships apply across all brain structures and species: (1) the glia/neuron ratio varies with the total neuronal mass in the tissue (which in turn depends on variations in average neuronal cell mass), and (2) the neuronal mass per glial cell, and with it the neuronal mass fraction and neuron/glia mass ratio, varies with average glial cell mass in the tissue. We propose that there is a fundamental building block of brain tissue: the glial mass that accompanies a unit of neuronal mass. We argue that the scaling of this glial mass is a consequence of a universal mechanism whereby numbers of glial cells are added to the neuronal parenchyma during development, irrespective of whether the neurons composing it are large or small, but depending on the average mass of the glial cells being added. We also show how evolutionary variations in neuronal cell mass, glial cell mass and number of neurons suffice to determine the most basic characteristics of brain structures, such as mass, glia/neuron ratio, neuron/glia mass ratio, and cell densities.

Structural Similarities between Brain and Linguistic Data Provide Evidence of Semantic Relations in the Brain

PubMed Central

Crangle, Colleen E.; Perreau-Guimaraes, Marcos; Suppes, Patrick

2013-01-01

This paper presents a new method of analysis by which structural similarities between brain data and linguistic data can be assessed at the semantic level. It shows how to measure the strength of these structural similarities and so determine the relatively better fit of the brain data with one semantic model over another. The first model is derived from WordNet, a lexical database of English compiled by language experts. The second is given by the corpus-based statistical technique of latent semantic analysis (LSA), which detects relations between words that are latent or hidden in text. The brain data are drawn from experiments in which statements about the geography of Europe were presented auditorily to participants who were asked to determine their truth or falsity while electroencephalographic (EEG) recordings were made. The theoretical framework for the analysis of the brain and semantic data derives from axiomatizations of theories such as the theory of differences in utility preference. Using brain-data samples from individual trials time-locked to the presentation of each word, ordinal relations of similarity differences are computed for the brain data and for the linguistic data. In each case those relations that are invariant with respect to the brain and linguistic data, and are correlated with sufficient statistical strength, amount to structural similarities between the brain and linguistic data. Results show that many more statistically significant structural similarities can be found between the brain data and the WordNet-derived data than the LSA-derived data. The work reported here is placed within the context of other recent studies of semantics and the brain. The main contribution of this paper is the new method it presents for the study of semantics and the brain and the focus it permits on networks of relations detected in brain data and represented by a semantic model. PMID:23799009

The structural, connectomic and network covariance of the human brain.

PubMed

Irimia, Andrei; Van Horn, John D

2013-02-01

Though it is widely appreciated that complex structural, functional and morphological relationships exist between distinct areas of the human cerebral cortex, the extent to which such relationships coincide remains insufficiently appreciated. Here we determine the extent to which correlations between brain regions are modulated by either structural, connectomic or network-theoretic properties using a structural neuroimaging data set of magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) volumes acquired from N=110 healthy human adults. To identify the linear relationships between all available pairs of regions, we use canonical correlation analysis to test whether a statistically significant correlation exists between each pair of cortical parcels as quantified via structural, connectomic or network-theoretic measures. In addition to this, we investigate (1) how each group of canonical variables (whether structural, connectomic or network-theoretic) contributes to the overall correlation and, additionally, (2) whether each individual variable makes a significant contribution to the test of the omnibus null hypothesis according to which no correlation between regions exists across subjects. We find that, although region-to-region correlations are extensively modulated by structural and connectomic measures, there are appreciable differences in how these two groups of measures drive inter-regional correlation patterns. Additionally, our results indicate that the network-theoretic properties of the cortex are strong modulators of region-to-region covariance. Our findings are useful for understanding the structural and connectomic relationship between various parts of the brain, and can inform theoretical and computational models of cortical information processing. Published by Elsevier Inc.

Do antipsychotic drugs affect brain structure? A systematic and critical review of MRI findings.

PubMed

Navari, S; Dazzan, P

2009-11-01

The potential effects of antipsychotic drugs on brain structure represent a key factor in understanding neuroanatomical changes in psychosis. This review addresses two issues: (1) do antipsychotic medications induce changes in total or regional human brain volumes and (2) do such effects depend on antipsychotic type? A systematic review of studies reporting structural brain magnetic resonance imaging (MRI) measures: (1) directly in association with antipsychotic use; and (2) in patients receiving lifetime treatment with antipsychotics in comparison with drug-naive patients or healthy controls. We searched Medline and EMBASE databases using the medical subject heading terms: 'antipsychotics' AND 'brain' AND (MRI NOT functional). The search included studies published up to 31 January 2007. Wherever possible, we reported the effect size of the difference observed. Thirty-three studies met our inclusion criteria. The results suggest that antipsychotics act regionally rather than globally on the brain. These volumetric changes are of a greater magnitude in association with typical than with atypical antipsychotic use. Indeed, there is evidence of a specific effect of antipsychotic type on the basal ganglia, with typicals specifically increasing the volume of these structures. Differential effects of antipsychotic type may also be present on the thalamus and the cortex, but data on these and other brain areas are more equivocal. Antipsychotic treatment potentially contributes to the brain structural changes observed in psychosis. Future research should take into account these potential effects, and use adequate sample sizes, to allow improved interpretation of neuroimaging findings in these disorders.

Numerical analysis of the diffusive mass transport in brain tissues with applications to optical sensors

NASA Astrophysics Data System (ADS)

Neculae, Adrian P.; Otte, Andreas; Curticapean, Dan

2013-03-01

In the brain-cell microenvironment, diffusion plays an important role: apart from delivering glucose and oxygen from the vascular system to brain cells, it also moves informational substances between cells. The brain is an extremely complex structure of interwoven, intercommunicating cells, but recent theoretical and experimental works showed that the classical laws of diffusion, cast in the framework of porous media theory, can deliver an accurate quantitative description of the way molecules are transported through this tissue. The mathematical modeling and the numerical simulations are successfully applied in the investigation of diffusion processes in tissues, replacing the costly laboratory investigations. Nevertheless, modeling must rely on highly accurate information regarding the main parameters (tortuosity, volume fraction) which characterize the tissue, obtained by structural and functional imaging. The usual techniques to measure the diffusion mechanism in brain tissue are the radiotracer method, the real time iontophoretic method and integrative optical imaging using fluorescence microscopy. A promising technique for obtaining the values for characteristic parameters of the transport equation is the direct optical investigation using optical fibers. The analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. This paper presents a set of computations concerning the mass transport inside the brain tissue, for different types of cells. By measuring the time evolution of the concentration profile of an injected substance and using suitable fitting procedures, the main parameters characterizing the tissue can be determined. This type of analysis could be an important tool in understanding the functional mechanisms of effective drug delivery in complex structures such as the brain tissue. It also offers possibilities to realize optical imaging methods for in vitro and in vivo measurements using optical fibers. The model also may help in radiotracer biomarker models for the understanding of the mechanism of action of new chemical entities.

The Alzheimer’s Disease Neuroimaging Initiative: Progress report and future plans

PubMed Central

Weiner, Michael W.; Aisen, Paul S.; Jack, Clifford R.; Jagust, William J.; Trojanowski, John Q.; Shaw, Leslie; Saykin, Andrew J.; Morris, John C.; Cairns, Nigel; Beckett, Laurel A.; Toga, Arthur; Green, Robert; Walter, Sarah; Soares, Holly; Snyder, Peter; Siemers, Eric; Potter, William; Cole, Patricia E.; Schmidt, Mark

2010-01-01

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year re-search project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer’s disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD. PMID:20451868

Large-scale topology and the default mode network in the mouse connectome

PubMed Central

Stafford, James M.; Jarrett, Benjamin R.; Miranda-Dominguez, Oscar; Mills, Brian D.; Cain, Nicholas; Mihalas, Stefan; Lahvis, Garet P.; Lattal, K. Matthew; Mitchell, Suzanne H.; David, Stephen V.; Fryer, John D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans. PMID:25512496

Symptoms of posttraumatic stress disorder and exposure to traumatic stressors are related to brain structural volumes and behavioral measures of affective stimulus processing in police officers.

PubMed

Shucard, Janet Louise; Cox, Jennifer; Shucard, David William; Fetter, Holly; Chung, Charles; Ramasamy, Deepa; Violanti, John

2012-10-30

Traumatic experiences and subsequent symptoms of posttraumatic stress disorder (PTSD) have been shown to affect brain structure and function. Although police officers are routinely exposed to traumatic events, the neurobehavioral effects of trauma in this population have rarely been studied. In this study, police officers with exposure to trauma-related stressors underwent structural magnetic resonance imaging (MRI). They also provided valence and arousal ratings of neutral and negative (trauma-related) picture stimuli. Relationships were examined among PTSD symptom scores (avoidance, reexperiencing, and hyperarousal), picture ratings, structural MRI measures, and number of trauma exposures. We hypothesized that greater PTSD symptomatology would be related to higher valence and arousal ratings of trauma-related stimuli and to decreased volume of limbic and Basal ganglia structures. Results revealed that officers with higher reexperiencing scores tended to have higher arousal ratings of negative pictures and reduced amygdala, thalamus, and globus pallidus volumes. There was a trend toward higher reexperiencing and reduced hippocampal volume. The frequency of traumatic exposures was also related to MRI measures of atrophy and to increased PTSD symptomatology. These findings suggest that chronic reexperiencing of traumatic events may result in volumetric reductions in brain structures associated with autonomic arousal and the acquisition of conditioned fear. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Hemodynamic and morphologic responses in mouse brain during acute head injury imaged by multispectral structured illumination

NASA Astrophysics Data System (ADS)

Volkov, Boris; Mathews, Marlon S.; Abookasis, David

2015-03-01

Multispectral imaging has received significant attention over the last decade as it integrates spectroscopy, imaging, tomography analysis concurrently to acquire both spatial and spectral information from biological tissue. In the present study, a multispectral setup based on projection of structured illumination at several near-infrared wavelengths and at different spatial frequencies is applied to quantitatively assess brain function before, during, and after the onset of traumatic brain injury in an intact mouse brain (n=5). For the production of head injury, we used the weight drop method where weight of a cylindrical metallic rod falling along a metal tube strikes the mouse's head. Structured light was projected onto the scalp surface and diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse head. Following data analysis, we were able to concurrently show a series of hemodynamic and morphologic changes over time including higher deoxyhemoglobin, reduction in oxygen saturation, cell swelling, etc., in comparison with baseline measurements. Overall, results demonstrates the capability of multispectral imaging based structured illumination to detect and map of brain tissue optical and physiological properties following brain injury in a simple noninvasive and noncontact manner.

Development of representative magnetic resonance imaging-based atlases of the canine brain and evaluation of three methods for atlas-based segmentation.

PubMed

Milne, Marjorie E; Steward, Christopher; Firestone, Simon M; Long, Sam N; O'Brien, Terrence J; Moffat, Bradford A

2016-04-01

To develop representative MRI atlases of the canine brain and to evaluate 3 methods of atlas-based segmentation (ABS). 62 dogs without clinical signs of epilepsy and without MRI evidence of structural brain disease. The MRI scans from 44 dogs were used to develop 4 templates on the basis of brain shape (brachycephalic, mesaticephalic, dolichocephalic, and combined mesaticephalic and dolichocephalic). Atlas labels were generated by segmenting the brain, ventricular system, hippocampal formation, and caudate nuclei. The MRI scans from the remaining 18 dogs were used to evaluate 3 methods of ABS (manual brain extraction and application of a brain shape-specific template [A], automatic brain extraction and application of a brain shape-specific template [B], and manual brain extraction and application of a combined template [C]). The performance of each ABS method was compared by calculation of the Dice and Jaccard coefficients, with manual segmentation used as the gold standard. Method A had the highest mean Jaccard coefficient and was the most accurate ABS method assessed. Measures of overlap for ABS methods that used manual brain extraction (A and C) ranged from 0.75 to 0.95 and compared favorably with repeated measures of overlap for manual extraction, which ranged from 0.88 to 0.97. Atlas-based segmentation was an accurate and repeatable method for segmentation of canine brain structures. It could be performed more rapidly than manual segmentation, which should allow the application of computer-assisted volumetry to large data sets and clinical cases and facilitate neuroimaging research and disease diagnosis.

No association between hair cortisol or cortisone and brain morphology in children.

PubMed

Chen, Ruoqing; Muetzel, Ryan L; El Marroun, Hanan; Noppe, Gerard; van Rossum, Elisabeth F C; Jaddoe, Vincent W; Verhulst, Frank C; White, Tonya; Fang, Fang; Tiemeier, Henning

2016-12-01

Little is known about the relationship between the long-term hypothalamic-pituitary-adrenal (HPA) axis functioning and brain structure in children. Glucocorticoid in hair has emerged as an important biomarker of HPA activity. In this study, we investigated the associations of hair cortisol and cortisone concentrations with brain morphology in young children. We included 219 children aged 6-10 years from the Generation R Study in Rotterdam, the Netherlands. We examined cortisol and cortisone concentrations by hair analysis using liquid chromatography-tandem mass spectrometry, and assessed brain morphometric measures with structural magnetic resonance imaging. The relationships of hair cortisol and cortisone concentrations with brain volumetrics, cortical thickness, cortical surface area and gyrification were analyzed separately after adjustment for several potential confounding factors. We observed a positive association between cortisol concentrations and cortical surface area in the parietal lobe, positive associations of cortisone concentrations with thalamus volume, occipital lobe volume and cortical surface area in the parietal lobe, and a negative association between cortisone concentrations and cortical surface area in the temporal lobe in the regions of interest analyses. A negative association between cortisol or cortisone concentrations and hippocampal volume was observed in children with behavioral problems. The whole brain vertex-wise analyses did however not show any association between cortisol or cortisone concentration and brain morphometric measures after correction for multiple testing. Although some associations are noted in region of interest analyses, we do not observe clear association of hair cortisol or cortisone with brain morphometric measures in typically developing young children. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling the impact of COPD on the brain.

PubMed

Borson, Soo; Scanlan, James; Friedman, Seth; Zuhr, Elizabeth; Fields, Julie; Aylward, Elizabeth; Mahurin, Rodney; Richards, Todd; Anzai, Yoshimi; Yukawa, Michi; Yeh, Shingshing

2008-01-01

Previous studies have shown that COPD adversely affects distant organs and body systems, including the brain. This pilot study aims to model the relationships between respiratory insufficiency and domains related to brain function, including low mood, subtly impaired cognition, systemic inflammation, and brain structural and neurochemical abnormalities. Nine healthy controls were compared with 18 age- and education-matched medically stable-COPD patients, half of whom were oxygen-dependent. Measures included depression, anxiety, cognition, health status, spirometry, oximetry at rest and during 6-minute walk, and resting plasma cytokines and soluble receptors, brain MRI, and MR spectroscopy in regions relevant to mood and cognition. ANOVA was used to compare controls with patients and with COPD subgroups (oxygen users [n = 9] and nonusers [n = 9]), and only variables showing group differences at p < or = 0.05 were included in multiple regressions controlling for age, gender, and education to develop the final model. Controls and COPD patients differed significantly in global cognition and memory, mood, and soluble TNFR1 levels but not brain structural or neurochemical measures. Multiple regressions identified pathways linking disease severity with impaired performance on sensitive cognitive processing measures, mediated through oxygen dependence, and with systemic inflammation (TNFR1), related through poor 6-minute walk performance. Oxygen desaturation with activity was related to indicators of brain tissue damage (increased frontal choline, which in turn was associated with subcortical white matter attenuation). This empirically derived model provides a conceptual framework for future studies of clinical interventions to protect the brain in patients with COPD, such as earlier oxygen supplementation for patients with desaturation during everyday activities.

Modeling the impact of COPD on the brain

PubMed Central

Borson, Soo; Scanlan, James; Friedman, Seth; Zuhr, Elizabeth; Fields, Julie; Aylward, Elizabeth; Mahurin, Rodney; Richards, Todd; Anzai, Yoshimi; Yukawa, Michi; Yeh, Shingshing

2008-01-01

Previous studies have shown that COPD adversely affects distant organs and body systems, including the brain. This pilot study aims to model the relationships between respiratory insufficiency and domains related to brain function, including low mood, subtly impaired cognition, systemic inflammation, and brain structural and neurochemical abnormalities. Nine healthy controls were compared with 18 age- and education-matched medically stable COPD patients, half of whom were oxygen-dependent. Measures included depression, anxiety, cognition, health status, spirometry, oximetry at rest and during 6-minute walk, and resting plasma cytokines and soluble receptors, brain MRI, and MR spectroscopy in regions relevant to mood and cognition. ANOVA was used to compare controls with patients and with COPD subgroups (oxygen users [n = 9] and nonusers [n = 9]), and only variables showing group differences at p ≤ 0.05 were included in multiple regressions controlling for age, gender, and education to develop the final model. Controls and COPD patients differed significantly in global cognition and memory, mood, and soluble TNFR1 levels but not brain structural or neurochemical measures. Multiple regressions identified pathways linking disease severity with impaired performance on sensitive cognitive processing measures, mediated through oxygen dependence, and with systemic inflammation (TNFR1), related through poor 6-minute walk performance. Oxygen desaturation with activity was related to indicators of brain tissue damage (increased frontal choline, which in turn was associated with subcortical white matter attenuation). This empirically derived model provides a conceptual framework for future studies of clinical interventions to protect the brain in patients with COPD, such as earlier oxygen supplementation for patients with desaturation during everyday activities. PMID:18990971

Brain Connectivity and Visual Attention

PubMed Central

Parks, Emily L.

2013-01-01

Abstract Emerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures. PMID:23597177

Syringe Injectable Electronics: Precise Targeted Delivery with Quantitative Input/Output Connectivity.

PubMed

Hong, Guosong; Fu, Tian-Ming; Zhou, Tao; Schuhmann, Thomas G; Huang, Jinlin; Lieber, Charles M

2015-10-14

Syringe-injectable mesh electronics with tissue-like mechanical properties and open macroporous structures is an emerging powerful paradigm for mapping and modulating brain activity. Indeed, the ultraflexible macroporous structure has exhibited unprecedented minimal/noninvasiveness and the promotion of attractive interactions with neurons in chronic studies. These same structural features also pose new challenges and opportunities for precise targeted delivery in specific brain regions and quantitative input/output (I/O) connectivity needed for reliable electrical measurements. Here, we describe new results that address in a flexible manner both of these points. First, we have developed a controlled injection approach that maintains the extended mesh structure during the "blind" injection process, while also achieving targeted delivery with ca. 20 μm spatial precision. Optical and microcomputed tomography results from injections into tissue-like hydrogel, ex vivo brain tissue, and in vivo brains validate our basic approach and demonstrate its generality. Second, we present a general strategy to achieve up to 100% multichannel I/O connectivity using an automated conductive ink printing methodology to connect the mesh electronics and a flexible flat cable, which serves as the standard "plug-in" interface to measurement electronics. Studies of resistance versus printed line width were used to identify optimal conditions, and moreover, frequency-dependent noise measurements show that the flexible printing process yields values comparable to commercial flip-chip bonding technology. Our results address two key challenges faced by syringe-injectable electronics and thereby pave the way for facile in vivo applications of injectable mesh electronics as a general and powerful tool for long-term mapping and modulation of brain activity in fundamental neuroscience through therapeutic biomedical studies.

Structural whole-brain covariance of the anterior and posterior hippocampus: Associations with age and memory.

PubMed

Nordin, Kristin; Persson, Jonas; Stening, Eva; Herlitz, Agneta; Larsson, Elna-Marie; Söderlund, Hedvig

2018-02-01

The hippocampus (HC) interacts with distributed brain regions to support memory and shows significant volume reductions in aging, but little is known about age effects on hippocampal whole-brain structural covariance. It is also unclear whether the anterior and posterior HC show similar or distinct patterns of whole-brain covariance and to what extent these are related to memory functions organized along the hippocampal longitudinal axis. Using the multivariate approach partial least squares, we assessed structural whole-brain covariance of the HC in addition to regional volume, in young, middle-aged and older adults (n = 221), and assessed associations with episodic and spatial memory. Based on findings of sex differences in both memory and brain aging, we further considered sex as a potential modulating factor of age effects. There were two main covariance patterns: one capturing common anterior and posterior covariance, and one differentiating the two regions by capturing anterior-specific covariance only. These patterns were differentially related to associative memory while unrelated to measures of single-item memory and spatial memory. Although patterns were qualitatively comparable across age groups, participants' expression of both patterns decreased with age, independently of sex. The results suggest that the organization of hippocampal structural whole-brain covariance remains stable across age, but that the integrity of these networks decreases as the brain undergoes age-related alterations. © 2017 Wiley Periodicals, Inc.

Neuroanatomy of the killer whale (Orcinus orca): a magnetic resonance imaging investigation of structure with insights on function and evolution.

PubMed

Wright, Alexandra; Scadeng, Miriam; Stec, Dominik; Dubowitz, Rebecca; Ridgway, Sam; Leger, Judy St

2017-01-01

The evolutionary process of adaptation to an obligatory aquatic existence dramatically modified cetacean brain structure and function. The brain of the killer whale (Orcinus orca) may be the largest of all taxa supporting a panoply of cognitive, sensory, and sensorimotor abilities. Despite this, examination of the O. orca brain has been limited in scope resulting in significant deficits in knowledge concerning its structure and function. The present study aims to describe the neural organization and potential function of the O. orca brain while linking these traits to potential evolutionary drivers. Magnetic resonance imaging was used for volumetric analysis and three-dimensional reconstruction of an in situ postmortem O. orca brain. Measurements were determined for cortical gray and cerebral white matter, subcortical nuclei, cerebellar gray and white matter, corpus callosum, hippocampi, superior and inferior colliculi, and neuroendocrine structures. With cerebral volume comprising 81.51 % of the total brain volume, this O. orca brain is one of the most corticalized mammalian brains studied to date. O. orca and other delphinoid cetaceans exhibit isometric scaling of cerebral white matter with increasing brain size, a trait that violates an otherwise evolutionarily conserved cerebral scaling law. Using comparative neurobiology, it is argued that the divergent cerebral morphology of delphinoid cetaceans compared to other mammalian taxa may have evolved in response to the sensorimotor demands of the aquatic environment. Furthermore, selective pressures associated with the evolution of echolocation and unihemispheric sleep are implicated in substructure morphology and function. This neuroanatomical dataset, heretofore absent from the literature, provides important quantitative data to test hypotheses regarding brain structure, function, and evolution within Cetacea and across Mammalia.

A thermocouple thermode for small animals

NASA Technical Reports Server (NTRS)

Williams, B. A.

1972-01-01

Thermode composed of two thin-walled stainless steel hypodermic needles and cooper-constantan thermocouple or small thermistor to indicate temperature at point of perfusion is used to measure brain temperature in animals. Because of relatively small size of thermode, structural damage to brain is minimized.

Common and distinct changes of default mode and salience network in schizophrenia and major depression.

PubMed

Shao, Junming; Meng, Chun; Tahmasian, Masoud; Brandl, Felix; Yang, Qinli; Luo, Guangchun; Luo, Cheng; Yao, Dezhong; Gao, Lianli; Riedl, Valentin; Wohlschläger, Afra; Sorg, Christian

2018-02-19

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.

Long-term effects of marijuana use on the brain

PubMed Central

Filbey, Francesca M.; Aslan, Sina; Calhoun, Vince D.; Spence, Jeffrey S.; Damaraju, Eswar; Caprihan, Arvind; Segall, Judith

2014-01-01

Questions surrounding the effects of chronic marijuana use on brain structure continue to increase. To date, however, findings remain inconclusive. In this comprehensive study that aimed to characterize brain alterations associated with chronic marijuana use, we measured gray matter (GM) volume via structural MRI across the whole brain by using voxel-based morphology, synchrony among abnormal GM regions during resting state via functional connectivity MRI, and white matter integrity (i.e., structural connectivity) between the abnormal GM regions via diffusion tensor imaging in 48 marijuana users and 62 age- and sex-matched nonusing controls. The results showed that compared with controls, marijuana users had significantly less bilateral orbitofrontal gyri volume, higher functional connectivity in the orbitofrontal cortex (OFC) network, and higher structural connectivity in tracts that innervate the OFC (forceps minor) as measured by fractional anisotropy (FA). Increased OFC functional connectivity in marijuana users was associated with earlier age of onset. Lastly, a quadratic trend was observed suggesting that the FA of the forceps minor tract initially increased following regular marijuana use but decreased with protracted regular use. This pattern may indicate differential effects of initial and chronic marijuana use that may reflect complex neuroadaptive processes in response to marijuana use. Despite the observed age of onset effects, longitudinal studies are needed to determine causality of these effects. PMID:25385625

Brain structure characteristics in intellectually superior schizophrenia.

PubMed

Vaskinn, Anja; Hartberg, Cecilie B; Sundet, Kjetil; Westlye, Lars T; Andreassen, Ole A; Melle, Ingrid; Agartz, Ingrid

2015-04-30

The current study aims to fill a gap in the knowledge base by investigating the structural brain characteristics of individuals with schizophrenia and superior intellectual abilities. Subcortical volumes, cortical thickness and cortical surface area were examined in intellectually normal and intellectually superior participants with schizophrenia and their IQ-matched healthy controls, as well as in intellectually low schizophrenia participants. We replicated significant diagnostic group effects on hippocampal and ventricular size after correction for multiple comparisons. There were no statistically significant effects of intellectual level or of the interaction between diagnostic group and intellectual level. Effect sizes indicated that differences between schizophrenia and healthy control participants were of similar magnitude at both intellectual levels for all three types of morphological data. A secondary analysis within the schizophrenia group, including participants with low intellectual abilities, yielded numerical, but no statistically significant differences on any structural brain measure. The present findings indicate that the brain structure abnormalities in schizophrenia are present at all intellectual levels, and individuals with schizophrenia and superior intellectual abilities have brain structure abnormalities of the same magnitude as individuals with schizophrenia and normal intellectual abilities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Estimated maximal and current brain volume predict cognitive ability in old age.

PubMed

Royle, Natalie A; Booth, Tom; Valdés Hernández, Maria C; Penke, Lars; Murray, Catherine; Gow, Alan J; Maniega, Susana Muñoz; Starr, John; Bastin, Mark E; Deary, Ian J; Wardlaw, Joanna M

2013-12-01

Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging. Copyright © 2013 Elsevier Inc. All rights reserved.

Repeated head trauma is associated with smaller thalamic volumes and slower processing speed: the Professional Fighters’ Brain Health Study

PubMed Central

Bernick, Charles; Banks, Sarah J; Shin, Wanyong; Obuchowski, Nancy; Butler, Sam; Noback, Michael; Phillips, Michael; Lowe, Mark; Jones, Stephen; Modic, Michael

2015-01-01

Objectives Cumulative head trauma may alter brain structure and function. We explored the relationship between exposure variables, cognition and MRI brain structural measures in a cohort of professional combatants. Methods 224 fighters (131 mixed martial arts fighters and 93 boxers) participating in the Professional Fighters Brain Health Study, a longitudinal cohort study of licensed professional combatants, were recruited, as were 22 controls. Each participant underwent computerised cognitive testing and volumetric brain MRI. Fighting history including years of fighting and fights per year was obtained from self-report and published records. Statistical analyses of the baseline evaluations were applied cross-sectionally to determine the relationship between fight exposure variables and volumes of the hippocampus, amygdala, thalamus, caudate, putamen. Moreover, the relationship between exposure and brain volumes with cognitive function was assessed. Results Increasing exposure to repetitive head trauma measured by number of professional fights, years of fighting, or a Fight Exposure Score (FES) was associated with lower brain volumes, particularly the thalamus and caudate. In addition, speed of processing decreased with decreased thalamic volumes and with increasing fight exposure. Higher scores on a FES used to reflect exposure to repetitive head trauma were associated with greater likelihood of having cognitive impairment. Conclusions Greater exposure to repetitive head trauma is associated with lower brain volumes and lower processing speed in active professional fighters. PMID:25633832

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468

Brain function and structure and risk for incident diabetes: The Atherosclerosis Risk in Communities Study.

PubMed

Bancks, Michael P; Alonso, Alvaro; Gottesman, Rebecca F; Mosley, Thomas H; Selvin, Elizabeth; Pankow, James S

2017-12-01

Diabetes is prospectively associated with cognitive decline. Whether lower cognitive function and worse brain structure are prospectively associated with incident diabetes is unclear. We analyzed data for 10,133 individuals with cognitive function testing (1990-1992) and 1212 individuals with brain magnetic resonance imaging (1993-1994) from the Atherosclerosis Risk in Communities cohort. We estimated hazard ratios for incident diabetes through 2014 after adjustment for traditional diabetes risk factors and cohort attrition. Higher level of baseline cognitive function was associated with lower risk for diabetes (per 1 standard deviation, hazard ratio = 0.94; 95% confidence interval = 0.90, 0.98). This association did not persist after accounting for baseline glucose level, case ascertainment methods, and cohort attrition. No association was observed between any brain magnetic resonance imaging measure and incident diabetes. This is one of the first studies to prospectively evaluate the association between both cognitive function and brain structure and the incidence of diabetes. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

How age of acquisition influences brain architecture in bilinguals

PubMed Central

Wei, Miao; Joshi, Anand A.; Zhang, Mingxia; Mei, Leilei; Manis, Franklin R.; He, Qinghua; Beattie, Rachel L.; Xue, Gui; Shattuck, David W.; Leahy, Richard M.; Xue, Feng; Houston, Suzanne M.; Chen, Chuansheng; Dong, Qi; Lu, Zhong-Lin

2016-01-01

In the present study, we explored how Age of Acquisition (AoA) of L2 affected brain structures in bilingual individuals. Thirty-six native English speakers who were bilingual were scanned with high resolution MRI. After MRI signal intensity inhomogeneity correction, we applied both voxel-based morphometry (VBM) and surface-based morphometry (SBM) approaches to the data. VBM analysis was performed using FSL’s standard VBM processing pipeline. For the SBM analysis, we utilized a semi-automated sulci delineation procedure, registered the brains to an atlas, and extracted measures of twenty four pre-selected regions of interest. We addressed three questions: (1) Which areas are more susceptible to differences in AoA? (2) How do AoA, proficiency and current level of exposure work together in predicting structural differences in the brain? And (3) What is the direction of the effect of AoA on regional volumetric and surface measures? Both VBM and SBM results suggested that earlier second language exposure was associated with larger volumes in the right parietal cortex. Consistently, SBM showed that the cortical area of the right superior parietal lobule increased as AoA decreased. In contrast, in the right pars orbitalis of the inferior frontal gyrus, AoA, proficiency, and current level of exposure are equally important in accounting for the structural differences. We interpret our results in terms of current theory and research on the effects of L2 learning on brain structures and functions. PMID:27695193

Structural brain development between childhood and adulthood: Convergence across four longitudinal samples.

PubMed

Mills, Kathryn L; Goddings, Anne-Lise; Herting, Megan M; Meuwese, Rosa; Blakemore, Sarah-Jayne; Crone, Eveline A; Dahl, Ronald E; Güroğlu, Berna; Raznahan, Armin; Sowell, Elizabeth R; Tamnes, Christian K

2016-11-01

Longitudinal studies including brain measures acquired through magnetic resonance imaging (MRI) have enabled population models of human brain development, crucial for our understanding of typical development as well as neurodevelopmental disorders. Brain development in the first two decades generally involves early cortical grey matter volume (CGMV) increases followed by decreases, and monotonic increases in cerebral white matter volume (CWMV). However, inconsistencies regarding the precise developmental trajectories call into question the comparability of samples. This issue can be addressed by conducting a comprehensive study across multiple datasets from diverse populations. Here, we present replicable models for gross structural brain development between childhood and adulthood (ages 8-30years) by repeating analyses in four separate longitudinal samples (391 participants; 852 scans). In addition, we address how accounting for global measures of cranial/brain size affect these developmental trajectories. First, we found evidence for continued development of both intracranial volume (ICV) and whole brain volume (WBV) through adolescence, albeit following distinct trajectories. Second, our results indicate that CGMV is at its highest in childhood, decreasing steadily through the second decade with deceleration in the third decade, while CWMV increases until mid-to-late adolescence before decelerating. Importantly, we show that accounting for cranial/brain size affects models of regional brain development, particularly with respect to sex differences. Our results increase confidence in our knowledge of the pattern of brain changes during adolescence, reduce concerns about discrepancies across samples, and suggest some best practices for statistical control of cranial volume and brain size in future studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Brain Entropy Mapping Using fMRI

PubMed Central

Wang, Ze; Li, Yin; Childress, Anna Rose; Detre, John A.

2014-01-01

Entropy is an important trait for life as well as the human brain. Characterizing brain entropy (BEN) may provide an informative tool to assess brain states and brain functions. Yet little is known about the distribution and regional organization of BEN in normal brain. The purpose of this study was to examine the whole brain entropy patterns using a large cohort of normal subjects. A series of experiments were first performed to validate an approximate entropy measure regarding its sensitivity, specificity, and reliability using synthetic data and fMRI data. Resting state fMRI data from a large cohort of normal subjects (n = 1049) from multi-sites were then used to derive a 3-dimensional BEN map, showing a sharp low-high entropy contrast between the neocortex and the rest of brain. The spatial heterogeneity of resting BEN was further studied using a data-driven clustering method, and the entire brain was found to be organized into 7 hierarchical regional BEN networks that are consistent with known structural and functional brain parcellations. These findings suggest BEN mapping as a physiologically and functionally meaningful measure for studying brain functions. PMID:24657999

Divergent structural brain abnormalities between different genetic subtypes of children with Prader-Willi syndrome.

PubMed

Lukoshe, Akvile; White, Tonya; Schmidt, Marcus N; van der Lugt, Aad; Hokken-Koelega, Anita C

2013-10-22

Prader-Willi syndrome (PWS) is a complex neurogenetic disorder with symptoms that indicate not only hypothalamic, but also a global, central nervous system (CNS) dysfunction. However, little is known about developmental differences in brain structure in children with PWS. Thus, our aim was to investigate global brain morphology in children with PWS, including the comparison between different genetic subtypes of PWS. In addition, we performed exploratory cortical and subcortical focal analyses. High resolution structural magnetic resonance images were acquired in 20 children with genetically confirmed PWS (11 children carrying a deletion (DEL), 9 children with maternal uniparental disomy (mUPD)), and compared with 11 age- and gender-matched typically developing siblings as controls. Brain morphology measures were obtained using the FreeSurfer software suite. Both children with DEL and mUPD showed smaller brainstem volume, and a trend towards smaller cortical surface area and white matter volume. Children with mUPD had enlarged lateral ventricles and larger cortical cerebrospinal fluid (CSF) volume. Further, a trend towards increased cortical thickness was found in children with mUPD. Children with DEL had a smaller cerebellum, and smaller cortical and subcortical grey matter volumes. Focal analyses revealed smaller white matter volumes in left superior and bilateral inferior frontal gyri, right cingulate cortex, and bilateral precuneus areas associated with the default mode network (DMN) in children with mUPD. Children with PWS show signs of impaired brain growth. Those with mUPD show signs of early brain atrophy. In contrast, children with DEL show signs of fundamentally arrested, although not deviant brain development and presented few signs of cortical atrophy. Our results of global brain measurements suggest divergent neurodevelopmental patterns in children with DEL and mUPD.

Divergent structural brain abnormalities between different genetic subtypes of children with Prader–Willi syndrome

PubMed Central

2013-01-01

Background Prader–Willi syndrome (PWS) is a complex neurogenetic disorder with symptoms that indicate not only hypothalamic, but also a global, central nervous system (CNS) dysfunction. However, little is known about developmental differences in brain structure in children with PWS. Thus, our aim was to investigate global brain morphology in children with PWS, including the comparison between different genetic subtypes of PWS. In addition, we performed exploratory cortical and subcortical focal analyses. Methods High resolution structural magnetic resonance images were acquired in 20 children with genetically confirmed PWS (11 children carrying a deletion (DEL), 9 children with maternal uniparental disomy (mUPD)), and compared with 11 age- and gender-matched typically developing siblings as controls. Brain morphology measures were obtained using the FreeSurfer software suite. Results Both children with DEL and mUPD showed smaller brainstem volume, and a trend towards smaller cortical surface area and white matter volume. Children with mUPD had enlarged lateral ventricles and larger cortical cerebrospinal fluid (CSF) volume. Further, a trend towards increased cortical thickness was found in children with mUPD. Children with DEL had a smaller cerebellum, and smaller cortical and subcortical grey matter volumes. Focal analyses revealed smaller white matter volumes in left superior and bilateral inferior frontal gyri, right cingulate cortex, and bilateral precuneus areas associated with the default mode network (DMN) in children with mUPD. Conclusions Children with PWS show signs of impaired brain growth. Those with mUPD show signs of early brain atrophy. In contrast, children with DEL show signs of fundamentally arrested, although not deviant brain development and presented few signs of cortical atrophy. Our results of global brain measurements suggest divergent neurodevelopmental patterns in children with DEL and mUPD. PMID:24144356

Delineation of early brain development from fetuses to infants with diffusion MRI and beyond.

PubMed

Ouyang, Minhui; Dubois, Jessica; Yu, Qinlin; Mukherjee, Pratik; Huang, Hao

2018-04-12

Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders. Copyright © 2018 Elsevier Inc. All rights reserved.

Brain Morphometry using MRI in Schizophrenia Patients

NASA Astrophysics Data System (ADS)

Abanshina, I.; Pirogov, Yu.; Kupriyanov, D.; Orlova, V.

2010-01-01

Schizophrenia has been the focus of intense neuroimaging research. Although its fundamental pathobiology remains elusive, neuroimaging studies provide evidence of abnormalities of cerebral structure and function in patients with schizophrenia. We used morphometry as a quantitative method for estimation of volume of brain structures. Seventy eight right-handed subjects aged 18-45 years were exposed to MRI-examination. Patients were divided into 3 groups: patients with schizophrenia, their relatives and healthy controls. The volumes of interested structures (caudate nucleus, putamen, ventricles, frontal and temporal lobe) were measured using T2-weighted MR-images. Correlations between structural differences and functional deficit were evaluated.

Application of spatially modulated near-infrared structured light to study changes in optical properties of mouse brain tissue during heatstress.

PubMed

Shaul, Oren; Fanrazi-Kahana, Michal; Meitav, Omri; Pinhasi, Gad A; Abookasis, David

2017-11-10

Heat stress (HS) is a medical emergency defined by abnormally elevated body temperature that causes biochemical, physiological, and hematological changes. The goal of the present research was to detect variations in optical properties (absorption, reduced scattering, and refractive index coefficients) of mouse brain tissue during HS by using near-infrared (NIR) spatial light modulation. NIR spatial patterns with different spatial phases were used to differentiate the effects of tissue scattering from those of absorption. Decoupling optical scattering from absorption enabled the quantification of a tissue's chemical constituents (related to light absorption) and structural properties (related to light scattering). Technically, structured light patterns at low and high spatial frequencies of six wavelengths ranging between 690 and 970 nm were projected onto the mouse scalp surface while diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse scalp. Concurrently to pattern projection, brain temperature was measured with a thermal camera positioned slightly off angle from the mouse head while core body temperature was monitored by thermocouple probe. Data analysis demonstrated variations from baseline measurements in a battery of intrinsic brain properties following HS.

Validation of DTI Tractography-Based Measures of Primary Motor Area Connectivity in the Squirrel Monkey Brain

PubMed Central

Gao, Yurui; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Avison, Malcolm J.; Anderson, Adam W.

2013-01-01

Diffusion tensor imaging (DTI) tractography provides noninvasive measures of structural cortico-cortical connectivity of the brain. However, the agreement between DTI-tractography-based measures and histological ‘ground truth’ has not been quantified. In this study, we reconstructed the 3D density distribution maps (DDM) of fibers labeled with an anatomical tracer, biotinylated dextran amine (BDA), as well as DTI tractography-derived streamlines connecting the primary motor (M1) cortex to other cortical regions in the squirrel monkey brain. We evaluated the agreement in M1-cortical connectivity between the fibers labeled in the brain tissue and DTI streamlines on a regional and voxel-by-voxel basis. We found that DTI tractography is capable of providing inter-regional connectivity comparable to the neuroanatomical connectivity, but is less reliable measuring voxel-to-voxel variations within regions. PMID:24098365

Persistent post-traumatic headache vs. migraine: an MRI study demonstrating differences in brain structure.

PubMed

Schwedt, Todd J; Chong, Catherine D; Peplinski, Jacob; Ross, Katherine; Berisha, Visar

2017-08-22

The majority of individuals with post-traumatic headache have symptoms that are indistinguishable from migraine. The overlap in symptoms amongst these individuals raises the question as to whether post-traumatic headache has a unique pathophysiology or if head trauma triggers migraine. The objective of this study was to compare brain structure in individuals with persistent post-traumatic headache (i.e. headache lasting at least 3 months following a traumatic brain injury) attributed to mild traumatic brain injury to that of individuals with migraine. Twenty-eight individuals with persistent post-traumatic headache attributed to mild traumatic brain injury and 28 individuals with migraine underwent brain magnetic resonance imaging on a 3 T scanner. Regional volumes, cortical thickness, surface area and curvature measurements were calculated from T1-weighted sequences and compared between subject groups using ANCOVA. MRI data from 28 healthy control subjects were used to interpret the differences in brain structure between migraine and persistent post-traumatic headache. Differences in regional volumes, cortical thickness, surface area and brain curvature were identified when comparing the group of individuals with persistent post-traumatic headache to the group with migraine. Structure was different between groups for regions within the right lateral orbitofrontal lobe, left caudal middle frontal lobe, left superior frontal lobe, left precuneus and right supramarginal gyrus (p < .05). Considering these regions only, there were differences between individuals with persistent post-traumatic headache and healthy controls within the right lateral orbitofrontal lobe, right supramarginal gyrus, and left superior frontal lobe and no differences when comparing the migraine cohort to healthy controls. In conclusion, persistent post-traumatic headache and migraine are associated with differences in brain structure, perhaps suggesting differences in their underlying pathophysiology. Additional studies are needed to further delineate similarities and differences in brain structure and function that are associated with post-traumatic headache and migraine and to determine their specificity for each of the headache types.

Brain modularity controls the critical behavior of spontaneous activity.

PubMed

Russo, R; Herrmann, H J; de Arcangelis, L

2014-03-13

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.

Adaptive optical microscope for brain imaging in vivo

NASA Astrophysics Data System (ADS)

Wang, Kai

2017-04-01

The optical heterogeneity of biological tissue imposes a major limitation to acquire detailed structural and functional information deep in the biological specimens using conventional microscopes. To restore optimal imaging performance, we developed an adaptive optical microscope based on direct wavefront sensing technique. This microscope can reliably measure and correct biological samples induced aberration. We demonstrated its performance and application in structural and functional brain imaging in various animal models, including fruit fly, zebrafish and mouse.

Transfer coefficients for L-valine and the rate of incorporation of L-(1-/sup 14/C) valine into proteins in normal adult rat brain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirikae, M.; Diksic, M.; Yamamoto, Y.L.

1988-08-01

An autoradiographic method for the measurement of the rate of valine incorporation into brain proteins is described. The transfer coefficients for valine into and out of the brain and the rate of valine incorporation into normal rat brain proteins are given. The valine incorporation and the transfer constants of valine between different biological compartments are provided for 14 gray matter and 2 white matter structures of an adult rat brain. The rate of valine incorporation varies between 0.52 +/- 0.19 nmol/g/min in white matter and 1.94 +/- 0.47 in inferior colliculus (gray matter). Generally, the rate of valine incorporation ismore » about three to four times higher in the gray matter than in the white matter structures.« less

Double dissociation of structure-function relationships in memory and fluid intelligence observed with magnetic resonance elastography.

PubMed

Johnson, Curtis L; Schwarb, Hillary; Horecka, Kevin M; McGarry, Matthew D J; Hillman, Charles H; Kramer, Arthur F; Cohen, Neal J; Barbey, Aron K

2018-05-01

Brain tissue mechanical properties, measured in vivo with magnetic resonance elastography (MRE), have proven to be sensitive metrics of neural tissue integrity. Recently, our group has reported on the positive relationship between viscoelasticity of the hippocampus and performance on a relational memory task in healthy young adults, which highlighted the potential of sensitive MRE measures for studying brain health and its relation to cognitive function; however, structure-function relationships outside of the hippocampus have not yet been explored. In this study, we examined the relationships between viscoelasticity of both the hippocampus and the orbitofrontal cortex and performance on behavioral assessments of relational memory and fluid intelligence. In a sample of healthy, young adults (N = 53), there was a significant, positive relationship between orbitofrontal cortex viscoelasticity and fluid intelligence performance (r = 0.42; p = .002). This finding is consistent with the previously reported relationship between hippocampal viscoelasticity and relational memory performance (r = 0.41; p = .002). Further, a significant double dissociation between the orbitofrontal-fluid intelligence relationship and the hippocampal-relational memory relationship was observed. These data support the specificity of regional brain MRE measures in support of separable cognitive functions. This report of a structure-function relationship observed with MRE beyond the hippocampus suggests a future role for MRE as a sensitive neuroimaging technique for brain mapping. Copyright © 2018 Elsevier Inc. All rights reserved.

Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

PubMed Central

Liu, Yaou; Duan, Yunyun; Li, Kuncheng

2015-01-01

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain. PMID:26539535

Amphetamine Dependence and Co-Morbid Alcohol Abuse: Associations to Brain Cortical Thickness

PubMed Central

2010-01-01

Background Long-term amphetamine and methamphetamine dependence has been linked to cerebral blood perfusion, metabolic, and white matter abnormalities. Several studies have linked methamphetamine abuse to cortical grey matter reduction, though with divergent findings. Few publications investigate unmethylated amphetamine's potential effects on cortical grey matter. This work investigated if amphetamine dependent patients showed reduced cortical grey matter thickness. Subjects were 40 amphetamine dependent subjects and 40 healthy controls. While all subjects were recruited to be free of alcohol dependence, structured clinical interviews revealed significant patterns of alcohol use in the patients. Structural magnetic resonance brain images were obtained from the subjects using a 1.5 Tesla GE Signa machine. Brain cortical thickness was measured with submillimeter precision at multiple finely spaced cortical locations using semi-automated post-processing (FreeSurfer). Contrast analysis of a general linear model was used to test for differences between the two groups at each cortical location. In addition to contrasting patients with controls, a number of analyses sought to identify possible confounding effects from alcohol. Results No significant cortical thickness differences were observed between the full patient group and controls, nor between non-drinking patients and controls. Patients with a history of co-morbid heavy alcohol use (n = 29) showed reductions in the superior-frontal right hemisphere and pre-central left hemisphere when compared to healthy controls (n = 40). Conclusions Amphetamine usage was associated with reduced cortical thickness only in patients co-morbid for heavy alcohol use. Since cortical thickness is but one measure of brain structure and does not capture brain function, further studies of brain structure and function in amphetamine dependence are warranted. PMID:20487539

Altered resting brain function and structure in professional badminton players.

PubMed

Di, Xin; Zhu, Senhua; Jin, Hua; Wang, Pin; Ye, Zhuoer; Zhou, Ke; Zhuo, Yan; Rao, Hengyi

2012-01-01

Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills.

3D shape analysis of the brain's third ventricle using a midplane encoded symmetric template model

PubMed Central

Kim, Jaeil; Valdés Hernández, Maria del C.; Royle, Natalie A.; Maniega, Susana Muñoz; Aribisala, Benjamin S.; Gow, Alan J.; Bastin, Mark E.; Deary, Ian J.; Wardlaw, Joanna M.; Park, Jinah

2016-01-01

Background Structural changes of the brain's third ventricle have been acknowledged as an indicative measure of the brain atrophy progression in neurodegenerative and endocrinal diseases. To investigate the ventricular enlargement in relation to the atrophy of the surrounding structures, shape analysis is a promising approach. However, there are hurdles in modeling the third ventricle shape. First, it has topological variations across individuals due to the inter-thalamic adhesion. In addition, as an interhemispheric structure, it needs to be aligned to the midsagittal plane to assess its asymmetric and regional deformation. Method To address these issues, we propose a model-based shape assessment. Our template model of the third ventricle consists of a midplane and a symmetric mesh of generic shape. By mapping the template's midplane to the individuals’ brain midsagittal plane, we align the symmetric mesh on the midline of the brain before quantifying the third ventricle shape. To build the vertex-wise correspondence between the individual third ventricle and the template mesh, we employ a minimal-distortion surface deformation framework. In addition, to account for topological variations, we implement geometric constraints guiding the template mesh to have zero width where the inter-thalamic adhesion passes through, preventing vertices crossing between left and right walls of the third ventricle. The individual shapes are compared using a vertex-wise deformity from the symmetric template. Results Experiments on imaging and demographic data from a study of aging showed that our model was sensitive in assessing morphological differences between individuals in relation to brain volume (i.e. proxy for general brain atrophy), gender and the fluid intelligence at age 72. It also revealed that the proposed method can detect the regional and asymmetrical deformation unlike the conventional measures: volume (median 1.95 ml, IQR 0.96 ml) and width of the third ventricle. Similarity measures between binary masks and the shape model showed that the latter reconstructed shape details with high accuracy (Dice coefficient ≥0.9, mean distance 0.5 mm and Hausdorff distance 2.7 mm). Conclusions We have demonstrated that our approach is suitable to morphometrical analyses of the third ventricle, providing high accuracy and inter-subject consistency in the shape quantification. This shape modeling method with geometric constraints based on anatomical landmarks could be extended to other brain structures which require a consistent measurement basis in the morphometry. PMID:27084320

Grey matter abnormalities in children and adolescents with functional neurological symptom disorder.

PubMed

Kozlowska, Kasia; Griffiths, Kristi R; Foster, Sheryl L; Linton, James; Williams, Leanne M; Korgaonkar, Mayuresh S

2017-01-01

Functional neurological symptom disorder refers to the presence of neurological symptoms not explained by neurological disease. Although this disorder is presumed to reflect abnormal function of the brain, recent studies in adults show neuroanatomical abnormalities in brain structure . These structural brain abnormalities have been presumed to reflect long-term adaptations to the disorder, and it is unknown whether child and adolescent patients, with illness that is typically of shorter duration, show similar deficits or have normal brain structure. High-resolution, three-dimensional T1-weighted magnetic resonance images (MRIs) were acquired in 25 patients (aged 10-18 years) and 24 healthy controls. Structure was quantified in terms of grey matter volume using voxel-based morphometry. Post hoc, we examined whether regions of structural difference related to a measure of motor readiness to emotional signals and to clinical measures of illness duration, illness severity, and anxiety/depression. Patients showed greater volumes in the left supplementary motor area (SMA) and right superior temporal gyrus (STG) and dorsomedial prefrontal cortex (DMPFC) (corrected p < 0.05). Previous studies of adult patients have also reported alterations of the SMA. Greater SMA volumes correlated with faster reaction times in identifying emotions but not with clinical measures. The SMA, STG, and DMPFC are known to be involved in the perception of emotion and the modulation of motor responses. These larger volumes may reflect the early expression of an experience-dependent plasticity process associated with increased vigilance to others' emotional states and enhanced motor readiness to organize self-protectively in the context of the long-standing relational stress that is characteristic of this disorder.

When structure affects function--the need for partial volume effect correction in functional and resting state magnetic resonance imaging studies.

PubMed

Dukart, Juergen; Bertolino, Alessandro

2014-01-01

Both functional and also more recently resting state magnetic resonance imaging have become established tools to investigate functional brain networks. Most studies use these tools to compare different populations without controlling for potential differences in underlying brain structure which might affect the functional measurements of interest. Here, we adapt a simulation approach combined with evaluation of real resting state magnetic resonance imaging data to investigate the potential impact of partial volume effects on established functional and resting state magnetic resonance imaging analyses. We demonstrate that differences in the underlying structure lead to a significant increase in detected functional differences in both types of analyses. Largest increases in functional differences are observed for highest signal-to-noise ratios and when signal with the lowest amount of partial volume effects is compared to any other partial volume effect constellation. In real data, structural information explains about 25% of within-subject variance observed in degree centrality--an established resting state connectivity measurement. Controlling this measurement for structural information can substantially alter correlational maps obtained in group analyses. Our results question current approaches of evaluating these measurements in diseased population with known structural changes without controlling for potential differences in these measurements.

Brain structure correlates of component reading processes: implications for reading disability.

PubMed

Phinney, Erin; Pennington, Bruce F; Olson, Richard; Filley, Christopher M; Filipek, Pauline A

2007-08-01

Brain structures implicated in developmental dyslexia (reading disability - RD) vary greatly across structural magnetic resonance imaging (MRI) studies due to methodological differences regarding the definition of RD and the exact measurements of a specific brain structure. The current study attempts to resolve some of those methodological concerns by examining brain volume as it relates to components of proposed RD subtypes. We performed individual regression analyses on total cerebral volume, neocortical volume, subcortical volume, 9 neo-cortical structures and 2 sub-cortical structures. These analyses used three dimensions of reading, phonemic ability (PA), orthographic ability, and rapid naming (RN) ability, while accounting for total cerebral volume, age, and performance IQ (PIQ). Primary analyses included membership to a group (poor reader vs. good reader) in the analysis. The result was a significant interaction between PA and reading ability as it predicts total cerebral volume. Analyses revealed that poor readers lacked a relationship between PA and brain size, but that good readers had a significant positive relationship. This pattern of interaction was not present for the other two reading component factors. These findings bring into question the general belief that individuals with RD are at the low end of a reading ability distribution and do not have a unique disorder. Additional analyses revealed only a few significant relationships between brain size and task performance, most notably a positive correlation between orthographic ability and the angular gyrus (AG), as well as a negative correlation between RN ability and the parietal operculum (PO).

Brain structure variation in great apes, with attention to the mountain gorilla (Gorilla beringei beringei).

PubMed

Sherwood, Chet C; Cranfield, Michael R; Mehlman, Patrick T; Lilly, Alecia A; Garbe, Jo Anne L; Whittier, Christopher A; Nutter, Felicia B; Rein, Thomas R; Bruner, Harlan J; Holloway, Ralph L; Tang, Cheuk Y; Naidich, Thomas P; Delman, Bradley N; Steklis, H Dieter; Erwin, Joseph M; Hof, Patrick R

2004-07-01

This report presents data regarding the brain structure of mountain gorillas (Gorilla beringei beringei) in comparison with other great apes. Magnetic resonance (MR) images of three mountain gorilla brains were obtained with a 3T scanner, and the volume of major neuroanatomical structures (neocortical gray matter, hippocampus, thalamus, striatum, and cerebellum) was measured. These data were included with our existing database that includes 23 chimpanzees, three western lowland gorillas, and six orangutans. We defined a multidimensional space by calculating the principal components (PCs) from the correlation matrix of brain structure fractions in the well-represented sample of chimpanzees. We then plotted data from all of the taxa in this space to examine phyletic variation in neural organization. Most of the variance in mountain gorillas, as well as other great apes, was contained within the chimpanzee range along the first two PCs, which accounted for 61.73% of the total variance. Thus, the majority of interspecific variation in brain structure observed among these ape taxa was no greater than the within-species variation seen in chimpanzees. The loadings on PCs indicated that the brain structure of great apes differs among taxa mostly in the relative sizes of the striatum, cerebellum, and hippocampus. These findings suggest possible functional differences among taxa in terms of neural adaptations for ecological and locomotor capacities. Importantly, these results fill a critical gap in current knowledge regarding great ape neuroanatomical diversity.

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity.

PubMed

Lizier, Joseph T; Heinzle, Jakob; Horstmann, Annette; Haynes, John-Dylan; Prokopenko, Mikhail

2011-02-01

The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between brain regions, and how that structure changes according to behavioral conditions. This method is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only directional and non-linear relationships, but also collective interactions. Importantly, the method is able to estimate multivariate information measures with only relatively little data. We demonstrate the method to analyze functional magnetic resonance imaging time series to establish the directed information structure between brain regions involved in a visuo-motor tracking task. Importantly, this results in a tiered structure, with known movement planning regions driving visual and motor control regions. Also, we examine the changes in this structure as the difficulty of the tracking task is increased. We find that task difficulty modulates the coupling strength between regions of a cortical network involved in movement planning and between motor cortex and the cerebellum which is involved in the fine-tuning of motor control. It is likely these methods will find utility in identifying interregional structure (and experimentally induced changes in this structure) in other cognitive tasks and data modalities.

Disruption to functional networks in neonates with perinatal brain injury predicts motor skills at 8 months.

PubMed

Linke, Annika C; Wild, Conor; Zubiaurre-Elorza, Leire; Herzmann, Charlotte; Duffy, Hester; Han, Victor K; Lee, David S C; Cusack, Rhodri

2018-01-01

Functional connectivity magnetic resonance imaging (fcMRI) of neonates with perinatal brain injury could improve prediction of motor impairment before symptoms manifest, and establish how early brain organization relates to subsequent development. This cohort study is the first to describe and quantitatively assess functional brain networks and their relation to later motor skills in neonates with a diverse range of perinatal brain injuries. Infants ( n  = 65, included in final analyses: n  = 53) were recruited from the neonatal intensive care unit (NICU) and were stratified based on their age at birth (premature vs. term), and on whether neuropathology was diagnosed from structural MRI. Functional brain networks and a measure of disruption to functional connectivity were obtained from 14 min of fcMRI acquired during natural sleep at term-equivalent age. Disruption to connectivity of the somatomotor and frontoparietal executive networks predicted motor impairment at 4 and 8 months. This disruption in functional connectivity was not found to be driven by differences between clinical groups, or by any of the specific measures we captured to describe the clinical course. fcMRI was predictive over and above other clinical measures available at discharge from the NICU, including structural MRI. Motor learning was affected by disruption to somatomotor networks, but also frontoparietal executive networks, which supports the functional importance of these networks in early development. Disruption to these two networks might be best addressed by distinct intervention strategies.

Infant brain structures, executive function, and attention deficit/hyperactivity problems at preschool age. A prospective study.

PubMed

Ghassabian, Akhgar; Herba, Catherine M; Roza, Sabine J; Govaert, Paul; Schenk, Jacqueline J; Jaddoe, Vincent W; Hofman, Albert; White, Tonya; Verhulst, Frank C; Tiemeier, Henning

2013-01-01

Neuroimaging findings have provided evidence for a relation between variations in brain structures and attention deficit/hyperactivity disorder (ADHD). However, longitudinal neuroimaging studies are typically confined to children who have already been diagnosed with ADHD. In a population-based study, we aimed to characterize the prospective association between brain structures measured during infancy and executive function and attention deficit/hyperactivity problems assessed at preschool age. In the Generation R Study, the corpus callosum length, the gangliothalamic ovoid diameter (encompassing the basal ganglia and thalamus), and the ventricular volume were measured in 784 6-week-old children using cranial postnatal ultrasounds. Parents rated executive functioning at 4 years using the behavior rating inventory of executive function-preschool version in five dimensions: inhibition, shifting, emotional control, working memory, and planning/organizing. Attention deficit/hyperactivity problems were assessed at ages 3 and 5 years using the child behavior checklist. A smaller corpus callosum length during infancy was associated with greater deficits in executive functioning at 4 years. This was accounted for by higher problem scores on inhibition and emotional control. The corpus callosum length during infancy did not predict attention deficit/hyperactivity problem at 3 and 5 years, when controlling for the confounders. We did not find any relation between gangliothalamic ovoid diameter and executive function or Attention deficit/hyperactivity problem. Variations in brain structures detectible in infants predicted subtle impairments in inhibition and emotional control. However, in this population-based study, we could not demonstrate that early structural brain variations precede symptoms of ADHD. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.

Advanced lesion symptom mapping analyses and implementation as BCBtoolkit.

PubMed

Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika; Volle, Emmanuelle; Thiebaut de Schotten, Michel

2018-03-01

Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1].

Brain responses in 4-month-old infants are already language specific.

PubMed

Friederici, Angela D; Friedrich, Manuela; Christophe, Anne

2007-07-17

Language is the most important faculty that distinguishes humans from other animals. Infants learn their native language fast and effortlessly during the first years of life, as a function of the linguistic input in their environment. Behavioral studies reported the discrimination of melodic contours [1] and stress patterns [2, 3] in 1-4-month-olds. Behavioral [4, 5] and brain measures [6-8] have shown language-independent discrimination of phonetic contrasts at that age. Language-specific discrimination, however, has been reported for phonetic contrasts only for 6-12-month-olds [9-12]. Here we demonstrate language-specific discrimination of stress patterns in 4-month-old German and French infants by using electrophysiological brain measures. We compare the processing of disyllabic words differing in their rhythmic structure, mimicking German words being stressed on the first syllable, e.g., pápa/daddy[13], and French ones being stressed on the second syllable, e.g., papá/daddy. Event-related brain potentials reveal that experience with German and French differentially affects the brain responses of 4-month-old infants, with each language group displaying a processing advantage for the rhythmic structure typical in its native language. These data indicate language-specific neural representations of word forms in the infant brain as early as 4 months of age.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.

PubMed

Ji, Shuiwang

2013-07-11

The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship.

Developmental changes in organization of structural brain networks.

PubMed

Khundrakpam, Budhachandra S; Reid, Andrew; Brauer, Jens; Carbonell, Felix; Lewis, John; Ameis, Stephanie; Karama, Sherif; Lee, Junki; Chen, Zhang; Das, Samir; Evans, Alan C

2013-09-01

Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.

Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain

PubMed Central

Barrett, Lisa Feldman; Satpute, Ajay

2013-01-01

Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. PMID:23352202

Executive function and functional and structural brain differences in middle-age adults with autism spectrum disorder.

PubMed

Braden, B Blair; Smith, Christopher J; Thompson, Amiee; Glaspy, Tyler K; Wood, Emily; Vatsa, Divya; Abbott, Angela E; McGee, Samuel C; Baxter, Leslie C

2017-12-01

There is a rapidly growing group of aging adults with autism spectrum disorder (ASD) who may have unique needs, yet cognitive and brain function in older adults with ASD is understudied. We combined functional and structural neuroimaging and neuropsychological tests to examine differences between middle-aged men with ASD and matched neurotypical (NT) men. Participants (ASD, n = 16; NT, n = 17) aged 40-64 years were well-matched according to age, IQ (range: 83-131), and education (range: 9-20 years). Middle-age adults with ASD made more errors on an executive function task (Wisconsin Card Sorting Test) but performed similarly to NT adults on tests of delayed verbal memory (Rey Auditory Verbal Learning Test) and local visual search (Embedded Figures Task). Independent component analysis of a functional MRI working memory task (n-back) completed by most participants (ASD = 14, NT = 17) showed decreased engagement of a cortico-striatal-thalamic-cortical neural network in older adults with ASD. Structurally, older adults with ASD had reduced bilateral hippocampal volumes, as measured by FreeSurfer. Findings expand our understanding of ASD as a lifelong condition with persistent cognitive and functional and structural brain differences evident at middle-age. Autism Res 2017, 10: 1945-1959. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. We compared cognitive abilities and brain measures between 16 middle-age men with high-functioning autism spectrum disorder (ASD) and 17 typical middle-age men to better understand how aging affects an older group of adults with ASD. Men with ASD made more errors on a test involving flexible thinking, had less activity in a flexible thinking brain network, and had smaller volume of a brain structure related to memory than typical men. We will follow these older adults over time to determine if aging changes are greater for individuals with ASD. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Origin of hyperbolicity in brain-to-brain coordination networks

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Andjelković, Miroslav; Šuvakov, Milovan

2018-02-01

Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are delta-hyperbolic with delta_max=1 and the graph diameter D=3 in each brain. While the emergent hyperbolicity in the two-brain networks satisfies delta_max/D/2 < 1 and can be attributed to the topology of the subgraph formed around the cross-brains linking channels. We identify these subgraphs in each studied two-brain network and decompose their structure into simple geometric descriptors (triangles, tetrahedra and cliques of higher orders) that contribute to hyperbolicity. Considering topologies that exceed two separate brain networks as a measure of coordination synergy between the brains, we identify different neuronal correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener’s self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

Head circumference and brain size in autism spectrum disorder: A systematic review and meta-analysis.

PubMed

Sacco, Roberto; Gabriele, Stefano; Persico, Antonio M

2015-11-30

Macrocephaly and brain overgrowth have been associated with autism spectrum disorder. We performed a systematic review and meta-analysis to provide an overall estimate of effect size and statistical significance for both head circumference and total brain volume in autism. Our literature search strategy identified 261 and 391 records, respectively; 27 studies defining percentages of macrocephalic patients and 44 structural brain imaging studies providing total brain volumes for patients and controls were included in our meta-analyses. Head circumference was significantly larger in autistic compared to control individuals, with 822/5225 (15.7%) autistic individuals displaying macrocephaly. Structural brain imaging studies measuring brain volume estimated effect size. The effect size is higher in low functioning autistics compared to high functioning and ASD individuals. Brain overgrowth was recorded in 142/1558 (9.1%) autistic patients. Finally, we found a significant interaction between age and total brain volume, resulting in larger head circumference and brain size during early childhood. Our results provide conclusive effect sizes and prevalence rates for macrocephaly and brain overgrowth in autism, confirm the variation of abnormal brain growth with age, and support the inclusion of this endophenotype in multi-biomarker diagnostic panels for clinical use. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

One of the most important goals of neuroscience is to establish precise structure–function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure–function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure–function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples. PMID:15610393

Networks of myelin covariance.

PubMed

Melie-Garcia, Lester; Slater, David; Ruef, Anne; Sanabria-Diaz, Gretel; Preisig, Martin; Kherif, Ferath; Draganski, Bogdan; Lutti, Antoine

2018-04-01

Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, ). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these "networks of myelin covariance" (Myelin-Nets). The Myelin-Nets were built from quantitative Magnetization Transfer data-an in-vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin-Nets. We therefore selected two age groups: Young-Age (20-31 years old) and Old-Age (60-71 years old) and a pool of participants from 48 to 87 years old for a Myelin-Nets aging trajectory study. We found that the topological organization of the Myelin-Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin-Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Resolving Structural Variability in Network Models and the Brain

PubMed Central

Klimm, Florian; Bassett, Danielle S.; Carlson, Jean M.; Mucha, Peter J.

2014-01-01

Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling—in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the statistical inference of brain network structure from neuroimaging data. PMID:24675546

The sequential structure of brain activation predicts skill.

PubMed

Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

2016-01-29

In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Association of allostatic load with brain structure and cognitive ability in later life

PubMed Central

Booth, Tom; Royle, Natalie A.; Corley, Janie; Gow, Alan J.; Valdés Hernández, Maria del C.; Muñoz Maniega, Susana; Ritchie, Stuart J.; Bastin, Mark E.; Starr, John M.; Wardlaw, Joanna M.; Deary, Ian J.

2015-01-01

Allostatic load (AL) has been proposed as a general framework for understanding the cumulative effects of life stress on individuals. Despite growing interest in AL, limited research has been conducted on aging samples. We consider the association of AL (operationalized by a range of inflammatory, cardiovascular, and metabolic measures) with a range of brain volume measurements and cognitive ability in a large cohort sample of older adults (n = 658, mean age = 72.5 years, standard deviation = 0.7) using structural equation modeling. AL was significantly inversely associated with total brain volume (range of standardized β = −0.16 to −0.20) and white-matter volume (−0.35 to −0.36) and positively with hippocampal volume (0.10–0.15) but not gray-matter volume (0.04). AL was also significantly inversely associated with general cognitive ability (range β = −0.13 to −0.20), processing speed (−0.20 to −0.22), and knowledge (−0.18 to −0.20) but not memory or nonverbal reasoning. The associations of AL with cognitive abilities were not mediated by these brain volume measures. AL did not predict cognitive change from age 11 to approximately age 73. The findings suggest a link between AL and later life brain health and cognitive functioning. PMID:25659881

MRI Guided Brain Stimulation without the Use of a Neuronavigation System

PubMed Central

Vaghefi, Ehsan; Byblow, Winston D.; Stinear, Cathy M.; Thompson, Benjamin

2015-01-01

A key issue in the field of noninvasive brain stimulation (NIBS) is the accurate localization of scalp positions that correspond to targeted cortical areas. The current gold standard is to combine structural and functional brain imaging with a commercially available “neuronavigation” system. However, neuronavigation systems are not commonplace outside of specialized research environments. Here we describe a technique that allows for the use of participant-specific functional and structural MRI data to guide NIBS without a neuronavigation system. Surface mesh representations of the head were generated using Brain Voyager and vectors linking key anatomical landmarks were drawn on the mesh. Our technique was then used to calculate the precise distances on the scalp corresponding to these vectors. These calculations were verified using actual measurements of the head and the technique was used to identify a scalp position corresponding to a brain area localized using functional MRI. PMID:26413537

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Cortical thickness and surface area correlates with cognitive dysfunction among first-episode psychosis patients.

PubMed

Haring, L; Müürsepp, A; Mõttus, R; Ilves, P; Koch, K; Uppin, K; Tarnovskaja, J; Maron, E; Zharkovsky, A; Vasar, E; Vasar, V

2016-07-01

In studies using magnetic resonance imaging (MRI), some have reported specific brain structure-function relationships among first-episode psychosis (FEP) patients, but findings are inconsistent. We aimed to localize the brain regions where cortical thickness (CTh) and surface area (cortical area; CA) relate to neurocognition, by performing an MRI on participants and measuring their neurocognitive performance using the Cambridge Neuropsychological Test Automated Battery (CANTAB), in order to investigate any significant differences between FEP patients and control subjects (CS). Exploration of potential correlations between specific cognitive functions and brain structure was performed using CANTAB computer-based neurocognitive testing and a vertex-by-vertex whole-brain MRI analysis of 63 FEP patients and 30 CS. Significant correlations were found between cortical parameters in the frontal, temporal, cingular and occipital brain regions and performance in set-shifting, working memory manipulation, strategy usage and sustained attention tests. These correlations were significantly dissimilar between FEP patients and CS. Significant correlations between CTh and CA with neurocognitive performance were localized in brain areas known to be involved in cognition. The results also suggested a disrupted structure-function relationship in FEP patients compared with CS.

Brain network connectivity in women exposed to intimate partner violence: a graph theory analysis study.

PubMed

Roos, Annerine; Fouche, Jean-Paul; Stein, Dan J

2017-12-01

Evidence suggests that women who suffer from intimate partner violence (IPV) and posttraumatic stress disorder (PTSD) have structural and functional alterations in specific brain regions. Yet, little is known about how brain connectivity may be altered in individuals with IPV, but without PTSD. Women exposed to IPV (n = 18) and healthy controls (n = 18) underwent structural brain imaging using a Siemens 3T MRI. Global and regional brain network connectivity measures were determined, using graph theory analyses. Structural covariance networks were created using volumetric and cortical thickness data after controlling for intracranial volume, age and alcohol use. Nonparametric permutation tests were used to investigate group differences. Findings revealed altered connectivity on a global and regional level in the IPV group of regions involved in cognitive-emotional control, with principal involvement of the caudal anterior cingulate, the middle temporal gyrus, left amygdala and ventral diencephalon that includes the thalamus. To our knowledge, this is the first evidence showing different brain network connectivity in global and regional networks in women exposed to IPV, and without PTSD. Altered cognitive-emotional control in IPV may underlie adaptive neural mechanisms in environments characterized by potentially dangerous cues.

Dissociable brain biomarkers of fluid intelligence.

PubMed

Paul, Erick J; Larsen, Ryan J; Nikolaidis, Aki; Ward, Nathan; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Barbey, Aron K

2016-08-15

Cognitive neuroscience has long sought to understand the biological foundations of human intelligence. Decades of research have revealed that general intelligence is correlated with two brain-based biomarkers: the concentration of the brain biochemical N-acetyl aspartate (NAA) measured by proton magnetic resonance spectroscopy (MRS) and total brain volume measured using structural MR imaging (MRI). However, the relative contribution of these biomarkers in predicting performance on core facets of human intelligence remains to be well characterized. In the present study, we sought to elucidate the role of NAA and brain volume in predicting fluid intelligence (Gf). Three canonical tests of Gf (BOMAT, Number Series, and Letter Sets) and three working memory tasks (Reading, Rotation, and Symmetry span tasks) were administered to a large sample of healthy adults (n=211). We conducted exploratory factor analysis to investigate the factor structure underlying Gf independent from working memory and observed two Gf components (verbal/spatial and quantitative reasoning) and one working memory component. Our findings revealed a dissociation between two brain biomarkers of Gf (controlling for age and sex): NAA concentration correlated with verbal/spatial reasoning, whereas brain volume correlated with quantitative reasoning and working memory. A follow-up analysis revealed that this pattern of findings is observed for males and females when analyzed separately. Our results provide novel evidence that distinct brain biomarkers are associated with specific facets of human intelligence, demonstrating that NAA and brain volume are independent predictors of verbal/spatial and quantitative facets of Gf. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Tracking brain motion during the cardiac cycle using spiral cine-DENSE MRI

PubMed Central

Zhong, Xiaodong; Meyer, Craig H.; Schlesinger, David J.; Sheehan, Jason P.; Epstein, Frederick H.; Larner, James M.; Benedict, Stanley H.; Read, Paul W.; Sheng, Ke; Cai, Jing

2009-01-01

Cardiac-synchronized brain motion is well documented, but the accurate measurement of such motion on the pixel-by-pixel basis has been hampered by the lack of proper imaging technique. In this article, the authors present the implementation of an autotracking spiral cine displacement-encoded stimulation echo (DENSE) magnetic resonance imaging (MRI) technique for the measurement of pulsatile brain motion during the cardiac cycle. Displacement-encoded dynamic MR images of three healthy volunteers were acquired throughout the cardiac cycle using the spiral cine-DENSE pulse sequence gated to the R wave of an electrocardiogram. Pixelwise Lagrangian displacement maps were computed, and 2D displacement as a function of time was determined for selected regions of interests. Different intracranial structures exhibited characteristic motion amplitude, direction, and pattern throughout the cardiac cycle. Time-resolved displacement curves revealed the pathway of pulsatile motion from brain stem to peripheral brain lobes. These preliminary results demonstrated that the spiral cine-DENSE MRI technique can be used to measure cardiac-synchronized pulsatile brain motion on the pixel-by-pixel basis with high temporal∕spatial resolution and sensitivity. PMID:19746774

Predicting age from cortical structure across the lifespan.

PubMed

Madan, Christopher R; Kensinger, Elizabeth A

2018-03-01

Despite interindividual differences in cortical structure, cross-sectional and longitudinal studies have demonstrated a large degree of population-level consistency in age-related differences in brain morphology. This study assessed how accurately an individual's age could be predicted by estimates of cortical morphology, comparing a variety of structural measures, including thickness, gyrification and fractal dimensionality. Structural measures were calculated across up to seven different parcellation approaches, ranging from one region to 1000 regions. The age prediction framework was trained using morphological measures obtained from T1-weighted MRI volumes collected from multiple sites, yielding a training dataset of 1056 healthy adults, aged 18-97. Age predictions were calculated using a machine-learning approach that incorporated nonlinear differences over the lifespan. In two independent, held-out test samples, age predictions had a median error of 6-7 years. Age predictions were best when using a combination of cortical metrics, both thickness and fractal dimensionality. Overall, the results reveal that age-related differences in brain structure are systematic enough to enable reliable age prediction based on metrics of cortical morphology. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Structural brain correlates associated with professional handball playing.

PubMed

Hänggi, Jürgen; Langer, Nicolas; Lutz, Kai; Birrer, Karin; Mérillat, Susan; Jäncke, Lutz

2015-01-01

There is no doubt that good bimanual performance is very important for skilled handball playing. The control of the non-dominant hand is especially demanding since efficient catching and throwing needs both hands. We investigated training-induced structural neuroplasticity in professional handball players using several structural neuroimaging techniques and analytic approaches and also provide a review of the literature about sport-induced structural neuroplastic alterations. Structural brain adaptations were expected in regions relevant for motor and somatosensory processing such as the grey matter (GM) of the primary/secondary motor (MI/supplementary motor area, SMA) and somatosensory cortex (SI/SII), basal ganglia, thalamus, and cerebellum and in the white matter (WM) of the corticospinal tract (CST) and corpus callosum, stronger in brain regions controlling the non-dominant left hand. Increased GM volume in handball players compared with control subjects were found in the right MI/SI, bilateral SMA/cingulate motor area, and left intraparietal sulcus. Fractional anisotropy (FA) and axial diffusivity were increased within the right CST in handball players compared with control women. Age of handball training commencement correlated inversely with GM volume in the right and left MI/SI and years of handball training experience correlated inversely with radial diffusivity in the right CST. Subcortical structures tended to be larger in handball players. The anatomical measures of the brain regions associated with handball playing were positively correlated in handball players, but not interrelated in control women. Training-induced structural alterations were found in the somatosensory-motor network of handball players, more pronounced in the right hemisphere controlling the non-dominant left hand. Correlations between handball training-related measures and anatomical differences suggest neuroplastic adaptations rather than a genetic predisposition for a ball playing affinity. Investigations of neuroplasticity specifically in sportsmen might help to understand the neural mechanisms of expertise in general.

Networks of myelin covariance

PubMed Central

Slater, David; Ruef, Anne; Sanabria‐Diaz, Gretel; Preisig, Martin; Kherif, Ferath; Draganski, Bogdan; Lutti, Antoine

2017-01-01

Abstract Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, 2013). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these “networks of myelin covariance” (Myelin‐Nets). The Myelin‐Nets were built from quantitative Magnetization Transfer data—an in‐vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin‐Nets. We therefore selected two age groups: Young‐Age (20–31 years old) and Old‐Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin‐Nets aging trajectory study. We found that the topological organization of the Myelin‐Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin‐Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging. PMID:29271053

Sex differences in the structural connectome of the human brain.

PubMed

Ingalhalikar, Madhura; Smith, Alex; Parker, Drew; Satterthwaite, Theodore D; Elliott, Mark A; Ruparel, Kosha; Hakonarson, Hakon; Gur, Raquel E; Gur, Ruben C; Verma, Ragini

2014-01-14

Sex differences in human behavior show adaptive complementarity: Males have better motor and spatial abilities, whereas females have superior memory and social cognition skills. Studies also show sex differences in human brains but do not explain this complementarity. In this work, we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged 8-22 y, 428 males and 521 females) and discovered unique sex differences in brain connectivity during the course of development. Connection-wise statistical analysis, as well as analysis of regional and global network measures, presented a comprehensive description of network characteristics. In all supratentorial regions, males had greater within-hemispheric connectivity, as well as enhanced modularity and transitivity, whereas between-hemispheric connectivity and cross-module participation predominated in females. However, this effect was reversed in the cerebellar connections. Analysis of these changes developmentally demonstrated differences in trajectory between males and females mainly in adolescence and in adulthood. Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.

Attention Performance Measured by Attention Network Test Is Correlated with Global and Regional Efficiency of Structural Brain Networks

PubMed Central

Xiao, Min; Ge, Haitao; Khundrakpam, Budhachandra S.; Xu, Junhai; Bezgin, Gleb; Leng, Yuan; Zhao, Lu; Tang, Yuchun; Ge, Xinting; Jeon, Seun; Xu, Wenjian; Evans, Alan C.; Liu, Shuwei

2016-01-01

Functional neuroimaging studies have indicated the involvement of separate brain areas in three distinct attention systems: alerting, orienting, and executive control (EC). However, the structural correlates underlying attention remains unexplored. Here, we utilized graph theory to examine the neuroanatomical substrates of the three attention systems measured by attention network test (ANT) in 65 healthy subjects. White matter connectivity, assessed with diffusion tensor imaging deterministic tractography was modeled as a structural network comprising 90 nodes defined by the automated anatomical labeling (AAL) template. Linear regression analyses were conducted to explore the relationship between topological parameters and the three attentional effects. We found a significant positive correlation between EC function and global efficiency of the whole brain network. At the regional level, node-specific correlations were discovered between regional efficiency and all three ANT components, including dorsolateral superior frontal gyrus, thalamus and parahippocampal gyrus for EC, thalamus and inferior parietal gyrus for alerting, and paracentral lobule and inferior occipital gyrus for orienting. Our findings highlight the fundamental architecture of interregional structural connectivity involved in attention and could provide new insights into the anatomical basis underlying human behavior. PMID:27777556

Maintaining brain health by monitoring inflammatory processes: a mechanism to promote successful aging.

PubMed

Rosano, Caterina; Marsland, Anna L; Gianaros, Peter J

2012-02-01

Maintaining brain health promotes successful aging. The main determinants of brain health are the preservation of cognitive function and remaining free from structural and metabolic abnormalities, including loss of neuronal synapses, atrophy, small vessel disease and focal amyloid deposits visible by neuroimaging. Promising studies indicate that these determinants are to some extent modifiable, even among adults seventy years and older. Converging animal and human evidence further suggests that inflammation is a shared mechanism, contributing to both cognitive decline and abnormalities in brain structure and metabolism. Thus, inflammation may provide a target for intervention. Specifically, circulating inflammatory markers have been associated with declines in cognitive function and worsening of brain structural and metabolic characteristics. Additionally, it has been proposed that older brains are characterized by a sensitization to neuroinflammatory responses, even in the absence of overt disease. This increased propensity to central inflammation may contribute to poor brain health and premature brain aging. Still unknown is whether and how peripheral inflammatory factors directly contribute to decline of brain health. Human research is limited by the challenges of directly measuring neuroinflammation in vivo. This review assesses the role that inflammation may play in the brain changes that often accompany aging, focusing on relationships between peripheral inflammatory markers and brain health among well-functioning, community-dwelling adults seventy years and older. We propose that monitoring and maintaining lower levels of systemic and central inflammation among older adults could help preserve brain health and support successful aging. Hence, we also identify plausible ways and novel experimental study designs of maintaining brain health late in age through interventions that target the immune system.

Non-invasive Brain Stimulation: Probing Intracortical Circuits and Improving Cognition in the Aging Brain

PubMed Central

Gomes-Osman, Joyce; Indahlastari, Aprinda; Fried, Peter J.; Cabral, Danylo L. F.; Rice, Jordyn; Nissim, Nicole R.; Aksu, Serkan; McLaren, Molly E.; Woods, Adam J.

2018-01-01

The impact of cognitive aging on brain function and structure is complex, and the relationship between aging-related structural changes and cognitive function are not fully understood. Physiological and pathological changes to the aging brain are highly variable, making it difficult to estimate a cognitive trajectory with which to monitor the conversion to cognitive decline. Beyond the information on the structural and functional consequences of cognitive aging gained from brain imaging and neuropsychological studies, non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) can enable stimulation of the human brain in vivo, offering useful insights into the functional integrity of intracortical circuits using electrophysiology and neuromodulation. TMS measurements can be used to identify and monitor changes in cortical reactivity, the integrity of inhibitory and excitatory intracortical circuits, the mechanisms of long-term potentiation (LTP)/depression-like plasticity and central cholinergic function. Repetitive TMS and tDCS can be used to modulate neuronal excitability and enhance cortical function, and thus offer a potential means to slow or reverse cognitive decline. This review will summarize and critically appraise relevant literature regarding the use of TMS and tDCS to probe cortical areas affected by the aging brain, and as potential therapeutic tools to improve cognitive function in the aging population. Challenges arising from intra-individual differences, limited reproducibility, and methodological differences will be discussed.

Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration

PubMed Central

Klein, Arno; Andersson, Jesper; Ardekani, Babak A.; Ashburner, John; Avants, Brian; Chiang, Ming-Chang; Christensen, Gary E.; Collins, D. Louis; Gee, James; Hellier, Pierre; Song, Joo Hyun; Jenkinson, Mark; Lepage, Claude; Rueckert, Daniel; Thompson, Paul; Vercauteren, Tom; Woods, Roger P.; Mann, J. John; Parsey, Ramin V.

2009-01-01

All fields of neuroscience that employ brain imaging need to communicate their results with reference to anatomical regions. In particular, comparative morphometry and group analysis of functional and physiological data require coregistration of brains to establish correspondences across brain structures. It is well established that linear registration of one brain to another is inadequate for aligning brain structures, so numerous algorithms have emerged to nonlinearly register brains to one another. This study is the largest evaluation of nonlinear deformation algorithms applied to brain image registration ever conducted. Fourteen algorithms from laboratories around the world are evaluated using 8 different error measures. More than 45,000 registrations between 80 manually labeled brains were performed by algorithms including: AIR, ANIMAL, ART, Diffeomorphic Demons, FNIRT, IRTK, JRD-fluid, ROMEO, SICLE, SyN, and four different SPM5 algorithms (“SPM2-type” and regular Normalization, Unified Segmentation, and the DARTEL Toolbox). All of these registrations were preceded by linear registration between the same image pairs using FLIRT. One of the most significant findings of this study is that the relative performances of the registration methods under comparison appear to be little affected by the choice of subject population, labeling protocol, and type of overlap measure. This is important because it suggests that the findings are generalizable to new subject populations that are labeled or evaluated using different labeling protocols. Furthermore, we ranked the 14 methods according to three completely independent analyses (permutation tests, one-way ANOVA tests, and indifference-zone ranking) and derived three almost identical top rankings of the methods. ART, SyN, IRTK, and SPM's DARTEL Toolbox gave the best results according to overlap and distance measures, with ART and SyN delivering the most consistently high accuracy across subjects and label sets. Updates will be published on the http://www.mindboggle.info/papers/ website. PMID:19195496

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks

PubMed Central

Colon-Perez, Luis M.; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R.; Price, Catherine; Mareci, Thomas H.

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime. PMID:26173147

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks.

PubMed

Colon-Perez, Luis M; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R; Price, Catherine; Mareci, Thomas H

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime.

A Statistical Analysis of Brain Morphology Using Wild Bootstrapping

PubMed Central

Ibrahim, Joseph G.; Tang, Niansheng; Rowe, Daniel B.; Hao, Xuejun; Bansal, Ravi; Peterson, Bradley S.

2008-01-01

Methods for the analysis of brain morphology, including voxel-based morphology and surface-based morphometries, have been used to detect associations between brain structure and covariates of interest, such as diagnosis, severity of disease, age, IQ, and genotype. The statistical analysis of morphometric measures usually involves two statistical procedures: 1) invoking a statistical model at each voxel (or point) on the surface of the brain or brain subregion, followed by mapping test statistics (e.g., t test) or their associated p values at each of those voxels; 2) correction for the multiple statistical tests conducted across all voxels on the surface of the brain region under investigation. We propose the use of new statistical methods for each of these procedures. We first use a heteroscedastic linear model to test the associations between the morphological measures at each voxel on the surface of the specified subregion (e.g., cortical or subcortical surfaces) and the covariates of interest. Moreover, we develop a robust test procedure that is based on a resampling method, called wild bootstrapping. This procedure assesses the statistical significance of the associations between a measure of given brain structure and the covariates of interest. The value of this robust test procedure lies in its computationally simplicity and in its applicability to a wide range of imaging data, including data from both anatomical and functional magnetic resonance imaging (fMRI). Simulation studies demonstrate that this robust test procedure can accurately control the family-wise error rate. We demonstrate the application of this robust test procedure to the detection of statistically significant differences in the morphology of the hippocampus over time across gender groups in a large sample of healthy subjects. PMID:17649909

The Effects of Explosive Blast as Compared to Post-Traumatic Stress Disorder on Brain Function and Structure

DTIC Science & Technology

2010-04-01

Aviyente, S., Kang, S.S., & Sponheim, S.R (2009, October). Beyond Wavelets : Utilizing uniform time and frequency resolution to improve measurement...may also help military leadership and health care professionals prescribe treatments that are personalized to an individual’s underlying brain pathology

The Relative Importance of Spatial Versus Temporal Structure in the Perception of Biological Motion: An Event-Related Potential Study

ERIC Educational Resources Information Center

Hirai, Masahiro; Hiraki, Kazuo

2006-01-01

We investigated how the spatiotemporal structure of animations of biological motion (BM) affects brain activity. We measured event-related potentials (ERPs) during the perception of BM under four conditions: normal spatial and temporal structure; scrambled spatial and normal temporal structure; normal spatial and scrambled temporal structure; and…

Individual differences in the dominance of interhemispheric connections predict cognitive ability beyond sex and brain size.

PubMed

Martínez, Kenia; Janssen, Joost; Pineda-Pardo, José Ángel; Carmona, Susanna; Román, Francisco Javier; Alemán-Gómez, Yasser; Garcia-Garcia, David; Escorial, Sergio; Quiroga, María Ángeles; Santarnecchi, Emiliano; Navas-Sánchez, Francisco Javier; Desco, Manuel; Arango, Celso; Colom, Roberto

2017-07-15

Global structural brain connectivity has been reported to be sex-dependent with women having increased interhemispheric connectivity (InterHc) and men having greater intrahemispheric connectivity (IntraHc). However, (a) smaller brains show greater InterHc, (b) larger brains show greater IntraHc, and (c) women have, on average, smaller brains than men. Therefore, sex differences in brain size may modulate sex differences in global brain connectivity. At the behavioural level, sex-dependent differences in connectivity are thought to contribute to men-women differences in spatial and verbal abilities. But this has never been tested at the individual level. The current study assessed whether individual differences in global structural connectome measures (InterHc, IntraHc and the ratio of InterHc relative to IntraHc) predict spatial and verbal ability while accounting for the effect of sex and brain size. The sample included forty men and forty women, who did neither differ in age nor in verbal and spatial latent components defined by a broad battery of tests and tasks. High-resolution T 1 -weighted and diffusion-weighted images were obtained for computing brain size and reconstructing the structural connectome. Results showed that men had higher IntraHc than women, while women had an increased ratio InterHc/IntraHc. However, these sex differences were modulated by brain size. Increased InterHc relative to IntraHc predicted higher spatial and verbal ability irrespective of sex and brain size. The positive correlations between the ratio InterHc/IntraHc and the spatial and verbal abilities were confirmed in 1000 random samples generated by bootstrapping. Therefore, sex differences in global structural connectome connectivity were modulated by brain size and did not underlie sex differences in verbal and spatial abilities. Rather, the level of dominance of InterHc over IntraHc may be associated with individual differences in verbal and spatial abilities in both men and women. Copyright © 2017 Elsevier Inc. All rights reserved.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cabral, Joana; Department of Psychiatry, University of Oxford, Oxford OX3 7JX; Fernandes, Henrique M.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the rolemore » of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.« less

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

NASA Astrophysics Data System (ADS)

Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

2013-12-01

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

Migraine Subclassification via a Data-Driven Automated Approach Using Multimodality Factor Mixture Modeling of Brain Structure Measurements.

PubMed

Schwedt, Todd J; Si, Bing; Li, Jing; Wu, Teresa; Chong, Catherine D

2017-07-01

The current subclassification of migraine is according to headache frequency and aura status. The variability in migraine symptoms, disease course, and response to treatment suggest the presence of additional heterogeneity or subclasses within migraine. The study objective was to subclassify migraine via a data-driven approach, identifying latent factors by jointly exploiting multiple sets of brain structural features obtained via magnetic resonance imaging (MRI). Migraineurs (n = 66) and healthy controls (n = 54) had brain MRI measurements of cortical thickness, cortical surface area, and volumes for 68 regions. A multimodality factor mixture model was used to subclassify MRIs and to determine the brain structural factors that most contributed to the subclassification. Clinical characteristics of subjects in each subgroup were compared. Automated MRI classification divided the subjects into two subgroups. Migraineurs in subgroup #1 had more severe allodynia symptoms during migraines (6.1 ± 5.3 vs. 3.6 ± 3.2, P = .03), more years with migraine (19.2 ± 11.3 years vs 13 ± 8.3 years, P = .01), and higher Migraine Disability Assessment (MIDAS) scores (25 ± 22.9 vs 15.7 ± 12.2, P = .04). There were not differences in headache frequency or migraine aura status between the two subgroups. Data-driven subclassification of brain MRIs based upon structural measurements identified two subgroups. Amongst migraineurs, the subgroups differed in allodynia symptom severity, years with migraine, and migraine-related disability. Since allodynia is associated with this imaging-based subclassification of migraine and prior publications suggest that allodynia impacts migraine treatment response and disease prognosis, future migraine diagnostic criteria could consider allodynia when defining migraine subgroups. © 2017 American Headache Society.

Trigeminal pathways deliver a low molecular weight drug from the nose to the brain and orofacial structures.

PubMed

Johnson, Neil J; Hanson, Leah R; Frey, William H

2010-06-07

Intranasal delivery has been shown to noninvasively deliver drugs from the nose to the brain in minutes along the olfactory and trigeminal nerve pathways, bypassing the blood-brain barrier. However, no one has investigated whether nasally applied drugs target orofacial structures, despite high concentrations observed in the trigeminal nerve innervating these tissues. Following intranasal administration of lidocaine to rats, trigeminally innervated structures (teeth, temporomandibular joint (TMJ), and masseter muscle) were found to have up to 20-fold higher tissue concentrations of lidocaine than the brain and blood as measured by ELISA. This concentration difference could allow intranasally administered therapeutics to treat disorders of orofacial structures (i.e., teeth, TMJ, and masseter muscle) without causing unwanted side effects in the brain and the rest of the body. In this study, an intranasally administered infrared dye reached the brain within 10 minutes. Distribution of dye is consistent with dye entering the trigeminal nerve after intranasal administration through three regions with high drug concentrations in the nasal cavity: the middle concha, the maxillary sinus, and the choana. In humans the trigeminal nerve passes through the maxillary sinus to innervate the maxillary teeth. Delivering lidocaine intranasally may provide an effective anesthetic technique for a noninvasive maxillary nerve block. Intranasal delivery could be used to target vaccinations and treat disorders with fewer side effects such as tooth pain, TMJ disorder, trigeminal neuralgia, headache, and brain diseases.

BDNF and BMI effects on brain structures of bipolar offspring: results from the global mood and brain science initiative.

PubMed

Mansur, R B; Brietzke, E; McIntyre, R S; Cao, B; Lee, Y; Japiassú, L; Chen, K; Lu, R; Lu, W; Li, T; Xu, G; Lin, K

2017-12-01

To compare brain-derived neurotrophic factor (BDNF) levels between offspring of individuals with bipolar disorders (BD) and healthy controls (HCs) and investigate the effects of BDNF levels and body mass index (BMI) on brain structures. Sixty-seven bipolar offspring and 45 HCs were included (ages 8-28). Structural images were acquired using 3.0 Tesla magnetic resonance imaging. Serum BDNF levels were measured using enzyme-linked immunosorbent assay. Multivariate and univariate analyses of covariance were conducted. Significantly higher BDNF levels were observed among bipolar offspring, relative to HCs (P > 0.025). Offspring status moderated the association between BDNF and BMI (F 1 =4.636, P = 0.034). After adjustment for relevant covariates, there was a trend for a significant interaction of group and BDNF on neuroimaging parameters (Wilks'λ F 56,94 =1.463, P = 0.052), with significant effects on cerebellar white matter and superior and middle frontal regions. Brain volume and BDNF were positively correlated among HCs and negatively correlated among bipolar offspring. Interactions between BDNF and BMI on brain volumes were non-significant among HCs (Wilks'λ F 28,2 =2.229, P = 0.357), but significant among bipolar offspring (Wilks'λ F 28,12 =2.899, P = 0.028). Offspring status and BMI moderate the association between BDNF levels and brain structures among bipolar offspring, underscoring BDNF regulation and overweight/obesity as key moderators of BD pathogenesis. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Sleep Duration and Age-Related Changes in Brain Structure and Cognitive Performance

PubMed Central

Lo, June C.; Loh, Kep Kee; Zheng, Hui; Sim, Sam K.Y.; Chee, Michael W.L.

2014-01-01

Study Objectives: To investigate the contribution of sleep duration and quality to age-related changes in brain structure and cognitive performance in relatively healthy older adults. Design: Community-based longitudinal brain and cognitive aging study using a convenience sample. Setting: Participants were studied in a research laboratory. Participants: Relatively healthy adults aged 55 y and older at study commencement. Interventions: N/A. Measurements and Results: Participants underwent magnetic resonance imaging and neuropsychological assessment every 2 y. Subjective assessments of sleep duration and quality and blood samples were obtained. Each hour of reduced sleep duration at baseline augmented the annual expansion rate of the ventricles by 0.59% (P = 0.007) and the annual decline rate in global cognitive performance by 0.67% (P = 0.050) in the subsequent 2 y after controlling for the effects of age, sex, education, and body mass index. In contrast, global sleep quality at baseline did not modulate either brain or cognitive aging. High-sensitivity C-reactive protein, a marker of systemic inflammation, showed no correlation with baseline sleep duration, brain structure, or cognitive performance. Conclusions: In healthy older adults, short sleep duration is associated with greater age-related brain atrophy and cognitive decline. These associations are not associated with elevated inflammatory responses among short sleepers. Citation: Lo JC, Loh KK, Zheng H, Sim SK, Chee MW. Sleep duration and age-related changes in brain structure and cognitive performance. SLEEP 2014;37(7):1171-1178. PMID:25061245

Normal variation in early parental sensitivity predicts child structural brain development.

PubMed

Kok, Rianne; Thijssen, Sandra; Bakermans-Kranenburg, Marian J; Jaddoe, Vincent W V; Verhulst, Frank C; White, Tonya; van IJzendoorn, Marinus H; Tiemeier, Henning

2015-10-01

Early caregiving can have an impact on brain structure and function in children. The influence of extreme caregiving experiences has been demonstrated, but studies on the influence of normal variation in parenting quality are scarce. Moreover, no studies to date have included the role of both maternal and paternal sensitivity in child brain maturation. This study examined the prospective relation between mothers' and fathers' sensitive caregiving in early childhood and brain structure later in childhood. Participants were enrolled in a population-based prenatal cohort. For 191 families, maternal and paternal sensitivity was repeatedly observed when the child was between 1 year and 4 years of age. Head circumference was assessed at 6 weeks, and brain structure was assessed using magnetic resonance imaging (MRI) measurements at 8 years of age. Higher levels of parental sensitivity in early childhood were associated with larger total brain volume (adjusted β = 0.15, p = .01) and gray matter volume (adjusted β = 0.16, p = .01) at 8 years, controlling for infant head size. Higher levels of maternal sensitivity in early childhood were associated with a larger gray matter volume (adjusted β = 0.13, p = .04) at 8 years, independent of infant head circumference. Associations with maternal versus paternal sensitivity were not significantly different. Normal variation in caregiving quality is related to markers of more optimal brain development in children. The results illustrate the important role of both mothers and fathers in child brain development. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Material and physical model for evaluation of deep brain activity contribution to EEG recordings

NASA Astrophysics Data System (ADS)

Ye, Yan; Li, Xiaoping; Wu, Tiecheng; Li, Zhe; Xie, Wenwen

2015-12-01

Deep brain activity is conventionally recorded with surgical implantation of electrodes. During the neurosurgery, brain tissue damage and the consequent side effects to patients are inevitably incurred. In order to eliminate undesired risks, we propose that deep brain activity should be measured using the noninvasive scalp electroencephalography (EEG) technique. However, the deeper the neuronal activity is located, the noisier the corresponding scalp EEG signals are. Thus, the present study aims to evaluate whether deep brain activity could be observed from EEG recordings. In the experiment, a three-layer cylindrical head model was constructed to mimic a human head. A single dipole source (sine wave, 10 Hz, altering amplitudes) was embedded inside the model to simulate neuronal activity. When the dipole source was activated, surface potential was measured via electrodes attached on the top surface of the model and raw data were recorded for signal analysis. Results show that the dipole source activity positioned at 66 mm depth in the model, equivalent to the depth of deep brain structures, is clearly observed from surface potential recordings. Therefore, it is highly possible that deep brain activity could be observed from EEG recordings and deep brain activity could be measured using the noninvasive scalp EEG technique.

Brain MRI atrophy quantification in MS

PubMed Central

Rocca, Maria A.; Battaglini, Marco; Benedict, Ralph H.B.; De Stefano, Nicola; Geurts, Jeroen J.G.; Henry, Roland G.; Horsfield, Mark A.; Jenkinson, Mark; Pagani, Elisabetta

2017-01-01

Patients with the main clinical phenotypes of multiple sclerosis (MS) manifest varying degrees of brain atrophy beyond that of normal aging. Assessment of atrophy helps to distinguish clinically and cognitively deteriorating patients and predicts those who will have a less-favorable clinical outcome over the long term. Atrophy can be measured from brain MRI scans, and many technological improvements have been made over the last few years. Several software tools, with differing requirements on technical ability and levels of operator intervention, are currently available and have already been applied in research or clinical trial settings. Despite this, the measurement of atrophy in routine clinical practice remains an unmet need. After a short summary of the pathologic substrates of brain atrophy in MS, this review attempts to guide the clinician towards a better understanding of the methods currently used for quantifying brain atrophy in this condition. Important physiologic factors that affect brain volume measures are also considered. Finally, the most recent research on brain atrophy in MS is summarized, including whole brain and various compartments thereof (i.e., white matter, gray matter, selected CNS structures). Current methods provide sufficient precision for cohort studies, but are not adequate for confidently assessing changes in individual patients over the scale of months or a few years. PMID:27986875

From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery.

PubMed

Pang, Elizabeth W; Snead Iii, O C

2016-01-01

New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the traditional use of MEG for functional neurosurgery, describe recent advances in MEG connectivity analyses, and consider the additional benefits that could be gained with the inclusion of MEG connectivity studies. Since MEG has been most widely applied to the study of epilepsy, we will frame this article within the context of epilepsy surgery and functional neurosurgery for epilepsy.

Altered Resting Brain Function and Structure in Professional Badminton Players

PubMed Central

Di, Xin; Zhu, Senhua; Wang, Pin; Ye, Zhuoer; Zhou, Ke; Zhuo, Yan

2012-01-01

Abstract Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills. PMID:22840241

STRUCTURAL AND CONNECTOMIC NEUROIMAGING FOR THE PERSONALIZED STUDY OF LONGITUDINAL ALTERATIONS IN CORTICAL SHAPE, THICKNESS AND CONNECTIVITY AFTER TRAUMATIC BRAIN INJURY

PubMed Central

Irimia, A.; Goh, S.-Y. M.; Torgerson, C. M.; Vespa, P. M.; Van Horn, J. D.

2014-01-01

The integration of longitudinal brain structure analysis with neurointensive care strategies continues to be a substantial difficulty facing the traumatic brain injury (TBI) research community. For patient-tailored case analysis, it remains challenging to establish how lesion profile modulates longitudinal changes in cortical structure and connectivity, as well as how these changes lead to behavioral, cognitive and neural dysfunction. Additionally, despite the clinical potential of morphometric and connectomic studies, few analytic tools are available for their study in TBI. Here we review the state of the art in structural and connectomic neuroimaging for the study of TBI and illustrate a set of recently-developed, patient-tailored approaches for the study of TBI-related brain atrophy and alterations in morphometry as well as inter-regional connectivity. The ability of such techniques to quantify how injury modulates longitudinal changes in cortical shape, structure and circuitry is highlighted. Quantitative approaches such as these can be used to assess and monitor the clinical condition and evolution of TBI victims, and can have substantial translational impact, especially when used in conjunction with measures of neuropsychological function. PMID:24844173

Increased densities of monocarboxylate transporter MCT1 after chronic hyperglycemia in rat brain.

PubMed

Canis, Martin; Maurer, Martin H; Kuschinsky, Wolfgang; Duembgen, Lutz; Duelli, Roman

2009-02-27

The brain is capable of taking up monocarboxylates as energy substrates. Under physiological conditions, plasma levels of monocarboxylates are very low and glucose is the primary energy substrate in brain metabolism. However, given conditions such as hyperglycemia and ketosis, levels of circulating monocarboxylates such as lactate and pyruvate are elevated. Previous studies reported an increased expression of monocarboxylate transporter MCT1 in brain following ketotic diet. The major aim of the present study was to answer the question whether chronic hyperglycemia is likewise sufficient to change local densities of MCT1 in the brain. Moreover, chronic hyperglycemia increases local cerebral glucose utilization (LCGU) in particular brain areas. Glucose hereby enters the brain parenchyma via glucose transporters and is partially metabolised by astrocytes, which then release lactate to meet the energetic demands of surrounding neurons. Streptozotocin was given intravenously to induce chronic hyperglycemia and local densities of MCT1 were measured by immunoautoradiographic methods in cryosections of rat brains. The density of monocarboxylate transporter MCT1 was significantly increased in 10 of 24 brain structures investigated (median increase 11.7+/-3.4 %). Immunocytochemical stainings of these substructures revealed an expression of MCT1 within endothelial cells and astrocytes. A comparison of MCT1 densities with LCGU measured in a previous study under normo- and hyperglycemic conditions revealed a partial correlation between both parameters and under both conditions. Four out of 10 brain areas, which showed a significant increase in MCT1 density due to hyperglycemia, also showed a significant increase in LCGU. In summary, our data show that chronic hyperglycemia induces a moderate increase of local and global density of MCT1 in several brain structures. However, in terms of brain topologies and substructures this phenomenon did only partially match with increased LCGU. It is concluded that MCT1 transporters were up-regulated during chronic hyperglycemia at the level of brain substructures and independently of LCGU.

Abnormal brain chemistry in chronic back pain: an in vivo proton magnetic resonance spectroscopy study.

PubMed

Grachev, I D; Fredrickson, B E; Apkarian, A V

2000-12-15

The neurobiology of chronic pain, including chronic back pain, is unknown. Structural imaging studies of the spine cannot explain all cases of chronic back pain. Functional brain imaging studies indicate that the brain activation patterns are different between chronic pain patients and normal subjects, and the thalamus, and prefrontal and cingulate cortices are involved in some types of chronic pain. Animal models of chronic pain suggest abnormal spinal cord chemistry. Does chronic pain cause brain chemistry changes? We examined brain chemistry changes in patients with chronic back pain using in vivo single- voxel proton magnetic resonance spectroscopy ((1)H-MRS). In vivo (1)H-MRS was used to measure relative concentrations of N-acetyl aspartate, creatine, choline, glutamate, glutamine, gamma-aminobutyric acid, inositol, glucose and lactate in relation to the concentration of creatine. These measurements were performed in six brain regions of nine chronic low back pain patients and 11 normal volunteers. All chronic back pain subjects underwent clinical evaluation and perceptual measures of pain and anxiety. We show that chronic back pain alters the human brain chemistry. Reductions of N-acetyl aspartate and glucose were demonstrated in the dorsolateral prefrontal cortex. Cingulate, sensorimotor, and other brain regions showed no chemical concentration differences. In chronic back pain, the interrelationship between chemicals within and across brain regions was abnormal, and there was a specific relationship between regional chemicals and perceptual measures of pain and anxiety. These findings provide direct evidence of abnormal brain chemistry in chronic back pain, which may be useful in diagnosis and future development of more effective pharmacological treatments.

Relationship between brain function (aEEG) and brain structure (MRI) and their predictive value for neurodevelopmental outcome of preterm infants.

PubMed

Hüning, Britta; Storbeck, Tobias; Bruns, Nora; Dransfeld, Frauke; Hobrecht, Julia; Karpienski, Julia; Sirin, Selma; Schweiger, Bernd; Weiss, Christel; Felderhoff-Müser, Ursula; Müller, Hanna

2018-05-22

To improve the prediction of neurodevelopmental outcome in very preterm infants, this study used the combination of amplitude-integrated electroencephalography (aEEG) within the first 72 h of life and cranial magnetic resonance imaging (MRI) at term equivalent age. A single-center cohort of 38 infants born before 32 weeks of gestation was subjected to both investigations. Structural measurements were performed on MRI. Multiple regression analysis was used to identify independent factors including functional and structural brain measurements associated with outcome at a corrected age of 24 months. aEEG parameters significantly correlated with MRI measurements. Reduced deep gray matter volume was associated with low Burdjalov Score on day 3 (p < 0.0001) and day 1-3 (p = 0.0012). The biparietal width and the transcerebellar diameter were related to Burdjalov Score on day 1 (p = 0.0111; p = 0.0002). The final multiple regression analysis revealed independent predictors of neurodevelopmental outcome: intraventricular hemorrhage (p = 0.0060) and interhemispheric distance (p = 0.0052) for mental developmental index; Burdjalov Score day 1 (p = 0.0201) and interhemispheric distance (p = 0.0142) for psychomotor developmental index. Functional aEEG parameters were associated with altered brain maturation on MRI. The combination of aEEG and MRI contributes to the prediction of outcome at 24 months. What is Known: • Prematurity remains a risk factor for impaired neurodevelopment. • aEEG is used to measure brain activity in preterm infants and cranial MRI is performed to identify structural gray and white matter abnormalities with impact on neurodevelopmental outcome. What is New: • aEEG parameters observed within the first 72 h of life were associated with altered deep gray matter volumes, biparietal width, and transcerebellar diameter at term equivalent age. • The combination of aEEG and MRI contributes to the prediction of neurodevelopmental outcome at 2 years of corrected age in very preterm infants.

Time-dependence of graph theory metrics in functional connectivity analysis

PubMed Central

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J.; Haneef, Zulfi; Stern, John M.

2016-01-01

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. PMID:26518632

Time-dependence of graph theory metrics in functional connectivity analysis.

PubMed

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M

2016-01-15

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. Copyright © 2015 Elsevier Inc. All rights reserved.

Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury

PubMed Central

De Simoni, Sara; Jenkins, Peter O; Bourke, Niall J; Fleminger, Jessica J; Jolly, Amy E; Patel, Maneesh C; Leech, Robert; Sharp, David J

2018-01-01

Abstract Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with measures of executive dysfunction. We show for the first time that altered subcortical connectivity is associated with large-scale network disruption in traumatic brain injury and that this disruption is related to the cognitive impairments seen in these patients. PMID:29186356

Thalamic and extrathalamic mechanisms of consciousness after severe brain injury.

PubMed

Lutkenhoff, Evan S; Chiang, Jeffrey; Tshibanda, Luaba; Kamau, Evelyn; Kirsch, Murielle; Pickard, John D; Laureys, Steven; Owen, Adrian M; Monti, Martin M

2015-07-01

What mechanisms underlie the loss and recovery of consciousness after severe brain injury? We sought to establish, in the largest cohort of patients with disorders of consciousness (DOC) to date, the link between gold standard clinical measures of awareness and wakefulness, and specific patterns of local brain pathology-thereby possibly providing a mechanistic framework for patient diagnosis, prognosis, and treatment development. Structural T1-weighted magnetic resonance images were collected, in a continuous sample of 143 severely brain-injured patients with DOC (and 96 volunteers), across 2 tertiary expert centers. Brain atrophy in subcortical regions (bilateral thalamus, basal ganglia, hippocampus, basal forebrain, and brainstem) was assessed across (1) healthy volunteers and patients, (2) clinical entities (eg, vegetative state, minimally conscious state), (3) clinical measures of consciousness (Coma Recovery Scale-Revised), and (4) injury etiology. Compared to volunteers, patients exhibited significant atrophy across all structures (p < 0.05, corrected). Strikingly, we found almost no significant differences across clinical entities. Nonetheless, the clinical measures of awareness and wakefulness upon which differential diagnosis rely were systematically associated with tissue atrophy within thalamic and basal ganglia nuclei, respectively; the basal forebrain was atrophied in proportion to patients' response to sensory stimulation. In addition, nontraumatic injuries exhibited more extensive thalamic atrophy. These findings provide, for the first time, a grounding in pathology for gold standard behavior-based clinical measures of consciousness, and reframe our current models of DOC by stressing the different links tying thalamic mechanisms to willful behavior and extrathalamic mechanisms to behavioral (and electrocortical) arousal. © 2015 American Neurological Association.

Investigating brain community structure abnormalities in bipolar disorder using path length associated community estimation.

PubMed

Gadelkarim, Johnson J; Ajilore, Olusola; Schonfeld, Dan; Zhan, Liang; Thompson, Paul M; Feusner, Jamie D; Kumar, Anand; Altshuler, Lori L; Leow, Alex D

2014-05-01

In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling. Copyright © 2013 Wiley Periodicals, Inc.

Interaction of parenting experiences and brain structure in the prediction of depressive symptoms in adolescents.

PubMed

Yap, Marie B H; Whittle, Sarah; Yücel, Murat; Sheeber, Lisa; Pantelis, Christos; Simmons, Julian G; Allen, Nicholas B

2008-12-01

Although some evidence suggests that neuroanatomic abnormalities may confer risk for major depressive disorder, findings are inconsistent. One potential explanation for this is the moderating role of environmental context, with individuals differing in their biological sensitivity to context. To examine the influence of adverse parenting as an environmental moderator of the association between brain structure and depressive symptoms. Cross-sectional measurement of brain structure, adverse parenting, and depressive symptoms in early adolescents. General community. A total of 106 students aged 11 to 13 years (55 males [51%]), recruited from primary schools in Melbourne, Australia, and their mothers. Selection was based on affective temperament, aimed at producing a sample representing a broad range of risk for major depressive disorder. No participant evidenced current or past case-level depressive, substance use, or eating disorder. (1) Volumetric measures of adolescents' amygdala, hippocampus, and anterior cingulate cortex (ACC); (2) frequency of observed maternal aggressive behavior during a mother-adolescent conflict-resolution interaction; and (3) adolescent depressive symptoms. Boys with smaller right amygdalas reported more depressive symptoms. However, neither hippocampal volume nor asymmetry measures of limbic or paralimbic ACC were directly related to level of depressive symptoms. Importantly, frequency of maternal aggressive behaviors moderated the associations between both the amygdala and ACC, and adolescent symptoms. Particularly, in conditions of low levels of maternal aggressiveness, boys with larger right amygdalas, girls with smaller bilateral amygdalas, and both boys and girls with smaller left paralimbic ACC reported fewer symptoms. These findings help elucidate the complex relationships between brain structure, environmental factors, and depressive symptoms. Further longitudinal research is required to examine how these factors contribute to the onset of case-level disorder, but given that family context risk factors are modifiable, our findings do suggest the potential utility of targeted early parenting interventions.

Time-dependent differences in cortical measures and their associations with behavioral measures following mild traumatic brain injury.

PubMed

Bajaj, Sahil; Dailey, Natalie S; Rosso, Isabelle M; Rauch, Scott L; Killgore, William D S

2018-05-01

There is currently a critical need to establish an improved understanding of time-dependent differences in brain structure following mild traumatic brain injury (mTBI). We compared differences in brain structure, specifically cortical thickness (CT), cortical volume (CV), and cortical surface area (CSA) in 54 individuals who sustained a recent mTBI and 33 healthy controls (HCs). Individuals with mTBI were split into three groups, depending on their time since injury. By comparing structural measures between mTBI and HC groups, differences in CT reflected cortical thickening within several areas following 0-3 (time-point, TP1) and 3-6 months (TP2) post-mTBI. Compared with the HC group, the mTBI group at TP2 showed lower CSA within several areas. Compared with the mTBI group at TP2, the mTBI group during the most chronic stage (TP3: 6-18 months post-mTBI) showed significantly higher CSA in several areas. All the above reported differences in CT and CSA were significant at a cluster-forming p < .01 (corrected for multiple comparisons). We also found that in the mTBI group at TP2, CT within two clusters (i.e., the left rostral middle frontal gyrus (L. RMFG) and the right postcentral gyrus (R. PostCG)) was negatively correlated with basic attention abilities (L. RMFG: r = -.41, p = .05 and R. PostCG: r = -.44, p = .03). Our findings suggest that alterations in CT and associated neuropsychological assessments may be more prominent during the early stages of mTBI. However, alterations in CSA may reflect compensatory structural recovery during the chronic stages of mTBI. © 2018 Wiley Periodicals, Inc.

Identification of alterations associated with age in the clustering structure of functional brain networks.

PubMed

Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre

2018-01-01

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

Associations Between Left Ventricular Dysfunction and Brain Structure and Function: Findings From the SABRE (Southall and Brent Revisited) Study.

PubMed

Park, Chloe M; Williams, Emily D; Chaturvedi, Nish; Tillin, Therese; Stewart, Robert J; Richards, Marcus; Shibata, Dean; Mayet, Jamil; Hughes, Alun D

2017-04-18

Subclinical left ventricular (LV) dysfunction has been inconsistently associated with early cognitive impairment, and mechanistic pathways have been poorly considered. We investigated the cross-sectional relationship between LV dysfunction and structural/functional measures of the brain and explored the role of potential mechanisms. A total of 1338 individuals (69±6 years) from the Southall and Brent Revisited study underwent echocardiography for systolic (tissue Doppler imaging peak systolic wave) and diastolic (left atrial diameter) assessment. Cognitive function was assessed and total and hippocampal brain volumes were measured by magnetic resonance imaging. Global LV function was assessed by circulating N-terminal pro-brain natriuretic peptide. The role of potential mechanistic pathways of arterial stiffness, atherosclerosis, microvascular disease, and inflammation were explored. After adjusting for age, sex, and ethnicity, lower systolic function was associated with lower total brain (beta±standard error, 14.9±3.2 cm 3 ; P <0.0001) and hippocampal volumes (0.05±0.02 cm 3 , P =0.01). Reduced diastolic function was associated with poorer working memory (-0.21±0.07, P =0.004) and fluency scores (-0.18±0.08, P =0.02). Reduced global LV function was associated with smaller hippocampal volume (-0.10±0.03 cm 3 , P =0.004) and adverse visual memory (-0.076±0.03, P =0.02) and processing speed (0.063±0.02, P =0.006) scores. Separate adjustment for concomitant cardiovascular risk factors attenuated associations with hippocampal volume and fluency only. Further adjustment for the alternative pathways of microvascular disease or arterial stiffness attenuated the relationship between global LV function and visual memory. In a community-based sample of older people, measures of LV function were associated with structural/functional measures of the brain. These associations were not wholly explained by concomitant risk factors or potential mechanistic pathways. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Altered small-world topology of structural brain networks in infants with intrauterine growth restriction and its association with later neurodevelopmental outcome.

PubMed

Batalle, Dafnis; Eixarch, Elisenda; Figueras, Francesc; Muñoz-Moreno, Emma; Bargallo, Nuria; Illa, Miriam; Acosta-Rojas, Ruthy; Amat-Roldan, Ivan; Gratacos, Eduard

2012-04-02

Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the architecture of neural circuitry and developing imaging biomarkers of poor neurodevelopment outcome in infants with prenatal diseases. Copyright © 2012 Elsevier Inc. All rights reserved.

Advanced lesion symptom mapping analyses and implementation as BCBtoolkit

PubMed Central

Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika

2018-01-01

Abstract Background Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Findings Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. Conclusions The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1]. PMID:29432527

Prenatal Brain MR Imaging: Reference Linear Biometric Centiles between 20 and 24 Gestational Weeks.

PubMed

Conte, G; Milani, S; Palumbo, G; Talenti, G; Boito, S; Rustico, M; Triulzi, F; Righini, A; Izzo, G; Doneda, C; Zolin, A; Parazzini, C

2018-05-01

Evaluation of biometry is a fundamental step in prenatal brain MR imaging. While different studies have reported reference centiles for MR imaging biometric data of fetuses in the late second and third trimesters of gestation, no one has reported them in fetuses in the early second trimester. We report centiles of normal MR imaging linear biometric data of a large cohort of fetal brains within 24 weeks of gestation. From the data bases of 2 referral centers of fetal medicine, accounting for 3850 examinations, we retrospectively collected 169 prenatal brain MR imaging examinations of singleton pregnancies, between 20 and 24 weeks of gestational age, with normal brain anatomy at MR imaging and normal postnatal neurologic development. To trace the reference centiles, we used the CG-LMS method. Reference biometric centiles for the developing structures of the cerebrum, cerebellum, brain stem, and theca were obtained. The overall interassessor agreement was adequate for all measurements. Reference biometric centiles of the brain structures in fetuses between 20 and 24 weeks of gestational age may be a reliable tool in assessing fetal brain development. © 2018 by American Journal of Neuroradiology.

Early parental care is important for hippocampal maturation: evidence from brain morphology in humans.

PubMed

Rao, Hengyi; Betancourt, Laura; Giannetta, Joan M; Brodsky, Nancy L; Korczykowski, Marc; Avants, Brian B; Gee, James C; Wang, Jiongjiong; Hurt, Hallam; Detre, John A; Farah, Martha J

2010-01-01

The effects of early life experience on later brain structure and function have been studied extensively in animals, yet the relationship between childhood experience and normal brain development in humans remains largely unknown. Using a unique longitudinal data set including ecologically valid in-home measures of early experience during childhood (at age 4 and 8 years) and high-resolution structural brain imaging during adolescence (mean age 14 years), we examined the effects on later brain morphology of two dimensions of early experience: parental nurturance and environmental stimulation. Parental nurturance at age 4 predicts the volume of the left hippocampus in adolescence, with better nurturance associated with smaller hippocampal volume. In contrast, environmental stimulation did not correlate with hippocampal volume. Moreover, the association between hippocampal volume and parental nurturance disappears at age 8, supporting the existence of a sensitive developmental period for brain maturation. These findings indicate that variation in normal childhood experience is associated with differences in brain morphology, and hippocampal volume is specifically associated with early parental nurturance. Our results provide neuroimaging evidence supporting the important role of warm parental care during early childhood for brain maturation.

Developmental Changes in Organization of Structural Brain Networks

PubMed Central

Khundrakpam, Budhachandra S.; Reid, Andrew; Brauer, Jens; Carbonell, Felix; Lewis, John; Ameis, Stephanie; Karama, Sherif; Lee, Junki; Chen, Zhang; Das, Samir; Evans, Alan C.; Ball, William S.; Byars, Anna Weber; Schapiro, Mark; Bommer, Wendy; Carr, April; German, April; Dunn, Scott; Rivkin, Michael J.; Waber, Deborah; Mulkern, Robert; Vajapeyam, Sridhar; Chiverton, Abigail; Davis, Peter; Koo, Julie; Marmor, Jacki; Mrakotsky, Christine; Robertson, Richard; McAnulty, Gloria; Brandt, Michael E.; Fletcher, Jack M.; Kramer, Larry A.; Yang, Grace; McCormack, Cara; Hebert, Kathleen M.; Volero, Hilda; Botteron, Kelly; McKinstry, Robert C.; Warren, William; Nishino, Tomoyuki; Robert Almli, C.; Todd, Richard; Constantino, John; McCracken, James T.; Levitt, Jennifer; Alger, Jeffrey; O'Neil, Joseph; Toga, Arthur; Asarnow, Robert; Fadale, David; Heinichen, Laura; Ireland, Cedric; Wang, Dah-Jyuu; Moss, Edward; Zimmerman, Robert A.; Bintliff, Brooke; Bradford, Ruth; Newman, Janice; Evans, Alan C.; Arnaoutelis, Rozalia; Bruce Pike, G.; Louis Collins, D.; Leonard, Gabriel; Paus, Tomas; Zijdenbos, Alex; Das, Samir; Fonov, Vladimir; Fu, Luke; Harlap, Jonathan; Leppert, Ilana; Milovan, Denise; Vins, Dario; Zeffiro, Thomas; Van Meter, John; Lange, Nicholas; Froimowitz, Michael P.; Botteron, Kelly; Robert Almli, C.; Rainey, Cheryl; Henderson, Stan; Nishino, Tomoyuki; Warren, William; Edwards, Jennifer L.; Dubois, Diane; Smith, Karla; Singer, Tish; Wilber, Aaron A.; Pierpaoli, Carlo; Basser, Peter J.; Chang, Lin-Ching; Koay, Chen Guan; Walker, Lindsay; Freund, Lisa; Rumsey, Judith; Baskir, Lauren; Stanford, Laurence; Sirocco, Karen; Gwinn-Hardy, Katrina; Spinella, Giovanna; McCracken, James T.; Alger, Jeffry R.; Levitt, Jennifer; O'Neill, Joseph

2013-01-01

Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8–8.4 year; late childhood: 8.5–11.3 year; early adolescence: 11.4–14.7 year; late adolescence: 14.8–18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces. PMID:22784607

Spaceflight Effects on Neurocognitive Performance: Extent, Longevity and Neural Bases

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Kofman, I. S.; Cassady, K.; Yuan, P.; De Dios, Y. E.; Gadd, N.; Riascos, R. F.; Wood, S. J.;

Subregional neuroanatomical change as a biomarker for Alzheimer's disease

PubMed Central

Holland, Dominic; Brewer, James B.; Hagler, Donald J.; Fennema-Notestine, Christine; Dale, Anders M.; Weiner, Michael; Thal, Leon; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowki, John; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Gamst, Anthony; Potter, William Z.; Montine, Tom; Anders, Dale; Bernstein, Matthew; Felmlee, Joel; Fox, Nick; Thompson, Paul; Schuff, Norbert; Alexander, Gene; Bandy, Dan; Koeppe, Robert A.; Foster, Norm; Reiman, Eric M.; Chen, Kewei; Shaw, Les; Lee, Virginia M.-Y.; Korecka, Magdalena; Crawford, Karen; Neu, Scott; Harvey, Danielle; Kornak, John; Kachaturian, Zaven; Frank, Richard; Snyder, Peter J.; Molchan, Susan; Kaye, Jeffrey; Vorobik, Remi; Quinn, Joseph; Schneider, Lon; Pawluczyk, Sonia; Spann, Bryan; Fleisher, Adam S.; Vanderswag, Helen; Heidebrink, Judith L.; Lord, Joanne L.; Johnson, Kris; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Morris, John C.; Mintun, Mark A.; Schneider, Stacy; Marson, Daniel; Griffith, Randall; Badger, Beverly; Grossman, Hillel; Tang, Cheuk; Stern, Jessica; deToledo-Morrell, Leyla; Shah, Raj C.; Bach, Julie; Duara, Ranjan; Isaacson, Richard; Strauman, Silvia; Albert, Marilyn S.; Pedroso, Julia; Toroney, Jaimie; Rusinek, Henry; de Leon, Mony J.; De Santi, Susan M.; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Aiello, Marilyn; Clark, Christopher M.; Pham, Cassie; Nunez, Jessica; Smith, Charles D.; Given, Curtis A.; Hardy, Peter; DeKosky, Steven T.; Oakley, MaryAnn; Simpson, Donna M.; Ismail, M. Saleem; Porsteinsson, Anton; McCallum, Colleen; Cramer, Steven C.; Mulnard, Ruth A.; McAdams-Ortiz, Catherine; Diaz-Arrastia, Ramon; Martin-Cook, Kristen; DeVous, Michael; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Anderson, Heather S.; Laubinger, Mary M.; Bartzokis, George; Silverman, Daniel H. S.; Lu, Po H.; Fletcher, Rita; Parfitt, Francine; Johnson, Heather; Farlow, Martin; Herring, Scott; Hake, Ann M.; van Dyck, Christopher H.; MacAvoy, Martha G.; Bifano, Laurel A.; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Graham, Simon; Caldwell, Curtis; Feldman, Howard; Assaly, Michele; Hsiung, Ging-Yuek R.; Kertesz, Andrew; Rogers, John; Trost, Dick; Bernick, Charles; Gitelman, Darren; Johnson, Nancy; Mesulam, Marsel; Sadowsky, Carl; Villena, Teresa; Mesner, Scott; Aisen, Paul S.; Johnson, Kathleen B.; Behan, Kelly E.; Sperling, Reisa A.; Rentz, Dorene M.; Johnson, Keith A.; Rosen, Allyson; Tinklenberg, Jared; Ashford, Wes; Sabbagh, Marwan; Connor, Donald; Obradov, Sanja; Killiany, Ron; Norbash, Alex; Obisesan, Thomas O.; Jayam-Trouth, Annapurni; Wang, Paul; Auchus, Alexander P.; Huang, Juebin; Friedland, Robert P.; DeCarli, Charles; Fletcher, Evan; Carmichael, Owen; Kittur, Smita; Mirje, Seema; Johnson, Sterling C.; Borrie, Michael; Lee, T.-Y.; Asthana, Sanjay; Carlsson, Cynthia M.; Potkin, Steven G.; Highum, Diane; Preda, Adrian; Nguyen, Dana; Tariot, Pierre N.; Hendin, Barry A.; Scharre, Douglas W.; Kataki, Maria; Beversdorf, David Q.; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Gandy, Sam; Marenberg, Marjorie E.; Rovner, Barry W.; Pearlson, Godfrey; Blank, Karen; Anderson, Karen; Saykin, Andrew J.; Santulli, Robert B.; Pare, Nadia; Williamson, Jeff D.; Sink, Kaycee M.; Potter, Huntington; Ashok Raj, B.; Giordano, Amy; Ott, Brian R.; Wu, Chuang-Kuo; Cohen, Ronald; Wilks, Kerri L.; Safirstein, Beth E.

2009-01-01

Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease. PMID:19996185

Subregional neuroanatomical change as a biomarker for Alzheimer's disease.

PubMed

Holland, Dominic; Brewer, James B; Hagler, Donald J; Fennema-Notestine, Christine; Fenema-Notestine, Christine; Dale, Anders M

2009-12-08

Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.

Comparison of Brain Activity Correlating with Self-Report versus Narrative Attachment Measures during Conscious Appraisal of an Attachment Figure

PubMed Central

Yaseen, Zimri S.; Zhang, Xian; Muran, J. Christopher; Winston, Arnold; Galynker, Igor I.

2016-01-01

Objectives: The Adult Attachment Interview (AAI) has been the gold standard of attachment assessment, but requires special training. The Relationship Scales Questionnaire (RSQ) is a widely used self-report measure. We investigate how each correlates with brain activity during appraisal of subjects’ mothers. Methods: Twenty-eight women were scored on the AAI, RSQ, and mood measures. During functional magnetic resonance imaging, subjects viewed their mothers in neutral-, valence-, and salience-rating conditions. We identified regions where contrasts in brain activity between appraisal and neutral viewing conditions correlated with each measure of attachment after covarying for mood. AAI and RSQ measures were then compared in terms of the extent to which regions of correlating brain activity overlapped with “default mode network” (DMN) vs. executive frontal network (EFN) masks and cortical vs. subcortical masks. Additionally, interactions with mood were examined. Results: Salience and valence processing associated with increased thalamo-striatal, posterior cingulate, and visual cortex activity. Salience processing decreased PFC activity, whereas valence processing increased left insula activity. Activity correlating with AAI vs. RSQ measures demonstrated significantly more DMN and subcortical involvement. Interactions with mood were observed in the middle temporal gyrus and precuneus for both measures. Conclusion: The AAI appears to disproportionately correlate with conscious appraisal associated activity in DMN and subcortical structures, while the RSQ appears to tap EFN structures more extensively. Thus, the AAI may assess more interoceptive, ‘core-self’-related processes, while the RSQ captures higher-order cognitions involved in attachment. Shared interaction effects between mood and AAI and RSQ-measures may suggest that processes tapped by each belong to a common system. PMID:27014022

Comparison of Brain Activity Correlating with Self-Report versus Narrative Attachment Measures during Conscious Appraisal of an Attachment Figure.

PubMed

Yaseen, Zimri S; Zhang, Xian; Muran, J Christopher; Winston, Arnold; Galynker, Igor I

2016-01-01

The Adult Attachment Interview (AAI) has been the gold standard of attachment assessment, but requires special training. The Relationship Scales Questionnaire (RSQ) is a widely used self-report measure. We investigate how each correlates with brain activity during appraisal of subjects' mothers. Twenty-eight women were scored on the AAI, RSQ, and mood measures. During functional magnetic resonance imaging, subjects viewed their mothers in neutral-, valence-, and salience-rating conditions. We identified regions where contrasts in brain activity between appraisal and neutral viewing conditions correlated with each measure of attachment after covarying for mood. AAI and RSQ measures were then compared in terms of the extent to which regions of correlating brain activity overlapped with "default mode network" (DMN) vs. executive frontal network (EFN) masks and cortical vs. subcortical masks. Additionally, interactions with mood were examined. Salience and valence processing associated with increased thalamo-striatal, posterior cingulate, and visual cortex activity. Salience processing decreased PFC activity, whereas valence processing increased left insula activity. Activity correlating with AAI vs. RSQ measures demonstrated significantly more DMN and subcortical involvement. Interactions with mood were observed in the middle temporal gyrus and precuneus for both measures. The AAI appears to disproportionately correlate with conscious appraisal associated activity in DMN and subcortical structures, while the RSQ appears to tap EFN structures more extensively. Thus, the AAI may assess more interoceptive, 'core-self'-related processes, while the RSQ captures higher-order cognitions involved in attachment. Shared interaction effects between mood and AAI and RSQ-measures may suggest that processes tapped by each belong to a common system.

Graph theory analysis of cortical thickness networks in adolescents with d-transposition of the great arteries.

PubMed

Watson, Christopher G; Stopp, Christian; Newburger, Jane W; Rivkin, Michael J

2018-02-01

Adolescents with d-transposition of the great arteries (d-TGA) who had the arterial switch operation in infancy have been found to have structural brain differences compared to healthy controls. We used cortical thickness measurements obtained from structural brain MRI to determine group differences in global brain organization using a graph theoretical approach. Ninety-two d-TGA subjects and 49 controls were scanned using one of two identical 1.5-Tesla MRI systems. Mean cortical thickness was obtained from 34 regions per hemisphere using Freesurfer. A linear model was used for each brain region to adjust for subject age, sex, and scanning location. Structural connectivity for each group was inferred based on the presence of high inter-regional correlations of the linear model residuals, and binary connectivity matrices were created by thresholding over a range of correlation values for each group. Graph theory analysis was performed using packages in R. Permutation tests were performed to determine significance of between-group differences in global network measures. Within-group connectivity patterns were qualitatively different between groups. At lower network densities, controls had significantly more long-range connections. The location and number of hub regions differed between groups: controls had a greater number of hubs at most network densities. The control network had a significant rightward asymmetry compared to the d-TGA group at all network densities. Using graph theory analysis of cortical thickness correlations, we found differences in brain structural network organization among d-TGA adolescents compared to controls. These may be related to the white matter and gray matter differences previously found in this cohort, and in turn may be related to the cognitive deficits this cohort presents.

Age Related Changes in Topological Properties of Brain Functional Network and Structural Connectivity.

PubMed

Shah, Chandan; Liu, Jia; Lv, Peilin; Sun, Huaiqiang; Xiao, Yuan; Liu, Jieke; Zhao, Youjin; Zhang, Wenjing; Yao, Li; Gong, Qiyong; Lui, Su

2018-01-01

Introduction: There are still uncertainties about the true nature of age related changes in topological properties of the brain functional network and its structural connectivity during various developmental stages. In this cross- sectional study, we investigated the effects of age and its relationship with regional nodal properties of the functional brain network and white matter integrity. Method: DTI and fMRI data were acquired from 458 healthy Chinese participants ranging from age 8 to 81 years. Tractography was conducted on the DTI data using FSL. Graph Theory analyses were conducted on the functional data yielding topological properties of the functional network using SPM and GRETNA toolbox. Two multiple regressions were performed to investigate the effects of age on nodal topological properties of the functional brain network and white matter integrity. Result: For the functional studies, we observed that regional nodal characteristics such as node betweenness were decreased while node degree and node efficiency was increased in relation to increasing age. Perversely, we observed that the relationship between nodal topological properties and fasciculus structures were primarily positive for nodal betweenness but negative for nodal degree and nodal efficiency. Decrease in functional nodal betweenness was primarily located in superior frontal lobe, right occipital lobe and the global hubs. These brain regions also had both direct and indirect anatomical relationships with the 14 fiber bundles. A linear age related decreases in the Fractional anisotropy (FA) value was found in the callosum forceps minor. Conclusion: These results suggests that age related differences were more pronounced in the functional than in structural measure indicating these measures do not have direct one-to-one mapping. Our study also indicates that the fiber bundles with longer fibers exhibited a more pronounced effect on the properties of functional network.

Early development of structural networks and the impact of prematurity on brain connectivity.

PubMed

Batalle, Dafnis; Hughes, Emer J; Zhang, Hui; Tournier, J-Donald; Tusor, Nora; Aljabar, Paul; Wali, Luqman; Alexander, Daniel C; Hajnal, Joseph V; Nosarti, Chiara; Edwards, A David; Counsell, Serena J

2017-04-01

Preterm infants are at high risk of neurodevelopmental impairment, which may be due to altered development of brain connectivity. We aimed to (i) assess structural brain development from 25 to 45 weeks gestational age (GA) using graph theoretical approaches and (ii) test the hypothesis that preterm birth results in altered white matter network topology. Sixty-five infants underwent MRI between 25 +3 and 45 +6 weeks GA. Structural networks were constructed using constrained spherical deconvolution tractography and were weighted by measures of white matter microstructure (fractional anisotropy, neurite density and orientation dispersion index). We observed regional differences in brain maturation, with connections to and from deep grey matter showing most rapid developmental changes during this period. Intra-frontal, frontal to cingulate, frontal to caudate and inter-hemispheric connections matured more slowly. We demonstrated a core of key connections that was not affected by GA at birth. However, local connectivity involving thalamus, cerebellum, superior frontal lobe, cingulate gyrus and short range cortico-cortical connections was related to the degree of prematurity and contributed to altered global topology of the structural brain network. The relative preservation of core connections at the expense of local connections may support more effective use of impaired white matter reserve following preterm birth. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering

PubMed Central

2013-01-01

Background The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. Results In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Conclusions Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship. PMID:23845024

Brain structure and function correlates of cognitive subtypes in schizophrenia.

PubMed

Geisler, Daniel; Walton, Esther; Naylor, Melissa; Roessner, Veit; Lim, Kelvin O; Charles Schulz, S; Gollub, Randy L; Calhoun, Vince D; Sponheim, Scott R; Ehrlich, Stefan

2015-10-30

Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Detection of Alzheimer’s disease amyloid-beta plaque deposition by deep brain impedance profiling

NASA Astrophysics Data System (ADS)

Béduer, Amélie; Joris, Pierre; Mosser, Sébastien; Fraering, Patrick C.; Renaud, Philippe

2015-04-01

Objective. Alzheimer disease (AD) is the most common form of neurodegenerative disease in elderly people. Toxic brain amyloid-beta (Aß) aggregates and ensuing cell death are believed to play a central role in the pathogenesis of the disease. In this study, we investigated if we could monitor the presence of these aggregates by performing in situ electrical impedance spectroscopy measurements in AD model mice brains. Approach. In this study, electrical impedance spectroscopy measurements were performed post-mortem in APPPS1 transgenic mice brains. This transgenic model is commonly used to study amyloidogenesis, a pathological hallmark of AD. We used flexible probes with embedded micrometric electrodes array to demonstrate the feasibility of detecting senile plaques composed of Aß peptides by localized impedance measurements. Main results. We particularly focused on deep brain structures, such as the hippocampus. Ex vivo experiments using brains from young and old APPPS1 mice lead us to show that impedance measurements clearly correlate with the percentage of Aβ plaque load in the brain tissues. We could monitor the effects of aging in the AD APPPS1 mice model. Significance. We demonstrated that a localized electrical impedance measurement constitutes a valuable technique to monitor the presence of Aβ-plaques, which is complementary with existing imaging techniques. This method does not require prior Aβ staining, precluding the risk of variations in tissue uptake of dyes or tracers, and consequently ensuring reproducible data collection.

Adolescent Executive Dysfunction in Daily Life: Relationships to Risks, Brain Structure and Substance Use

PubMed Central

Clark, Duncan B.; Chung, Tammy; Martin, Christopher S.; Hasler, Brant P.; Fitzgerald, Douglas H.; Luna, Beatriz; Brown, Sandra A.; Tapert, Susan F.; Brumback, Ty; Cummins, Kevin; Pfefferbaum, Adolf; Sullivan, Edith V.; Pohl, Kilian M.; Colrain, Ian M.; Baker, Fiona C.; De Bellis, Michael D.; Nooner, Kate B.; Nagel, Bonnie J.

2017-01-01

During adolescence, problems reflecting cognitive, behavioral and affective dysregulation, such as inattention and emotional dyscontrol, have been observed to be associated with substance use disorder (SUD) risks and outcomes. Prior studies have typically been with small samples, and have typically not included comprehensive measurement of executive dysfunction domains. The relationships of executive dysfunction in daily life with performance based testing of cognitive skills and structural brain characteristics, thought to be the basis for executive functioning, have not been definitively determined. The aims of this study were to determine the relationships between executive dysfunction in daily life, measured by the Behavior Rating Inventory of Executive Function (BRIEF), cognitive skills and structural brain characteristics, and SUD risks, including a global SUD risk indicator, sleep quality, and risky alcohol and cannabis use. In addition to bivariate relationships, multivariate models were tested. The subjects (n = 817; ages 12 through 21) were participants in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study. The results indicated that executive dysfunction was significantly related to SUD risks, poor sleep quality, risky alcohol use and cannabis use, and was not significantly related to cognitive skills or structural brain characteristics. In multivariate models, the relationship between poor sleep quality and risky substance use was mediated by executive dysfunction. While these cross-sectional relationships need to be further examined in longitudinal analyses, the results suggest that poor sleep quality and executive dysfunction may be viable preventive intervention targets to reduce adolescent substance use. PMID:29180956

State-dependent changes in cortical gain control as measured by auditory evoked responses to varying intensity stimuli.

PubMed

Phillips, Derrick J; Schei, Jennifer L; Meighan, Peter C; Rector, David M

2011-11-01

Auditory evoked potential (AEP) components correspond to sequential activation of brain structures within the auditory pathway and reveal neural activity during sensory processing. To investigate state-dependent modulation of stimulus intensity response profiles within different brain structures, we assessed AEP components across both stimulus intensity and state. We implanted adult female Sprague-Dawley rats (N = 6) with electrodes to measure EEG, EKG, and EMG. Intermittent auditory stimuli (6-12 s) varying from 50 to 75 dBa were delivered over a 24-h period. Data were parsed into 2-s epochs and scored for wake/sleep state. All AEP components increased in amplitude with increased stimulus intensity during wake. During quiet sleep, however, only the early latency response (ELR) showed this relationship, while the middle latency response (MLR) increased at the highest 75 dBa intensity, and the late latency response (LLR) showed no significant change across the stimulus intensities tested. During rapid eye movement sleep (REM), both ELR and LLR increased, similar to wake, but MLR was severely attenuated. Stimulation intensity and the corresponding AEP response profile were dependent on both brain structure and sleep state. Lower brain structures maintained stimulus intensity and neural response relationships during sleep. This relationship was not observed in the cortex, implying state-dependent modification of stimulus intensity coding. Since AEP amplitude is not modulated by stimulus intensity during sleep, differences between paired 75/50 dBa stimuli could be used to determine state better than individual intensities.

Neuroimaging of child abuse: a critical review

PubMed Central

Hart, Heledd; Rubia, Katya

2012-01-01

Childhood maltreatment is a stressor that can lead to the development of behavior problems and affect brain structure and function. This review summarizes the current evidence for the effects of childhood maltreatment on behavior, cognition and the brain in adults and children. Neuropsychological studies suggest an association between child abuse and deficits in IQ, memory, working memory, attention, response inhibition and emotion discrimination. Structural neuroimaging studies provide evidence for deficits in brain volume, gray and white matter of several regions, most prominently the dorsolateral and ventromedial prefrontal cortex but also hippocampus, amygdala, and corpus callosum (CC). Diffusion tensor imaging (DTI) studies show evidence for deficits in structural interregional connectivity between these areas, suggesting neural network abnormalities. Functional imaging studies support this evidence by reporting atypical activation in the same brain regions during response inhibition, working memory, and emotion processing. There are, however, several limitations of the abuse research literature which are discussed, most prominently the lack of control for co-morbid psychiatric disorders, which make it difficult to disentangle which of the above effects are due to maltreatment, the associated psychiatric conditions or a combination or interaction between both. Overall, the better controlled studies that show a direct correlation between childhood abuse and brain measures suggest that the most prominent deficits associated with early childhood abuse are in the function and structure of lateral and ventromedial fronto-limbic brain areas and networks that mediate behavioral and affect control. Future, large scale multimodal neuroimaging studies in medication-naïve subjects, however, are needed that control for psychiatric co-morbidities in order to elucidate the structural and functional brain sequelae that are associated with early environmental adversity, independently of secondary co-morbid conditions. PMID:22457645

Socioeconomic Status and Functional Brain Development--Associations in Early Infancy

ERIC Educational Resources Information Center

Tomalski, Przemyslaw; Moore, Derek G.; Ribeiro, Helena; Axelsson, Emma L.; Murphy, Elizabeth; Karmiloff-Smith, Annette; Johnson, Mark H.; Kushnerenko, Elena

2013-01-01

Socioeconomic status (SES) impacts on both structural and functional brain development in childhood, but how early its effects can be demonstrated is unknown. In this study we measured resting baseline EEG activity in the gamma frequency range in awake 6-9-month-olds from areas of East London with high socioeconomic deprivation. Between-subject…

Quantifying hydrologic connectivity with measures from the brain neurosciences - a feasibility study

NASA Astrophysics Data System (ADS)

Rinderer, Michael; Ali, Genevieve; Larsen, Laurel

2017-04-01

While the concept of connectivity is increasingly applied in hydrology and ecology, little agreement exists on its definition and quantification approaches. In contrast, the neurosciences have developed a systematic conceptualization of connectivity and methods to quantify it. In particular, neuroscientists make a clear distinction between: 1) structural connectivity, which is determined by the anatomy of the brain neural network, 2) functional connectivity, that is based on statistical dependencies between neural signals, and 3) effective connectivity, that allows to infer causal relations based on the assumption that "true" interactions occur with a certain time delay. In a similar vein, in hydrology, structural connectivity can be defined as the physical adjacency of landscape elements that are seen as a prerequisite of material transfer, while functional or process connectivity would rather describe interactions or causal relations between spatial adjacency characteristics and temporally varying factors. While hydrologists have suggested methods to derive structural connectivity (SC), the quantification of functional (FC) or effective connectivity (EC) has remained elusive. The goal of the current study was therefore to apply timeseries analysis methods from brain neuroscience to quantify EC and FC among groundwater (n = 34) and stream discharge (n = 1) monitoring sites in a 20-ha Swiss catchment where topography is assumed to be a major driver of connectivity. SC was assessed through influence maps that quantify the percentage of flow from an upslope site to a downslope site by applying a multiple flow direction algorithm. FC was assessed by cross-correlation, total and partial mutual information while EC was quantified via total and partial entropy, Granger causality and a phase slope index. Our results showed that many structural connections were also expressed as functional or effective connections, which is reasonable in a catchment with shallow perched groundwater tables. The differentiation between FC and EC measures allowed us to distinguish between hydrological connectivity (i.e., Darcian fluxes of water) and hydraulic connectivity (i.e. pressure wave-driven processes). However, some FC and EC measures also detected the presence of connectivity despite the absence of SC, which highlights the limits of applying brain connectivity measures to hydrology. We therefore conclude that brain neuroscience methods for assessing FC and EC can be powerful tools in assessing hydrological connectivity as long as they are constrained by SC measures.

Automatic cortical thickness analysis on rodent brain

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Ehlers, Cindy; Crews, Fulton; Niethammer, Marc; Budin, Francois; Paniagua, Beatriz; Sulik, Kathy; Johns, Josephine; Styner, Martin; Oguz, Ipek

2011-03-01

Localized difference in the cortex is one of the most useful morphometric traits in human and animal brain studies. There are many tools and methods already developed to automatically measure and analyze cortical thickness for the human brain. However, these tools cannot be directly applied to rodent brains due to the different scales; even adult rodent brains are 50 to 100 times smaller than humans. This paper describes an algorithm for automatically measuring the cortical thickness of mouse and rat brains. The algorithm consists of three steps: segmentation, thickness measurement, and statistical analysis among experimental groups. The segmentation step provides the neocortex separation from other brain structures and thus is a preprocessing step for the thickness measurement. In the thickness measurement step, the thickness is computed by solving a Laplacian PDE and a transport equation. The Laplacian PDE first creates streamlines as an analogy of cortical columns; the transport equation computes the length of the streamlines. The result is stored as a thickness map over the neocortex surface. For the statistical analysis, it is important to sample thickness at corresponding points. This is achieved by the particle correspondence algorithm which minimizes entropy between dynamically moving sample points called particles. Since the computational cost of the correspondence algorithm may limit the number of corresponding points, we use thin-plate spline based interpolation to increase the number of corresponding sample points. As a driving application, we measured the thickness difference to assess the effects of adolescent intermittent ethanol exposure that persist into adulthood and performed t-test between the control and exposed rat groups. We found significantly differing regions in both hemispheres.

Fractal dimension assessment of brain white matter structural complexity post stroke in relation to upper-extremity motor function

PubMed Central

Zhang, Luduan; Butler, Andrew J.; Sun, Chang-Kai; Sahgal, Vinod; Wittenberg, George F.; Yue, Guang H.

2008-01-01

Little is known about the association between brain white matter (WM) structure and motor function in humans. This study investigated complexity of brain WM interior shape as determined by magnetic resonance imaging (MRI) and its relationship with upper-extremity (UE) motor function in patients post stroke. We hypothesized that (1) the WM complexity would decrease following stroke, and (2) higher WM complexity in non-affected cortical areas would be related to greater UE motor function. Thirty-eight stroke patients (16 with left-hemisphere lesions) underwent MRI anatomical brain scans. Fractal dimension (FD), a quantitative shape metric, was applied onto skeletonized brain WM images to evaluate WM internal structural complexity. Wolf Motor Function Test (WMFT) and Fugl-Meyer Motor Assessment (FM) scores were measured to assess motor function of the affected limb. The WM complexity was lower in the stroke-affected hemisphere. The FD was associated with better motor function in two subgroups: with left-subcortical lesions, FD values of the lesion-free areas of the left hemisphere were associated with better FM scores; with right-cortical lesions, FD values of lesion-free regions were robustly associated with better WMFT scores. These findings suggest that greater residual WM complexity is associated with less impaired UE motor function, which is more robust in patients with right-hemisphere lesions. No correlations were found between lesion volume and WMFT or FM scores. This study addressed WM complexity in stroke patients and its relationship with UE motor function. Measurement of brain WM reorganization may be a sensitive correlate of UE function in people recovering from stroke. PMID:18590710

Multiple cortical thickness sub-networks and cognitive impairments in first episode, drug naïve patients with late life depression: A graph theory analysis.

PubMed

Shin, Jeong-Hyeon; Um, Yu Hyun; Lee, Chang Uk; Lim, Hyun Kook; Seong, Joon-Kyung

2018-03-15

Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients. Additionally, we investigated the structural sub-networks correlated with several clinical measurements including cognitive impairment and depression severity. We observed that small worldness, clustering coefficients, global and local efficiency, and hub structures in the brains of LLD patients were significantly different from healthy controls. We further found that a sub-network including the anterior cingulate, dorsolateral prefrontal cortex and superior prefrontal cortex is significantly associated with attention control and executive function. The severity of depression was associated with the sub-networks comprising the salience network, including the anterior cingulate and insula. We investigated cortico-cortical connectivity, but omitted the subcortical structures such as the striatum and thalamus. We report differences in patterns between several clinical measurements and sub-networks from large-scale and individual-level cortical thickness networks in LLD. Copyright © 2018 Elsevier B.V. All rights reserved.

Regional growth and atlasing of the developing human brain

PubMed Central

Makropoulos, Antonios; Aljabar, Paul; Wright, Robert; Hüning, Britta; Merchant, Nazakat; Arichi, Tomoki; Tusor, Nora; Hajnal, Joseph V.; Edwards, A. David; Counsell, Serena J.; Rueckert, Daniel

2016-01-01

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45 weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area. PMID:26499811

Regional growth and atlasing of the developing human brain.

PubMed

Makropoulos, Antonios; Aljabar, Paul; Wright, Robert; Hüning, Britta; Merchant, Nazakat; Arichi, Tomoki; Tusor, Nora; Hajnal, Joseph V; Edwards, A David; Counsell, Serena J; Rueckert, Daniel

2016-01-15

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Is Traumatic and Non-Traumatic Neck Pain Associated with Brain Alterations? - A Systematic Review.

PubMed

DePauw, Robby; Coppieters, Iris; Meeus, Mira; Caeyenberghs, Karen; Danneels, Lieven; Cagnie, Barbara

2017-05-01

Chronic neck pain affects 50% - 85% of people who have experienced an acute episode. This transition and the persistence of chronic complaints are believed to be mediated by brain alterations among different central mechanisms. This study aimed to systematically review and critically appraise the current existing evidence regarding structural and functional brain alterations in patients with whiplash associated disorders (WAD) and idiopathic neck pain (INP). Additionally, associations between brain alterations and clinical symptoms reported in neck pain patients were evaluated. Systematic review. The present systematic review was performed according to the PRISMA guidelines. PubMed, Web of Science, and Cochrane databases were searched. First, the obtained articles were screened based on title and abstract. Secondly, the screening was based on the full text. Risk of bias in included studies was investigated. Twelve studies met the inclusion criteria. Alterations in brain morphology and function, including perfusion, neurotransmission, and blood oxygenation level dependent-signal, were demonstrated in chronic neck pain patients. There is some to moderate evidence for both structural and functional brain alterations in patients with chronic neck pain. In contrast, no evidence for structural brain alterations in acute neck pain patients was found. Only 12 articles were included, which allows only cautious conclusions to be drawn. Brain alterations were observed in both patients with chronic WAD and chronic INP. Furthermore, more evidence exists for brain alterations in chronic WAD, and different underlying mechanisms might be present in both pathologies. In addition, pain and disability were correlated with the observed brain alterations. Accordingly, morphological and functional brain alterations should be further investigated in patients with chronic WAD and chronic INP with newer and more sensitive techniques, and associative clinical measurements seem indispensable in future research.

Immunological biomarkers associated with brain structure and executive function in late-life depression: exploratory pilot study.

PubMed

Smagula, Stephen F; Lotrich, Francis E; Aizenstein, Howard J; Diniz, Breno S; Krystek, Jeffrey; Wu, Gregory F; Mulsant, Benoit H; Butters, Meryl A; Reynolds, Charles F; Lenze, Eric J

2017-06-01

Several immunological biomarkers are altered in late-life major depressive disorder (LLD). Immunological alterations could contribute to LLD's consequences, but little is known about the relations between specific immunological biomarkers and brain health in LLD. We performed an exploratory pilot study to identify, from several candidates, the specific immunological biomarkers related to important aspects of brain health that are altered in LLD (brain structure and executive function). Adults (n = 31) were at least 60 years old and had major depressive disorder. A multiplex immunoassay assessed 13 immunological biomarkers, and we examined their associations with structural MRI (grey matter volume and white matter hyperintensity volume (WMH)) and executive function (Color-Word Interference and Trail-Making tests) measures. Vascular endothelial growth factor (VEGF) and the chemokine eotaxin had significant negative associations with grey matter volume (VEGF: n = 31, r = -0.65; eotaxin: n = 29, r = -0.44). Tumor necrosis factor alpha (TNF-α) had a significant positive relationship with WMHs (n = 30, r = 0.52); interferon-γ (IFN-γ) and macrophage inflammatory protein-1α (MIP-1α) were also significantly associated with WMHs (IFN-γ: n = 31, r = 0.48; MIP-1α: n = 29, r = 0.45). Only eotaxin was associated with executive function (set-shifting performance as measured with the Trail-making test: n = 33, r = -0.43). Immunological markers are associated with brain structure in LLD. We found the immunological correlates of grey and white matter differ. Prospective studies are needed to evaluate whether these immunological correlates of brain health increase the risk of LLD's consequences. Eotaxin, which correlated with both grey matter volume and set-shifting performance, may be particularly relevant to neurodegeneration and cognition in LLD. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

Association between MRI structural features and cognitive measures in pediatric multiple sclerosis

NASA Astrophysics Data System (ADS)

Amoroso, N.; Bellotti, R.; Fanizzi, A.; Lombardi, A.; Monaco, A.; Liguori, M.; Margari, L.; Simone, M.; Viterbo, R. G.; Tangaro, S.

2017-09-01

Multiple sclerosis (MS) is an inflammatory and demyelinating disease associated with neurodegenerative processes that lead to brain structural changes. The disease affects mostly young adults, but 3-5% of cases has a pediatric onset (POMS). Magnetic Resonance Imaging (MRI) is generally used for diagnosis and follow-up in MS patients, however the most common MRI measures (e.g. new or enlarging T2-weighted lesions, T1-weighted gadolinium- enhancing lesions) have often failed as surrogate markers of MS disability and progression. MS is clinically heterogenous with symptoms that can include both physical changes (such as visual loss or walking difficulties) and cognitive impairment. 30-50% of POMS experience prominent cognitive dysfunction. In order to investigate the association between cognitive measures and brain morphometry, in this work we present a fully automated pipeline for processing and analyzing MRI brain scans. Relevant anatomical structures are segmented with FreeSurfer; besides, statistical features are computed. Thus, we describe the data referred to 12 patients with early POMS (mean age at MRI: 15.5 +/- 2.7 years) with a set of 181 structural features. The major cognitive abilities measured are verbal and visuo-spatial learning, expressive language and complex attention. Data was collected at the Department of Basic Sciences, Neurosciences and Sense Organs, University of Bari, and exploring different abilities like the verbal and visuo-spatial learning, expressive language and complex attention. Different regression models and parameter configurations are explored to assess the robustness of the results, in particular Generalized Linear Models, Bayes Regression, Random Forests, Support Vector Regression and Artificial Neural Networks are discussed.

Aberrant brain stem morphometry associated with sleep disturbance in drug-naïve subjects with Alzheimer's disease.

PubMed

Lee, Ji Han; Jung, Won Sang; Choi, Woo Hee; Lim, Hyun Kook

2016-01-01

Among patients with Alzheimer's disease (AD), sleep disturbances are common and serious noncognitive symptoms. Previous studies of AD patients have identified deformations in the brain stem, which may play an important role in the regulation of sleep. The aim of this study was to further investigate the relationship between sleep disturbances and alterations in brain stem morphology in AD. In 44 patients with AD and 40 healthy elderly controls, sleep disturbances were measured using the Neuropsychiatry Inventory sleep subscale. We employed magnetic resonance imaging-based automated segmentation tools to examine the relationship between sleep disturbances and changes in brain stem morphology. Analyses of the data from AD subjects revealed significant correlations between the Neuropsychiatry Inventory sleep-subscale scores and structural alterations in the left posterior lateral region of the brain stem, as well as normalized brain stem volumes. In addition, significant group differences in posterior brain stem morphology were observed between the AD group and the control group. This study is the first to analyze an association between sleep disturbances and brain stem morphology in AD. In line with previous findings, this study lends support to the possibility that brain stem structural abnormalities might be important neurobiological mechanisms underlying sleep disturbances associated with AD. Further longitudinal research is needed to confirm these findings.

Intelligence is associated with the modular structure of intrinsic brain networks.

PubMed

Hilger, Kirsten; Ekman, Matthias; Fiebach, Christian J; Basten, Ulrike

2017-11-22

General intelligence is a psychological construct that captures in a single metric the overall level of behavioural and cognitive performance in an individual. While previous research has attempted to localise intelligence in circumscribed brain regions, more recent work focuses on functional interactions between regions. However, even though brain networks are characterised by substantial modularity, it is unclear whether and how the brain's modular organisation is associated with general intelligence. Modelling subject-specific brain network graphs from functional MRI resting-state data (N = 309), we found that intelligence was not associated with global modularity features (e.g., number or size of modules) or the whole-brain proportions of different node types (e.g., connector hubs or provincial hubs). In contrast, we observed characteristic associations between intelligence and node-specific measures of within- and between-module connectivity, particularly in frontal and parietal brain regions that have previously been linked to intelligence. We propose that the connectivity profile of these regions may shape intelligence-relevant aspects of information processing. Our data demonstrate that not only region-specific differences in brain structure and function, but also the network-topological embedding of fronto-parietal as well as other cortical and subcortical brain regions is related to individual differences in higher cognitive abilities, i.e., intelligence.

The Effects of Spaceflight and a Spaceflight Analog on Neurocognitive Perfonnance: Extent, Longevity, and Neural Bases

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Erdeniz, B.; Kofman, I. S.; DeDios, Y. E.; Szecsy, D. L.; Riascos-Castaneda, R. F.; Wood, S. J.; Bloomberg, J. J.

2014-01-01

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission and following 70 days exposure to a spaceflight analog, head down tilt bedrest. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post intervention (spaceflight, bedrest). Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that will be conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. With the bedrest study, we will be able to determine the neural and neurocognitive effects of extended duration unloading, reduced sensory inputs, and increased cephalic fluid distribution. This will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe in the flight study. In this presentation I will discuss preliminary results from six participants who have undergone the bed rest protocol. These individuals show decrements in balance and functional mobility, and alterations in brain structure and function, in association with extended bed rest.

Brain structural differences associated with the behavioural phenotype in children with Williams syndrome.

PubMed

Campbell, Linda E; Daly, Eileen; Toal, Fiona; Stevens, Angela; Azuma, Rayna; Karmiloff-Smith, Annette; Murphy, Declan G M; Murphy, Kieran C

2009-03-03

We investigated structural brain morphology of intellectually disabled children with Williams (WS) syndrome and its relationship to the behavioural phenotype. We compared the neuroanatomy of 15 children (mean age:13+/-2) with WS and 15 age/gender-matched healthy children using a manual region-of-interest analysis to measure bulk (white+grey) tissue volumes and unbiased fully-automated voxel-based morphometry to assess differences in grey/white matter throughout the brain. Ratings of abnormal behaviours were correlated with brain structure. Compared to controls, the brains of children with WS had a decreased volume of the right parieto-occipital regions and basal ganglia. We identified reductions of grey matter of the parieto-occipital regions, left putamen/globus pallidus and thalamus; and in white matter of the basal ganglia and right posterior cingulate gyrus. In contrast, significant increases of grey matter were identified in the frontal lobes, anterior cingulate gyrus, left temporal lobe, and of white matter bilaterally in the anterior cingulate. Inattention in WS was correlated with volumetric differences in the frontal lobes, caudate nucleus and cerebellum, and hyperactivity was related to differences in the left temporal and parietal lobes and cerebellum. Finally, ratings of peer problems were related to differences in the temporal lobes, right basal ganglia and frontal lobe. In one of the first studies of brain structure in intellectually disabled children with WS using voxel-based morphometry, our findings suggest that this group has specific differences in grey/white matter morphology. In addition, it was found that structural differences were correlated to ratings of inattention, hyperactivity and peer problems in children with WS.

Early changes in brain structure correlate with language outcomes in children with neonatal encephalopathy.

PubMed

Shapiro, Kevin A; Kim, Hosung; Mandelli, Maria Luisa; Rogers, Elizabeth E; Gano, Dawn; Ferriero, Donna M; Barkovich, A James; Gorno-Tempini, Maria Luisa; Glass, Hannah C; Xu, Duan

2017-01-01

Global patterns of brain injury correlate with motor, cognitive, and language outcomes in survivors of neonatal encephalopathy (NE). However, it is still unclear whether local changes in brain structure predict specific deficits. We therefore examined whether differences in brain structure at 6 months of age are associated with neurodevelopmental outcomes in this population. We enrolled 32 children with NE, performed structural brain MR imaging at 6 months, and assessed neurodevelopmental outcomes at 30 months. All subjects underwent T1-weighted imaging at 3 T using a 3D IR-SPGR sequence. Images were normalized in intensity and nonlinearly registered to a template constructed specifically for this population, creating a deformation field map. We then used deformation based morphometry (DBM) to correlate variation in the local volume of gray and white matter with composite scores on the Bayley Scales of Infant and Toddler Development (Bayley-III) at 30 months. Our general linear model included gestational age, sex, birth weight, and treatment with hypothermia as covariates. Regional brain volume was significantly associated with language scores, particularly in perisylvian cortical regions including the left supramarginal gyrus, posterior superior and middle temporal gyri, and right insula, as well as inferior frontoparietal subcortical white matter. We did not find significant correlations between regional brain volume and motor or cognitive scale scores. We conclude that, in children with a history of NE, local changes in the volume of perisylvian gray and white matter at 6 months are correlated with language outcome at 30 months. Quantitative measures of brain volume on early MRI may help identify infants at risk for poor language outcomes.

Brain age predicts mortality

PubMed Central

Cole, J H; Ritchie, S J; Bastin, M E; Valdés Hernández, M C; Muñoz Maniega, S; Royle, N; Corley, J; Pattie, A; Harris, S E; Zhang, Q; Wray, N R; Redmond, P; Marioni, R E; Starr, J M; Cox, S R; Wardlaw, J M; Sharp, D J; Deary, I J

2018-01-01

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death. PMID:28439103

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emin, David, E-mail: emin@unm.edu; Akhtari, Massoud; Ellingson, B. M.

We analyze the transient-dc and frequency-dependent electrical conductivities between blocking electrodes. We extend this analysis to measurements of ions’ transport in freshly excised bulk samples of human brain tissue whose complex cellular structure produces blockages. The associated ionic charge-carrier density and diffusivity are consistent with local values for sodium cations determined non-invasively in brain tissue by MRI (NMR) and diffusion-MRI (spin-echo NMR). The characteristic separation between blockages, about 450 microns, is very much shorter than that found for sodium-doped gel proxies for brain tissue, >1 cm.

Structure-function clustering in multiplex brain networks

NASA Astrophysics Data System (ADS)

Crofts, J. J.; Forrester, M.; O'Dea, R. D.

2016-10-01

A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.

Boltzmann brains and the scale-factor cutoff measure of the multiverse

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Simone, Andrea; Guth, Alan H.; Linde, Andrei

2010-09-15

To make predictions for an eternally inflating 'multiverse', one must adopt a procedure for regulating its divergent spacetime volume. Recently, a new test of such spacetime measures has emerged: normal observers - who evolve in pocket universes cooling from hot big bang conditions - must not be vastly outnumbered by 'Boltzmann brains' - freak observers that pop in and out of existence as a result of rare quantum fluctuations. If the Boltzmann brains prevail, then a randomly chosen observer would be overwhelmingly likely to be surrounded by an empty world, where all but vacuum energy has redshifted away, rather thanmore » the rich structure that we observe. Using the scale-factor cutoff measure, we calculate the ratio of Boltzmann brains to normal observers. We find the ratio to be finite, and give an expression for it in terms of Boltzmann brain nucleation rates and vacuum decay rates. We discuss the conditions that these rates must obey for the ratio to be acceptable, and we discuss estimates of the rates under a variety of assumptions.« less

Preclinical studies of photodynamic therapy of intracranial tissues

NASA Astrophysics Data System (ADS)

Lilge, Lothar D.; Sepers, Marja; Park, Jane; O'Carroll, Cindy; Pournazari, Poupak; Prosper, Joe; Wilson, Brian C.

1997-05-01

The applicability and limitations of the photodynamic threshold model were investigated for an intracranial tumor (VX2) and normal brain tissues in a rabbit model. Photodynamic threshold values for four different photosensitizers, i.e., Photofrin, 5(delta) -aminolaevulinic acid (5(delta) -ALA) induced Protoporphyrin IX (PPIX), Tin Ethyl Etiopurpurin (SnET2), and chloroaluminum phthalocyanine (AlClPc), were determined based on measured light fluence distributions, macroscopic photosensitizer concentration in various brain structures, and histologically determined extent of tissue necrosis following PDT. For Photofrin, AlClPc, and SnET2, normal brain displayed a significantly lower threshold value than VX2 tumor. For 5(delta) -ALA induced PPIX and SnET2 no or very little white matter damage, equalling to very high or infinite threshold values, was observed. Additionally, the latter two photosensitizers showed significantly lower uptake in white matter compared to other brain structures and VX2 tumor. Normal brain structures lacking a blood- brain-barrier, such as the choroid plexus and the meninges, showed high photosensitizer uptake for all photosensitizers, and, hence, are at risk when exposed to light. Results to date suggest that the photodynamic threshold values iares valid for white matter, cortex and VX2 tumor. For clinical PDT of intracranial neoplasms 5(delta) -ALA induced PPIX and SnET2 appear to be the most promising for selective tumor necrosis.However, the photosensitizer concentration in each normal brain structure and the fluence distribution throughout the treatment volume and adjacent tissues at risk must be monitored to maximize the selectivity of PDT for intracranial tumors.

Relations between Brain Structure and Attentional Function in Spina Bifida: Utilization of Robust Statistical Approaches

PubMed Central

Kulesz, Paulina A.; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M.; Francis, David J.

2015-01-01

Objective Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Method Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product moment correlation was compared with four robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator Results All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Conclusions Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PMID:25495830

Two Alzheimer’s disease risk genes increase entorhinal cortex volume in young adults

PubMed Central

DiBattista, Amanda Marie; Stevens, Benson W.; Rebeck, G. William; Green, Adam E.

2014-01-01

Alzheimer’s disease (AD) risk genes alter brain structure and function decades before disease onset. Apolipoprotein E (APOE) is the strongest known genetic risk factor for AD, and a related gene, apolipoprotein J (APOJ), also affects disease risk. However, the extent to which these genes affect brain structure in young adults remains unclear. Here, we report that AD risk alleles of these two genes, APOE-ε4 and APOJ-C, cumulatively alter brain volume in young adults. Using voxel-based morphometry (VBM) in 57 individuals, we examined the entorhinal cortex, one of the earliest brain regions affected in AD pathogenesis. Apolipoprotein E-ε4 carriers exhibited higher right entorhinal cortex volume compared to non-carriers. Interestingly, APOJ-C risk genotype was associated with higher bilateral entorhinal cortex volume in non-APOE-ε4 carriers. To determine the combined disease risk of APOE and APOJ status per subject, we used cumulative odds ratios as regressors for volumetric measurements. Higher disease risk corresponded to greater right entorhinal cortex volume. These results suggest that, years before disease onset, two key AD genetic risk factors may exert influence on the structure of a brain region where AD pathogenesis takes root. PMID:25339884

Brain structure-function associations in multi-generational families genetically enriched for bipolar disorder.

PubMed

Fears, Scott C; Schür, Remmelt; Sjouwerman, Rachel; Service, Susan K; Araya, Carmen; Araya, Xinia; Bejarano, Julio; Knowles, Emma; Gomez-Makhinson, Juliana; Lopez, Maria C; Aldana, Ileana; Teshiba, Terri M; Abaryan, Zvart; Al-Sharif, Noor B; Navarro, Linda; Tishler, Todd A; Altshuler, Lori; Bartzokis, George; Escobar, Javier I; Glahn, David C; Thompson, Paul M; Lopez-Jaramillo, Carlos; Macaya, Gabriel; Molina, Julio; Reus, Victor I; Sabatti, Chiara; Cantor, Rita M; Freimer, Nelson B; Bearden, Carrie E

2015-07-01

Recent theories regarding the pathophysiology of bipolar disorder suggest contributions of both neurodevelopmental and neurodegenerative processes. While structural neuroimaging studies indicate disease-associated neuroanatomical alterations, the behavioural correlates of these alterations have not been well characterized. Here, we investigated multi-generational families genetically enriched for bipolar disorder to: (i) characterize neurobehavioural correlates of neuroanatomical measures implicated in the pathophysiology of bipolar disorder; (ii) identify brain-behaviour associations that differ between diagnostic groups; (iii) identify neurocognitive traits that show evidence of accelerated ageing specifically in subjects with bipolar disorder; and (iv) identify brain-behaviour correlations that differ across the age span. Structural neuroimages and multi-dimensional assessments of temperament and neurocognition were acquired from 527 (153 bipolar disorder and 374 non-bipolar disorder) adults aged 18-87 years in 26 families with heavy genetic loading for bipolar disorder. We used linear regression models to identify significant brain-behaviour associations and test whether brain-behaviour relationships differed: (i) between diagnostic groups; and (ii) as a function of age. We found that total cortical and ventricular volume had the greatest number of significant behavioural associations, and included correlations with measures from multiple cognitive domains, particularly declarative and working memory and executive function. Cortical thickness measures, in contrast, showed more specific associations with declarative memory, letter fluency and processing speed tasks. While the majority of brain-behaviour relationships were similar across diagnostic groups, increased cortical thickness in ventrolateral prefrontal and parietal cortical regions was associated with better declarative memory only in bipolar disorder subjects, and not in non-bipolar disorder family members. Additionally, while age had a relatively strong impact on all neurocognitive traits, the effects of age on cognition did not differ between diagnostic groups. Most brain-behaviour associations were also similar across the age range, with the exception of cortical and ventricular volume and lingual gyrus thickness, which showed weak correlations with verbal fluency and inhibitory control at younger ages that increased in magnitude in older subjects, regardless of diagnosis. Findings indicate that neuroanatomical traits potentially impacted by bipolar disorder are significantly associated with multiple neurobehavioural domains. Structure-function relationships are generally preserved across diagnostic groups, with the notable exception of ventrolateral prefrontal and parietal association cortex, volumetric increases in which may be associated with cognitive resilience specifically in individuals with bipolar disorder. Although age impacted all neurobehavioural traits, we did not find any evidence of accelerated cognitive decline specific to bipolar disorder subjects. Regardless of diagnosis, greater global brain volume may represent a protective factor for the effects of ageing on executive functioning. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Structural brain differences in school-age children with and without single-suture craniosynostosis.

PubMed

Aldridge, Kristina; Collett, Brent R; Wallace, Erin R; Birgfeld, Craig; Austin, Jordan R; Yeh, Regina; Feil, Madison; Kapp-Simon, Kathleen A; Aylward, Elizabeth H; Cunningham, Michael L; Speltz, Matthew L

2017-04-01

OBJECTIVE Single-suture craniosynostosis (SSC), the premature fusion of a cranial suture, is characterized by dysmorphology of the craniofacial skeleton. Evidence to suggest that children with SSC are at an elevated risk of mild to moderate developmental delays and neurocognitive deficits is mounting, but the associations among premature suture fusion, neuroanatomy, and neurocognition are unexplained. The goals of this study were to determine 1) whether differences in the brain are present in young children with the 2 most common forms of SSC (sagittal and metopic) several years following surgical correction, and 2) whether the pattern of differences varies by affected suture (sagittal or metopic). Examination of differences in the brains of children with SSC several years after surgery may illuminate the growth trajectory of the brain after the potential constraint of the dysmorphic cranium has been relieved. METHODS The authors compared quantitative measures of the brain acquired from MR images obtained from children with sagittal or metopic craniosynostosis (n = 36) at 7 years of age to those obtained from a group of unaffected controls (n = 27) at the same age. The authors measured the volumes of the whole brain, cerebral cortex, cerebral white matter, cerebral cortex by lobe, and ventricles. Additionally, they measured the midsagittal area of the corpus callosum and its segments and of the cerebellar vermis and its component lobules. Measurements obtained from children with SSC and controls were compared using linear regression models. RESULTS No volume measures of the cerebrum or of the whole brain differed significantly between patients with SSC and controls (p > 0.05). However, ventricle volume was significantly increased in patients with SSC (p = 0.001), particularly in those with sagittal craniosynostosis (p < 0.001). In contrast, the area of the corpus callosum was significantly reduced in patients with metopic synostosis (p = 0.04), particularly in the posterior segments (p = 0.004). Similarly, the area of lobules VI-VII of the cerebellar vermis was reduced in patients with SSC (p = 0.03), with those with metopic craniosynostosis showing the greatest reduction (p = 0.01). CONCLUSIONS The lack of differences in overall brain size or regional differences in the size of the lobes of the cerebrum in children with metopic and sagittal synostosis suggests that the elevated risk of neurodevelopmental deficits is not likely to be associated with differences in the cerebral cortex. Instead, this study showed localized differences between sagittal and metopic craniosynostosis cases as compared with controls in the ventricles and in the midsagittal structures of the corpus callosum and the cerebellum. It remains to be tested whether these structural differences are associated with the increased risk for developmental delay and neurocognitive deficits in children with SSC.

Structural brain aging and speech production: a surface-based brain morphometry study.

PubMed

Tremblay, Pascale; Deschamps, Isabelle

2016-07-01

While there has been a growing number of studies examining the neurofunctional correlates of speech production over the past decade, the neurostructural correlates of this immensely important human behaviour remain less well understood, despite the fact that previous studies have established links between brain structure and behaviour, including speech and language. In the present study, we thus examined, for the first time, the relationship between surface-based cortical thickness (CT) and three different behavioural indexes of sublexical speech production: response duration, reaction times and articulatory accuracy, in healthy young and older adults during the production of simple and complex meaningless sequences of syllables (e.g., /pa-pa-pa/ vs. /pa-ta-ka/). The results show that each behavioural speech measure was sensitive to the complexity of the sequences, as indicated by slower reaction times, longer response durations and decreased articulatory accuracy in both groups for the complex sequences. Older adults produced longer speech responses, particularly during the production of complex sequence. Unique age-independent and age-dependent relationships between brain structure and each of these behavioural measures were found in several cortical and subcortical regions known for their involvement in speech production, including the bilateral anterior insula, the left primary motor area, the rostral supramarginal gyrus, the right inferior frontal sulcus, the bilateral putamen and caudate, and in some region less typically associated with speech production, such as the posterior cingulate cortex.

Imaging structural and functional brain networks in temporal lobe epilepsy.

PubMed

Bernhardt, Boris C; Hong, Seokjun; Bernasconi, Andrea; Bernasconi, Neda

2013-10-01

Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy.

Methodological issues in volumetric magnetic resonance imaging of the brain in the Edinburgh High Risk Project.

PubMed

Whalley, H C; Kestelman, J N; Rimmington, J E; Kelso, A; Abukmeil, S S; Best, J J; Johnstone, E C; Lawrie, S M

1999-07-30

The Edinburgh High Risk Project is a longitudinal study of brain structure (and function) in subjects at high risk of developing schizophrenia in the next 5-10 years for genetic reasons. In this article we describe the methods of volumetric analysis of structural magnetic resonance images used in the study. We also consider potential sources of error in these methods: the validity of our image analysis techniques; inter- and intra-rater reliability; possible positional variation; and thresholding criteria used in separating brain from cerebro-spinal fluid (CSF). Investigation with a phantom test object (of similar imaging characteristics to the brain) provided evidence for the validity of our image acquisition and analysis techniques. Both inter- and intra-rater reliability were found to be good in whole brain measures but less so for smaller regions. There were no statistically significant differences in positioning across the three study groups (patients with schizophrenia, high risk subjects and normal volunteers). A new technique for thresholding MRI scans longitudinally is described (the 'rescale' method) and compared with our established method (thresholding by eye). Few differences between the two techniques were seen at 3- and 6-month follow-up. These findings demonstrate the validity and reliability of the structural MRI analysis techniques used in the Edinburgh High Risk Project, and highlight methodological issues of general concern in cross-sectional and longitudinal studies of brain structure in healthy control subjects and neuropsychiatric populations.

Microstructure abnormalities in adolescents with internet addiction disorder.

PubMed

Yuan, Kai; Qin, Wei; Wang, Guihong; Zeng, Fang; Zhao, Liyan; Yang, Xuejuan; Liu, Peng; Liu, Jixin; Sun, Jinbo; von Deneen, Karen M; Gong, Qiyong; Liu, Yijun; Tian, Jie

2011-01-01

Recent studies suggest that internet addiction disorder (IAD) is associated with structural abnormalities in brain gray matter. However, few studies have investigated the effects of internet addiction on the microstructural integrity of major neuronal fiber pathways, and almost no studies have assessed the microstructural changes with the duration of internet addiction. We investigated the morphology of the brain in adolescents with IAD (N = 18) using an optimized voxel-based morphometry (VBM) technique, and studied the white matter fractional anisotropy (FA) changes using the diffusion tensor imaging (DTI) method, linking these brain structural measures to the duration of IAD. We provided evidences demonstrating the multiple structural changes of the brain in IAD subjects. VBM results indicated the decreased gray matter volume in the bilateral dorsolateral prefrontal cortex (DLPFC), the supplementary motor area (SMA), the orbitofrontal cortex (OFC), the cerebellum and the left rostral ACC (rACC). DTI analysis revealed the enhanced FA value of the left posterior limb of the internal capsule (PLIC) and reduced FA value in the white matter within the right parahippocampal gyrus (PHG). Gray matter volumes of the DLPFC, rACC, SMA, and white matter FA changes of the PLIC were significantly correlated with the duration of internet addiction in the adolescents with IAD. Our results suggested that long-term internet addiction would result in brain structural alterations, which probably contributed to chronic dysfunction in subjects with IAD. The current study may shed further light on the potential brain effects of IAD.

Effects of low-level exposure to sarin and cyclosarin during the 1991 Gulf War on brain function and brain structure in US veterans

PubMed Central

Chao, Linda L.; Rothlind, Johannes C.; Cardenas, Valerie A.; Meyerhoff, Dieter J.; Weiner, Michael W.

2010-01-01

Background Potentially more than 100,000 US troops may have been exposed to the organophosphate chemical warfare agents sarin (GB) and cyclosarin (GF) when a munitions dump at Khamisiyah, Iraq was destroyed during the Gulf War (GW) in 1991. Although little is known about the long-term neurobehavioral or neurophysiological effects of low-dose exposure to GB/GF in humans, recent studies of GW veterans from the Devens Cohort suggest decrements in certain cognitive domains and atrophy in brain white matter occur individuals with higher estimated levels of presumed GB/GF exposure. The goal of the current study is to determine the generalizability of these findings in another cohort of GW veterans with suspected GB/GF exposure. Methods Neurobehavioral and imaging data collected in a study on Gulf War Illness between 2002–2007 were used in this study. We focused on the data of 40 GW-deployed veterans categorized as having been exposed to GB/GF at Khamisiyah, Iraq and 40 matched controls. Magnetic resonance images (MRI) of the brain were analyzed using automated and semi-automated image processing techniques that produced volumetric measurements of gray matter (GM), white matter (WM), cerebrospinal fluid (CSF) and hippocampus. Results GW veterans with suspected GB/GF exposure had reduced total GM and hippocampal volumes compared to their unexposed peers (p≤0.01). Although there were no group differences in measures of cognitive function or total WM volume, there were significant, positive correlations between total WM volume and measures of executive function and visuospatial abilities in veterans with suspected GB/GF exposure. Conclusions These findings suggest that low-level exposure to GB/GF can have deleterious effects on brain structure and brain function more than decade later. PMID:20580739

Sex differences in the adolescent brain and body: Findings from the saguenay youth study.

PubMed

Paus, Tomáš; Wong, Angelita Pui-Yee; Syme, Catriona; Pausova, Zdenka

2017-01-02

This Mini-Review describes sex differences in 66 quantitative characteristics of the brain and body measured in a community-based sample of 1,024 adolescents 12-18 years of age, members of the Saguenay Youth Study. Using an extensive phenotyping protocol, we have obtained measures in a number of domains, including brain structure, cognition, mental health, substance use, body composition, metabolism, cardiovascular reactivity, and life style. For each measure, we provide estimates of effect size (Cohen's d) and sex-specific correlations with age (Pearson R). In total 59 of the 66 characteristics showed sex differences (at a nominal P < 0.05), with small (32), medium-sized (13), and large (11) effects. Some, but not all, of these sex differences increase during adolescence; this appears to be the case mostly for anatomical and physiological measures. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Sparse brain network using penalized linear regression

NASA Astrophysics Data System (ADS)

Lee, Hyekyoung; Lee, Dong Soo; Kang, Hyejin; Kim, Boong-Nyun; Chung, Moo K.

2011-03-01

Sparse partial correlation is a useful connectivity measure for brain networks when it is difficult to compute the exact partial correlation in the small-n large-p setting. In this paper, we formulate the problem of estimating partial correlation as a sparse linear regression with a l1-norm penalty. The method is applied to brain network consisting of parcellated regions of interest (ROIs), which are obtained from FDG-PET images of the autism spectrum disorder (ASD) children and the pediatric control (PedCon) subjects. To validate the results, we check their reproducibilities of the obtained brain networks by the leave-one-out cross validation and compare the clustered structures derived from the brain networks of ASD and PedCon.

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

PubMed

Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

2015-10-01

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley & Sons, Ltd.

A multiscale cerebral neurochemical connectome of the rat brain

PubMed Central

Schöttler, Judith; Ercsey-Ravasz, Maria; Cosa-Linan, Alejandro; Varga, Melinda; Toroczkai, Zoltan; Spanagel, Rainer

2017-01-01

Understanding the rat neurochemical connectome is fundamental for exploring neuronal information processing. By using advanced data mining, supervised machine learning, and network analysis, this study integrates over 5 decades of neuroanatomical investigations into a multiscale, multilayer neurochemical connectome of the rat brain. This neurochemical connectivity database (ChemNetDB) is supported by comprehensive systematically-determined receptor distribution maps. The rat connectome has an onion-type structural organization and shares a number of structural features with mesoscale connectomes of mouse and macaque. Furthermore, we demonstrate that extremal values of graph theoretical measures (e.g., degree and betweenness) are associated with evolutionary-conserved deep brain structures such as amygdala, bed nucleus of the stria terminalis, dorsal raphe, and lateral hypothalamus, which regulate primitive, yet fundamental functions, such as circadian rhythms, reward, aggression, anxiety, and fear. The ChemNetDB is a freely available resource for systems analysis of motor, sensory, emotional, and cognitive information processing. PMID:28671956

Heritability of changes in brain volume over time in twin pairs discordant for schizophrenia.

PubMed

Brans, Rachel G H; van Haren, Neeltje E M; van Baal, G Caroline M; Schnack, Hugo G; Kahn, René S; Hulshoff Pol, Hilleke E

2008-11-01

Structural brain abnormalities have consistently been found in schizophrenia, with increased familial risk for the disease associated with these abnormalities. Some brain volume changes are progressive over the course of the illness. Whether these progressive brain volume changes are mediated by genetic or disease-related factors is unknown. To investigate whether genetic and/or environmental factors are associated with progressive brain volume changes in schizophrenia. Longitudinal 5-year follow-up in monozygotic (MZ) and dizygotic (DZ) twin pairs discordant for schizophrenia and healthy comparison twin pairs using brain magnetic resonance imaging. Participants were recruited from the twin pair cohort at the University Medical Center Utrecht. A total of 92 participants completed the study: 9 MZ and 10 DZ twin pairs discordant for schizophrenia and 14 MZ and 13 DZ healthy twin pairs. Percentage volume changes of the whole brain; cerebral gray and white matter of the frontal, temporal, parietal, and occipital lobes; cerebellum; and lateral and third ventricles over time between and within twin pairs were compared using repeated measures analysis of covariance. Structural equation modeling was applied to estimate contributions of additive genetic and common and unique environmental factors. Significant decreases over time in whole brain and frontal and temporal lobe volumes were found in patients with schizophrenia and their unaffected co-twins compared with control twins. Bivariate structural equation modeling using cross-trait/cross-twin correlations revealed significant additive genetic influences on the correlations between schizophrenia liability and progressive whole brain (66%; 95% confidence interval [CI], 51%-100%), frontal lobe (76%; 95% CI, 54%-100%), and temporal lobe (79%; CI, 56%-100%) volume change. The progressive brain volume loss found in patients with schizophrenia and their unaffected co-twins is at least partly attributable to genetic factors related to the illness.

Imaging of rat brain using short graded-index multimode fiber

NASA Astrophysics Data System (ADS)

Sato, Manabu; Kanno, Takahiro; Ishihara, Syoutarou; Suto, Hiroshi; Takahashi, Toshihiro; Kurotani, Reiko; Abe, Hiroyuki; Nishidate, Izumi

2014-03-01

Clinically it is important to image structures of brain at deeper areas with low invasions, for example, the pathological information is not obtained enough from the white matter. Preliminarily we have measured transmission images of rat brain using the short graded-index multimode fiber (SMMF) with the diameter of 140μm and length of 5mm. SMMF (core diameter, 100μm) was cut using a fiber cleaver and was fixed in a jig. Fiber lengths inside and outside jig were 3mm and 2mm, respectively. The jig was attached at the 20x objective lens. The conventional optical microscope was used to measure images. In basic characteristics, it was confirmed that the imaging conditions almost corresponded to calculations with the ray-transfer matrix and the spatial resolution was evaluated at about 4.4μm by measuring the test pattern. After euthanasia the rat parietal brain was excised with thickness around 1.5mm and was set on the slide glass. The tissue was illuminated through the slide glass by the bundle fiber with Halogen lamp. The tip of SMMF was inserted into the tissue by lifting the sample stage. The transmission image at each depth from 0.1mm to 1.53mm was measured. Around the depth of 1.45mm, granular structures with sizes of 4-5μm were recognized and corresponded to images by HE stained tissue. Total measurement time was within 2 hours. The feasibilities to image the depth of 5 mm with SMMF have been shown.

Adolescent Neurobiological Susceptibility to Social Context

PubMed Central

Schriber, Roberta A.; Guyer, Amanda E.

2016-01-01

Adolescence has been characterized as a period of heightened sensitivity to social contexts. However, adolescents vary in how their social contexts affect them. According to neurobiological susceptibility models, endogenous, biological factors confer some individuals, relative to others, with greater susceptibility to environmental influences, whereby more susceptible individuals fare the best or worst of all individuals, depending on the environment they encounter (e.g., high vs. low parental warmth). Until recently, research guided by these theoretical frameworks has not incorporated direct measures of brain structure or function to index this sensitivity. Drawing on prevailing models of adolescent neurodevelopment and a growing number of neuroimaging studies on the interrelations among social contexts, the brain, and developmental outcomes, we review research that supports the idea of adolescent neurobiological susceptibility to social context for understanding why and how adolescents differ in development and well-being. We propose that adolescent development is shaped in part by brain-based individual differences in sensitivity to social contexts – be they positive or negative – such as those created through relationships with parents/caregivers and peers. As such, we recommend that future research measure brain function and structure to operationalize susceptibility factors that moderate the influence of social contexts on developmental outcomes. PMID:26773514

Psychophysiological correlates of aggression and violence: an integrative review.

PubMed

Patrick, Christopher J

2008-08-12

This paper reviews existing psychophysiological studies of aggression and violent behaviour including research employing autonomic, electrocortical and neuroimaging measures. Robust physiological correlates of persistent aggressive behaviour evident in this literature include low baseline heart rate, enhanced autonomic reactivity to stressful or aversive stimuli, enhanced EEG slow wave activity, reduced P300 brain potential response and indications from structural and functional neuroimaging studies of dysfunction in frontocortical and limbic brain regions that mediate emotional processing and regulation. The findings are interpreted within a conceptual framework that draws on two integrative models in the literature. The first is a recently developed hierarchical model of impulse control (externalizing) problems, in which various disinhibitory syndromes including aggressive and addictive behaviours of different kinds are seen as arising from common as well as distinctive aetiologic factors. This model represents an approach to organizing these various interrelated phenotypes and investigating their common and distinctive aetiologic substrates. The other is a neurobiological model that posits impairments in affective regulatory circuits in the brain as a key mechanism for impulsive aggressive behaviour. This model provides a perspective for integrating findings from studies employing different measures that have implicated varying brain structures and physiological systems in violent and aggressive behaviour.

Decreased frontal white-matter volume in chronic substance abuse.

PubMed

Schlaepfer, Thomas E; Lancaster, Eric; Heidbreder, Rebecca; Strain, Eric C; Kosel, Markus; Fisch, Hans-Ulrich; Pearlson, Godfrey D

2006-04-01

There is quite a body of work assessing functional brain changes in chronic substance abuse, much less is known about structural brain abnormalities in this patient population. In this study we used magnetic resonance imaging (MRI) to determine if structural brain differences exist in patients abusing illicit drugs compared to healthy controls. Sixteen substance abusers who abused heroin, cocaine and cannabis but not alcohol and 16 age-, sex- and race-matched controls were imaged on a MRI scanner. Contiguous, 5-mm-thick axial slices were acquired with simultaneous T2 and proton density sequences. Volumes were estimated for total grey and white matter, frontal grey and white matter, ventricles, and CSF using two different methods: a conventional segmentation and a stereological method based on the Cavalieri principle. Overall brain volume differences were corrected for by expressing the volumes of interest as a percentage of total brain volume. Volume measures obtained with the two methods were highly correlated (r=0.65, p<0.001). Substance abusers had significantly less frontal white-matter volume percentage than controls. There were no significant differences in any of the other brain volumes measured. This difference in frontal lobe white matter might be explained by a direct neurotoxic effect of drug use on white matter, a pre-existing abnormality in the development of the frontal lobe or a combination of both effects. This last explanation might be compelling based on the fact that newer concepts on shared aspects of some neuropsychiatric disorders focus on the promotion and inhibition of the process of myelination throughout brain development and subsequent degeneration.

BRAPH: A graph theory software for the analysis of brain connectivity

PubMed Central

Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B.; Westman, Eric; Volpe, Giovanni

2017-01-01

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. PMID:28763447

BRAPH: A graph theory software for the analysis of brain connectivity.

PubMed

Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B; Westman, Eric; Volpe, Giovanni

2017-01-01

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.

Non-invasive detection and quantification of brain microvascular deficits by near-infrared spectroscopy in a rat model of Vascular Cognitive Impairment

NASA Astrophysics Data System (ADS)

Hallacoglu, Bertan; Sassaroli, Angelo M.; Rosenberg, Irwin H.; Troen, Aron; Fantini, Sergio

2011-02-01

Structural abnormalities in brain microvasculature are commonly associated with Alzheimer's Disease and other dementias. However, the extent to which structural microvascular abnormalities cause functional impairments in brain circulation and thereby to cognitive impairment is unclear. Non-invasive, near-infrared spectroscopy (NIRS) methods can be used to determine the absolute hemoglobin concentration and saturation in brain tissue, from which additional parameters such as cerebral blood volume (a theoretical correlate of brain microvascular density) can be derived. Validating such NIRS parameters in animal models, and understanding their relationship to cognitive function is an important step in the ultimate application of these methods to humans. To this end we applied a non-invasive multidistance NIRS method to determine the absolute concentration and saturation of cerebral hemoglobin in rat, by separately measuring absorption and reduced scattering coefficients without relying on pre- or post-correction factors. We applied this method to study brain circulation in folate deficient rats, which express brain microvascular pathology1 and which we have shown to develop cognitive impairment.2 We found absolute brain hemoglobin concentration ([HbT]) and oxygen saturation (StO2) to be significantly lower in folate deficient rats (n=6) with respect to control rats (n=5) (for [HbT]: 73+/-10 μM vs. 95+/-14 μM for StO2: 55%+/-7% vs. 66% +/-4%), implicating microvascular pathology and diminished oxygen delivery as a mechanism of cognitive impairment. More generally, our study highlights how noninvasive, absolute NIRS measurements can provide unique insight into the pathophysiology of Vascular Cognitive Impairment. Applying this method to this and other rat models of cognitive impairment will help to validate physiologically meaningful NIRS parameters for the ultimate goal of studying cerebral microvascular disease and cognitive decline in humans.

Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain.

PubMed

Lopopolo, Alessandro; Frank, Stefan L; van den Bosch, Antal; Willems, Roel M

2017-01-01

Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

PubMed Central

Altmann, Andre; Botía, Juan A; Jahanshad, Neda; Hibar, Derrek P; Absil, Julie; Alhusaini, Saud; Alvim, Marina K M; Auvinen, Pia; Bartolini, Emanuele; Bergo, Felipe P G; Bernardes, Tauana; Blackmon, Karen; Braga, Barbara; Caligiuri, Maria Eugenia; Calvo, Anna; Carr, Sarah J; Chen, Jian; Chen, Shuai; Cherubini, Andrea; David, Philippe; Domin, Martin; Foley, Sonya; França, Wendy; Haaker, Gerrit; Isaev, Dmitry; Keller, Simon S; Kotikalapudi, Raviteja; Kowalczyk, Magdalena A; Kuzniecky, Ruben; Langner, Soenke; Lenge, Matteo; Leyden, Kelly M; Liu, Min; Loi, Richard Q; Martin, Pascal; Mascalchi, Mario; Morita, Marcia E; Pariente, Jose C; Rodríguez-Cruces, Raul; Rummel, Christian; Saavalainen, Taavi; Semmelroch, Mira K; Severino, Mariasavina; Thomas, Rhys H; Tondelli, Manuela; Tortora, Domenico; Vaudano, Anna Elisabetta; Vivash, Lucy; von Podewils, Felix; Wagner, Jan; Weber, Bernd; Yao, Yi; Yasuda, Clarissa L; Zhang, Guohao; Bargalló, Nuria; Bender, Benjamin; Bernasconi, Neda; Bernasconi, Andrea; Bernhardt, Boris C; Blümcke, Ingmar; Carlson, Chad; Cavalleri, Gianpiero L; Cendes, Fernando; Concha, Luis; Delanty, Norman; Depondt, Chantal; Devinsky, Orrin; Doherty, Colin P; Focke, Niels K; Gambardella, Antonio; Guerrini, Renzo; Hamandi, Khalid; Jackson, Graeme D; Kälviäinen, Reetta; Kochunov, Peter; Kwan, Patrick; Labate, Angelo; McDonald, Carrie R; Meletti, Stefano; O'Brien, Terence J; Ourselin, Sebastien; Richardson, Mark P; Striano, Pasquale; Thesen, Thomas; Wiest, Roland; Zhang, Junsong; Vezzani, Annamaria; Ryten, Mina; Thompson, Paul M

2018-01-01

Abstract Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen’s d = −0.24 to −0.73; P < 1.49 × 10−4), and lower thickness in the precentral gyri bilaterally (d = −0.34 to −0.52; P < 4.31 × 10−6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = −1.73 to −1.91, P < 1.4 × 10−19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = −0.36 to −0.52; P < 1.49 × 10−4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = −0.29 to −0.54; P < 1.49 × 10−4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = −0.27 to −0.51; P < 1.49 × 10−4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < −0.0018; P < 1.49 × 10−4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed. PMID:29365066

Repairing the brain with physical exercise: Cortical thickness and brain volume increases in long-term pediatric brain tumor survivors in response to a structured exercise intervention.

PubMed

Szulc-Lerch, Kamila U; Timmons, Brian W; Bouffet, Eric; Laughlin, Suzanne; de Medeiros, Cynthia B; Skocic, Jovanka; Lerch, Jason P; Mabbott, Donald J

2018-01-01

There is growing evidence that exercise induced experience dependent plasticity may foster structural and functional recovery following brain injury. We examined the efficacy of exercise training for neural and cognitive recovery in long-term pediatric brain tumor survivors treated with radiation. We conducted a controlled clinical trial with crossover of exercise training (vs. no training) in a volunteer sample of 28 children treated with cranial radiation for brain tumors (mean age = 11.5 yrs.; mean time since diagnosis = 5.7 yrs). The endpoints were anatomical T1 MRI data and multiple behavioral outcomes presenting a broader analysis of structural MRI data across the entire brain. This included an analysis of changes in cortical thickness and brain volume using automated, user unbiased approaches. A series of general linear mixed effects models evaluating the effects of exercise training on cortical thickness were performed in a voxel and vertex-wise manner, as well as for specific regions of interest. In exploratory analyses, we evaluated the relationship between changes in cortical thickness after exercise with multiple behavioral outcomes, as well as the relation of these measures at baseline. Exercise was associated with increases in cortical thickness within the right pre and postcentral gyri. Other notable areas of increased thickness related to training were present in the left pre and postcentral gyri, left temporal pole, left superior temporal gyrus, and left parahippocampal gyrus. Further, we observed that compared to a separate cohort of healthy children, participants displayed multiple areas with a significantly thinner cortex prior to training and fewer differences following training, indicating amelioration of anatomical deficits. Partial least squares analysis (PLS) revealed specific patterns of relations between cortical thickness and various behavioral outcomes both after training and at baseline. Overall, our results indicate that exercise training in pediatric brain tumor patients treated with radiation has a beneficial impact on brain structure. We argue that exercise training should be incorporated into the development of neuro-rehabilitative treatments for long-term pediatric brain tumor survivors and other populations with acquired brain injury. (ClinicalTrials.gov, NCT01944761).

Brain structure links everyday creativity to creative achievement.

PubMed

Zhu, Wenfeng; Chen, Qunlin; Tang, Chaoying; Cao, Guikang; Hou, Yuling; Qiu, Jiang

2016-03-01

Although creativity is commonly considered to be a cornerstone of human progress and vital to all realms of our lives, its neural basis remains elusive, partly due to the different tasks and measurement methods applied in research. In particular, the neural correlates of everyday creativity that can be experienced by everyone, to some extent, are still unexplored. The present study was designed to investigate the brain structure underlying individual differences in everyday creativity, as measured by the Creative Behavioral Inventory (CBI) (N=163). The results revealed that more creative activities were significantly and positively associated with larger gray matter volume (GMV) in the regional premotor cortex (PMC), which is a motor planning area involved in the creation and selection of novel actions and inhibition. In addition, the gray volume of the PMC had a significant positive relationship with creative achievement and Art scores, which supports the notion that training and practice may induce changes in brain structures. These results indicate that everyday creativity is linked to the PMC and that PMC volume can predict creative achievement, supporting the view that motor planning may play a crucial role in creative behavior. Published by Elsevier Inc.

Quantitative MRI of the spinal cord and brain in adrenomyeloneuropathy: in vivo assessment of structural changes.

PubMed

Castellano, Antonella; Papinutto, Nico; Cadioli, Marcello; Brugnara, Gianluca; Iadanza, Antonella; Scigliuolo, Graziana; Pareyson, Davide; Uziel, Graziella; Köhler, Wolfgang; Aubourg, Patrick; Falini, Andrea; Henry, Roland G; Politi, Letterio S; Salsano, Ettore

2016-06-01

Adrenomyeloneuropathy is the late-onset form of X-linked adrenoleukodystrophy, and is considered the most frequent metabolic hereditary spastic paraplegia. In adrenomyeloneuropathy the spinal cord is the main site of pathology. Differently from quantitative magnetic resonance imaging of the brain, little is known about the feasibility and utility of advanced neuroimaging in quantifying the spinal cord abnormalities in hereditary diseases. Moreover, little is known about the subtle pathological changes that can characterize the brain of adrenomyeloneuropathy subjects in the early stages of the disease. We performed a cross-sectional study on 13 patients with adrenomyeloneuropathy and 12 age-matched healthy control subjects who underwent quantitative magnetic resonance imaging to assess the structural changes of the upper spinal cord and brain. Total cord areas from C2-3 to T2-3 level were measured, and diffusion tensor imaging metrics, i.e. fractional anisotropy, mean, axial and radial diffusivity values were calculated in both grey and white matter of spinal cord. In the brain, grey matter regions were parcellated with Freesurfer and average volume and thickness, and mean diffusivity and fractional anisotropy from co-registered diffusion maps were calculated in each region. Brain white matter diffusion tensor imaging metrics were assessed using whole-brain tract-based spatial statistics, and tractography-based analysis on corticospinal tracts. Correlations among clinical, structural and diffusion tensor imaging measures were calculated. In patients total cord area was reduced by 26.3% to 40.2% at all tested levels (P < 0.0001). A mean 16% reduction of spinal cord white matter fractional anisotropy (P ≤ 0.0003) with a concomitant 9.7% axial diffusivity reduction (P < 0.009) and 34.5% radial diffusivity increase (P < 0.009) was observed, suggesting co-presence of axonal degeneration and demyelination. Brain tract-based spatial statistics showed a marked reduction of fractional anisotropy, increase of radial diffusivity (P < 0.001) and no axial diffusivity changes in several white matter tracts, including corticospinal tracts and optic radiations, indicating predominant demyelination. Tractography-based analysis confirmed the results within corticospinal tracts. No significant cortical volume and thickness reduction or grey matter diffusion tensor imaging values alterations were observed in patients. A correlation between radial diffusivity and disease duration along the corticospinal tracts (r = 0.806, P < 0.01) was found. In conclusion, in adrenomyeloneuropathy patients quantitative magnetic resonance imaging-derived measures identify and quantify structural changes in the upper spinal cord and brain which agree with the expected histopathology, and suggest that the disease could be primarily caused by a demyelination rather than a primitive axonal damage. The results of this study may also encourage the employment of quantitative magnetic resonance imaging in other hereditary diseases with spinal cord involvement. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results.

PubMed

Lyden, Hannah; Gimbel, Sarah I; Del Piero, Larissa; Tsai, A Bryna; Sachs, Matthew E; Kaplan, Jonas T; Margolin, Gayla; Saxbe, Darby

2016-01-01

Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant). The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations were found between early family aggression exposure and brain volume depending on the segmentation method used.

Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results

PubMed Central

Lyden, Hannah; Gimbel, Sarah I.; Del Piero, Larissa; Tsai, A. Bryna; Sachs, Matthew E.; Kaplan, Jonas T.; Margolin, Gayla; Saxbe, Darby

2016-01-01

Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant). The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations were found between early family aggression exposure and brain volume depending on the segmentation method used. PMID:27656121

Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue

PubMed Central

Bjornsson, Christopher S; Lin, Gang; Al-Kofahi, Yousef; Narayanaswamy, Arunachalam; Smith, Karen L; Shain, William; Roysam, Badrinath

2009-01-01

Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic ‘divide and conquer’ methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick (~100 μm) slices of rat brain tissue were labeled using 3 – 5 fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features were used to classify astrocytes, microglia, neurons, and endothelial cells. Associations among cells and between cells and vasculature were computed and represented as graphical networks to enable further analysis. The automated results were validated using a graphical interface that permits investigator inspection and corrective editing of each cell in 3D. Nuclear counting accuracy was >89%, and cell classification accuracy ranged from 81–92% depending on cell type. We present a software system named FARSIGHT implementing our methodology. Its output is a detailed XML file containing measurements that may be used for diverse quantitative hypothesis-driven and exploratory studies of the central nervous system. PMID:18294697

Neural Correlates of Emotional Personality: A Structural and Functional Magnetic Resonance Imaging Study

PubMed Central

Koelsch, Stefan; Skouras, Stavros; Jentschke, Sebastian

2013-01-01

Studies addressing brain correlates of emotional personality have remained sparse, despite the involvement of emotional personality in health and well-being. This study investigates structural and functional brain correlates of psychological and physiological measures related to emotional personality. Psychological measures included neuroticism, extraversion, and agreeableness scores, as assessed using a standard personality questionnaire. As a physiological measure we used a cardiac amplitude signature, the so-called E κ value (computed from the electrocardiogram) which has previously been related to tender emotionality. Questionnaire scores and E κ values were related to both functional (eigenvector centrality mapping, ECM) and structural (voxel-based morphometry, VBM) neuroimaging data. Functional magnetic resonance imaging (fMRI) data were obtained from 22 individuals (12 females) while listening to music (joy, fear, or neutral music). ECM results showed that agreeableness scores correlated with centrality values in the dorsolateral prefrontal cortex, the anterior cingulate cortex, and the ventral striatum (nucleus accumbens). Individuals with higher E κ values (indexing higher tender emotionality) showed higher centrality values in the subiculum of the right hippocampal formation. Structural MRI data from an independent sample of 59 individuals (34 females) showed that neuroticism scores correlated with volume of the left amygdaloid complex. In addition, individuals with higher E κ showed larger gray matter volume in the same portion of the subiculum in which individuals with higher E κ showed higher centrality values. Our results highlight a role of the amygdala in neuroticism. Moreover, they indicate that a cardiac signature related to emotionality (E κ) correlates with both function (increased network centrality) and structure (grey matter volume) of the subiculum of the hippocampal formation, suggesting a role of the hippocampal formation for emotional personality. Results are the first to show personality-related differences using eigenvector centrality mapping, and the first to show structural brain differences for a physiological measure associated with personality. PMID:24312166

Atrophy of spared gray matter tissue predicts poorer motor recovery and rehabilitation response in chronic stroke.

PubMed

Gauthier, Lynne V; Taub, Edward; Mark, Victor W; Barghi, Ameen; Uswatte, Gitendra

2012-02-01

Although the motor deficit after stroke is clearly due to the structural brain damage that has been sustained, this relationship is attenuated from the acute to chronic phases. We investigated the possibility that motor impairment and response to constraint-induced movement therapy in patients with chronic stroke may relate more strongly to the structural integrity of brain structures remote from the lesion than to measures of overt tissue damage. Voxel-based morphometry analysis was performed on MRI scans from 80 patients with chronic stroke to investigate whether variations in gray matter density were correlated with extent of residual motor impairment or with constraint-induced movement therapy-induced motor recovery. Decreased gray matter density in noninfarcted motor regions was significantly correlated with magnitude of residual motor deficit. In addition, reduced gray matter density in multiple remote brain regions predicted a lesser extent of motor improvement from constraint-induced movement therapy. Atrophy in seemingly healthy parts of the brain that are distant from the infarct accounts for at least a portion of the sustained motor deficit in chronic stroke.

Atrophy of spared grey matter tissue predicts poorer motor recovery and rehabilitation response in chronic stroke

PubMed Central

Gauthier, Lynne V.; Taub, Edward; Mark, Victor W.; Barghi, Ameen; Uswatte, Gitendra

2011-01-01

Background and Purpose Although the motor deficit following stroke is clearly due to the structural brain damage that has been sustained, this relationship is attenuated from the acute to chronic phases. We investigated the possibility that motor impairment and response to Constraint-Induced Movement therapy (CI therapy) in chronic stroke patients may relate more strongly to the structural integrity of brain structures remote from the lesion than to measures of overt tissue damage. Methods Voxel-based morphometry (VBM) analysis was performed on MRI scans from 80 chronic stroke patients to investigate whether variations in grey matter density were correlated with extent of residual motor impairment or with CI therapy-induced motor recovery. Results Decreased grey matter density in non-infarcted motor regions was significantly correlated with magnitude of residual motor deficit. In addition, reduced grey matter density in multiple remote brain regions predicted a lesser extent of motor improvement from CI therapy. Conclusions Atrophy in seemingly healthy parts of the brain that are distant from the infarct accounts for at least a portion of the sustained motor deficit in chronic stroke. PMID:22096036

Structural Brain Correlates Associated with Professional Handball Playing

PubMed Central

Hänggi, Jürgen; Langer, Nicolas; Lutz, Kai; Birrer, Karin; Mérillat, Susan; Jäncke, Lutz

2015-01-01

Background There is no doubt that good bimanual performance is very important for skilled handball playing. The control of the non-dominant hand is especially demanding since efficient catching and throwing needs both hands. Methodology/Hypotheses We investigated training-induced structural neuroplasticity in professional handball players using several structural neuroimaging techniques and analytic approaches and also provide a review of the literature about sport-induced structural neuroplastic alterations. Structural brain adaptations were expected in regions relevant for motor and somatosensory processing such as the grey matter (GM) of the primary/secondary motor (MI/supplementary motor area, SMA) and somatosensory cortex (SI/SII), basal ganglia, thalamus, and cerebellum and in the white matter (WM) of the corticospinal tract (CST) and corpus callosum, stronger in brain regions controlling the non-dominant left hand. Results Increased GM volume in handball players compared with control subjects were found in the right MI/SI, bilateral SMA/cingulate motor area, and left intraparietal sulcus. Fractional anisotropy (FA) and axial diffusivity were increased within the right CST in handball players compared with control women. Age of handball training commencement correlated inversely with GM volume in the right and left MI/SI and years of handball training experience correlated inversely with radial diffusivity in the right CST. Subcortical structures tended to be larger in handball players. The anatomical measures of the brain regions associated with handball playing were positively correlated in handball players, but not interrelated in control women. Discussion/Conclusion Training-induced structural alterations were found in the somatosensory-motor network of handball players, more pronounced in the right hemisphere controlling the non-dominant left hand. Correlations between handball training-related measures and anatomical differences suggest neuroplastic adaptations rather than a genetic predisposition for a ball playing affinity. Investigations of neuroplasticity specifically in sportsmen might help to understand the neural mechanisms of expertise in general. PMID:25915906

Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging☆

PubMed Central

Oishi, Kenichi; Faria, Andreia V.; Yoshida, Shoko; Chang, Linda; Mori, Susumu

2013-01-01

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a “growth percentile chart,” which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application. PMID:23796902

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

PubMed Central

Kraft, Reuben H.; Mckee, Phillip Justin; Dagro, Amy M.; Grafton, Scott T.

2012-01-01

This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the “damaged” network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times () network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight. PMID:22915997

Comparison of Automated Brain Volume Measures obtained with NeuroQuant and FreeSurfer.

PubMed

Ochs, Alfred L; Ross, David E; Zannoni, Megan D; Abildskov, Tracy J; Bigler, Erin D

2015-01-01

To examine intermethod reliabilities and differences between FreeSurfer and the FDA-cleared congener, NeuroQuant, both fully automated methods for structural brain MRI measurements. MRI scans from 20 normal control subjects, 20 Alzheimer's disease patients, and 20 mild traumatically brain-injured patients were analyzed with NeuroQuant and with FreeSurfer. Intermethod reliability was evaluated. Pairwise correlation coefficients, intraclass correlation coefficients, and effect size differences were computed. NeuroQuant versus FreeSurfer measures showed excellent to good intermethod reliability for the 21 regions evaluated (r: .63 to .99/ICC: .62 to .99/ES: -.33 to 2.08) except for the pallidum (r/ICC/ES = .31/.29/-2.2) and cerebellar white matter (r/ICC/ES = .31/.31/.08). Volumes reported by NeuroQuant were generally larger than those reported by FreeSurfer with the whole brain parenchyma volume reported by NeuroQuant 6.50% larger than the volume reported by FreeSurfer. There was no systematic difference in results between the 3 subgroups. NeuroQuant and FreeSurfer showed good to excellent intermethod reliability in volumetric measurements for all brain regions examined with the only exceptions being the pallidum and cerebellar white matter. This finding was robust for normal individuals, patients with Alzheimer's disease, and patients with mild traumatic brain injury. Copyright © 2015 by the American Society of Neuroimaging.

Asymmetry of different brain structures in homing pigeons with and without navigational experience.

PubMed

Mehlhorn, Julia; Haastert, Burkhard; Rehkämper, Gerd

2010-07-01

Homing pigeons (Columba livia f.d.) are well-known for their homing abilities, and their brains seem to be functionally adapted to homing as exemplified, e.g. by their larger hippocampi and olfactory bulbs. Their hippocampus size is influenced by navigational experience, and, as in other birds, functional specialisation of the left and right hemispheres ('lateralisation') occurs in homing pigeons. To show in what way lateralisation is reflected in brain structure volume, and whether some lateralisation or asymmetry in homing pigeons is caused by experience, we compared brains of homing pigeons with and without navigational experience referring to this. Fourteen homing pigeons were raised under identical constraints. After fledging, seven of them were allowed to fly around the loft and participated successfully in races. The other seven stayed permanently in the loft and thus did not share the navigational experiences of the first group. After reaching sexual maturity, all individuals were killed and morphometric analyses were carried out to measure the volumes of five basic brain parts and eight telencephalic brain parts. Measurements of telencephalic brain parts and optic tectum were done separately for the left and right hemispheres. The comparison of left/right quotients of both groups reveal that pigeons with navigational experience show a smaller left mesopallium in comparison with the right mesopallium and pigeons without navigational experience a larger left mesopallium in comparison with the right one. Additionally, there are significant differences between left and right brain subdivisions within the two pigeon groups, namely a larger left hyperpallium apicale in both pigeon groups and a larger right nidopallium, left hippocampus and right optic tectum in pigeons with navigational experience. Pigeons without navigational experience did not show more significant differences between their left and right brain subdivisions. The results of our study confirm that the brain of homing pigeons is an example for mosaic evolution and indicates that lateralisation is correlated with individual life history (experience) and not exclusively based on heritable traits.

The association of antipsychotic medication and lithium with brain measures in patients with bipolar disorder.

PubMed

Abramovic, Lucija; Boks, Marco P M; Vreeker, Annabel; Bouter, Diandra C; Kruiper, Caitlyn; Verkooijen, Sanne; van Bergen, Annet H; Ophoff, Roel A; Kahn, René S; van Haren, Neeltje E M

2016-11-01

There is evidence that brain structure is abnormal in patients with bipolar disorder. Lithium intake appears to ׳normalise׳ global and local brain volumes, but effects of antipsychotic medication on brain volume or cortical thickness are less clear. Here, we aim to disentangle disease-specific brain deviations from those induced by antipsychotic medication and lithium intake using a large homogeneous sample of patients with bipolar disorder type I. Magnetic resonance imaging brain scans were obtained from 266 patients and 171 control subjects. Subcortical volumes and global and focal cortical measures (volume, thickness, and surface area) were compared between patients and controls. In patients, the association between lithium and antipsychotic medication intake and global, subcortical and cortical measures was investigated. Patients showed significantly larger lateral and third ventricles, smaller total brain, caudate nucleus, and pallidum volumes and thinner cortex in some small clusters in frontal, parietal and cingulate regions as compared with controls. Lithium-free patients had significantly smaller total brain, thalamus, putamen, pallidum, hippocampus and accumbens volumes compared to patients on lithium. In patients, use of antipsychotic medication was related to larger third ventricle and smaller hippocampus and supramarginal cortex volume. Patients with bipolar disorder show abnormalities in total brain, subcortical, and ventricle volume, particularly in the nucleus caudate and pallidum. Abnormalities in cortical thickness were scattered and clusters were relatively small. Lithium-free patients showed more pronounced abnormalities as compared with those on lithium. The associations between antipsychotic medication and brain volume are subtle and less pronounced than those of lithium. Copyright © 2016 Elsevier B.V. and ECNP. All rights reserved.

Structural brain MRI trait polygenic score prediction of cognitive abilities

PubMed Central

Luciano, Michelle; Marioni, Riccardo E; Hernández, Maria Valdés; Maniega, Susana Munoz; Hamilton, Iona F; Royle, Natalie A.; Scotland, Generation; Chauhan, Ganesh; Bis, Joshua C.; Debette, Stephanie; DeCarli, Charles; Fornage, Myriam; Schmidt, Reinhold; Ikram, M. Arfan; Launer, Lenore J.; Seshadri, Sudha; Bastin, Mark E.; Porteous, David J.; Wardlaw, Joanna; Deary, Ian J

2016-01-01

Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association for brain infarcts, white matter hyperintensities, intracranial, hippocampal and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to 1) predict corresponding MRI traits in the LBC1936 (numbers ranged 573 to 630 across traits) and 2) predict cognitive traits in all three cohorts (in 8,115 to 8,250 persons). In the LBC1936, all MRI phenotypic traits were correlated with at least one cognitive measure; and polygenic prediction of MRI traits was observed for intracranial volume. Meta-analysis of the correlations between MRI polygenic scores and cognitive traits revealed a significant negative correlation (maximal r=0.08) between the hippocampal volume polygenic score and measures of global cognitive ability collected in childhood and in old age in the Lothian Birth Cohorts. The lack of association to a related general cognitive measure when including the GS:SFHS points to either type 1 error or the importance of using prediction samples that closely match the demographics of the genome-wide association samples from which prediction is based. Ideally, these analyses should be repeated in larger samples with data on both MRI and cognition, and using MRI GWA results from even larger meta-analysis studies. PMID:26427786

Structural development of human brain white matter from mid-fetal to perinatal stage

NASA Astrophysics Data System (ADS)

Ouyang, Austin; Yu, Qiaowen; Mishra, Virendra; Chalak, Lina; Jeon, Tina; Sivarajan, Muraleedharan; Jackson, Greg; Rollins, Nancy; Liu, Shuwei; Huang, Hao

2015-03-01

The structures of developing human brain white matter (WM) tracts can be effectively quantified by DTI-derived metrics, including fractional anisotropy (FA), mean, axial and radial diffusivity (MD, AD and RD). However, dynamics of WM microstructure during very early developmental period from mid-fetal to perinatal stage is unknown. It is difficult to accurately measure microstructural properties of these WM tracts due to severe contamination from cerebrospinal fluid (CSF). In this study, high resolution DTI of fetal brains at mid-fetal stage (20 weeks of gestation or 20wg), 19 brains in the middle of 3rd trimester (35wg) and 17 brains around term (40wg) were acquired. We established first population-averaged DTI templates at these three time points and extracted WM skeleton. 16 major WM tracts in limbic, projection, commissural and association tract groups were traced with DTI tractography in native space. The WM skeleton in the template space was inversely transformed back to the native space for measuring core WM microstructures of each individual tract. Continuous microstructural enhancement and volumetric increase of WM tracts were found from 20wg to 40wg. The microstructural enhancement from FA measurement is decelerated in late 3rd trimester compared to mid-fetal to middle 3rd trimester, while volumetric increase of prefrontal WM tracts is accelerated. The microstructural enhancement from 35wg to 40wg is heterogeneous among different tract groups with microstructures of association tracts undergoing most dramatic change. Besides decreases of RD indicating active myelination, the decrease of AD for most WM tracts during late 3rd trimester suggests axonal packing process.

Relations between prospective memory, cognitive abilities, and brain structure in adolescents who vary in prenatal drug exposure

PubMed Central

Robey, Alison; Buckingham-Howes, Stacy; Salmeron, Betty Jo; Black, Maureen M.; Riggins, Tracy

2014-01-01

This investigation examined how prospective memory (PM) relates to cognitive abilities (i.e., executive function, attention, working memory, and retrospective memory), and brain structure in adolescents who vary in prenatal drug exposure (PDE). The sample included 105 (55 female, 50 male) urban, primarily African American adolescents (mean age 15.5 years) from low socioeconomic status (SES) families; 56% (n=59) were prenatally exposed to drugs (heroin and/or cocaine) and 44% (n=46) were not prenatally exposed, but similar in age, gender, race, and SES. Executive functioning, attentional control, working memory, retrospective memory, and overall cognitive ability were assessed by validated performance measures. Executive functioning was also measured by caregiver report. A subset of 52 adolescents completed MRI scans, which provided measures of subcortical gray matter volumes and thickness of prefrontal, parietal and temporal cortices. Results revealed no differences in PM performance by PDE status, even after adjusting for age and IQ. Executive function, retrospective memory, cortical thickness in frontal and parietal regions, and volume of subcortical regions (i.e., putamen and hippocampus) were related to PM performance in the sample overall, even after adjusting for age, IQ, and total gray matter volume. Findings suggest that variations in PM ability during adolescence are robustly related to individual differences in cognitive abilities, in particular executive function and retrospective memory, and brain structure, but do not vary by PDE status. PMID:24630759

From Nose to Brain: Un-Sensed Electrical Currents Applied in the Nose Alter Activity in Deep Brain Structures

PubMed Central

Weiss, Tali; Shushan, Sagit; Ravia, Aharon; Hahamy, Avital; Secundo, Lavi; Weissbrod, Aharon; Ben-Yakov, Aya; Holtzman, Yael; Cohen-Atsmoni, Smadar; Roth, Yehudah; Sobel, Noam

2016-01-01

Rules linking patterns of olfactory receptor neuron activation in the nose to activity patterns in the brain and ensuing odor perception remain poorly understood. Artificially stimulating olfactory neurons with electrical currents and measuring ensuing perception may uncover these rules. We therefore inserted an electrode into the nose of 50 human volunteers and applied various currents for about an hour in each case. This induced assorted non-olfactory sensations but never once the perception of odor. To validate contact with the olfactory path, we used functional magnetic resonance imaging to measure resting-state brain activity in 18 subjects before and after un-sensed stimulation. We observed stimulation-induced neural decorrelation specifically in primary olfactory cortex, implying contact with the olfactory path. These results suggest that indiscriminate olfactory activation does not equate with odor perception. Moreover, this effort serendipitously uncovered a novel path for minimally invasive brain stimulation through the nose. PMID:27591145

Ageing and brain white matter structure in 3,513 UK Biobank participants

PubMed Central

Cox, Simon R.; Ritchie, Stuart J.; Tucker-Drob, Elliot M.; Liewald, David C.; Hagenaars, Saskia P.; Davies, Gail; Wardlaw, Joanna M.; Gale, Catharine R.; Bastin, Mark E.; Deary, Ian J.

2016-01-01

Quantifying the microstructural properties of the human brain's connections is necessary for understanding normal ageing and disease. Here we examine brain white matter magnetic resonance imaging (MRI) data in 3,513 generally healthy people aged 44.64–77.12 years from the UK Biobank. Using conventional water diffusion measures and newer, rarely studied indices from neurite orientation dispersion and density imaging, we document large age associations with white matter microstructure. Mean diffusivity is the most age-sensitive measure, with negative age associations strongest in the thalamic radiation and association fibres. White matter microstructure across brain tracts becomes increasingly correlated in older age. This may reflect an age-related aggregation of systemic detrimental effects. We report several other novel results, including age associations with hemisphere and sex, and comparative volumetric MRI analyses. Results from this unusually large, single-scanner sample provide one of the most extensive characterizations of age associations with major white matter tracts in the human brain. PMID:27976682

Familial and environmental influences on brain volumes in twins with schizophrenia.

PubMed

Picchioni, Marco M; Rijsdijk, Fruhling; Toulopoulou, Timothea; Chaddock, Christopher; Cole, James H; Ettinger, Ulrich; Oses, Ana; Metcalfe, Hugo; Murray, Robin M; McGuire, Philip

2017-03-01

Reductions in whole brain and grey matter volumes are robust features of schizophrenia, yet their etiological influences are unclear. We investigated the association between the genetic and environmental risk for schizophrenia and brain volumes. Whole brain, grey matter and white matter volumes were established from structural MRIs from twins varying in their zygosity and concordance for schizophrenia. Hippocampal volumes were measured manually. We conducted between-group testing and full genetic modelling. We included 168 twins in our study. Whole brain, grey matter, white matter and right hippocampal volumes were smaller in twins with schizophrenia. Twin correlations were larger for whole brain, grey matter and white matter volumes in monozygotic than dizygotic twins and were significantly heritable, whereas hippocampal volume was the most environmentally sensitive. There was a significant phenotypic correlation between schizophrenia and reductions in all the brain volumes except for that of the left hippocampus. For whole brain, grey matter and the right hippocampus the etiological links with schizophrenia were principally associated with the shared familial environment. Lower birth weight and perinatal hypoxia were both associated with lower whole brain volume and with lower white matter and grey matter volumes, respectively. Scan data were collected across 2 sites, and some groups were modest in size. Whole brain, grey matter and right hippocampal volume reductions are linked to schizophrenia through correlated familial risk (i.e., the shared familial environment). The degree of influence of etiological factors varies between brain structures, leading to the possibility of a neuroanatomically specific etiological imprint.

Real-time interactive tractography analysis for multimodal brain visualization tool: MultiXplore

NASA Astrophysics Data System (ADS)

Bakhshmand, Saeed M.; de Ribaupierre, Sandrine; Eagleson, Roy

2017-03-01

Most debilitating neurological disorders can have anatomical origins. Yet unlike other body organs, the anatomy alone cannot easily provide an understanding of brain functionality. In fact, addressing the challenge of linking structural and functional connectivity remains in the frontiers of neuroscience. Aggregating multimodal neuroimaging datasets may be critical for developing theories that span brain functionality, global neuroanatomy and internal microstructures. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are main such techniques that are employed to investigate the brain under normal and pathological conditions. FMRI records blood oxygenation level of the grey matter (GM), whereas DTI is able to reveal the underlying structure of the white matter (WM). Brain global activity is assumed to be an integration of GM functional hubs and WM neural pathways that serve to connect them. In this study we developed and evaluated a two-phase algorithm. This algorithm is employed in a 3D interactive connectivity visualization framework and helps to accelerate clustering of virtual neural pathways. In this paper, we will detail an algorithm that makes use of an index-based membership array formed for a whole brain tractography file and corresponding parcellated brain atlas. Next, we demonstrate efficiency of the algorithm by measuring required times for extracting a variety of fiber clusters, which are chosen in such a way to resemble all sizes probable output data files that algorithm will generate. The proposed algorithm facilitates real-time visual inspection of neuroimaging data to further the discovery in structure-function relationship of the brain networks.

The impacts of pesticide and nicotine exposures on functional brain networks in Latino immigrant workers.

PubMed

Bahrami, Mohsen; Laurienti, Paul J; Quandt, Sara A; Talton, Jennifer; Pope, Carey N; Summers, Phillip; Burdette, Jonathan H; Chen, Haiying; Liu, Jing; Howard, Timothy D; Arcury, Thomas A; Simpson, Sean L

2017-09-01

Latino immigrants that work on farms experience chronic exposures to potential neurotoxicants, such as pesticides, as part of their work. For tobacco farmworkers there is the additional risk of exposure to moderate to high doses of nicotine. Pesticide and nicotine exposures have been associated with neurological changes in the brain. Long-term exposure to cholinesterase-inhibiting pesticides, such as organophosphates and carbamates, and nicotine place this vulnerable population at risk for developing neurological dysfunction. In this study we examined whole-brain connectivity patterns and brain network properties of Latino immigrant workers. Comparisons were made between farmworkers and non-farmworkers using resting-state functional magnetic resonance imaging data and a mixed-effects modeling framework. We also evaluated how measures of pesticide and nicotine exposures contributed to the findings. Our results indicate that despite having the same functional connectivity density and strength, brain networks in farmworkers had more clustered and modular structures when compared to non-farmworkers. Our findings suggest increased functional specificity and decreased functional integration in farmworkers when compared to non-farmworkers. Cholinesterase activity was associated with population differences in community structure and the strength of brain network functional connections. Urinary cotinine, a marker of nicotine exposure, was associated with the differences in network community structure. Brain network differences between farmworkers and non-farmworkers, as well as pesticide and nicotine exposure effects on brain functional connections in this study, may illuminate underlying mechanisms that cause neurological implications in later life. Copyright © 2017 Elsevier B.V. All rights reserved.

Nicotine increases brain functional network efficiency.

PubMed

Wylie, Korey P; Rojas, Donald C; Tanabe, Jody; Martin, Laura F; Tregellas, Jason R

2012-10-15

Despite the use of cholinergic therapies in Alzheimer's disease and the development of cholinergic strategies for schizophrenia, relatively little is known about how the system modulates the connectivity and structure of large-scale brain networks. To better understand how nicotinic cholinergic systems alter these networks, this study examined the effects of nicotine on measures of whole-brain network communication efficiency. Resting state fMRI was acquired from fifteen healthy subjects before and after the application of nicotine or placebo transdermal patches in a single blind, crossover design. Data, which were previously examined for default network activity, were analyzed with network topology techniques to measure changes in the communication efficiency of whole-brain networks. Nicotine significantly increased local efficiency, a parameter that estimates the network's tolerance to local errors in communication. Nicotine also significantly enhanced the regional efficiency of limbic and paralimbic areas of the brain, areas which are especially altered in diseases such as Alzheimer's disease and schizophrenia. These changes in network topology may be one mechanism by which cholinergic therapies improve brain function. Published by Elsevier Inc.

Assessing the mean strength and variations of the time-to-time fluctuations of resting-state brain activity.

PubMed

Li, Zhengjun; Zang, Yu-Feng; Ding, Jianping; Wang, Ze

2017-04-01

The time-to-time fluctuations (TTFs) of resting-state brain activity as captured by resting-state fMRI (rsfMRI) have been repeatedly shown to be informative of functional brain structures and disease-related alterations. TTFs can be characterized by the mean and the range of successive difference. The former can be measured with the mean squared successive difference (MSSD), which is mathematically similar to standard deviation; the latter can be calculated by the variability of the successive difference (VSD). The purpose of this study was to evaluate both the resting state-MSSD and VSD of rsfMRI regarding their test-retest stability, sensitivity to brain state change, as well as their biological meanings. We hypothesized that MSSD and VSD are reliable in resting brain; both measures are sensitive to brain state changes such as eyes-open compared to eyes-closed condition; both are predictive of age. These hypotheses were tested with three rsfMRI datasets and proven true, suggesting both MSSD and VSD as reliable and useful tools for resting-state studies.

Nicotine Increases Brain Functional Network Efficiency

PubMed Central

Wylie, Korey P.; Rojas, Donald C.; Tanabe, Jody; Martin, Laura F.; Tregellas, Jason R.

2012-01-01

Despite the use of cholinergic therapies in Alzheimer’s disease and the development of cholinergic strategies for schizophrenia, relatively little is known about how the system modulates the connectivity and structure of large-scale brain networks. To better understand how nicotinic cholinergic systems alter these networks, this study examined the effects of nicotine on measures of whole-brain network communication efficiency. Resting-state fMRI was acquired from fifteen healthy subjects before and after the application of nicotine or placebo transdermal patches in a single blind, crossover design. Data, which were previously examined for default network activity, were analyzed with network topology techniques to measure changes in the communication efficiency of whole-brain networks. Nicotine significantly increased local efficiency, a parameter that estimates the network’s tolerance to local errors in communication. Nicotine also significantly enhanced the regional efficiency of limbic and paralimbic areas of the brain, areas which are especially altered in diseases such as Alzheimer’s disease and schizophrenia. These changes in network topology may be one mechanism by which cholinergic therapies improve brain function. PMID:22796985

A Testosterone-Related Structural Brain Phenotype Predicts Aggressive Behavior From Childhood to Adulthood

PubMed Central

Nguyen, Tuong-Vi; McCracken, James T; Albaugh, Matthew D; Botteron, Kelly N.; Hudziak, James J; Ducharme, Simon

2015-01-01

Structural covariance, the examination of anatomic correlations between brain regions, has emerged recently as a valid and useful measure of developmental brain changes. Yet the exact biological processes leading to changes in covariance, and the relation between such covariance and behavior, remain largely unexplored. The steroid hormone testosterone represents a compelling mechanism through which this structural covariance may be developmentally regulated in humans. Although steroid hormone receptors can be found throughout the central nervous system, the amygdala represents a key target for testosterone-specific effects, given its high density of androgen receptors. In addition, testosterone has been found to impact cortical thickness (CTh) across the whole brain, suggesting that it may also regulate the structural relationship, or covariance, between the amygdala and CTh. Here we examined testosterone-related covariance between amygdala volumes and whole-brain CTh, as well as its relationship to aggression levels, in a longitudinal sample of children, adolescents, and young adults 6 to 22 years old. We found: (1) testosterone-specific modulation of the covariance between the amygdala and medial prefrontal cortex (mPFC); (2) a significant relationship between amygdala-mPFC covariance and levels of aggression; and (3) mediation effects of amygdala-mPFC covariance on the relationship between testosterone and aggression. These effects were independent of sex, age, pubertal stage, estradiol levels and anxious-depressed symptoms. These findings are consistent with prior evidence that testosterone targets the neural circuits regulating affect and impulse regulation, and show, for the first time in humans, how androgen-dependent organizational effects may regulate a very specific, aggression-related structural brain phenotype from childhood to young adulthood. PMID:26431805

A testosterone-related structural brain phenotype predicts aggressive behavior from childhood to adulthood.

PubMed

Nguyen, Tuong-Vi; McCracken, James T; Albaugh, Matthew D; Botteron, Kelly N; Hudziak, James J; Ducharme, Simon

2016-01-01

Structural covariance, the examination of anatomic correlations between brain regions, has emerged recently as a valid and useful measure of developmental brain changes. Yet the exact biological processes leading to changes in covariance, and the relation between such covariance and behavior, remain largely unexplored. The steroid hormone testosterone represents a compelling mechanism through which this structural covariance may be developmentally regulated in humans. Although steroid hormone receptors can be found throughout the central nervous system, the amygdala represents a key target for testosterone-specific effects, given its high density of androgen receptors. In addition, testosterone has been found to impact cortical thickness (CTh) across the whole brain, suggesting that it may also regulate the structural relationship, or covariance, between the amygdala and CTh. Here, we examined testosterone-related covariance between amygdala volumes and whole-brain CTh, as well as its relationship to aggression levels, in a longitudinal sample of children, adolescents, and young adults 6-22 years old. We found: (1) testosterone-specific modulation of the covariance between the amygdala and medial prefrontal cortex (mPFC); (2) a significant relationship between amygdala-mPFC covariance and levels of aggression; and (3) mediation effects of amygdala-mPFC covariance on the relationship between testosterone and aggression. These effects were independent of sex, age, pubertal stage, estradiol levels and anxious-depressed symptoms. These findings are consistent with prior evidence that testosterone targets the neural circuits regulating affect and impulse regulation, and show, for the first time in humans, how androgen-dependent organizational effects may regulate a very specific, aggression-related structural brain phenotype from childhood to young adulthood. Copyright © 2015 Elsevier Ltd. All rights reserved.

Diffuse optical systems and methods to image physiological changes of the brain in response to focal TBI (Conference Presentation)

NASA Astrophysics Data System (ADS)

Abookasis, David; Volkov, Boris; Kofman, Itamar

2017-02-01

During the last four decades, various optical techniques have been proposed and intensively used for biomedical diagnosis and therapy both in animal model and in human. These techniques have several advantages over the traditional existing methods: simplicity in structure, low-cost, easy to handle, portable, can be used repeatedly over time near the patient bedside for continues monitoring, and offer high spatiotemporal resolution. In this work, we demonstrate the use of two optical imaging modalities namely, spatially modulated illumination and dual-wavelength laser speckle to image the changes in brain tissue chromophores, morphology, and metabolic before, during, and after the onset of focal traumatic brain injury in intact mouse head (n=15). Injury was applied in anesthetized mice by weight-drop apparatus using 50gram metal rod striking the mouse's head. Following data analysis, we show a series of hemodynamic and structural changes over time including higher deoxyhemoglobin, reduction in oxygen saturation and blood flow, cell swelling, etc., in comparison with baseline measurements. In addition, to validate the monitoring of cerebral blood flow by the imaging system, measurements with laser Doppler flowmetry were also performed (n=5), which confirmed reduction in blood flow following injury. Overall, our result demonstrates the capability of diffuse optical modalities to monitor and map brain tissue optical and physiological properties following brain trauma.

Poor Brain Growth in Extremely Preterm Neonates Long Before the Onset of Autism Spectrum Disorder Symptoms.

PubMed

Padilla, Nelly; Eklöf, Eva; Mårtensson, Gustaf E; Bölte, Sven; Lagercrantz, Hugo; Ådén, Ulrika

2017-02-01

Preterm infants face an increased risk of autism spectrum disorder (ASD). The relationship between autism during childhood and early brain development remains unexplored. We studied 84 preterm children born at <27 weeks of gestation, who underwent neonatal magnetic resonance imaging (MRI) at term and were screened for ASD at 6.5 years. Full-scale intelligence quotient was measured and neonatal morbidities were recorded. Structural brain morphometric studies were performed in 33 infants with high-quality MRI and no evidence of focal brain lesions. Twenty-three (27.4%) of the children tested ASD positive and 61 (72.6%) tested ASD negative. The ASD-positive group had a significantly higher frequency of neonatal complications than the ASD-negative group. In the subgroup of 33 children, the ASD infants had reduced volumes in the temporal, occipital, insular, and limbic regions and in the brain areas involved in social/behavior and salience integration. This study shows that the neonatal MRI scans of extremely preterm children, subsequently diagnosed with ASD at 6.5 years, showed brain structural alterations, localized in the regions that play a key role in the core features of autism. Early detection of these structural alterations may allow the early identification and intervention of children at risk of ASD. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Early life stress-induced alterations in rat brain structures measured with high resolution MRI.

PubMed

Sarabdjitsingh, R Angela; Loi, Manila; Joëls, Marian; Dijkhuizen, Rick M; van der Toorn, Annette

2017-01-01

Adverse experiences early in life impair cognitive function both in rodents and humans. In humans this increases the vulnerability to develop mental illnesses while in the rodent brain early life stress (ELS) abnormalities are associated with changes in synaptic plasticity, excitability and microstructure. Detailed information on the effects of ELS on rodent brain structural integrity at large and connectivity within the brain is currently lacking; this information is highly relevant for understanding the mechanism by which early life stress predisposes to mental illnesses. Here, we exposed rats to 24 hours of maternal deprivation (MD) at postnatal day 3, a paradigm known to increase corticosterone levels and thereby activate glucocorticoid receptors in the brain. Using structural magnetic resonance imaging we examined: i) volumetric changes and white/grey matter properties of the whole cerebrum and of specific brain areas; and ii) whether potential alterations could be normalized by blocking glucocorticoid receptors with mifepristone during the critical developmental window of early adolescence, i.e. between postnatal days 26 and 28. The results show that MD caused a volumetric reduction of the prefrontal cortex, particularly the ventromedial part, and the orbitofrontal cortex. Within the whole cerebrum, white (relative to grey) matter volume was decreased and region-specifically in prefrontal cortex and dorsomedial striatum following MD. A trend was found for the hippocampus. Grey matter fractions were not affected. Treatment with mifepristone did not normalize these changes. This study indicates that early life stress in rodents has long lasting consequences for the volume and structural integrity of the brain. However, changes were relatively modest and-unlike behavior- not mitigated by blockade of glucocorticoid receptors during a critical developmental period.

Diffusion tensor imaging reveals adolescent binge ethanol-induced brain structural integrity alterations in adult rats that correlate with behavioral dysfunction.

PubMed

Vetreno, Ryan P; Yaxley, Richard; Paniagua, Beatriz; Crews, Fulton T

2016-07-01

Adolescence is characterized by considerable brain maturation that coincides with the development of adult behavior. Binge drinking is common during adolescence and can have deleterious effects on brain maturation because of the heightened neuroplasticity of the adolescent brain. Using an animal model of adolescent intermittent ethanol [AIE; 5.0 g/kg, intragastric, 20 percent EtOH w/v; 2 days on/2 days off from postnatal day (P)25 to P55], we assessed the adult brain structural volumes and integrity on P80 and P220 using diffusion tensor imaging (DTI). While we did not observe a long-term effect of AIE on structural volumes, AIE did reduce axial diffusivity (AD) in the cerebellum, hippocampus and neocortex. Radial diffusivity (RD) was reduced in the hippocampus and neocortex of AIE-treated animals. Prior AIE treatment did not affect fractional anisotropy (FA), but did lead to long-term reductions of mean diffusivity (MD) in both the cerebellum and corpus callosum. AIE resulted in increased anxiety-like behavior and diminished object recognition memory, the latter of which was positively correlated with DTI measures. Across aging, whole brain volumes increased, as did volumes of the corpus callosum and neocortex. This was accompanied by age-associated AD reductions in the cerebellum and neocortex as well as RD and MD reductions in the cerebellum. Further, we found that FA increased in both the cerebellum and corpus callosum as rats aged from P80 to P220. Thus, both age and AIE treatment caused long-term changes to brain structural integrity that could contribute to cognitive dysfunction. © 2015 Society for the Study of Addiction.

Longitudinal regression analysis of spatial-temporal growth patterns of geometrical diffusion measures in early postnatal brain development with diffusion tensor imaging

PubMed Central

Chen, Yasheng; An, Hongyu; Zhu, Hongtu; Jewells, Valerie; Armao, Diane; Shen, Dinggang; Gilmore, John H.; Lin, Weili

2011-01-01

Although diffusion tensor imaging (DTI) has provided substantial insights into early brain development, most DTI studies based on fractional anisotropy (FA) and mean diffusivity (MD) may not capitalize on the information derived from the three principal diffusivities (e.g. eigenvalues). In this study, we explored the spatial and temporal evolution of white matter structures during early brain development using two geometrical diffusion measures, namely, linear (Cl) and planar (Cp) diffusion anisotropies, from 71 longitudinal datasets acquired from 29 healthy, full-term pediatric subjects. The growth trajectories were estimated with generalized estimating equations (GEE) using linear fitting with logarithm of age (days). The presence of the white matter structures in Cl and Cp was observed in neonates, suggesting that both the cylindrical and fanning or crossing structures in various white matter regions may already have been formed at birth. Moreover, we found that both Cl and Cp evolved in a temporally nonlinear and spatially inhomogeneous manner. The growth velocities of Cl in central white matter were significantly higher when compared to peripheral, or more laterally located, white matter: central growth velocity Cl = 0.0465±0.0273/log(days), versus peripheral growth velocity Cl=0.0198±0.0127/log(days), p<10−6. In contrast, the growth velocities of Cp in central white matter were significantly lower than that in peripheral white matter: central growth velocity Cp= 0.0014±0.0058/log(days), versus peripheral growth velocity Cp = 0.0289±0.0101/log(days), p<10−6. Depending on the underlying white matter site which is analyzed, our findings suggest that ongoing physiologic and microstructural changes in the developing brain may exert different effects on the temporal evolution of these two geometrical diffusion measures. Thus, future studies utilizing DTI with correlative histological analysis in the study of early brain development are warranted. PMID:21784163

Brain structural connectivity and context-dependent extinction memory.

PubMed

Hermann, Andrea; Stark, Rudolf; Blecker, Carlo R; Milad, Mohammed R; Merz, Christian J

2017-08-01

Extinction of conditioned fear represents an important mechanism in the treatment of anxiety disorders. Return of fear after successful extinction or exposure therapy in patients with anxiety disorders might be linked to poor temporal or contextual generalization of extinction due to individual differences in brain structural connectivity. The goal of this magnetic resonance imaging study was therefore to investigate the association of context-dependent extinction recall with brain structural connectivity. Diffusion-tensor imaging was used to determine the fractional anisotropy as a measure of white matter structural integrity of fiber tracts connecting central brain regions of the fear and extinction circuit (uncinate fasciculus, cingulum). Forty-five healthy men participated in a two-day fear conditioning experiment with fear acquisition in context A and extinction learning in context B on the first day. Extinction recall in the extinction context as well as renewal in the acquisition context and a novel context C took place one day later. Renewal of conditioned fear (skin conductance responses) in the acquisition context was associated with higher structural integrity of the hippocampal part of the cingulum. Enhanced structural integrity of the cingulum might be related to stronger hippocampal modulation of the dorsal anterior cingulate cortex, a region important for modulating conditioned fear output by excitatory projections to the amygdala. This finding underpins the crucial role of individual differences in the structural integrity of relevant fiber tracts for context-dependent extinction recall and return of fear after exposure therapy in anxiety disorders. © 2017 Wiley Periodicals, Inc.

Brain metabolism in patients with vegetative state after post-resuscitated hypoxic-ischemic brain injury: statistical parametric mapping analysis of F-18 fluorodeoxyglucose positron emission tomography.

PubMed

Kim, Yong Wook; Kim, Hyoung Seop; An, Young-sil

2013-03-01

Hypoxic-ischemic brain injury (HIBI) after cardiopulmonary resuscitation is one of the most devastating neurological conditions that causing the impaired consciousness. However, there were few studies investigated the changes of brain metabolism in patients with vegetative state (VS) after post-resuscitated HIBI. This study aimed to analyze the change of overall brain metabolism and elucidated the brain area correlated with the level of consciousness (LOC) in patients with VS after post-resuscitated HIBI. We consecutively enrolled 17 patients with VS after HIBI, who experienced cardiopulmonary resuscitation. Overall brain metabolism was measured by F-18 fluorodeoxyglucose positron emission tomography (F-18 FDG PET) and we compared regional brain metabolic patterns from 17 patients with those from 15 normal controls using voxel-by-voxel based statistical parametric mapping analysis. Additionally, we correlated the LOC measured by the JFK-coma recovery scale-revised of each patient with brain metabolism by covariance analysis. Compared with normal controls, the patients with VS after post-resuscitated HIBI revealed significantly decreased brain metabolism in bilateral precuneus, bilateral posterior cingulate gyrus, bilateral middle frontal gyri, bilateral superior parietal gyri, bilateral middle occipital gyri, bilateral precentral gyri (PFEW correctecd < 0.0001), and increased brain metabolism in bilateral insula, bilateral cerebella, and the brainstem (PFEW correctecd < 0.0001). In covariance analysis, the LOC was significantly correlated with brain metabolism in bilateral fusiform and superior temporal gyri (Puncorrected < 0.005). Our study demonstrated that the precuneus, the posterior cingulate area and the frontoparietal cortex, which is a component of neural correlate for consciousness, may be relevant structure for impaired consciousness in patient with VS after post-resuscitated HIBI. In post-resuscitated HIBI, measurement of brain metabolism using PET images may be helpful for investigating the brain function that cannot be obtained by morphological imaging and can be used to assess the brain area responsible for consciousness.

Socioeconomic status moderates age-related differences in the brain's functional network organization and anatomy across the adult lifespan.

PubMed

Chan, Micaela Y; Na, Jinkyung; Agres, Phillip F; Savalia, Neil K; Park, Denise C; Wig, Gagan S

2018-05-14

An individual's environmental surroundings interact with the development and maturation of their brain. An important aspect of an individual's environment is his or her socioeconomic status (SES), which estimates access to material resources and social prestige. Previous characterizations of the relation between SES and the brain have primarily focused on earlier or later epochs of the lifespan (i.e., childhood, older age). We broaden this work to examine the relationship between SES and the brain across a wide range of human adulthood (20-89 years), including individuals from the less studied middle-age range. SES, defined by education attainment and occupational socioeconomic characteristics, moderates previously reported age-related differences in the brain's functional network organization and whole-brain cortical structure. Across middle age (35-64 years), lower SES is associated with reduced resting-state system segregation (a measure of effective functional network organization). A similar but less robust relationship exists between SES and age with respect to brain anatomy: Lower SES is associated with reduced cortical gray matter thickness in middle age. Conversely, younger and older adulthood do not exhibit consistent SES-related difference in the brain measures. The SES-brain relationships persist after controlling for measures of physical and mental health, cognitive ability, and participant demographics. Critically, an individual's childhood SES cannot account for the relationship between their current SES and functional network organization. These findings provide evidence that SES relates to the brain's functional network organization and anatomy across adult middle age, and that higher SES may be a protective factor against age-related brain decline. Copyright © 2018 the Author(s). Published by PNAS.

Observed Measures of Negative Parenting Predict Brain Development during Adolescence.

PubMed

Whittle, Sarah; Vijayakumar, Nandita; Dennison, Meg; Schwartz, Orli; Simmons, Julian G; Sheeber, Lisa; Allen, Nicholas B

2016-01-01

Limited attention has been directed toward the influence of non-abusive parenting behaviour on brain structure in adolescents. It has been suggested that environmental influences during this period are likely to impact the way that the brain develops over time. The aim of this study was to investigate the association between aggressive and positive parenting behaviors on brain development from early to late adolescence, and in turn, psychological and academic functioning during late adolescence, using a multi-wave longitudinal design. Three hundred and sixty seven magnetic resonance imaging (MRI) scans were obtained over three time points from 166 adolescents (11-20 years). At the first time point, observed measures of maternal aggressive and positive behaviors were obtained. At the final time point, measures of psychological and academic functioning were obtained. Results indicated that a higher frequency of maternal aggressive behavior was associated with alterations in the development of right superior frontal and lateral parietal cortical thickness, and of nucleus accumbens volume, in males. Development of the superior frontal cortex in males mediated the relationship between maternal aggressive behaviour and measures of late adolescent functioning. We suggest that our results support an association between negative parenting and adolescent functioning, which may be mediated by immature or delayed brain maturation.

Observed Measures of Negative Parenting Predict Brain Development during Adolescence

PubMed Central

Whittle, Sarah; Vijayakumar, Nandita; Dennison, Meg; Schwartz, Orli; Simmons, Julian G.; Sheeber, Lisa; Allen, Nicholas B.

2016-01-01

Limited attention has been directed toward the influence of non-abusive parenting behaviour on brain structure in adolescents. It has been suggested that environmental influences during this period are likely to impact the way that the brain develops over time. The aim of this study was to investigate the association between aggressive and positive parenting behaviors on brain development from early to late adolescence, and in turn, psychological and academic functioning during late adolescence, using a multi-wave longitudinal design. Three hundred and sixty seven magnetic resonance imaging (MRI) scans were obtained over three time points from 166 adolescents (11–20 years). At the first time point, observed measures of maternal aggressive and positive behaviors were obtained. At the final time point, measures of psychological and academic functioning were obtained. Results indicated that a higher frequency of maternal aggressive behavior was associated with alterations in the development of right superior frontal and lateral parietal cortical thickness, and of nucleus accumbens volume, in males. Development of the superior frontal cortex in males mediated the relationship between maternal aggressive behaviour and measures of late adolescent functioning. We suggest that our results support an association between negative parenting and adolescent functioning, which may be mediated by immature or delayed brain maturation. PMID:26824348

Computerised cognitive training in acquired brain injury: A systematic review of outcomes using the International Classification of Functioning (ICF).

PubMed

Sigmundsdottir, Linda; Longley, Wendy A; Tate, Robyn L

2016-10-01

Computerised cognitive training (CCT) is an increasingly popular intervention for people experiencing cognitive symptoms. This systematic review evaluated the evidence for CCT in adults with acquired brain injury (ABI), focusing on how outcome measures used reflect efficacy across components of the International Classification of Functioning, Disability and Health. Database searches were conducted of studies investigating CCT to treat cognitive symptoms in adult ABI. Scientific quality was rated using the PEDro-P and RoBiNT Scales. Ninety-six studies met the criteria. Most studies examined outcomes using measures of mental functions (93/96, 97%); fewer studies included measures of activities/participation (41/96, 43%) or body structures (8/96, 8%). Only 14 studies (15%) provided Level 1 evidence (randomised controlled trials with a PEDro-P score ≥ 6/10), with these studies suggesting strong evidence for CCT improving processing speed in multiple sclerosis (MS) and moderate evidence for improving memory in MS and brain tumour populations. There is a large body of research examining the efficacy of CCT, but relatively few Level 1 studies and evidence is largely limited to body function outcomes. The routine use of outcome measures of activities/participation would provide more meaningful evidence for the efficacy of CCT. The use of body structure outcome measures (e.g., neuroimaging) is a newly emerging area, with potential to increase understanding of mechanisms of action for CCT.

Studying neuroanatomy using MRI.

PubMed

Lerch, Jason P; van der Kouwe, André J W; Raznahan, Armin; Paus, Tomáš; Johansen-Berg, Heidi; Miller, Karla L; Smith, Stephen M; Fischl, Bruce; Sotiropoulos, Stamatios N

2017-02-23

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging and disease. Developments in MRI acquisition, image processing and data modeling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and for inferring microstructural properties; we also describe key artifacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, although methods need to improve and caution is required in interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works.

Predicting the conversion of mild cognitive impairment to Alzheimer's disease based on the volumetric measurements of the selected brain structures in magnetic resonance imaging.

PubMed

Nesteruk, Marta; Nesteruk, Tomasz; Styczyńska, Maria; Barczak, Anna; Mandecka, Monika; Walecki, Jerzy; Barcikowska-Kotowicz, Maria

2015-01-01

Mild cognitive impairment (MCI) is defined as abnormal cognitive state, but does not meet the criteria for the diagnosis of dementia. According to the new guidelines Alzheimer's disease (AD) involves not only dementia's phase but also predementia phase which is asymptomatic and pathological process in the brain is already present. For this reason it is very important to determine the suitability of markers which should be positive before onset of the first symptoms. One of these biomarkers is a structural magnetic resonance imaging with hippocampal volumetric assessment. The aim of this study was to investigate the usefulness of structural brain magnetic resonance imaging with volumetric assessment of the hippocampus and entorhinal cortex, posterior cingulate gyrus, parahippocampal gyrus, temporal gyri: superior, medial and inferior, to predict the conversion of MCI to AD. Magnetic resonance imaging of brain was performed at the baseline visit in 101 patients diagnosed with MCI. Clinic follow-ups were scheduled after 6.12 and 24 months. Amongst 101 patients with MCI, 17 (16.8%) converted into AD within two years of observation. All measured volumes were lower in converters than non-converters. Discriminant analysis was conducted and sensitivity for MCI conversion to AD was 64.7%, specificity 96.4%. 91% of patients were correctly classified (converter or non-converter). Volumetric measurements may help clinicians to predict MCI conversion to AD but due to low sensitivity it cannot be use separately. The study group requires further observation. Copyright © 2015 Polish Neurological Society. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Reduced variance in monozygous twins for multiple MR parameters: implications for disease studies and the genetic basis of brain structure.

PubMed

Pell, Gaby S; Briellmann, Regula S; Lawrence, Kate M; Glencross, Deborah; Wellard, R Mark; Berkovic, Samuel F; Jackson, Graeme D

2010-01-15

Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.

The impact of glucose disorders on cognition and brain volumes in the elderly: the Sydney Memory and Ageing Study.

PubMed

Samaras, Katherine; Lutgers, Helen L; Kochan, Nicole A; Crawford, John D; Campbell, Lesley V; Wen, Wei; Slavin, Melissa J; Baune, Bernard T; Lipnicki, Darren M; Brodaty, Henry; Trollor, Julian N; Sachdev, Perminder S

2014-04-01

Type 2 diabetes predicts accelerated cognitive decline and brain atrophy. We hypothesized that impaired fasting glucose (IFG) and incident glucose disorders have detrimental effects on global cognition and brain volume. We further hypothesized that metabolic and inflammatory derangements accompanying hyperglycaemia contribute to change in brain structure and function. This was a longitudinal study of a community-dwelling elderly cohort with neuropsychological testing (n = 880) and brain volumes by magnetic resonance imaging (n = 312) measured at baseline and 2 years. Primary outcomes were global cognition and total brain volume. Secondary outcomes were cognitive domains (processing speed, memory, language, visuospatial and executive function) and brain volumes (hippocampal, parahippocampal, precuneus and frontal lobe). Participants were categorised as normal, impaired fasting glucose at both assessments (stable IFG), baseline diabetes or incident glucose disorders (incident diabetes or IFG at 2 years). Measures included inflammatory cytokines and oxidative metabolites. Covariates were age, sex, education, non-English speaking background, smoking, blood pressure, lipid-lowering or antihypertensive medications, mood score, apolipoprotein E genotype and baseline cognition or brain volume. Participants with incident glucose disorders had greater decline in global cognition and visuospatial function compared to normal, similar to that observed in baseline diabetes. Homocysteine was independently associated with the observed effect of diabetes on executive function. Apolipoprotein E genotype did not influence the observed effects of diabetes on cognition. Incident glucose disorders and diabetes were also associated with greater 2-year decline in total brain volume, compared to normal (40.0 ± 4.2 vs. 46.7 ± 5.7 mm(3) vs. 18.1 ± 6.2, respectively, p < 0.005). Stable IFG did not show greater decline in global cognition or brain volumes compared to normal. Incident glucose disorders, like diabetes, are associated with accelerated decline in global cognition and brain volumes in non-demented elderly, whereas stable IFG is not. Preventing deterioration in glucose metabolism in the elderly may help preserve brain structure and function.

Effects of Long-Term Treatment on Brain Volume in Patients with Obstructive Sleep Apnea Syndrome

PubMed Central

Kim, Hosung; Joo, Eun Yeon; Suh, Sooyeon; Kim, Jae-Hun; Kim, Sung Tae; Hong, Seung Bong

2015-01-01

We assessed structural brain damage in obstructive sleep apnea syndrome (OSA) patients (21 males) and the effects of long-term continuous positive airway pressure (CPAP) treatment (18.2 ± 12.4 months; 8-44 months) on brain structures and investigated the relationship between severity of OSA and effects of treatment. Using deformation-based morphometry to measure local volume changes, we identified widespread neocortical and cerebellar atrophy in untreated patients compared to controls (59 males; Cohen's D = 0.6; FDR < 0.05). Analysis of longitudinally scanned magnetic resonance imaging (MRI) scans both before and after treatment showed increased brain volume following treatment (FDR < 0.05). Volume increase was correlated with longer treatment in the cortical areas that largely overlapped with the initial atrophy. The areas overlying the hippocampal dentate gyrus and the cerebellar dentate nucleus displayed a volume increase after treatment. Patients with very severe OSA (AHI > 64) presented with prefrontal atrophy and displayed an additional volume increase in this area following treatment. Higher impairment of working memory in patients prior to treatment correlated with prefrontal volume increase after treatment. The large overlap between the initial brain damage and the extent of recovery after treatment suggests partial recovery of non-permanent structural damage. Volume increases in the dentate gyrus and the dentate nucleus possibly likely indicate compensatory neurogenesis in response to diminishing oxidative stress. Such changes in other brain structures may explain gliosis, dendritic volume increase, or inflammation. This study provides neuroimaging evidence that revealed the positive effects of long-term CPAP treatment in patients with OSA. PMID:26503297

The Effects of Long Duration Head Down Tilt Bed Rest on Neurocognitive Performance: The Effects of Exercise Interventions

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Erdeniz. B.; Kofman, I. S.; DeDios, Y. E.; Szecsy, D. L.; Riascos-Castaneda, R. F.; Wood, S. J.; Bloomberg, J. J.

2014-01-01

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission and following 70 days exposure to a spaceflight analog, head down tilt bedrest. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post intervention (spaceflight, bedrest). Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that will be conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. Our ongoing bed rest participants are also engaging in exercise studies directed by Dr. Lori Ploutz Snyder. In this presentation, I will briefly highlight the existing literature linking exercise and fitness to brain and behavioral functions. I will also overview the metrics from my study that could be investigated in relation to the exercise and control subgroups.

TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE.

PubMed

Prasad, Gautam; Nir, Talia M; Toga, Arthur W; Thompson, Paul M

2013-04-01

Brain connectivity declines in Alzheimer's disease (AD), both functionally and structurally. Connectivity maps and networks derived from diffusion-based tractography offer new ways to track disease progression and to understand how AD affects the brain. Here we set out to identify (1) which fiber network measures show greatest differences between AD patients and controls, and (2) how these effects depend on the density of fibers extracted by the tractography algorithm. We computed brain networks from diffusion-weighted images (DWI) of the brain, in 110 subjects (28 normal elderly, 56 with early and 11 with late mild cognitive impairment, and 15 with AD). We derived connectivity matrices and network topology measures, for each subject, from whole-brain tractography and cortical parcellations. We used an ODF lookup table to speed up fiber extraction, and to exploit the full information in the orientation distribution function (ODF). This made it feasible to compute high density connectivity maps. We used accelerated tractography to compute a large number of fibers to understand what effect fiber density has on network measures and in distinguishing different disease groups in our data. We focused on global efficiency, transitivity, path length, mean degree, density, modularity, small world, and assortativity measures computed from weighted and binary undirected connectivity matrices. Of all these measures, the mean nodal degree best distinguished diagnostic groups. High-density fiber matrices were most helpful for picking up the more subtle clinical differences, e.g. between mild cognitively impaired (MCI) and normals, or for distinguishing subtypes of MCI (early versus late). Care is needed in clinical analyses of brain connectivity, as the density of extracted fibers may affect how well a network measure can pick up differences between patients and controls.

Prenatal Exposure of Guinea Pigs to the Organophosphorus Pesticide Chlorpyrifos Disrupts the Structural and Functional Integrity of the Brain

PubMed Central

Mullins, Roger J.; Xu, Su; Pereira, Edna F.R.; Pescrille, Joseph D.; Todd, Spencer W.; Mamczarz, Jacek; Albuquerque, Edson X.; Gullapalli, Rao P.

2015-01-01

This study was designed to test the hypothesis that prenatal exposure of guinea pigs to the organophosphorus (OP) pesticide chlorpyrifos (CPF) disrupts the structural and functional integrity of the brain. Pregnant guinea pigs were injected with chlorpyrifos (20 mg/kg, s.c.) or vehicle (peanut oil) once per day for ten consecutive days, starting approximately on the 50th day of gestation. Cognitive behavior of female offspring was examined starting at 40–45 post-natal days (PND) using the Morris Water Maze (MWM), and brain structural integrity was analyzed at PND 70 using magnetic resonance imaging (MRI) methods, including T2-weighted anatomical scans and Diffusion Kurtosis Imaging (DKI). The offspring of exposed mothers had significantly decreased body weight and brain volume, particularly in the frontal regions of the brain including the striatum. Furthermore, the offspring demonstrated significant spatial learning deficits in MWM recall compared to the vehicle group. Diffusion measures revealed reduced white matter integrity within the striatum and amygdala that correlated with spatial learning performance. These findings reveal the lasting effect of pre-natal exposure to CPF as well as the danger of mother to child transmission of CPF in the environment. PMID:25704171

Creative females have larger white matter structures: Evidence from a large sample study.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Makoto Miyauchi, Carlos; Shinada, Takamitsu; Sakaki, Kohei; Sassa, Yuko; Nozawa, Takayuki; Ikeda, Shigeyuki; Yokota, Susumu; Daniele, Magistro; Kawashima, Ryuta

2017-01-01

The importance of brain connectivity for creativity has been theoretically suggested and empirically demonstrated. Studies have shown sex differences in creativity measured by divergent thinking (CMDT) as well as sex differences in the structural correlates of CMDT. However, the relationships between regional white matter volume (rWMV) and CMDT and associated sex differences have never been directly investigated. In addition, structural studies have shown poor replicability and inaccuracy of multiple comparisons over the whole brain. To address these issues, we used the data from a large sample of healthy young adults (776 males and 560 females; mean age: 20.8 years, SD = 0.8). We investigated the relationship between CMDT and WMV using the newest version of voxel-based morphometry (VBM). We corrected for multiple comparisons over whole brain using the permutation-based method, which is known to be quite accurate and robust. Significant positive correlations between rWMV and CMDT scores were observed in widespread areas below the neocortex specifically in females. These associations with CMDT were not observed in analyses of fractional anisotropy using diffusion tensor imaging. Using rigorous methods, our findings further supported the importance of brain connectivity for creativity as well as its female-specific association. Hum Brain Mapp 38:414-430, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

In vivo correlation between axon diameter and conduction velocity in the human brain.

PubMed

Horowitz, Assaf; Barazany, Daniel; Tavor, Ido; Bernstein, Moran; Yovel, Galit; Assaf, Yaniv

2015-01-01

The understanding of the relationship between structure and function has always characterized biology in general and neurobiology in particular. One such fundamental relationship is that between axon diameter and the axon's conduction velocity (ACV). Measurement of these neuronal properties, however, requires invasive procedures that preclude direct elucidation of this relationship in vivo. Here we demonstrate that diffusion-based MRI is sensitive to the fine microstructural elements of brain wiring and can be used to quantify axon diameter in vivo. Moreover, we demonstrate the in vivo correlation between the diameter of an axon and its conduction velocity in the human brain. Using AxCaliber, a novel magnetic resonance imaging technique that enables us to estimate in vivo axon diameter distribution (ADD) and by measuring the interhemispheric transfer time (IHTT) by electroencephalography, we found significant linear correlation, across a cohort of subjects, between brain microstructure morphology (ADD) and its physiology (ACV) in the tactile and visual sensory domains. The ability to make a quantitative assessment of a fundamental physiological property in the human brain from in vivo measurements of ADD may shed new light on neurological processes occurring in neuroplasticity as well as in neurological disorders and neurodegenerative diseases.

Trail making test performance in youth varies as a function of anatomical coupling between the prefrontal cortex and distributed cortical regions

PubMed Central

Lee, Nancy Raitano; Wallace, Gregory L.; Raznahan, Armin; Clasen, Liv S.; Giedd, Jay N.

2014-01-01

While researchers have gained a richer understanding of the neural correlates of executive function in adulthood, much less is known about how these abilities are represented in the developing brain and what structural brain networks underlie them. Thus, the current study examined how individual differences in executive function, as measured by the Trail Making Test (TMT), relate to structural covariance in the pediatric brain. The sample included 146 unrelated, typically developing youth (80 females), ages 9–14 years, who completed a structural MRI scan of the brain and the Halstead-Reitan TMT (intermediate form). TMT scores used to index executive function included those that evaluated set-shifting ability: Trails B time (number-letter sequencing) and the difference in time between Trails B and A (number sequencing only). Anatomical coupling was measured by examining correlations between mean cortical thickness (MCT) across the entire cortical ribbon and individual vertex thickness measured at ~81,000 vertices. To examine how TMT scores related to anatomical coupling strength, linear regression was utilized and the interaction between age-normed TMT scores and both age and sex-normed MCT was used to predict vertex thickness. Results revealed that stronger Trails B scores were associated with greater anatomical coupling between a large swath of prefrontal cortex and the rest of cortex. For the difference between Trails B and A, a network of regions in the frontal, temporal, and parietal lobes was found to be more tightly coupled with the rest of cortex in stronger performers. This study is the first to highlight the importance of structural covariance in in the prediction of individual differences in executive function skills in youth. Thus, it adds to the growing literature on the neural correlates of childhood executive functions and identifies neuroanatomic coupling as a biological substrate that may contribute to executive function and dysfunction in childhood. PMID:25071613

Verbal and non-verbal intelligence changes in the teenage brain.

PubMed

Ramsden, Sue; Richardson, Fiona M; Josse, Goulven; Thomas, Michael S C; Ellis, Caroline; Shakeshaft, Clare; Seghier, Mohamed L; Price, Cathy J

2011-10-19

Intelligence quotient (IQ) is a standardized measure of human intellectual capacity that takes into account a wide range of cognitive skills. IQ is generally considered to be stable across the lifespan, with scores at one time point used to predict educational achievement and employment prospects in later years. Neuroimaging allows us to test whether unexpected longitudinal fluctuations in measured IQ are related to brain development. Here we show that verbal and non-verbal IQ can rise or fall in the teenage years, with these changes in performance validated by their close correlation with changes in local brain structure. A combination of structural and functional imaging showed that verbal IQ changed with grey matter in a region that was activated by speech, whereas non-verbal IQ changed with grey matter in a region that was activated by finger movements. By using longitudinal assessments of the same individuals, we obviated the many sources of variation in brain structure that confound cross-sectional studies. This allowed us to dissociate neural markers for the two types of IQ and to show that general verbal and non-verbal abilities are closely linked to the sensorimotor skills involved in learning. More generally, our results emphasize the possibility that an individual's intellectual capacity relative to their peers can decrease or increase in the teenage years. This would be encouraging to those whose intellectual potential may improve, and would be a warning that early achievers may not maintain their potential.

Effects of One Year of Spaceflight on Neurocognitive Function

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Kofman, I. S.; Cassady, K.; Yuan , P.; De Dios, Y. E.; Gadd, N.; Riascos, R. F.; Wood, S. J.;

Assessing the clinical effect of residual cortical disconnection after ischemic strokes.

PubMed

Bonilha, Leonardo; Rorden, Chris; Fridriksson, Julius

2014-04-01

Studies assessing the relationship between chronic poststroke language impairment (aphasia) and ischemic brain damage usually rely on measuring the extent of brain necrosis observed on MRI. Nonetheless, clinical observation suggests that patients can exhibit deficits that are more severe than what would be expected based on lesion location and size. This phenomenon is commonly explained as being the result of cortical disconnection. To understand whether disconnection contributes to clinical symptoms, we assessed the relationship between language impairments and structural brain connectivity (the connectome) in patients with chronic aphasia after a stroke. Thirty-nine patients with chronic aphasia underwent language assessment and MRI scanning. Relying on MRI data, we reconstructed the individual connectome from T1-weighted and diffusion tensor imaging. Deterministic fiber tractography was used to assess connectivity between each possible pair of cortical Brodmann areas. Multiple linear regression analyses were performed to evaluate the relationship between language performance and cortical necrosis and cortical disconnection. We observed that structural disconnection of Brodmann area 45 (spared by the necrotic tissue) was independently associated with naming performance, controlling for the extent of Brodmann area 45 necrosis (F=4.62; P<0.01; necrosis: β=0.43; P=0.03; disconnection β=1.21; P<0.001). We suggest that cortical disconnection, as measured by the structural connectome, is an independent predictor of naming impairment in patients with chronic aphasia. The full extent of clinically relevant brain damage after an ischemic stroke may be underappreciated by visual inspection of cortical necrosis alone.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

Evidence from a rare case study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation.

PubMed

van Hartevelt, Tim J; Cabral, Joana; Møller, Arne; FitzGerald, James J; Green, Alexander L; Aziz, Tipu Z; Deco, Gustavo; Kringelbach, Morten L

2015-01-01

It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

Imaging structural and functional brain networks in temporal lobe epilepsy

PubMed Central

Bernhardt, Boris C.; Hong, SeokJun; Bernasconi, Andrea; Bernasconi, Neda

2013-01-01

Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy. PMID:24098281

Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks

PubMed Central

Hosseini, S. M. Hadi; Kesler, Shelli R.

2013-01-01

In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures. PMID:23840672

Important considerations in lesion-symptom mapping: Illustrations from studies of word comprehension.

PubMed

Shahid, Hinna; Sebastian, Rajani; Schnur, Tatiana T; Hanayik, Taylor; Wright, Amy; Tippett, Donna C; Fridriksson, Julius; Rorden, Chris; Hillis, Argye E

2017-06-01

Lesion-symptom mapping is an important method of identifying networks of brain regions critical for functions. However, results might be influenced substantially by the imaging modality and timing of assessment. We tested the hypothesis that brain regions found to be associated with acute language deficits depend on (1) timing of behavioral measurement, (2) imaging sequences utilized to define the "lesion" (structural abnormality only or structural plus perfusion abnormality), and (3) power of the study. We studied 191 individuals with acute left hemisphere stroke with MRI and language testing to identify areas critical for spoken word comprehension. We use the data from this study to examine the potential impact of these three variables on lesion-symptom mapping. We found that only the combination of structural and perfusion imaging within 48 h of onset identified areas where more abnormal voxels was associated with more severe acute deficits, after controlling for lesion volume and multiple comparisons. The critical area identified with this methodology was the left posterior superior temporal gyrus, consistent with other methods that have identified an important role of this area in spoken word comprehension. Results have implications for interpretation of other lesion-symptom mapping studies, as well as for understanding areas critical for auditory word comprehension in the healthy brain. We propose that lesion-symptom mapping at the acute stage of stroke addresses a different sort of question about brain-behavior relationships than lesion-symptom mapping at the chronic stage, but that timing of behavioral measurement and imaging modalities should be considered in either case. Hum Brain Mapp 38:2990-3000, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Neural correlates of gait variability in people with multiple sclerosis with fall history.

PubMed

Kalron, Alon; Allali, Gilles; Achiron, Anat

2018-05-28

Investigate the association between step time variability and related brain structures in accordance with fall status in people with multiple sclerosis (PwMS). The study included 225 PwMS. A whole-brain MRI was performed by a high-resolution 3.0-Telsa MR scanner in addition to volumetric analysis based on 3D T1-weighted images using the FreeSurfer image analysis suite. Step time variability was measured by an electronic walkway. Participants were defined as "fallers" (at least two falls during the previous year) and "non-fallers". One hundred and five PwMS were defined as fallers and had a greater step time variability compared to non-fallers (5.6% (S.D.=3.4) vs. 3.4% (S.D.=1.5); p=0.001). MS fallers exhibited a reduced volume in the left caudate and both cerebellum hemispheres compared to non-fallers. By using a linear regression analysis no association was found between gait variability and related brain structures in the total cohort and non-fallers group. However, the analysis found an association between the left hippocampus and left putamen volumes with step time variability in the faller group; p=0.031, 0.048, respectively, controlling for total cranial volume, walking speed, disability, age and gender. Nevertheless, according to the hierarchical regression model, the contribution of these brain measures to predict gait variability was relatively small compared to walking speed. An association between low left hippocampal, putamen volumes and step time variability was found in PwMS with a history of falls, suggesting brain structural characteristics may be related to falls and increased gait variability in PwMS. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Trace element distribution in the rat cerebellum

NASA Astrophysics Data System (ADS)

Kwiatek, W. M.; Long, G. J.; Pounds, J. G.; Reuhl, K. R.; Hanson, A. L.; Jones, K. W.

1990-04-01

Spatial distributions and concentrations of trace elements (TE) in the brain are important because TE perform catalytic and structural functions in enzymes which regulate brain function and development. We have investigated the distributions of TE in rat cerebellum. Structures were sectioned and analyzed by the Synchrotron Radiation Induced X-ray Emission (SRIXE) method using the NSLS X-26 white-light microprobe facility. Advantages important for TE analysis of biological specimens with X-ray microscopy include short time of measurement, high brightness and flux, good spatial resolution, multielemental detection, good sensitivity, and nondestructive irradiation. Trace elements were measured in thin rat brain sections of 20 μm thickness. The analyses were performed on sample volumes as small as 0.2 nl with Minimum Detectable Limits (MDL) of 50 ppb wet weight for Fe, 100 ppb wet weight for Cu, and Zn, and 1 ppm wet weight for Pb. The distribution of TE in the molecular cell layer, granule cell layer and fiber tract of rat cerebella was investigated. Both point analyses and two-dimensional semiquantitative mapping of the TE distribution in a section were used. All analyzed elements were observed in each structure of the cerebellum except mercury which was not observed in granule cell layer or fiber tract. This approach permits an exacting correlation of the TE distribution in complex structure with the diet, toxic elements, and functional status of the animal.

Large-scale structural alteration of brain in epileptic children with SCN1A mutation.

PubMed

Lee, Yun-Jeong; Yum, Mi-Sun; Kim, Min-Jee; Shim, Woo-Hyun; Yoon, Hee Mang; Yoo, Il Han; Lee, Jiwon; Lim, Byung Chan; Kim, Ki Joong; Ko, Tae-Sung

2017-01-01

Mutations in SCN1A gene encoding the alpha 1 subunit of the voltage gated sodium channel are associated with several epilepsy syndromes including genetic epilepsy with febrile seizures plus (GEFS +) and severe myoclonic epilepsy of infancy (SMEI). However, in most patients with SCN1A mutation, brain imaging has reported normal or non-specific findings including cerebral or cerebellar atrophy. The aim of this study was to investigate differences in brain morphometry in epileptic children with SCN1A mutation compared to healthy control subjects. We obtained cortical morphology (thickness, and surface area) and brain volume (global, subcortical, and regional) measurements using FreeSurfer (version 5.3.0, https://surfer.nmr.mgh.harvard.edu) and compared measurements of children with epilepsy and SCN1A gene mutation ( n  = 21) with those of age and gender matched healthy controls ( n  = 42). Compared to the healthy control group, children with epilepsy and SCN1A gene mutation exhibited smaller total brain, total gray matter and white matter, cerebellar white matter, and subcortical volumes, as well as mean surface area and mean cortical thickness. A regional analysis revealed significantly reduced gray matter volume in the patient group in the bilateral inferior parietal, left lateral orbitofrontal, left precentral, right postcentral, right isthmus cingulate, right middle temporal area with smaller surface area and white matter volume in some of these areas. However, the regional cortical thickness was not significantly different in two groups. This study showed large-scale developmental brain changes in patients with epilepsy and SCN1A gene mutation, which may be associated with the core symptoms of the patients. Further longitudinal MRI studies with larger cohorts are required to confirm the effect of SCN1A gene mutation on structural brain development.

Neural predictors of individual differences in response to math tutoring in primary-grade school children

PubMed Central

Supekar, Kaustubh; Swigart, Anna G.; Tenison, Caitlin; Jolles, Dietsje D.; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2013-01-01

Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8–9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures. PMID:23630286

Neural predictors of individual differences in response to math tutoring in primary-grade school children.

PubMed

Supekar, Kaustubh; Swigart, Anna G; Tenison, Caitlin; Jolles, Dietsje D; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2013-05-14

Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8-9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures.

Brain Connectivity Networks and the Aesthetic Experience of Music.

PubMed

Reybrouck, Mark; Vuust, Peter; Brattico, Elvira

2018-06-12

Listening to music is above all a human experience, which becomes an aesthetic experience when an individual immerses himself/herself in the music, dedicating attention to perceptual-cognitive-affective interpretation and evaluation. The study of these processes where the individual perceives, understands, enjoys and evaluates a set of auditory stimuli has mainly been focused on the effect of music on specific brain structures, as measured with neurophysiology and neuroimaging techniques. The very recent application of network science algorithms to brain research allows an insight into the functional connectivity between brain regions. These studies in network neuroscience have identified distinct circuits that function during goal-directed tasks and resting states. We review recent neuroimaging findings which indicate that music listening is traceable in terms of network connectivity and activations of target regions in the brain, in particular between the auditory cortex, the reward brain system and brain regions active during mind wandering.

Glycosaminoglycan in cerebrum, cerebellum and brainstem of young sheep brain with particular reference to compositional and structural variations of chondroitin-dermatan sulfate and hyaluronan.

PubMed

Kilia, Virginia; Skandalis, Spyros S; Theocharis, Achilleas D; Theocharis, Dimitrios A; Karamanos, Nikos K; Papageorgakopoulou, Nickoletta

2008-09-01

Recent advances in the structural biology of chondroitin sulfate chains have suggested important biological functions in the development of the brain. Several studies have demonstrated that the composition of chondroitin sulfate chains changes with aging and normal brain maturation. In this study, we determined the concentration of all glycosaminoglycan types, i.e. chondroitin sulfate, dermatan sulfate, keratan sulfate, heparan sulfate, hyaluronan and chondroitin in cerebrum, cerebellum and brainstem of young sheep brain. In all cases, chondroitin sulfate was the predominant glycosaminoglycan type, comprising about 54-58% of total glycosaminoglycans, with hyaluronan being present also in significant amounts of about 19-28%. Of particular interest was the increased presence of the disulfated disaccharides and dermatan sulfate in cerebellum and brainstem, respectively, as well as the detectable and measurable occurrence of chondroitin in young sheep brain. Among the three brain areas, cerebrum was found to be significantly richer in chondroitin sulfate and hyaluronan, two major extracellular matrix components. These findings imply that the extracellular matrix of the cerebrum is different from those of cerebellum and brainstem, and probably this fact is related to the particular histological and functional characteristics of each anatomic area of the brain.

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.; ...

2016-05-09

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

The Behavioural Assessment of Self-Structuring (BASS): psychometric properties in a post-acute brain injury rehabilitation programme.

PubMed

Jackson, Howard F; Tunstall, Victoria; Hague, Gemma; Daniels, Leanne; Crompton, Stacey; Taplin, Kimberly

2014-01-01

Jackson et al. (this edition) argue that structure is an important component in reducing the handicaps caused by cognitive impairments following acquired brain injury and that post-acute neuropsychological brain injury rehabilitation programmes should not only endeavour to provide structure but also aim to develop self-structuring. However, at present there is no standardized device for assessing self-structuring. To provide preliminary analysis of the psychometric properties of the Behavioural Assessment of Self-Structuring (BASS) staff rating scale (a 26 item informant five point rating scale based on the degree of support client requires to achieve self-structuring item). BASS data was utilised for clients attending residential rehabilitation. Reliability (inter-rarer and intra-rater), validity (construct, concurrent and discriminate) and sensitivity to change were investigated. Initial results indicate that the BASS has reasonably good reliability, good construct validity (via principal components analysis), good discriminant validity, and good concurrent validity correlating well with a number of other outcome measures (HoNOS; NPDS, Supervision Rating Scale, MPAI, FIM and FAM). The BASS did not correlate well with the NPCNA. Finally, the BASS was shown to demonstrate sensitivity to change. Although some caution is required in drawing firm conclusions at the present time and further exploration of the psychometric properties of the BASS is required, initial results are encouraging for the use of the BASS in assessing rehabilitation progress. These findings are discussed in terms of the value of the concept of self-structuring to the rehabilitation process for individuals with neuropsychological impairments consequent on acquired brain injury.

Mindfulness training induces structural connectome changes in insula networks.

PubMed

Sharp, Paul B; Sutton, Bradley P; Paul, Erick J; Sherepa, Nikolai; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Prakash, Ruchika Shaurya; Heller, Wendy; Telzer, Eva H; Barbey, Aron K

2018-05-21

Although mindfulness meditation is known to provide a wealth of psychological benefits, the neural mechanisms involved in these effects remain to be well characterized. A central question is whether the observed benefits of mindfulness training derive from specific changes in the structural brain connectome that do not result from alternative forms of experimental intervention. Measures of whole-brain and node-level structural connectome changes induced by mindfulness training were compared with those induced by cognitive and physical fitness training within a large, multi-group intervention protocol (n = 86). Whole-brain analyses examined global graph-theoretical changes in structural network topology. A hypothesis-driven approach was taken to investigate connectivity changes within the insula, which was predicted here to mediate interoceptive awareness skills that have been shown to improve through mindfulness training. No global changes were observed in whole-brain network topology. However, node-level results confirmed a priori hypotheses, demonstrating significant increases in mean connection strength in right insula across all of its connections. Present findings suggest that mindfulness strengthens interoception, operationalized here as the mean insula connection strength within the overall connectome. This finding further elucidates the neural mechanisms of mindfulness meditation and motivates new perspectives about the unique benefits of mindfulness training compared to contemporary cognitive and physical fitness interventions.

Label-free NIR reflectance imaging as a complimentary tool for two-photon fluorescence microscopy: multimodal investigation of stroke (Conference Presentation)

NASA Astrophysics Data System (ADS)

Allegra Mascaro, Anna Letizia; Costantini, Irene; Margoni, Emilia; Iannello, Giulio; Bria, Alessandro; Sacconi, Leonardo; Pavone, Francesco S.

2016-03-01

Two-photon imaging combined with targeted fluorescent indicators is extensively used for visualizing critical features of brain functionality and structural plasticity. Back-scattered photons from the NIR laser provide complimentary information without introducing any exogenous labelling. Here, we describe a versatile approach that, by collecting the reflected NIR light, provides structural details on the myelinated axons and blood vessels in the brain, both in fixed samples and in live animals. Indeed, by combining NIR reflectance and two-photon imaging of a slice of hippocampus from Thy1-GFPm mice, we show the presence of randomly oriented axons intermingled with sparsely fluorescent neuronal processes. The back-scattered photons guide the contextualization of the fluorescence structure within brain atlas thanks to the recognition of characteristic hippocampal structures. Label-free detection of axonal elongations over the layer 2/3 of mouse cortex under a cranial window was also possible in live brain. Finally, blood flow could be measured in vivo, thus validating label free NIR reflectance as a tool for monitoring hemodynamic fluctuations. The prospective versatility of this label-free technique complimentary to two-photon fluorescence microscopy is demonstrated in a mouse model of photothrombotic stroke in which the axonal degeneration and blood flow remodeling can be investigated simultaneously.

Age-Related Effects and Sex Differences in Gray Matter Density, Volume, Mass, and Cortical Thickness from Childhood to Young Adulthood.

PubMed

Gennatas, Efstathios D; Avants, Brian B; Wolf, Daniel H; Satterthwaite, Theodore D; Ruparel, Kosha; Ciric, Rastko; Hakonarson, Hakon; Gur, Raquel E; Gur, Ruben C

2017-05-17

Developmental structural neuroimaging studies in humans have long described decreases in gray matter volume (GMV) and cortical thickness (CT) during adolescence. Gray matter density (GMD), a measure often assumed to be highly related to volume, has not been systematically investigated in development. We used T1 imaging data collected on the Philadelphia Neurodevelopmental Cohort to study age-related effects and sex differences in four regional gray matter measures in 1189 youths ranging in age from 8 to 23 years. Custom T1 segmentation and a novel high-resolution gray matter parcellation were used to extract GMD, GMV, gray matter mass (GMM; defined as GMD × GMV), and CT from 1625 brain regions. Nonlinear models revealed that each modality exhibits unique age-related effects and sex differences. While GMV and CT generally decrease with age, GMD increases and shows the strongest age-related effects, while GMM shows a slight decline overall. Females have lower GMV but higher GMD than males throughout the brain. Our findings suggest that GMD is a prime phenotype for the assessment of brain development and likely cognition and that periadolescent gray matter loss may be less pronounced than previously thought. This work highlights the need for combined quantitative histological MRI studies. SIGNIFICANCE STATEMENT This study demonstrates that different MRI-derived gray matter measures show distinct age and sex effects and should not be considered equivalent but complementary. It is shown for the first time that gray matter density increases from childhood to young adulthood, in contrast with gray matter volume and cortical thickness, and that females, who are known to have lower gray matter volume than males, have higher density throughout the brain. A custom preprocessing pipeline and a novel high-resolution parcellation were created to analyze brain scans of 1189 youths collected as part of the Philadelphia Neurodevelopmental Cohort. A clear understanding of normal structural brain development is essential for the examination of brain-behavior relationships, the study of brain disease, and, ultimately, clinical applications of neuroimaging. Copyright © 2017 the authors 0270-6474/17/375065-09$15.00/0.

Brain Structural Concomitants of Resting State Heart Rate Variability in the Young and Old – Evidence from Two Independent Samples

PubMed Central

Yoo, Hyun Joo; Thayer, Julian F; Greening, Steven; Lee, Tae-Ho; Ponzio, Allison; Min, Jungwon; Sakaki, Michiko; Nga, Lin; Mather, Mara; Koenig, Julian

2018-01-01

Previous research has shown associations between brain structure and resting state high-frequency heart rate variability (HF-HRV). Age affects both brain structure and HF-HRV. Therefore we sought to examine the relationship between brain structure and HF-HRV as a function of age. Data from two independent studies were used for the present analysis. Study 1 included 19 older adults (10 males, age range 62–78 years) and 19 younger adults (12 males, age range 19–37). Study 2 included 23 older adults (12 males; age range 55–75) and 27 younger adults (17 males; age range 18–34). The root-mean-square of successive R-R-interval differences (RMSSD) from ECG recordings was used as time-domain measure of HF-HRV. MRI scans were performed on a 3.0-T Siemens Magnetom Trio scanner. Cortical reconstruction and volumetric segmentation were performed with the Freesurfer image analysis suite, including 12 regions as regions-of-interests (ROI). Zero-order and partial correlations were used to assess the correlation of RMSSD with cortical thickness in selected ROIs. Lateral orbitofrontal cortex (OFC) cortical thickness was significantly associated with RMSSD. Further, both studies, in line with previous research, showed correlations between RMSSD and anterior cingulate cortex (ACC) cortical thickness. Meta-analysis on adjusted correlation coefficients from individual studies confirmed an association of RMSSD with the left rostral ACC and the left lateral OFC. Future longitudinal studies are necessary to trace individual trajectories in the association of HRV and brain structure across aging. PMID:28921167

Segregation of Brain Structural Networks Supports Spatio-Temporal Predictive Processing.

PubMed

Ciullo, Valentina; Vecchio, Daniela; Gili, Tommaso; Spalletta, Gianfranco; Piras, Federica

2018-01-01

The ability to generate probabilistic expectancies regarding when and where sensory stimuli will occur, is critical to derive timely and accurate inferences about updating contexts. However, the existence of specialized neural networks for inferring predictive relationships between events is still debated. Using graph theoretical analysis applied to structural connectivity data, we tested the extent of brain connectivity properties associated with spatio-temporal predictive performance across 29 healthy subjects. Participants detected visual targets appearing at one out of three locations after one out of three intervals; expectations about stimulus location (spatial condition) or onset (temporal condition) were induced by valid or invalid symbolic cues. Connectivity matrices and centrality/segregation measures, expressing the relative importance of, and the local interactions among specific cerebral areas respect to the behavior under investigation, were calculated from whole-brain tractography and cortico-subcortical parcellation. Results: Response preparedness to cued stimuli relied on different structural connectivity networks for the temporal and spatial domains. Significant covariance was observed between centrality measures of regions within a subcortical-fronto-parietal-occipital network -comprising the left putamen, the right caudate nucleus, the left frontal operculum, the right inferior parietal cortex, the right paracentral lobule and the right superior occipital cortex-, and the ability to respond after a short cue-target delay suggesting that the local connectedness of such nodes plays a central role when the source of temporal expectation is explicit. When the potential for functional segregation was tested, we found highly clustered structural connectivity across the right superior, the left middle inferior frontal gyrus and the left caudate nucleus as related to explicit temporal orienting. Conversely, when the interaction between explicit and implicit temporal orienting processes was considered at the long interval, we found that explicit processes were related to centrality measures of the bilateral inferior parietal lobule. Degree centrality of the same region in the left hemisphere covaried with behavioral measures indexing the process of attentional re-orienting. These results represent a crucial step forward the ordinary predictive processing description, as we identified the patterns of connectivity characterizing the brain organization associated with the ability to generate and update temporal expectancies in case of contextual violations.

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

Modelling information flow along the human connectome using maximum flow.

PubMed

Lyoo, Youngwook; Kim, Jieun E; Yoon, Sujung

2018-01-01

The human connectome is a complex network that transmits information between interlinked brain regions. Using graph theory, previously well-known network measures of integration between brain regions have been constructed under the key assumption that information flows strictly along the shortest paths possible between two nodes. However, it is now apparent that information does flow through non-shortest paths in many real-world networks such as cellular networks, social networks, and the internet. In the current hypothesis, we present a novel framework using the maximum flow to quantify information flow along all possible paths within the brain, so as to implement an analogy to network traffic. We hypothesize that the connection strengths of brain networks represent a limit on the amount of information that can flow through the connections per unit of time. This allows us to compute the maximum amount of information flow between two brain regions along all possible paths. Using this novel framework of maximum flow, previous network topological measures are expanded to account for information flow through non-shortest paths. The most important advantage of the current approach using maximum flow is that it can integrate the weighted connectivity data in a way that better reflects the real information flow of the brain network. The current framework and its concept regarding maximum flow provides insight on how network structure shapes information flow in contrast to graph theory, and suggests future applications such as investigating structural and functional connectomes at a neuronal level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Regional distribution of ependymins in goldfish brain measured by radioimmunoassay.

PubMed

Schmidt, R; Lapp, H

1987-01-01

Ependymins are goldfish glycoproteins known to participate in biochemical reactions of memory consolidation after an operant vestibulomotor training-task. The distribution of these proteins was analysed by means of a highly sensitive and specific radioimmunoassay. Ependymins were shown to be characteristic constituents of the nervous system, but they were virtually absent from all other tissues investigated. They were widely distributed over many brain regions and particularly enriched in mesencephalic structures. In the optic tectum, the tegmentum and in the vagal lobes ependymins constituted 3.2, 2.8 and 3.5%, respectively, of the total protein content. The highest steady-state concentration of ependymins (15.4% of protein) was measured, however, in the brain extracellular fluid including the cerebrospinal fluid. Lactate dehydrogenase activity was monitored to demonstrate that only negligible amounts of cytoplasmic constituents were released during the collection of extracellular proteins. Ependymin concentrations were lower in those brain areas which contain few cell bodies, but many glial and fibrous elements. The specific distribution of the intrinsic ependymins was compared with that of intracerebroventricularly injected [(125)I]-labeled ependymin. This exogenous marker substance was quickly incorporated and then cleared rapidly from the central nervous system with a half-life of 2 h. Our quantitative analysis of the distribution of ependymins reveals that they are specific major constituents of the goldfish nervous system. Their fast turnover, their wide distribution over many brain regions, with some enrichment in mesencephalic structures, and especially their very high concentration in the extracellular brain fluid suggest that ependymins may act on neuronal membranes from the extracellular fluid.

Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study.

PubMed

Kremen, William S; Prom-Wormley, Elizabeth; Panizzon, Matthew S; Eyler, Lisa T; Fischl, Bruce; Neale, Michael C; Franz, Carol E; Lyons, Michael J; Pacheco, Jennifer; Perry, Michele E; Stevens, Allison; Schmitt, J Eric; Grant, Michael D; Seidman, Larry J; Thermenos, Heidi W; Tsuang, Ming T; Eisen, Seth A; Dale, Anders M; Fennema-Notestine, Christine

2010-01-15

The impact of genetic and environmental factors on human brain structure is of great importance for understanding normative cognitive and brain aging as well as neuropsychiatric disorders. However, most studies of genetic and environmental influences on human brain structure have either focused on global measures or have had samples that were too small for reliable estimates. Using the classical twin design, we assessed genetic, shared environmental, and individual-specific environmental influences on individual differences in the size of 96 brain regions of interest (ROIs). Participants were 474 middle-aged male twins (202 pairs; 70 unpaired) in the Vietnam Era Twin Study of Aging (VETSA). They were 51-59 years old, and were similar to U.S. men in their age range in terms of sociodemographic and health characteristics. We measured thickness of cortical ROIs and volume of other ROIs. On average, genetic influences accounted for approximately 70% of the variance in the volume of global, subcortical, and ventricular ROIs and approximately 45% of the variance in the thickness of cortical ROIs. There was greater variability in the heritability of cortical ROIs (0.00-0.75) as compared with subcortical and ventricular ROIs (0.48-0.85). The results did not indicate lateralized heritability differences or greater genetic influences on the size of regions underlying higher cognitive functions. The findings provide key information for imaging genetic studies and other studies of brain phenotypes and endophenotypes. Longitudinal analysis will be needed to determine whether the degree of genetic and environmental influences changes for different ROIs from midlife to later life.

Structural network alterations and neurological dysfunction in cerebral amyloid angiopathy

PubMed Central

Reijmer, Yael D.; Fotiadis, Panagiotis; Martinez-Ramirez, Sergi; Salat, David H.; Schultz, Aaron; Shoamanesh, Ashkan; Ayres, Alison M.; Vashkevich, Anastasia; Rosas, Diana; Schwab, Kristin; Leemans, Alexander; Biessels, Geert-Jan; Rosand, Jonathan; Johnson, Keith A.; Viswanathan, Anand; Gurol, M. Edip

2015-01-01

Cerebral amyloid angiopathy is a common form of small-vessel disease and an important risk factor for cognitive impairment. The mechanisms linking small-vessel disease to cognitive impairment are not well understood. We hypothesized that in patients with cerebral amyloid angiopathy, multiple small spatially distributed lesions affect cognition through disruption of brain connectivity. We therefore compared the structural brain network in patients with cerebral amyloid angiopathy to healthy control subjects and examined the relationship between markers of cerebral amyloid angiopathy-related brain injury, network efficiency, and potential clinical consequences. Structural brain networks were reconstructed from diffusion-weighted magnetic resonance imaging in 38 non-demented patients with probable cerebral amyloid angiopathy (69 ± 10 years) and 29 similar aged control participants. The efficiency of the brain network was characterized using graph theory and brain amyloid deposition was quantified by Pittsburgh compound B retention on positron emission tomography imaging. Global efficiency of the brain network was reduced in patients compared to controls (0.187 ± 0.018 and 0.201 ± 0.015, respectively, P < 0.001). Network disturbances were most pronounced in the occipital, parietal, and posterior temporal lobes. Among patients, lower global network efficiency was related to higher cortical amyloid load (r = −0.52; P = 0.004), and to magnetic resonance imaging markers of small-vessel disease including increased white matter hyperintensity volume (P < 0.001), lower total brain volume (P = 0.02), and number of microbleeds (trend P = 0.06). Lower global network efficiency was also related to worse performance on tests of processing speed (r = 0.58, P < 0.001), executive functioning (r = 0.54, P = 0.001), gait velocity (r = 0.41, P = 0.02), but not memory. Correlations with cognition were independent of age, sex, education level, and other magnetic resonance imaging markers of small-vessel disease. These findings suggest that reduced structural brain network efficiency might mediate the relationship between advanced cerebral amyloid angiopathy and neurologic dysfunction and that such large-scale brain network measures may represent useful outcome markers for tracking disease progression. PMID:25367025

A pediatric brain structure atlas from T1-weighted MR images

NASA Astrophysics Data System (ADS)

Shan, Zuyao Y.; Parra, Carlos; Ji, Qing; Ogg, Robert J.; Zhang, Yong; Laningham, Fred H.; Reddick, Wilburn E.

2006-03-01

In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. We constructed a 3D triangular mesh model for each structure by triangulation of the structure's reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/BrainAtlas) can be used to plan treatment, to conduct knowledge and modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.

Deep grey matter growth predicts neurodevelopmental outcomes in very preterm children.

PubMed

Young, Julia M; Powell, Tamara L; Morgan, Benjamin R; Card, Dallas; Lee, Wayne; Smith, Mary Lou; Sled, John G; Taylor, Margot J

2015-05-01

We evaluated whether the volume and growth rate of critical brain structures measured by MRI in the first weeks of life following very preterm (<32/40 weeks) birth could predict subsequent neurodevelopmental outcomes at 4 years of age. A significant proportion of children born very prematurely have cognitive deficits, but these problems are often only detected at early school age. Structural T2-weighted magnetic resonance images were acquired in 96 very preterm neonates scanned within 2 weeks of birth and 70 of these at term-equivalent age. An automated 3D image analysis procedure was used to measure the volume of selected brain structures across all scans and time points. At 4 years of age, 53 children returned for neuropsychological assessments evaluating IQ, language and visual motor integration. Associations with maternal education and perinatal measures were also explored. Multiple regression analyses revealed that growth of the caudate and globus pallidus between preterm birth and term-equivalent age predicted visual motor integration scores after controlling for sex and gestational age. Further associations were found between caudate and putamen growth with IQ and language scores. Analyses at either preterm or term-equivalent age only found associations between normalized deep grey matter growth and visual motor integration scores at term-equivalent age. Maternal education levels were associated with measures of IQ and language, but not visual motor integration. Thalamic growth was additionally linked with perinatal measures and presence of white matter lesions. These results highlight deep grey matter growth rates as promising biomarkers of long-term outcomes following very preterm birth, and contribute to our understanding of the brain-behaviour relations in these children. Copyright © 2015 Elsevier Inc. All rights reserved.

[Estrogens and feminine brain maturation during adolescence: emergency contraceptive pill].

PubMed

López Moratalla, Natalia; Errasti Alcalá, Tania; Santiago, Esteban

2011-01-01

In the period between puberty and maturity takes place the process of brain maturation. Hormone levels induce changes in neurons and direct the architecture and structural functionality thus affecting patterns of development of different brain areas. The onset of puberty brings with it the invasion of the female brain by high levels of hormones, cyclic surges of estrogen and progesterone in addition to steroids produced in situ. Control centers of emotions (amygdala), memory and learning (hippocampus) and sexual activity (hypothalamus) are modified according to the cyclical concentrations of both hormones. Sex hormones stimulate multimodal actions, both short and longer terms, because neurons in various brain areas have different types of receptors, membrane, cytoplasmic and nuclear. The composition of emergency contraceptive pill (postcoital pill) with high hormonal content raises the urgency of a thorough knowledge about the possible effect that the lack of control of the menstrual cycle in a time of consolidation of brain maturation, can bring in structuring and development of brain circuitry. Changes in the availability of sex steroids during puberty and adolescence underlie psychiatric disorders whose prevalence is typically feminine, such as depression, anxiety disorders. It is a fundamental ethical duty to present scientific data about the influence of estrogen in young female brain maturation, both for full information to potential users, and also to induce the appropriate public health measures.

School-age effects of the newborn individualized developmental care and assessment program for preterm infants with intrauterine growth restriction: preliminary findings

PubMed Central

2013-01-01

Background The experience in the newborn intensive care nursery results in premature infants’ neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Methods Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother’s intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks’ lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Results Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore, executive function, spectral coherence and brain structural measures discriminated controls from experimentals. Executive function correlated with coherence and brain structure measures, and with newborn-period neurobehavioral assessment. Conclusion The intervention in the intensive care nursery improved executive function as well as spectral coherence between occipital and frontal as well as parietal regions. The experimentals’ cerebella were significantly larger than the controls’. These results, while preliminary, point to the possibility of long-term brain improvement even of intrauterine growth compromised preterms if individualized intervention begins with admission to the NICU and extends throughout transition home. Larger sample replications are required in order to confirm these results. Clinical trial registration The study is registered as a clinical trial. The trial registration number is NCT00914108. PMID:23421857

School-age effects of the newborn individualized developmental care and assessment program for preterm infants with intrauterine growth restriction: preliminary findings.

PubMed

McAnulty, Gloria; Duffy, Frank H; Kosta, Sandra; Weisenfeld, Neil I; Warfield, Simon K; Butler, Samantha C; Alidoost, Moona; Bernstein, Jane Holmes; Robertson, Richard; Zurakowski, David; Als, Heidelise

2013-02-19

The experience in the newborn intensive care nursery results in premature infants' neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother's intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks' lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore, executive function, spectral coherence and brain structural measures discriminated controls from experimentals. Executive function correlated with coherence and brain structure measures, and with newborn-period neurobehavioral assessment. The intervention in the intensive care nursery improved executive function as well as spectral coherence between occipital and frontal as well as parietal regions. The experimentals' cerebella were significantly larger than the controls'. These results, while preliminary, point to the possibility of long-term brain improvement even of intrauterine growth compromised preterms if individualized intervention begins with admission to the NICU and extends throughout transition home. Larger sample replications are required in order to confirm these results. The study is registered as a clinical trial. The trial registration number is NCT00914108.

Disconnection of network hubs and cognitive impairment after traumatic brain injury.

PubMed

Fagerholm, Erik D; Hellyer, Peter J; Scott, Gregory; Leech, Robert; Sharp, David J

2015-06-01

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Construction of population-specific Indian MRI brain template: Morphometric comparison with Chinese and Caucasian templates.

PubMed

Bhalerao, Gaurav Vivek; Parlikar, Rujuta; Agrawal, Rimjhim; Shivakumar, Venkataram; Kalmady, Sunil V; Rao, Naren P; Agarwal, Sri Mahavir; Narayanaswamy, Janardhanan C; Reddy, Y C Janardhan; Venkatasubramanian, Ganesan

2018-06-01

Spatial normalization of brain MR images is highly dependent on the choice of target brain template. Morphological differences caused by factors like genetic and environmental exposures, generates a necessity to construct population specific brain templates. Brain image analysis performed using brain templates from Caucasian population may not be appropriate for non-Caucasian population. In this study, our objective was to construct an Indian brain template from a large population (N = 157 subjects) and compare the morphometric parameters of this template with that of Chinese-56 and MNI-152 templates. In addition, using an independent MRI data of 15 Indian subjects, we also evaluated the potential registration accuracy differences using these three templates. Indian brain template was constructed using iterative routines as per established procedures. We compared our Indian template with standard MNI-152 template and Chinese template by measuring global brain features. We also examined accuracy of registration by aligning 15 new Indian brains to Indian, Chinese and MNI templates. Furthermore, we supported our measurement protocol with inter-rater and intra-rater reliability analysis. Our results showed that there were significant differences in global brain features of Indian template in comparison with Chinese and MNI brain templates. The results of registration accuracy analysis revealed that fewer deformations are required when Indian brains are registered to Indian template as compared to Chinese and MNI templates. This study concludes that population specific Indian template is likely to be more appropriate for structural and functional image analysis of Indian population. Copyright © 2018 Elsevier B.V. All rights reserved.

Convergent Findings of Altered Functional and Structural Brain Connectivity in Individuals with High Functioning Autism: A Multimodal MRI Study

PubMed Central

Samson, Andrea C.; Kirsch, Valerie; Blautzik, Janusch; Grothe, Michel; Erat, Okan; Hegenloh, Michael; Coates, Ute; Reiser, Maximilian F.; Hennig-Fast, Kristina; Meindl, Thomas

2013-01-01

Brain tissue changes in autism spectrum disorders seem to be rather subtle and widespread than anatomically distinct. Therefore a multimodal, whole brain imaging technique appears to be an appropriate approach to investigate whether alterations in white and gray matter integrity relate to consistent changes in functional resting state connectivity in individuals with high functioning autism (HFA). We applied diffusion tensor imaging (DTI), voxel-based morphometry (VBM) and resting state functional connectivity magnetic resonance imaging (fcMRI) to assess differences in brain structure and function between 12 individuals with HFA (mean age 35.5, SD 11.4, 9 male) and 12 healthy controls (mean age 33.3, SD 9.0, 8 male). Psychological measures of empathy and emotionality were obtained and correlated with the most significant DTI, VBM and fcMRI findings. We found three regions of convergent structural and functional differences between HFA participants and controls. The right temporo-parietal junction area and the left frontal lobe showed decreased fractional anisotropy (FA) values along with decreased functional connectivity and a trend towards decreased gray matter volume. The bilateral superior temporal gyrus displayed significantly decreased functional connectivity that was accompanied by the strongest trend of gray matter volume decrease in the temporal lobe of HFA individuals. FA decrease in the right temporo-parietal region was correlated with psychological measurements of decreased emotionality. In conclusion, our results indicate common sites of structural and functional alterations in higher order association cortex areas and may therefore provide multimodal imaging support to the long-standing hypothesis of autism as a disorder of impaired higher-order multisensory integration. PMID:23825652

Correlation between light scattering signal and tissue reversibility in rat brain exposed to hypoxia

NASA Astrophysics Data System (ADS)

Kawauchi, Satoko; Sato, Shunichi; Uozumi, Yoichi; Nawashiro, Hiroshi; Ishihara, Miya; Kikuchi, Makoto

2010-02-01

Light scattering signal is a potential indicator of tissue viability in brain because cellular and subcellular structural integrity should be associated with cell viability in brain tissue. We previously performed multiwavelength diffuse reflectance measurement for a rat global ischemic brain model and observed a unique triphasic change in light scattering at a certain time after oxygen and glucose deprivation. This triphasic scattering change (TSC) was shown to precede cerebral ATP exhaustion, suggesting that loss of brain tissue viability can be predicted by detecting scattering signal. In the present study, we examined correlation between light scattering signal and tissue reversibility in rat brain in vivo. We performed transcranial diffuse reflectance measurement for rat brain; under spontaneous respiration, hypoxia was induced for the rat by nitrogen gas inhalation and reoxygenation was started at various time points. We observed a TSC, which started at 140 +/- 15 s after starting nitrogen gas inhalation (mean +/- SD, n=8). When reoxygenation was started before the TSC, all rats survived (n=7), while no rats survived when reoxygenation was started after the TSC (n=8). When reoxygenation was started during the TSC, rats survived probabilistically (n=31). Disability of motor function was not observed for the survived rats. These results indicate that TSC can be used as an indicator of loss of tissue reversibility in brains, providing useful information on the critical time zone for treatment to rescue the brain.

Semi-automatic brain tumor segmentation by constrained MRFs using structural trajectories.

PubMed

Zhao, Liang; Wu, Wei; Corso, Jason J

2013-01-01

Quantifying volume and growth of a brain tumor is a primary prognostic measure and hence has received much attention in the medical imaging community. Most methods have sought a fully automatic segmentation, but the variability in shape and appearance of brain tumor has limited their success and further adoption in the clinic. In reaction, we present a semi-automatic brain tumor segmentation framework for multi-channel magnetic resonance (MR) images. This framework does not require prior model construction and only requires manual labels on one automatically selected slice. All other slices are labeled by an iterative multi-label Markov random field optimization with hard constraints. Structural trajectories-the medical image analog to optical flow and 3D image over-segmentation are used to capture pixel correspondences between consecutive slices for pixel labeling. We show robustness and effectiveness through an evaluation on the 2012 MICCAI BRATS Challenge Dataset; our results indicate superior performance to baselines and demonstrate the utility of the constrained MRF formulation.

Visceral fat is associated with brain structure independent of human immunodeficiency virus infection status.

PubMed

Lake, Jordan E; Popov, Mikhail; Post, Wendy S; Palella, Frank J; Sacktor, Ned; Miller, Eric N; Brown, Todd T; Becker, James T

2017-06-01

The combined effects of human immunodeficiency virus (HIV), obesity, and elevated visceral adipose tissue (VAT) on brain structure are unknown. In a cross-sectional analysis of Multicenter AIDS Cohort Study (MACS) participants, we determined associations between HIV serostatus, adiposity, and brain structure. Men (133 HIV+, 84 HIV-) in the MACS Cardiovascular 2 and magnetic resonance imaging (MRI) sub-studies with CT-quantified VAT and whole brain MRI measured within 1 year were assessed. Voxel-based morphometry analyzed brain volumes. Men were stratified by elevated (eVAT, ≥100cm 2 ) or "normal" (nVAT, <100cm 2 ) VAT. Forward stepwise modeling determined associations between clinical and demographic variables and regional brain volumes. eVAT was present in 67% of men. Groups were similar in age and education, but eVAT men were more likely to be HIV+ and have hypertension, diabetes mellitus, body mass index >25 kg/m 2 , smaller gray and white matter volumes, and larger cerebrospinal fluid volume than nVAT men. In multivariate analysis, hypertension, higher adiponectin, higher interleukin-6, age, diabetes mellitus, higher body mass index, and eVAT were associated with brain atrophy (p < 0.05, ordered by increasing strength of association), but HIV serostatus and related factors were generally not. No interactions were observed. Greater VAT was associated with smaller bilateral posterior hippocampus and left mesial temporal lobe and temporal stem white matter volume. Traditional risk factors are more strongly associated with brain atrophy than HIV serostatus, with VAT having the strongest association. However, HIV+ MACS men had disproportionately greater VAT, suggesting the risk for central nervous system effects may be amplified in this population.

Diattenuation of brain tissue and its impact on 3D polarized light imaging

PubMed Central

Menzel, Miriam; Reckfort, Julia; Weigand, Daniel; Köse, Hasan; Amunts, Katrin; Axer, Markus

2017-01-01

3D-polarized light imaging (3D-PLI) reconstructs nerve fibers in histological brain sections by measuring their birefringence. This study investigates another effect caused by the optical anisotropy of brain tissue – diattenuation. Based on numerical and experimental studies and a complete analytical description of the optical system, the diattenuation was determined to be below 4 % in rat brain tissue. It was demonstrated that the diattenuation effect has negligible impact on the fiber orientations derived by 3D-PLI. The diattenuation signal, however, was found to highlight different anatomical structures that cannot be distinguished with current imaging techniques, which makes Diattenuation Imaging a promising extension to 3D-PLI. PMID:28717561

Premorbid personality characteristics and attachment style moderate the effect of injury severity on occupational outcome in traumatic brain injury: another aspect of reserve.

PubMed

Sela-Kaufman, Michal; Rassovsky, Yuri; Agranov, Eugenia; Levi, Yifat; Vakil, Eli

2013-01-01

The concept of "reserve" has been proposed to account for the mismatch between brain pathology and its clinical expression. Prior efforts to characterize this concept focused mostly on brain or cognitive reserve measures. The present study was a preliminary attempt to evaluate premorbid personality and emotional aspects as potential moderators in moderate-to-severe traumatic brain injury. Using structural equation modeling and multiple regression analyses, we found that premorbid personality characteristics provided the most robust moderator of injury severity on occupational outcome. Findings offer preliminary support for premorbid personality features as another relevant reserve construct in predicting outcome in this population.

Blood pressure, brain structure, and cognition: opposite associations in men and women.

PubMed

Cherbuin, Nicolas; Mortby, Moyra E; Janke, Andrew L; Sachdev, Perminder S; Abhayaratna, Walter P; Anstey, Kaarin J

2015-02-01

Research on associations between blood pressure, brain structure, and cognitive function has produced somewhat inconsistent results. In part, this may be due to differences in age ranges studied and because of sex differences in physiology and/or exposure to risk factors, which may lead to different time course or patterns in cardiovascular disease progression. The aim of this study was to investigate the impact of sex on associations between blood pressure, regional cerebral volumes, and cognitive function in older individuals. In this cohort study, brachial blood pressure was measured twice at rest in 266 community-based individuals free of dementia aged 68-73 years who had also undergone a brain scan and a neuropsychological assessment. Associations between mean blood pressure (MAP), regional brain volumes, and cognition were investigated with voxel-wise regression analyses. Positive associations between MAP and regional volumes were detected in men, whereas negative associations were found in women. Similarly, there were sex differences in the brain-volume cognition relationship, with a positive relationship between regional brain volumes associated with MAP in men and a negative relationship in women. In this cohort of older individuals, higher MAP was associated with larger regional volume and better cognition in men, whereas opposite findings were demonstrated in women. These effects may be due to different lifetime risk exposure or because of physiological differences between men and women. Future studies investigating the relationship between blood pressure and brain structure or cognitive function should evaluate the potential for differential sex effects. © American Journal of Hypertension, Ltd 2014. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Volumetric MRI study of the intrauterine growth restriction fetal brain.

PubMed

Polat, A; Barlow, S; Ber, R; Achiron, R; Katorza, E

2017-05-01

Intrauterine growth restriction (IUGR) is a pathologic fetal condition known to affect the fetal brain regionally and associated with future neurodevelopmental abnormalities. This study employed MRI to assess in utero regional brain volume changes in IUGR fetuses compared to controls. Retrospectively, using MRI images of fetuses at 30-34 weeks gestational age, a total of 8 brain regions-supratentorial brain and cavity, cerebral hemispheres, temporal lobes and cerebellum-were measured for volume in 13 fetuses with IUGR due to placental insufficiency and in 21 controls. Volumes and their ratios were assessed for difference using regression models. Reliability was assessed by intraclass correlation coefficients (ICC) between two observers. In both groups, all structures increase in absolute volume during that gestation period, and the rate of cerebellar growth is higher compared to that of supratentorial structures. All structures' absolute volumes were significantly smaller for the IUGR group. Cerebellar to supratentorial ratios were found to be significantly smaller (P < 0.05) for IUGR compared to controls. No other significant ratio differences were found. ICC showed excellent agreement. The cerebellar to supratentorial volume ratio is affected in IUGR fetuses. Additional research is needed to assess this as a radiologic marker in relation to long-term outcome. • IUGR is a pathologic fetal condition affecting the brain • IUGR is associated with long-term neurodevelopmental abnormalities; fetal characterization is needed • This study aimed to evaluate regional brain volume differences in IUGR • Cerebellar to supratentorial volume ratios were smaller in IUGR fetuses • This finding may play a role in long-term development of IUGR fetuses.

Morphological covariance in anatomical MRI scans can identify discrete neural pathways in the brain and their disturbances in persons with neuropsychiatric disorders.

PubMed

Bansal, Ravi; Hao, Xuejun; Peterson, Bradley S

2015-05-01

We hypothesize that coordinated functional activity within discrete neural circuits induces morphological organization and plasticity within those circuits. Identifying regions of morphological covariation that are independent of morphological covariation in other regions therefore may therefore allow us to identify discrete neural systems within the brain. Comparing the magnitude of these variations in individuals who have psychiatric disorders with the magnitude of variations in healthy controls may allow us to identify aberrant neural pathways in psychiatric illnesses. We measured surface morphological features by applying nonlinear, high-dimensional warping algorithms to manually defined brain regions. We transferred those measures onto the surface of a unit sphere via conformal mapping and then used spherical wavelets and their scaling coefficients to simplify the data structure representing these surface morphological features of each brain region. We used principal component analysis (PCA) to calculate covariation in these morphological measures, as represented by their scaling coefficients, across several brain regions. We then assessed whether brain subregions that covaried in morphology, as identified by large eigenvalues in the PCA, identified specific neural pathways of the brain. To do so, we spatially registered the subnuclei for each eigenvector into the coordinate space of a Diffusion Tensor Imaging dataset; we used these subnuclei as seed regions to track and compare fiber pathways with known fiber pathways identified in neuroanatomical atlases. We applied these procedures to anatomical MRI data in a cohort of 82 healthy participants (42 children, 18 males, age 10.5 ± 2.43 years; 40 adults, 22 males, age 32.42 ± 10.7 years) and 107 participants with Tourette's Syndrome (TS) (71 children, 59 males, age 11.19 ± 2.2 years; 36 adults, 21 males, age 37.34 ± 10.9 years). We evaluated the construct validity of the identified covariation in morphology using DTI data from a different set of 20 healthy adults (10 males, mean age 29.7 ± 7.7 years). The PCA identified portions of structures that covaried across the brain, the eigenvalues measuring the magnitude of the covariation in morphology along the respective eigenvectors. Our results showed that the eigenvectors, and the DTI fibers tracked from their associated brain regions, corresponded with known neural pathways in the brain. In addition, the eigenvectors that captured morphological covariation across regions, and the principal components along those eigenvectors, identified neural pathways with aberrant morphological features associated with TS. These findings suggest that covariations in brain morphology can identify aberrant neural pathways in specific neuropsychiatric disorders. Copyright © 2015. Published by Elsevier Inc.

Cognitive correlates of gray matter abnormalities in adolescent siblings of patients with childhood-onset schizophrenia

PubMed Central

Wagshal, Dana; Knowlton, Barbara Jean; Cohen, Jessica Rachel; Bookheimer, Susan Yost; Bilder, Robert Martin; Fernandez, Vindia Gisela; Asarnow, Robert Franklin

2015-01-01

Patients with childhood onset schizophrenia (COS) display widespread gray matter (GM) structural brain abnormalities. Healthy siblings of COS patients share some of these structural abnormalities, suggesting that GM abnormalities are endophenotypes for schizophrenia. Another possible endophenotype for schizophrenia that has been relatively unexplored is corticostriatal dysfunction. The corticostriatal system plays an important role in skill learning. Our previous studies have demonstrated corticostriatal dysfunction in COS siblings with a profound skill learning deficit and abnormal pattern of brain activation during skill learning. This study investigated whether structural abnormalities measured using volumetric brain morphometry (VBM) were present in siblings of COS patients and whether these were related to deficits in cognitive skill learning. Results revealed smaller GM volume in COS siblings relative to controls in a number of regions, including occipital, parietal, and subcortical regions including the striatum, and greater GM volume relative to controls in several subcortical regions. Volume in the right superior frontal gyrus and cerebellum were related to performance differences between groups on the weather prediction task, a measure of cognitive skill learning. Our results support the idea that corticostriatal and cerebellar impairment in unaffected siblings of COS patients are behaviorally relevant and may reflect genetic risk for schizophrenia. PMID:25541139

Brain White Matter Shape Changes in Amyotrophic Lateral Sclerosis (ALS): A Fractal Dimension Study

PubMed Central

Allexandre, Didier; Zhang, Luduan; Wang, Xiao-Feng; Pioro, Erik P.; Yue, Guang H.

2013-01-01

Amyotrophic lateral sclerosis (ALS) is a fatal progressive neurodegenerative disorder. Current diagnosis time is about 12-months due to lack of objective methods. Previous brain white matter voxel based morphometry (VBM) studies in ALS reported inconsistent results. Fractal dimension (FD) has successfully been used to quantify brain WM shape complexity in various neurological disorders and aging, but not yet studied in ALS. Therefore, we investigated WM morphometric changes using FD analyses in ALS patients with different clinical phenotypes. We hypothesized that FD would better capture clinical features of the WM morphometry in different ALS phenotypes than VBM analysis. High resolution MRI T1-weighted images were acquired in controls (n = 11), and ALS patients (n = 89). ALS patients were assigned into four subgroups based on their clinical phenotypes.VBM analysis was carried out using SPM8. FD values were estimated for brain WM skeleton, surface and general structure in both controls and ALS patients using our previously published algorithm. No significant VBM WM changes were observed between controls and ALS patients and among the ALS subgroups. In contrast, significant (p<0.05) FD reductions in skeleton and general structure were observed between ALS with dementia and other ALS subgroups. No significant differences in any of the FD measures were observed between control and ALS patients. FD correlated significantly with revised ALS functional rating scale (ALSFRS-R) score a clinical measure of function. Results suggest that brain WM shape complexity is more sensitive to ALS disease process when compared to volumetric VBM analysis and FD changes are dependent on the ALS phenotype. Correlation between FD and clinical measures suggests that FD could potentially serve as a biomarker of ALS pathophysiology, especially after confirmation by longitudinal studies. PMID:24040000

25 years of neuroimaging in amyotrophic lateral sclerosis.

PubMed

Foerster, Bradley R; Welsh, Robert C; Feldman, Eva L

2013-09-01

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques--such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy--allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development.

25 years of neuroimaging in amyotrophic lateral sclerosis

PubMed Central

Foerster, Bradley R.; Welsh, Robert C.; Feldman, Eva L.

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques—such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy—allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development. PMID:23917850

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography

PubMed Central

Niso, Guiomar; Gorgolewski, Krzysztof J.; Bock, Elizabeth; Brooks, Teon L.; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N.; Jas, Mainak; Litvak, Vladimir; T. Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-01-01

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone. PMID:29917016

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography.

PubMed

Niso, Guiomar; Gorgolewski, Krzysztof J; Bock, Elizabeth; Brooks, Teon L; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N; Jas, Mainak; Litvak, Vladimir; T Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-06-19

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone.

Revealing mesoscopic structural universality with diffusion.

PubMed

Novikov, Dmitry S; Jensen, Jens H; Helpern, Joseph A; Fieremans, Els

2014-04-08

Measuring molecular diffusion is widely used for characterizing materials and living organisms noninvasively. This characterization relies on relations between macroscopic diffusion metrics and structure at the mesoscopic scale commensurate with the diffusion length. Establishing such relations remains a fundamental challenge, hindering progress in materials science, porous media, and biomedical imaging. Here we show that the dynamical exponent in the time dependence of the diffusion coefficient distinguishes between the universality classes of the mesoscopic structural complexity. Our approach enables the interpretation of diffusion measurements by objectively selecting and modeling the most relevant structural features. As an example, the specific values of the dynamical exponent allow us to identify the relevant mesoscopic structure affecting MRI-measured water diffusion in muscles and in brain, and to elucidate the structural changes behind the decrease of diffusion coefficient in ischemic stroke.

Disrupted Topological Patterns of Large-Scale Network in Conduct Disorder

PubMed Central

Jiang, Yali; Liu, Weixiang; Ming, Qingsen; Gao, Yidian; Ma, Ren; Zhang, Xiaocui; Situ, Weijun; Wang, Xiang; Yao, Shuqiao; Huang, Bingsheng

2016-01-01

Regional abnormalities in brain structure and function, as well as disrupted connectivity, have been found repeatedly in adolescents with conduct disorder (CD). Yet, the large-scale brain topology associated with CD is not well characterized, and little is known about the systematic neural mechanisms of CD. We employed graphic theory to investigate systematically the structural connectivity derived from cortical thickness correlation in a group of patients with CD (N = 43) and healthy controls (HCs, N = 73). Nonparametric permutation tests were applied for between-group comparisons of graphical metrics. Compared with HCs, network measures including global/local efficiency and modularity all pointed to hypo-functioning in CD, despite of preserved small-world organization in both groups. The hubs distribution is only partially overlapped with each other. These results indicate that CD is accompanied by both impaired integration and segregation patterns of brain networks, and the distribution of highly connected neural network ‘hubs’ is also distinct between groups. Such misconfiguration extends our understanding regarding how structural neural network disruptions may underlie behavioral disturbances in adolescents with CD, and potentially, implicates an aberrant cytoarchitectonic profiles in the brain of CD patients. PMID:27841320

Affection of Fundamental Brain Activity By Using Sounds For Patients With Prosodic Disorders: A Pilot Study

NASA Astrophysics Data System (ADS)

Imai, Emiko; Katagiri, Yoshitada; Seki, Keiko; Kawamata, Toshio

2011-06-01

We present a neural model of the production of modulated speech streams in the brain, referred to as prosody, which indicates the limbic structure essential for producing prosody both linguistically and emotionally. This model suggests that activating the fundamental brain including monoamine neurons at the basal ganglia will potentially contribute to helping patients with prosodic disorders coming from functional defects of the fundamental brain to overcome their speech problem. To establish effective clinical treatment for such prosodic disorders, we examine how sounds affect the fundamental activity by using electroencephalographic measurements. Throughout examinations with various melodious sounds, we found that some melodies with lilting rhythms successfully give rise to the fast alpha rhythms at the electroencephalogram which reflect the fundamental brain activity without any negative feelings.

Selective Activation of Resting-State Networks following Focal Stimulation in a Connectome-Based Network Model of the Human Brain

PubMed Central

2016-01-01

Abstract When the brain is stimulated, for example, by sensory inputs or goal-oriented tasks, the brain initially responds with activities in specific areas. The subsequent pattern formation of functional networks is constrained by the structural connectivity (SC) of the brain. The extent to which information is processed over short- or long-range SC is unclear. Whole-brain models based on long-range axonal connections, for example, can partly describe measured functional connectivity dynamics at rest. Here, we study the effect of SC on the network response to stimulation. We use a human whole-brain network model comprising long- and short-range connections. We systematically activate each cortical or thalamic area, and investigate the network response as a function of its short- and long-range SC. We show that when the brain is operating at the edge of criticality, stimulation causes a cascade of network recruitments, collapsing onto a smaller space that is partly constrained by SC. We found both short- and long-range SC essential to reproduce experimental results. In particular, the stimulation of specific areas results in the activation of one or more resting-state networks. We suggest that the stimulus-induced brain activity, which may indicate information and cognitive processing, follows specific routes imposed by structural networks explaining the emergence of functional networks. We provide a lookup table linking stimulation targets and functional network activations, which potentially can be useful in diagnostics and treatments with brain stimulation. PMID:27752540

Freesurfer-initialized large deformation diffeomorphic metric mapping with application to Parkinson's disease

NASA Astrophysics Data System (ADS)

Chen, Jingyun; Palmer, Samantha J.; Khan, Ali R.; Mckeown, Martin J.; Beg, Mirza Faial

2009-02-01

We apply a recently developed automated brain segmentation method, FS+LDDMM, to brain MRI scans from Parkinson's Disease (PD) subjects, and normal age-matched controls and compare the results to manual segmentation done by trained neuroscientists. The data set consisted of 14 PD subjects and 12 age-matched control subjects without neurologic disease and comparison was done on six subcortical brain structures (left and right caudate, putamen and thalamus). Comparison between automatic and manual segmentation was based on Dice Similarity Coefficient (Overlap Percentage), L1 Error, Symmetrized Hausdorff Distance and Symmetrized Mean Surface Distance. Results suggest that FS+LDDMM is well-suited for subcortical structure segmentation and further shape analysis in Parkinson's Disease. The asymmetry of the Dice Similarity Coefficient over shape change is also discussed based on the observation and measurement of FS+LDDMM segmentation results.

A histology-based atlas of the C57BL/6J mouse brain deformably registered to in vivo MRI for localized radiation and surgical targeting

NASA Astrophysics Data System (ADS)

Purger, David; McNutt, Todd; Achanta, Pragathi; Quiñones-Hinojosa, Alfredo; Wong, John; Ford, Eric

2009-12-01

The C57BL/6J laboratory mouse is commonly used in neurobiological research. Digital atlases of the C57BL/6J brain have been used for visualization, genetic phenotyping and morphometry, but currently lack the ability to accurately calculate deviations between individual mice. We developed a fully three-dimensional digital atlas of the C57BL/6J brain based on the histology atlas of Paxinos and Franklin (2001 The Mouse Brain in Stereotaxic Coordinates 2nd edn (San Diego, CA: Academic)). The atlas uses triangular meshes to represent the various structures. The atlas structures can be overlaid and deformed to individual mouse MR images. For this study, we selected 18 structures from the histological atlas. Average atlases can be created for any group of mice of interest by calculating the mean three-dimensional positions of corresponding individual mesh vertices. As a validation of the atlas' accuracy, we performed deformable registration of the lateral ventricles to 13 MR brain scans of mice in three age groups: 5, 8 and 9 weeks old. Lateral ventricle structures from individual mice were compared to the corresponding average structures and the original histology structures. We found that the average structures created using our method more accurately represent individual anatomy than histology-based atlases alone, with mean vertex deviations of 0.044 mm versus 0.082 mm for the left lateral ventricle and 0.045 mm versus 0.068 mm for the right lateral ventricle. Our atlas representation gives direct spatial deviations for structures of interest. Our results indicate that MR-deformable histology-based atlases represent an accurate method to obtain accurate morphometric measurements of a population of mice, and that this method may be applied to phenotyping experiments in the future as well as precision targeting of surgical procedures or radiation treatment.

Laser scattering by transcranial rat brain illumination

NASA Astrophysics Data System (ADS)

Sousa, Marcelo V. P.; Prates, Renato; Kato, Ilka T.; Sabino, Caetano P.; Suzuki, Luis C.; Ribeiro, Martha S.; Yoshimura, Elisabeth M.

2012-06-01

Due to the great number of applications of Low-Level-Laser-Therapy (LLLT) in Central Nervous System (CNS), the study of light penetration through skull and distribution in the brain becomes extremely important. The aim is to analyze the possibility of precise illumination of deep regions of the rat brain, measure the penetration and distribution of red (λ = 660 nm) and Near Infra-Red (NIR) (λ = 808 nm) diode laser light and compare optical properties of brain structures. The head of the animal (Rattus Novergicus) was epilated and divided by a sagittal cut, 2.3 mm away from mid plane. This section of rat's head was illuminated with red and NIR lasers in points above three anatomical structures: hippocampus, cerebellum and frontal cortex. A high resolution camera, perpendicularly positioned, was used to obtain images of the brain structures. Profiles of scattered intensities in the laser direction were obtained from the images. There is a peak in the scattered light profile corresponding to the skin layer. The bone layer gives rise to a valley in the profile indicating low scattering coefficient, or frontal scattering. Another peak in the region related to the brain is an indication of high scattering coefficient (μs) for this tissue. This work corroborates the use of transcranial LLLT in studies with rats which are subjected to models of CNS diseases. The outcomes of this study point to the possibility of transcranial LLLT in humans for a large number of diseases.

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post-Bed Rest and Space Flight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Peters, B.; De Dios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Oddsson, L.; Kreutzberg, G.; Zanello, S.;

Reduced rich-club connectivity is related to disability in primary progressive MS

PubMed Central

Hodecker, Sibylle; Cheng, Bastian; Wanke, Nadine; Young, Kim Lea; Hilgetag, Claus; Gerloff, Christian; Heesen, Christoph; Thomalla, Götz; Siemonsen, Susanne

2017-01-01

Objective: To investigate whether the structural connectivity of the brain's rich-club organization is altered in patients with primary progressive MS and whether such changes to this fundamental network feature are associated with disability measures. Methods: We recruited 37 patients with primary progressive MS and 21 healthy controls for an observational cohort study. Structural connectomes were reconstructed based on diffusion-weighted imaging data using probabilistic tractography and analyzed with graph theory. Results: We observed the same topological organization of brain networks in patients and controls. Consistent with the originally defined rich-club regions, we identified superior frontal, precuneus, superior parietal, and insular cortex in both hemispheres as rich-club nodes. Connectivity within the rich club was significantly reduced in patients with MS (p = 0.039). The extent of reduced rich-club connectivity correlated with clinical measurements of mobility (Kendall rank correlation coefficient τ = −0.20, p = 0.047), hand function (τ = −0.26, p = 0.014), and information processing speed (τ = −0.20, p = 0.049). Conclusions: In patients with primary progressive MS, the fundamental organization of the structural connectome in rich-club and peripheral nodes was preserved and did not differ from healthy controls. The proportion of rich-club connections was altered and correlated with disability measures. Thus, the rich-club organization of the brain may be a promising network phenotype for understanding the patterns and mechanisms of neurodegeneration in MS. PMID:28804744

Relations among prospective memory, cognitive abilities, and brain structure in adolescents who vary in prenatal drug exposure.

PubMed

Robey, Alison; Buckingham-Howes, Stacy; Salmeron, Betty Jo; Black, Maureen M; Riggins, Tracy

2014-11-01

This investigation examined how prospective memory (PM) relates to cognitive abilities (i.e., executive function, attention, working memory, and retrospective memory) and brain structure in adolescents who vary in prenatal drug exposure (PDE). The sample consisted of 105 (55 female and 50 male) urban, primarily African American adolescents (mean age=15.5 years) from low socioeconomic status (SES) families. Approximately 56% (n=59) were prenatally exposed to drugs (heroin and/or cocaine) and 44% (n=46) were not prenatally exposed, but the adolescents were similar in age, gender, race, and SES. Executive functioning, attentional control, working memory, retrospective memory, and overall cognitive ability were assessed by validated performance measures. Executive functioning was also measured by caregiver report. A subset of 52 adolescents completed MRI (magnetic resonance imaging) scans, which provided measures of subcortical gray matter volumes and thickness of prefrontal, parietal, and temporal cortices. Results revealed no differences in PM performance by PDE status, even after adjusting for age and IQ. Executive function, retrospective memory, cortical thickness in frontal and parietal regions, and volume of subcortical regions (i.e., putamen and hippocampus) were related to PM performance in the sample overall, even after adjusting for age, IQ, and total gray matter volume. Findings suggest that variations in PM ability during adolescence are robustly related to individual differences in cognitive abilities, in particular executive function and retrospective memory, and brain structure, but do not vary by PDE status. Copyright © 2014 Elsevier Inc. All rights reserved.

Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume?

PubMed

Lemaitre, Herve; Goldman, Aaron L; Sambataro, Fabio; Verchinski, Beth A; Meyer-Lindenberg, Andreas; Weinberger, Daniel R; Mattay, Venkata S

2012-03-01

Normal aging is accompanied by global as well as regional structural changes. While these age-related changes in gray matter volume have been extensively studied, less has been done using newer morphological indexes, such as cortical thickness and surface area. To this end, we analyzed structural images of 216 healthy volunteers, ranging from 18 to 87 years of age, using a surface-based automated parcellation approach. Linear regressions of age revealed a concomitant global age-related reduction in cortical thickness, surface area and volume. Cortical thickness and volume collectively confirmed the vulnerability of the prefrontal cortex, whereas in other cortical regions, such as in the parietal cortex, thickness was the only measure sensitive to the pronounced age-related atrophy. No cortical regions showed more surface area reduction than the global average. The distinction between these morphological measures may provide valuable information to dissect age-related structural changes of the brain, with each of these indexes probably reflecting specific histological changes occurring during aging. Published by Elsevier Inc.

Long-term reorganization of structural brain networks in a rabbit model of intrauterine growth restriction.

PubMed

Batalle, Dafnis; Muñoz-Moreno, Emma; Arbat-Plana, Ariadna; Illa, Miriam; Figueras, Francesc; Eixarch, Elisenda; Gratacos, Eduard

2014-10-15

Characterization of brain changes produced by intrauterine growth restriction (IUGR) is among the main challenges of modern fetal medicine and pediatrics. This condition affects 5-10% of all pregnancies and is associated with a wide range of neurodevelopmental disorders. Better understanding of the brain reorganization produced by IUGR opens a window of opportunity to find potential imaging biomarkers in order to identify the infants with a high risk of having neurodevelopmental problems and apply therapies to improve their outcomes. Structural brain networks obtained from diffusion magnetic resonance imaging (MRI) is a promising tool to study brain reorganization and to be used as a biomarker of neurodevelopmental alterations. In the present study this technique is applied to a rabbit animal model of IUGR, which presents some advantages including a controlled environment and the possibility to obtain high quality MRI with long acquisition times. Using a Q-Ball diffusion model, and a previously published rabbit brain MRI atlas, structural brain networks of 15 IUGR and 14 control rabbits at 70 days of age (equivalent to pre-adolescence human age) were obtained. The analysis of graph theory features showed a decreased network infrastructure (degree and binary global efficiency) associated with IUGR condition and a set of generalized fractional anisotropy (GFA) weighted measures associated with abnormal neurobehavior. Interestingly, when assessing the brain network organization independently of network infrastructure by means of normalized networks, IUGR showed increased global and local efficiencies. We hypothesize that this effect could reflect a compensatory response to reduced infrastructure in IUGR. These results present new evidence on the long-term persistence of the brain reorganization produced by IUGR that could underlie behavioral and developmental alterations previously described. The described changes in network organization have the potential to be used as biomarkers to monitor brain changes produced by experimental therapies in IUGR animal model. Copyright © 2014 Elsevier Inc. All rights reserved.

Gender differences in functional connectivities between insular subdivisions and selective pain-related brain structures.

PubMed

Dai, Yu-Jie; Zhang, Xin; Yang, Yang; Nan, Hai-Yan; Yu, Ying; Sun, Qian; Yan, Lin-Feng; Hu, Bo; Zhang, Jin; Qiu, Zi-Yu; Gao, Yi; Cui, Guang-Bin; Chen, Bi-Liang; Wang, Wen

2018-03-14

The incidence of pain disorders in women is higher than in men, making gender differences in pain a research focus. The human insular cortex is an important brain hub structure for pain processing and is divided into several subdivisions, serving different functions in pain perception. Here we aimed to examine the gender differences of the functional connectivities (FCs) between the twelve insular subdivisions and selected pain-related brain structures in healthy adults. Twenty-six healthy males and 11 age-matched healthy females were recruited in this cross-sectional study. FCs between the 12 insular subdivisions (as 12 regions of interest (ROIs)) and the whole brain (ROI-whole brain level) or 64 selected pain-related brain regions (64 ROIs, ROI-ROI level) were measured between the males and females. Significant gender differences in the FCs of the insular subdivisions were revealed: (1) The FCs between the dorsal dysgranular insula (dId) and other brain regions were significantly increased in males using two different techniques (ROI-whole brain and ROI-ROI analyses); (2) Based on the ROI-whole brain analysis, the FC increases in 4 FC-pairs were observed in males, including the left dId - the right median cingulate and paracingulate/ right posterior cingulate gyrus/ right precuneus, the left dId - the right median cingulate and paracingulate, the left dId - the left angular as well as the left dId - the left middle frontal gyrus; (3) According to the ROI-ROI analysis, increased FC between the left dId and the right rostral anterior cingulate cortex was investigated in males. In summary, the gender differences in the FCs of the insular subdivisions with pain-related brain regions were revealed in the current study, offering neuroimaging evidence for gender differences in pain processing. ClinicalTrials.gov, NCT02820974 . Registered 28 June 2016.

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

Cognitive training with action-related verbs induces neural plasticity in the action representation system as assessed by gray matter brain morphometry.

PubMed

Ghio, Marta; Locatelli, Matteo; Tettamanti, Andrea; Perani, Daniela; Gatti, Roberto; Tettamanti, Marco

2018-06-01

Embodied cognition theories of semantic memory still face the need for multiple sources of converging evidence in support of the involvement of sensory-motor systems in action-related knowledge. Previous studies showed that training manual actions improves semantic processing of verbs referring to the trained actions. The present work aimed to provide complementary evidence by measuring the brain plasticity effects of a cognitive training requiring sustained lexical-semantic processing of action-related verbs. We included two groups of participants, namely the Proximal Group (PG) and the Distal Group (DG), which underwent a 3-week training with verbs referring to actions involving the proximal and the distal upper limb musculature, respectively. Before and after training, we measured gray matter voxel brain morphometry based on T1 structural magnetic resonance imaging. By means of this 2 (Group: PG, DG) × 2 (Time: pre-, post-training) factorial design, we tested whether sustained cognitive experience with specific action-related verbs induces congruent brain plasticity modifications in target regions of interest pertaining to the action representation system. We found significant post- versus pre-training gray matter volume increases, specifically for PG in the left dorsal precentral gyrus, and for DG in the right cerebellar lobule VIIa. These preliminary results suggest that a cognitive training can induce structural plasticity modifications in brain regions specifically coding for the distal and proximal motor actions the trained verbs refer to. Copyright © 2018 Elsevier Ltd. All rights reserved.

Consciousness as a global property of brain dynamic activity

NASA Astrophysics Data System (ADS)

Mateos, D. M.; Wennberg, R.; Guevara, R.; Perez Velazquez, J. L.

2017-12-01

We seek general principles of the structure of the cellular collective activity associated with conscious awareness. Can we obtain evidence for features of the optimal brain organization that allows for adequate processing of stimuli and that may guide the emergence of cognition and consciousness? Analyzing brain recordings in conscious and unconscious states, we followed initially the classic approach in physics when it comes to understanding collective behaviours of systems composed of a myriad of units: the assessment of the number of possible configurations (microstates) that the system can adopt, for which we use a global entropic measure associated with the number of connected brain regions. Having found maximal entropy in conscious states, we then inspected the microscopic nature of the configurations of connections using an adequate complexity measure and found higher complexity in states characterized not only by conscious awareness but also by subconscious cognitive processing, such as sleep stages. Our observations indicate that conscious awareness is associated with maximal global (macroscopic) entropy and with the short time scale (microscopic) complexity of the configurations of connected brain networks in pathological unconscious states (seizures and coma), but the microscopic view captures the high complexity in physiological unconscious states (sleep) where there is information processing. As such, our results support the global nature of conscious awareness, as advocated by several theories of cognition. We thus hope that our studies represent preliminary steps to reveal aspects of the structure of cognition that leads to conscious awareness.

Cortical thickness and folding deficits in conduct-disordered adolescents

PubMed Central

Hyatt, Christopher J.; Haney-Caron, Emily; Stevens, Michael C.

2012-01-01

Background Studies of pediatric conduct disorder (CD) have described frontal and temporal lobe structural abnormalities that parallel findings in antisocial adults. The purpose of this study was to examine previously unexplored cortical thickness and folding as markers for brain abnormalities in “pure CD”-diagnosed adolescents. Based on current fronto-temporal theories, we hypothesized that CD youth would have thinner cortex or less cortical folding in temporal and frontal lobes than control subjects. Methods We obtained T1-weighted brain structure images from n=24 control and n=19 CD participants aged 12–18 years, matched by overall gender and age. We measured group differences in cortical thickness and local gyrification index (regional cortical folding measure) using surface-based morphometry with clusterwise correction for multiple comparisons. Results CD participants, when compared with controls, showed both reduced cortical thickness and folding. Thinner cortex was located primarily in posterior brain regions, including left superior temporal and parietal lobes, temporoparietal junction and paracentral lobule, right superior temporal and parietal lobes, temporoparietal junction and precuneus. Folding deficits were located mainly in anterior brain regions and included left insula, ventro- and dorsomedial prefrontal, anterior cingulate and orbitofrontal cortices, temporal lobe, right superior frontal and parietal lobes and paracentral lobule. Conclusions Our findings generally agree with previous CD volumetric studies, but here show the unique contributions of cortical thickness and folding to gray matter reductions in pure CD in different brain regions. PMID:22209639

Evaluating structural connectomics in relation to different Q-space sampling techniques.

PubMed

Rodrigues, Paulo; Prats-Galino, Alberto; Gallardo-Pujol, David; Villoslada, Pablo; Falcon, Carles; Prckovska, Vesna

2013-01-01

Brain networks are becoming forefront research in neuroscience. Network-based analysis on the functional and structural connectomes can lead to powerful imaging markers for brain diseases. However, constructing the structural connectome can be based upon different acquisition and reconstruction techniques whose information content and mutual differences has not yet been properly studied in a unified framework. The variations of the structural connectome if not properly understood can lead to dangerous conclusions when performing these type of studies. In this work we present evaluation of the structural connectome by analysing and comparing graph-based measures on real data acquired by the three most important Diffusion Weighted Imaging techniques: DTI, HARDI and DSI. We thus come to several important conclusions demonstrating that even though the different techniques demonstrate differences in the anatomy of the reconstructed fibers the respective connectomes show variations of 20%.

Morphological brain measures of cortico-limbic inhibition related to resilience.

PubMed

Gupta, Arpana; Love, Aubrey; Kilpatrick, Lisa A; Labus, Jennifer S; Bhatt, Ravi; Chang, Lin; Tillisch, Kirsten; Naliboff, Bruce; Mayer, Emeran A

2017-09-01

Resilience is the ability to adequately adapt and respond to homeostatic perturbations. Although resilience has been associated with positive health outcomes, the neuro-biological basis of resilience is poorly understood. The aim of the study was to identify associations between regional brain morphology and trait resilience with a focus on resilience-related morphological differences in brain regions involved in cortico-limbic inhibition. The relationship between resilience and measures of affect were also investigated. Forty-eight healthy subjects completed structural MRI scans. Self-reported resilience was measured using the Connor and Davidson Resilience Scale. Segmentation and regional parcellation of images was performed to yield a total of 165 regions. Gray matter volume (GMV), cortical thickness, surface area, and mean curvature were calculated for each region. Regression models were used to identify associations between morphology of regions belonging to executive control and emotional arousal brain networks and trait resilience (total and subscales) while controlling for age, sex, and total GMV. Correlations were also conducted between resilience scores and affect scores. Significant associations were found between GM changes in hypothesized brain regions (subparietal sulcus, intraparietal sulcus, amygdala, anterior mid cingulate cortex, and subgenual cingulate cortex) and resilience scores. There were significant positive correlations between resilience and positive affect and negative correlations with negative affect. Resilience was associated with brain morphology of regions involved in cognitive and affective processes related to cortico-limbic inhibition. Brain signatures associated with resilience may be a biomarker of vulnerability to disease. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Differential investment in visual and olfactory brain areas reflects behavioural choices in hawk moths

PubMed Central

Stöckl, Anna; Heinze, Stanley; Charalabidis, Alice; el Jundi, Basil; Warrant, Eric; Kelber, Almut

2016-01-01

Nervous tissue is one of the most metabolically expensive animal tissues, thus evolutionary investments that result in enlarged brain regions should also result in improved behavioural performance. Indeed, large-scale comparative studies in vertebrates and invertebrates have successfully linked differences in brain anatomy to differences in ecology and behaviour, but their precision can be limited by the detail of the anatomical measurements, or by only measuring behaviour indirectly. Therefore, detailed case studies are valuable complements to these investigations, and have provided important evidence linking brain structure to function in a range of higher-order behavioural traits, such as foraging experience or aggressive behaviour. Here, we show that differences in the size of both lower and higher-order sensory brain areas reflect differences in the relative importance of these senses in the foraging choices of hawk moths, as suggested by previous anatomical work in Lepidopterans. To this end we combined anatomical and behavioural quantifications of the relative importance of vision and olfaction in two closely related hawk moth species. We conclude that differences in sensory brain volume in these hawk moths can indeed be interpreted as differences in the importance of these senses for the animal’s behaviour. PMID:27185464

Effects of low-level exposure to sarin and cyclosarin during the 1991 Gulf War on brain function and brain structure in US veterans.

PubMed

Chao, Linda L; Rothlind, Johannes C; Cardenas, Valerie A; Meyerhoff, Dieter J; Weiner, Michael W

2010-09-01

Potentially more than 100,000 US troops may have been exposed to the organophosphate chemical warfare agents sarin (GB) and cyclosarin (GF) when a munitions dump at Khamisiyah, Iraq was destroyed during the Gulf War (GW) in 1991. Although little is known about the long-term neurobehavioral or neurophysiological effects of low-dose exposure to GB/GF in humans, recent studies of GW veterans from the Devens Cohort suggest decrements in certain cognitive domains and atrophy in brain white matter occur individuals with higher estimated levels of presumed GB/GF exposure. The goal of the current study is to determine the generalizability of these findings in another cohort of GW veterans with suspected GB/GF exposure. Neurobehavioral and imaging data collected in a study on Gulf War Illness between 2002 and 2007 were used in this study. We focused on the data of 40 GW-deployed veterans categorized as having been exposed to GB/GF at Khamisiyah, Iraq and 40 matched controls. Magnetic resonance images (MRI) of the brain were analyzed using automated and semi-automated image processing techniques that produced volumetric measurements of gray matter (GM), white matter (WM), cerebrospinal fluid (CSF) and hippocampus. GW veterans with suspected GB/GF exposure had reduced total GM and hippocampal volumes compared to their unexposed peers (p< or =0.01). Although there were no group differences in measures of cognitive function or total WM volume, there were significant, positive correlations between total WM volume and measures of executive function and visuospatial abilities in veterans with suspected GB/GF exposure. These findings suggest that low-level exposure to GB/GF can have deleterious effects on brain structure and brain function more than decade later. Copyright © 2010 Elsevier Inc. All rights reserved.

Spectral properties of the temporal evolution of brain network structure.

PubMed

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Spectral properties of the temporal evolution of brain network structure

NASA Astrophysics Data System (ADS)

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Long-term use of psychedelic drugs is associated with differences in brain structure and personality in humans.

PubMed

Bouso, José Carlos; Palhano-Fontes, Fernanda; Rodríguez-Fornells, Antoni; Ribeiro, Sidarta; Sanches, Rafael; Crippa, José Alexandre S; Hallak, Jaime E C; de Araujo, Draulio B; Riba, Jordi

2015-04-01

Psychedelic agents have a long history of use by humans for their capacity to induce profound modifications in perception, emotion and cognitive processes. Despite increasing knowledge of the neural mechanisms involved in the acute effects of these drugs, the impact of sustained psychedelic use on the human brain remains largely unknown. Molecular pharmacology studies have shown that psychedelic 5-hydroxytryptamine (5HT)2A agonists stimulate neurotrophic and transcription factors associated with synaptic plasticity. These data suggest that psychedelics could potentially induce structural changes in brain tissue. Here we looked for differences in cortical thickness (CT) in regular users of psychedelics. We obtained magnetic resonance imaging (MRI) images of the brains of 22 regular users of ayahuasca (a preparation whose active principle is the psychedelic 5HT2A agonist N,N-dimethyltryptamine (DMT)) and 22 controls matched for age, sex, years of education, verbal IQ and fluid IQ. Ayahuasca users showed significant CT differences in midline structures of the brain, with thinning in the posterior cingulate cortex (PCC), a key node of the default mode network. CT values in the PCC were inversely correlated with the intensity and duration of prior use of ayahuasca and with scores on self-transcendence, a personality trait measuring religiousness, transpersonal feelings and spirituality. Although direct causation cannot be established, these data suggest that regular use of psychedelic drugs could potentially lead to structural changes in brain areas supporting attentional processes, self-referential thought, and internal mentation. These changes could underlie the previously reported personality changes in long-term users and highlight the involvement of the PCC in the effects of psychedelics. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses

PubMed Central

Stephen, Emily P.; Lepage, Kyle Q.; Eden, Uri T.; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S.; Guenther, Frank H.; Kramer, Mark A.

2014-01-01

The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty—both in the functional network edges and the corresponding aggregate measures of network topology—are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here—appropriate for static and dynamic network inference and different statistical measures of coupling—permits the evaluation of confidence in network measures in a variety of settings common to neuroscience. PMID:24678295

Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses.

PubMed

Stephen, Emily P; Lepage, Kyle Q; Eden, Uri T; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S; Guenther, Frank H; Kramer, Mark A

2014-01-01

The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty-both in the functional network edges and the corresponding aggregate measures of network topology-are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here-appropriate for static and dynamic network inference and different statistical measures of coupling-permits the evaluation of confidence in network measures in a variety of settings common to neuroscience.

Sample entropy and regularity dimension in complexity analysis of cortical surface structure in early Alzheimer's disease and aging.

PubMed

Chen, Ying; Pham, Tuan D

2013-05-15

We apply for the first time the sample entropy (SampEn) and regularity dimension model for measuring signal complexity to quantify the structural complexity of the brain on MRI. The concept of the regularity dimension is based on the theory of chaos for studying nonlinear dynamical systems, where power laws and entropy measure are adopted to develop the regularity dimension for modeling a mathematical relationship between the frequencies with which information about signal regularity changes in various scales. The sample entropy and regularity dimension of MRI-based brain structural complexity are computed for early Alzheimer's disease (AD) elder adults and age and gender-matched non-demented controls, as well as for a wide range of ages from young people to elder adults. A significantly higher global cortical structure complexity is detected in AD individuals (p<0.001). The increase of SampEn and the regularity dimension are also found to be accompanied with aging which might indicate an age-related exacerbation of cortical structural irregularity. The provided model can be potentially used as an imaging bio-marker for early prediction of AD and age-related cognitive decline. Copyright © 2013 Elsevier B.V. All rights reserved.

Estimation of effective connectivity via data-driven neural modeling

PubMed Central

Freestone, Dean R.; Karoly, Philippa J.; Nešić, Dragan; Aram, Parham; Cook, Mark J.; Grayden, David B.

2014-01-01

This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination. PMID:25506315

Sex differences in the relationship between white matter connectivity and creativity.

PubMed

Ryman, Sephira G; van den Heuvel, Martijn P; Yeo, Ronald A; Caprihan, Arvind; Carrasco, Jessica; Vakhtin, Andrei A; Flores, Ranee A; Wertz, Christopher; Jung, Rex E

2014-11-01

Creative cognition emerges from a complex network of interacting brain regions. This study investigated the relationship between the structural organization of the human brain and aspects of creative cognition tapped by divergent thinking tasks. Diffusion weighted imaging (DWI) was used to obtain fiber tracts from 83 segmented cortical regions. This information was represented as a network and metrics of connectivity organization, including connectivity strength, clustering and communication efficiency were computed, and their relationship to individual levels of creativity was examined. Permutation testing identified significant sex differences in the relationship between global connectivity and creativity as measured by divergent thinking tests. Females demonstrated significant inverse relationships between global connectivity and creative cognition, whereas there were no significant relationships observed in males. Node specific analyses revealed inverse relationships across measures of connectivity, efficiency, clustering and creative cognition in widespread regions in females. Our findings suggest that females involve more regions of the brain in processing to produce novel ideas to solutions, perhaps at the expense of efficiency (greater path lengths). Males, in contrast, exhibited few, relatively weak positive relationships across these measures. Extending recent observations of sex differences in connectome structure, our findings of sexually dimorphic relationships suggest a unique topological organization of connectivity underlying the generation of novel ideas in males and females. Published by Elsevier Inc.

Multiplexed aberration measurement for deep tissue imaging in vivo

PubMed Central

Wang, Chen; Liu, Rui; Milkie, Daniel E.; Sun, Wenzhi; Tan, Zhongchao; Kerlin, Aaron; Chen, Tsai-Wen; Kim, Douglas S.; Ji, Na

2014-01-01

We describe a multiplexed aberration measurement method that modulates the intensity or phase of light rays at multiple pupil segments in parallel to determine their phase gradients. Applicable to fluorescent-protein-labeled structures of arbitrary complexity, it allows us to obtain diffraction-limited resolution in various samples in vivo. For the strongly scattering mouse brain, a single aberration correction improves structural and functional imaging of fine neuronal processes over a large imaging volume. PMID:25128976

Subjective cognitive impairment and brain structural networks in Chinese gynaecological cancer survivors compared with age-matched controls: a cross-sectional study.

PubMed

Zeng, Yingchun; Cheng, Andy S K; Song, Ting; Sheng, Xiujie; Zhang, Yang; Liu, Xiangyu; Chan, Chetwyn C H

2017-11-28

Subjective cognitive impairment can be a significant and prevalent problem for gynaecological cancer survivors. The aims of this study were to assess subjective cognitive functioning in gynaecological cancer survivors after primary cancer treatment, and to investigate the impact of cancer treatment on brain structural networks and its association with subjective cognitive impairment. This was a cross-sectional survey using a self-reported questionnaire by the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) to assess subjective cognitive functioning, and applying DTI (diffusion tensor imaging) and graph theoretical analyses to investigate brain structural networks after primary cancer treatment. A total of 158 patients with gynaecological cancer (mean age, 45.86 years) and 130 age-matched non-cancer controls (mean age, 44.55 years) were assessed. Patients reported significantly greater subjective cognitive functioning on the FACT-Cog total score and two subscales of perceived cognitive impairment and perceived cognitive ability (all p values <0.001). Compared with patients who had received surgery only and non-cancer controls, patients treated with chemotherapy indicated the most altered global brain structural networks, especially in one of properties of small-worldness (p = 0.004). Reduced small-worldness was significantly associated with a lower FACT-Cog total score (r = 0.412, p = 0.024). Increased characteristic path length was also significantly associated with more subjective cognitive impairment (r = -0.388, p = 0.034). When compared with non-cancer controls, a considerable proportion of gynaecological cancer survivors may exhibit subjective cognitive impairment. This study provides the first evidence of brain structural network alteration in gynaecological cancer patients at post-treatment, and offers novel insights regarding the possible neurobiological mechanism of cancer-related cognitive impairment (CRCI) in gynaecological cancer patients. As primary cancer treatment can result in a more random organisation of structural brain networks, this may reduce brain functional specificity and segregation, and have implications for cognitive impairment. Future prospective and longitudinal studies are needed to build upon the study findings in order to assess potentially relevant clinical and psychosocial variables and brain network measures, so as to more accurately understand the specific risk factors related to subjective cognitive impairment in the gynaecological cancer population. Such knowledge could inform the development of appropriate treatment and rehabilitation efforts to ameliorate cognitive impairment in gynaecological cancer survivors.

A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS).

PubMed

Job, Dominic E; Dickie, David Alexander; Rodriguez, David; Robson, Andrew; Danso, Sammy; Pernet, Cyril; Bastin, Mark E; Boardman, James P; Murray, Alison D; Ahearn, Trevor; Waiter, Gordon D; Staff, Roger T; Deary, Ian J; Shenkin, Susan D; Wardlaw, Joanna M

2017-01-01

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Decreased cerebral cortical serotonin transporter binding in ecstasy users: a positron emission tomography/[(11)C]DASB and structural brain imaging study.

PubMed

Kish, Stephen J; Lerch, Jason; Furukawa, Yoshiaki; Tong, Junchao; McCluskey, Tina; Wilkins, Diana; Houle, Sylvain; Meyer, Jeffrey; Mundo, Emanuela; Wilson, Alan A; Rusjan, Pablo M; Saint-Cyr, Jean A; Guttman, Mark; Collins, D Louis; Shapiro, Colin; Warsh, Jerry J; Boileau, Isabelle

2010-06-01

Animal data indicate that the recreational drug ecstasy (3,4-methylenedioxymethamphetamine) can damage brain serotonin neurons. However, human neuroimaging measurements of serotonin transporter binding, a serotonin neuron marker, remain contradictory, especially regarding brain areas affected; and the possibility that structural brain differences might account for serotonin transporter binding changes has not been explored. We measured brain serotonin transporter binding using [(11)C] N,N-dimethyl-2-(2-amino-4-cyanophenylthio) benzylamine in 50 control subjects and in 49 chronic (mean 4 years) ecstasy users (typically one to two tablets bi-monthly) withdrawn from the drug (mean 45 days). A magnetic resonance image for positron emission tomography image co-registration and structural analyses was acquired. Hair toxicology confirmed group allocation but also indicated use of other psychoactive drugs in most users. Serotonin transporter binding in ecstasy users was significantly decreased throughout all cerebral cortices (range -19 to -46%) and hippocampus (-21%) and related to the extent of drug use (years, maximum dose), but was normal in basal ganglia and midbrain. Substantial overlap was observed between control and user values except for insular cortex, in which 51% of ecstasy user values fell below the lower limit of the control range. Voxel-based analyses confirmed a caudorostral gradient of cortical serotonin transporter binding loss with occipital cortex most severely affected. Magnetic resonance image measurement revealed no overall regional volume differences between groups; however, a slight left-hemispheric biased cortical thinning was detected in methamphetamine-using ecstasy users. The serotonin transporter binding loss was not related to structural changes or partial volume effect, use of other stimulant drugs, blood testosterone or oestradiol levels, major serotonin transporter gene promoter polymorphisms, gender, psychiatric status, or self-reported hyperthermia or tolerance. The ecstasy group, although 'grossly behaviourally normal', reported subnormal mood and demonstrated generally modest deficits on some tests of attention, executive function and memory, with the latter associated with serotonin transporter decrease. Our findings suggest that the 'typical'/low dose (one to two tablets/session) chronic ecstasy-polydrug user might display a highly selective mild to marked loss of serotonin transporter in cerebral cortex/hippocampus in the range of that observed in Parkinson's disease, which is not gender-specific or completely accounted for by structural brain changes, recent use of other drugs (as assessed by hair analyses) or other potential confounds that we could address. The striking sparing of serotonin transporter-rich striatum (although possibly affected in 'heavier' users) suggests that serotonergic neurons innervating cerebral cortex are more susceptible, for unknown reasons, to ecstasy than those innervating subcortical regions and that behavioural problems in some ecstasy users during abstinence might be related to serotonin transporter changes limited to cortical regions.

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

PubMed

Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

The effects of musical training on structural brain development: a longitudinal study.

PubMed

Hyde, Krista L; Lerch, Jason; Norton, Andrea; Forgeard, Marie; Winner, Ellen; Evans, Alan C; Schlaug, Gottfried

2009-07-01

Long-term instrumental music training is an intense, multisensory and motor experience that offers an ideal opportunity to study structural brain plasticity in the developing brain in correlation with behavioral changes induced by training. Here, for the first time, we demonstrate structural brain changes after only 15 months of musical training in early childhood, which were correlated with improvements in musically relevant motor and auditory skills. These findings shed light on brain plasticity, and suggest that structural brain differences in adult experts (whether musicians or experts in other areas) are likely due to training-induced brain plasticity.

Cannabis use is quantitatively associated with nucleus accumbens and amygdala abnormalities in young adult recreational users.

PubMed

Gilman, Jodi M; Kuster, John K; Lee, Sang; Lee, Myung Joo; Kim, Byoung Woo; Makris, Nikos; van der Kouwe, Andre; Blood, Anne J; Breiter, Hans C

2014-04-16

Marijuana is the most commonly used illicit drug in the United States, but little is known about its effects on the human brain, particularly on reward/aversion regions implicated in addiction, such as the nucleus accumbens and amygdala. Animal studies show structural changes in brain regions such as the nucleus accumbens after exposure to Δ9-tetrahydrocannabinol, but less is known about cannabis use and brain morphometry in these regions in humans. We collected high-resolution MRI scans on young adult recreational marijuana users and nonusing controls and conducted three independent analyses of morphometry in these structures: (1) gray matter density using voxel-based morphometry, (2) volume (total brain and regional volumes), and (3) shape (surface morphometry). Gray matter density analyses revealed greater gray matter density in marijuana users than in control participants in the left nucleus accumbens extending to subcallosal cortex, hypothalamus, sublenticular extended amygdala, and left amygdala, even after controlling for age, sex, alcohol use, and cigarette smoking. Trend-level effects were observed for a volume increase in the left nucleus accumbens only. Significant shape differences were detected in the left nucleus accumbens and right amygdala. The left nucleus accumbens showed salient exposure-dependent alterations across all three measures and an altered multimodal relationship across measures in the marijuana group. These data suggest that marijuana exposure, even in young recreational users, is associated with exposure-dependent alterations of the neural matrix of core reward structures and is consistent with animal studies of changes in dendritic arborization.

Regional heterogeneity in limbic maturational changes: evidence from integrating cortical thickness, volumetric and diffusion tensor imaging measures.

PubMed

Grieve, Stuart M; Korgaonkar, Mayuresh S; Clark, C Richard; Williams, Leanne M

2011-04-01

Magnetic resonance imaging (MRI) studies of structural brain development have suggested that the limbic system is relatively preserved in comparison to other brain regions with healthy aging. The goal of this study was to systematically investigate age-related changes of the limbic system using measures of cortical thickness, volumetric and diffusion characteristics. We also investigated if the "relative preservation" concept is consistent across the individual sub-regions of the limbic system. T1 weighted structural MRI and Diffusion Tensor Imaging data from 476 healthy participants from the Brain Resource International Database was used for this study. Age-related changes in grey matter (GM)/white matter (WM) volume, cortical thickness, diffusional characteristics for the pericortical WM and for the fiber tracts associated with the limbic regions were quantified. A regional variability in the aging patterns across the limbic system was present. Four important patterns of age-related changes were highlighted for the limbic sub-regions: 1. early maturation of GM with late loss in the hippocampus and amygdala; 2. an extreme pattern of GM preservation in the entorhinal cortex; 3. a flat pattern of reduced GM loss in the anterior cingulate and the parahippocampus and; 4. accelerated GM loss in the isthmus and posterior cingulate. The GM volumetric data and cortical thickness measures proved to be internally consistent, while the diffusional measures provided complementary data that seem consistent with the GM trends identified. This heterogeneity can be hypothesized to be associated with age-related changes of cognitive function specialized for that region and direct connections to the other brain regions sub-serving these functions. Copyright © 2011 Elsevier Inc. All rights reserved.

Direct contact with particulate matter increases oxidative stress in different brain structures.

PubMed

Fagundes, Lucas Sagrillo; Fleck, Alan da Silveira; Zanchi, Ana Claudia; Saldiva, Paulo Hilário Nascimento; Rhoden, Cláudia Ramos

2015-01-01

Several experimental and epidemiological studies have demonstrated the neurological adverse effects caused by exposure to air pollution, specifically in relation to pollutant particulate matter (PM). The objective of this study was to investigate the direct effect of PM in increased concentrations in different brain regions, as well as the mechanisms involving its neurotoxicity, by evaluating oxidative stress parameters in vitro. Olfactory bulb, cerebral cortex, striatum, hippocampus and cerebellum of rats were homogenized and incubated with PM < 2.5 μm of diameter (PM2.5) at concentrations of 3, 5 and 10 µg/mg of tissue. The oxidative damage caused by lipid peroxidation of these structures was determined by testing the thiobarbituric acid reactive species (TBA-RS). In addition, we measured the activity of antioxidant enzyme catalase (CAT) and superoxide dismutase (SOD). All PM concentrations were able to damage the cerebellum and hippocampus, strongly enhancing the lipid peroxidation in both structures. PM incubation also decreased the CAT activity of the hippocampus, cerebellum, striatum and olfactory bulb, though it did not generate higher levels of lipid peroxidation in either of the last two structures. PM incubation did not alter any measurement of the cerebral cortex. The cerebellum and hippocampus seem to be more susceptible than other brain structures to in vitro direct PM exposure assay and the oxidative stress pathway catalyzes the neurotoxic effect of PM exposure, as evidenced by high consumption of CAT and high levels of TBA-RS. Thus, PM direct exposure seems to activate toxic neurological effects.

Information dynamics of brain-heart physiological networks during sleep

NASA Astrophysics Data System (ADS)

Faes, L.; Nollo, G.; Jurysta, F.; Marinazzo, D.

2014-10-01

This study proposes an integrated approach, framed in the emerging fields of network physiology and information dynamics, for the quantitative analysis of brain-heart interaction networks during sleep. With this approach, the time series of cardiac vagal autonomic activity and brain wave activities measured respectively as the normalized high frequency component of heart rate variability and the EEG power in the δ, θ, α, σ, and β bands, are considered as realizations of the stochastic processes describing the dynamics of the heart system and of different brain sub-systems. Entropy-based measures are exploited to quantify the predictive information carried by each (sub)system, and to dissect this information into a part actively stored in the system and a part transferred to it from the other connected systems. The application of this approach to polysomnographic recordings of ten healthy subjects led us to identify a structured network of sleep brain-brain and brain-heart interactions, with the node described by the β EEG power acting as a hub which conveys the largest amount of information flowing between the heart and brain nodes. This network was found to be sustained mostly by the transitions across different sleep stages, as the information transfer was weaker during specific stages than during the whole night, and vanished progressively when moving from light sleep to deep sleep and to REM sleep.

What is the role of brain mechanisms underlying arousal in recovery of motor function after structural brain injuries?

PubMed Central

Schiff, Nicholas D.

2013-01-01

Purpose of review Standard neurorehabilitation approaches have limited impact on motor recovery in patients with severe injuries. Consideration of the contributions of impaired arousal offers a novel approach to understand and enhance recovery. Recent findings Animal and human neuroimaging studies are elucidating the neuroanatomical bases of arousal and of arousal regulation, the process by which the cerebrum mobilizes resources. Studies of patients with disorders of consciousness have revealed that recovery of these processes is associated with marked improvements in motor performance. Recent studies have also demonstrated that patients with less severe brain injuries also have impaired arousal, manifesting as diminished sustained attention, fatigue and apathy. In these less severely injured patients it is difficult to connect disorders of arousal with motor recovery due to a lack of measures of arousal independent of motor function. Summary Arousal impairment is common after brain injury and likely plays a significant role in recovery of motor function. A more detailed understanding of this connection will help to develop new therapeutic strategies applicable for a wide range of patients. This requires new tools that continuously and objectively measure arousal in patients with brain injury, to correlate with detailed measures of motor performance and recovery. PMID:22002078

Altered Blood-Brain Barrier Permeability in Patients With Systemic Lupus Erythematosus: A Novel Imaging Approach.

PubMed

Gulati, Gaurav; Jones, Jordan T; Lee, Gregory; Altaye, Mekibib; Beebe, Dean W; Meyers-Eaton, Jamie; Wiley, Kasha; Brunner, Hermine I; DiFrancesco, Mark W

2017-02-01

To evaluate a safe, noninvasive magnetic resonance imaging (MRI) method to measure regional blood-brain barrier integrity and investigate its relationship with neurocognitive function and regional gray matter volume in juvenile-onset systemic lupus erythematosus (SLE). In this cross-sectional, case-control study, capillary permeability was measured as a marker of blood-brain barrier integrity in juvenile SLE patients and matched healthy controls, using a combination of arterial spin labeling and diffusion-weighted brain MRI. Regional gray matter volume was measured by voxel-based morphometry. Correlation analysis was done to investigate the relationship between regional capillary permeability and regional gray matter volume. Formal neurocognitive testing was completed (measuring attention, visuoconstructional ability, working memory, and psychomotor speed), and scores were regressed against regional blood-brain barrier integrity among juvenile SLE patients. Formal cognitive testing confirmed normal cognitive ability in all juvenile SLE subjects (n = 11) included in the analysis. Regional capillary permeability was negatively associated (P = 0.026) with neurocognitive performance concerning psychomotor speed in the juvenile SLE cohort. Compared with controls (n = 11), juvenile SLE patients had significantly greater capillary permeability involving Brodmann's areas 19, 28, 36, and 37 and caudate structures (P < 0.05 for all). There is imaging evidence of increased regional capillary permeability in juvenile SLE patients with normal cognitive performance using a novel noninvasive MRI technique. These blood-brain barrier outcomes appear consistent with functional neuronal network alterations and gray matter volume loss previously observed in juvenile SLE patients with overt neurocognitive deficits, supporting the notion that blood-brain barrier integrity loss precedes the loss of cognitive ability in juvenile SLE. Longitudinal studies are needed to confirm the findings of this pilot study. © 2016, American College of Rheumatology.

Left hemisphere structural connectivity abnormality in pediatric hydrocephalus patients following surgery.

PubMed

Yuan, Weihong; Meller, Artur; Shimony, Joshua S; Nash, Tiffany; Jones, Blaise V; Holland, Scott K; Altaye, Mekibib; Barnard, Holly; Phillips, Jannel; Powell, Stephanie; McKinstry, Robert C; Limbrick, David D; Rajagopal, Akila; Mangano, Francesco T

2016-01-01

Neuroimaging research in surgically treated pediatric hydrocephalus patients remains challenging due to the artifact caused by programmable shunt. Our previous study has demonstrated significant alterations in the whole brain white matter structural connectivity based on diffusion tensor imaging (DTI) and graph theoretical analysis in children with hydrocephalus prior to surgery or in surgically treated children without programmable shunts. This study seeks to investigate the impact of brain injury on the topological features in the left hemisphere, contratelateral to the shunt placement, which will avoid the influence of shunt artifacts and makes further group comparisons feasible for children with programmable shunt valves. Three groups of children (34 in the control group, 12 in the 3-month post-surgery group, and 24 in the 12-month post-surgery group, age between 1 and 18 years) were included in the study. The structural connectivity data processing and analysis were performed based on DTI and graph theoretical analysis. Specific procedures were revised to include only left brain imaging data in normalization, parcellation, and fiber counting from DTI tractography. Our results showed that, when compared to controls, children with hydrocephalus in both the 3-month and 12-month post-surgery groups had significantly lower normalized clustering coefficient, lower small-worldness, and higher global efficiency (all p  < 0.05, corrected). At a regional level, both patient groups showed significant alteration in one or more regional connectivity measures in a series of brain regions in the left hemisphere (8 and 10 regions in the 3-month post-surgery and the 12-month post-surgery group, respectively, all p  < 0.05, corrected). No significant correlation was found between any of the global or regional measures and the contemporaneous neuropsychological outcomes [the General Adaptive Composite (GAC) from the Adaptive Behavior Assessment System, Second Edition (ABAS-II)]. However, one global network measure (global efficiency) and two regional network measures in the insula (local efficiency and between centrality) tested at 3-month post-surgery were found to correlate with GAC score tested at 12-month post-surgery with statistical significance (all p  < 0.05, corrected). Our data showed that the structural connectivity analysis based on DTI and graph theory was sensitive in detecting both global and regional network abnormality when the analysis was conducted in the left hemisphere only. This approach provides a new avenue enabling the application of advanced neuroimaging analysis methods in quantifying brain damage in children with hydrocephalus surgically treated with programmable shunts.

Craniofacial and brain abnormalities in Laron syndrome (primary growth hormone insensitivity).

PubMed

Kornreich, L; Horev, G; Schwarz, M; Karmazyn, B; Laron, Z

2002-04-01

To investigate abnormalities in the craniofacial structures and in the brain in patients with Laron syndrome. Eleven patients with classical Laron syndrome, nine untreated adults aged 36-68 years and two children aged 4 and 9 years (the latter treated by IGF-I), were studied. Magnetic resonance images of the brain were obtained in all the patients. One patient also underwent computed tomography. The maximal diameter of the maxillary and frontal sinuses was measured and compared with reference values, the size of the sphenoid sinus was evaluated in relation to the sella, and the mastoids were evaluated qualitatively (small or normal). The brain was evaluated for congenital anomalies and parenchymal lesions. In the adult untreated patients, the paranasal sinuses and mastoids were small; in six patients, the bone marrow in the base of the skull was not mature. The diploe of the calvaria was thin. On computed tomography in one adult patient, the sutures were still open. A minimal or mild degree of diffuse brain parenchymal loss was seen in ten patients. One patient demonstrated a lacunar infarct and another periventricular high signals on T2-weighted images. Two patients had cerebellar atrophy. The present study has demonstrated the important role IGF-I plays in the development of the brain and bony structures of the cranium.

Light-scattering signal may indicate critical time zone to rescue brain tissue after hypoxia

NASA Astrophysics Data System (ADS)

Kawauchi, Satoko; Sato, Shunichi; Uozumi, Yoichi; Nawashiro, Hiroshi; Ishihara, Miya; Kikuchi, Makoto

2011-02-01

A light-scattering signal, which is sensitive to cellular/subcellular structural integrity, is a potential indicator of brain tissue viability because metabolic energy is used in part to maintain the structure of cells. We previously observed a unique triphasic scattering change (TSC) at a certain time after oxygen/glucose deprivation for blood-free rat brains; TSC almost coincided with the cerebral adenosine triphosphate (ATP) depletion. We examine whether such TSC can be observed in the presence of blood in vivo, for which transcranial diffuse reflectance measurement is performed for rat brains during hypoxia induced by nitrogen gas inhalation. At a certain time after hypoxia, diffuse reflectance intensity in the near-infrared region changes in three phases, which is shown by spectroscopic analysis to be due to scattering change in the tissue. During hypoxia, rats are reoxygenated at various time points. When the oxygen supply is started before TSC, all rats survive, whereas no rats survive when the oxygen supply is started after TSC. Survival is probabilistic when the oxygen supply is started during TSC, indicating that the period of TSC can be regarded as a critical time zone for rescuing the brain. The results demonstrate that light scattering signal can be an indicator of brain tissue reversibility.

Technetium-99m-HMPAO SPECT, CT and MRI in the evaluation of patients with chronic traumatic brain injury: a correlation with neuropsychological performance.

PubMed

Ichise, M; Chung, D G; Wang, P; Wortzman, G; Gray, B G; Franks, W

1994-02-01

The purposes of this study were: (1) to compare 99mTc-hexamethylpropyleneamineoxime (HMPAO) SPECT with CT and MRI in chronic traumatic brain injury (TBI) patients and (2) to correlate both functional and structural neuroimaging measurements of brain damage with neuropsychological (NP) performance. Twenty-nine patients (minor TBI, n = 15 and major TBI, n = 14) and 17 normal controls (NC) underwent HMPAO SPECT, CT, MRI and NP testing. Imaging data were analyzed both visually and quantitatively. Nineteen (66%) patients showed 42 abnormalities on SPECT images, whereas 13 (45%) and 10 (34%) patients showed 29 abnormalities on MRI and 24 abnormalities on CT. SPECT detected relatively more abnormalities than CT or MRI in the minor TBI subgroup. The TBI group showed impairment on 11 tests for memory, attention and executive function. Of these, the anterior-posterior ratio (APR) correlated with six tests, whereas the ventricle-to-brain ratio (VBR), a known structural index of a poor NP outcome, correlated with only two tests. In evaluating chronic TBI patients, HMPAO SPECT, as a complement to CT or MRI, may play a useful role by demonstrating brain dysfunction in morphologically intact brain regions and providing objective evidence for some of the impaired NP performance.

Complex Trajectories of Brain Development in the Healthy Human Fetus.

PubMed

Andescavage, Nickie N; du Plessis, Adre; McCarter, Robert; Serag, Ahmed; Evangelou, Iordanis; Vezina, Gilbert; Robertson, Richard; Limperopoulos, Catherine

2017-11-01

This study characterizes global and hemispheric brain growth in healthy human fetuses during the second half of pregnancy using three-dimensional MRI techniques. We studied 166 healthy fetuses that underwent MRI between 18 and 39 completed weeks gestation. We created three-dimensional high-resolution reconstructions of the brain and calculated volumes for left and right cortical gray matter (CGM), fetal white matter (FWM), deep subcortical structures (DSS), and the cerebellum. We calculated the rate of growth for each tissue class according to gestational age and described patterns of hemispheric growth. Each brain region demonstrated major increases in volume during the second half of gestation, the most pronounced being the cerebellum (34-fold), followed by FWM (22-fold), CGM (21-fold), and DSS (10-fold). The left cerebellar hemisphere, CGM, and DSS had larger volumes early in gestation, but these equalized by term. It has been increasingly recognized that brain asymmetry evolves throughout the human life span. Advanced quantitative MRI provides noninvasive measurements of early structural asymmetry between the left and right fetal brain that may inform functional and behavioral laterality differences seen in children and young adulthood. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Medication Overuse Headache: Pathophysiological Insights from Structural and Functional Brain MRI Research.

PubMed

Schwedt, Todd J; Chong, Catherine D

2017-07-01

Research imaging of brain structure and function has helped to elucidate the pathophysiology of medication overuse headache (MOH). This is a narrative review of imaging research studies that have investigated brain structural and functional alterations associated with MOH. Studies included in this review have investigated abnormal structure and function of pain processing regions in people with MOH, functional patterns that might predispose individuals to development of MOH, similarity of brain functional patterns in patients with MOH to those found in people with addiction, brain structure that could predict headache improvement following discontinuation of the overused medication, and changes in brain structure and function after discontinuation of medication overuse. MOH is associated with atypical structure and function of brain regions responsible for pain processing as well as brain regions that are commonly implicated in addiction. Several studies have shown "normalization" of structure and function in pain processing regions following discontinuation of the overused medication and resolution of MOH. However, some of the abnormalities in regions also implicated in addiction tend to persist following discontinuation of the overused medication, suggesting that they are a brain trait that predisposes certain individuals to medication overuse and MOH. © 2017 American Headache Society.

ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide☆☆☆★

PubMed Central

Thompson, Paul M.; Andreassen, Ole A.; Arias-Vasquez, Alejandro; Bearden, Carrie E.; Boedhoe, Premika S.; Brouwer, Rachel M.; Buckner, Randy L.; Buitelaar, Jan K.; Bulayeva, Kazima B.; Cannon, Dara M.; Cohen, Ronald A.; Conrod, Patricia J.; Dale, Anders M.; Deary, Ian J.; Dennis, Emily L.; de Reus, Marcel A.; Desrivieres, Sylvane; Dima, Danai; Donohoe, Gary; Fisher, Simon E.; Fouche, Jean-Paul; Francks, Clyde; Frangou, Sophia; Franke, Barbara; Ganjgahi, Habib; Garavan, Hugh; Glahn, David C.; Grabe, Hans J.; Guadalupe, Tulio; Gutman, Boris A.; Hashimoto, Ryota; Hibar, Derrek P.; Holland, Dominic; Hoogman, Martine; Pol, Hilleke E. Hulshoff; Hosten, Norbert; Jahanshad, Neda; Kelly, Sinead; Kochunov, Peter; Kremen, William S.; Lee, Phil H.; Mackey, Scott; Martin, Nicholas G.; Mazoyer, Bernard; McDonald, Colm; Medland, Sarah E.; Morey, Rajendra A.; Nichols, Thomas E.; Paus, Tomas; Pausova, Zdenka; Schmaal, Lianne; Schumann, Gunter; Shen, Li; Sisodiya, Sanjay M.; Smit, Dirk J.A.; Smoller, Jordan W.; Stein, Dan J.; Stein, Jason L.; Toro, Roberto; Turner, Jessica A.; van den Heuvel, Martijn P.; van den Heuvel, Odile L.; van Erp, Theo G.M.; van Rooij, Daan; Veltman, Dick J.; Walter, Henrik; Wang, Yalin; Wardlaw, Joanna M.; Whelan, Christopher D.; Wright, Margaret J.; Ye, Jieping

2016-01-01

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) – a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date – of schizophrenia and major depression – ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens – now numbering over 30,000 MRI scans – have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants – and genetic variants in general – may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures – from tens of thousands of people – that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far. PMID:26658930

Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders

PubMed Central

Sun, Yu; Li, Junhua; Suckling, John; Feng, Lei

2017-01-01

Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. PMID:29209197

Proton spectroscopy in the narcoleptic syndrome. Is there evidence of a brainstem lesion?

PubMed

Ellis, C M; Simmons, A; Lemmens, G; Williams, S C; Parkes, J D

1998-02-01

There is controversy regarding the relationship of structural or biochemical brainstem lesions to "idiopathic" narcolepsy. Most cases of the narcoleptic syndrome are considered to be idiopathic because no structural lesion is detectable, although some cases of secondary narcolepsy are known to be associated with no structural brainstem lesions. Using proton spectroscopy, we determined levels of ventral pontine metabolite pools in 12 normal subjects and 12 subjects with idiopathic narcolepsy. REM sleep is generated in ventral pontine areas. Proton spectroscopy was used to study levels of N-acetyl aspartate (NAA) as a marker of cell mass, creatine and phosphocreatine (Cr + PCr), and choline (Cho). The intensity of the peaks, as determined by the area under the peak (AUP), was measured. The AUP correlates with the quantity of chemical present. In this study, the ratios of NAA to Cr + PCr were similar in normal subjects and in narcoleptic subjects with idiopathic narcolepsy. No differences in measured metabolic ratio were observed in subjects who slept during the scan procedure compared with those who remained awake. Subjects with "symptomatic" narcolepsy accompanied by an obvious structural brain lesion were not studied. Proton spectroscopy of the brain initiates a new kind of neurochemistry, allowing the noninvasive study of metabolic pools in the living human brain without the use of any kind of tracer or radioactive molecule. In this study, there was no evidence of cell loss in the ventral pontine areas of subjects with the narcoleptic syndrome.

Motivational deficits after brain injury: effects of bromocriptine in 11 patients.

PubMed Central

Powell, J H; al-Adawi, S; Morgan, J; Greenwood, R J

1996-01-01

OBJECTIVE: To test the hypothesis that treatment with bromocriptine would ameliorate deficits in clinical motivation, responsiveness to reward, and frontal cognitive function after brain injury. METHOD: An open trial in six men and five women who had had either traumatic brain injury or subarachnoid haemorrhage between two months and five years previously. After repeated baseline assessments, bromocriptine was given in gradually increasing doses. Assessments were repeated at increasing doses, during maintenance, and after withdrawal. Novel structured instruments for quantifying motivation were developed; measures of anxiety and depression, and cognitive tests sensitive to motivation or frontal lobe involvement were also given. RESULTS: Bromocriptine treatment was followed by improved scores on all measures other than mood. Improvement was maintained after bromocriptine withdrawal in eight of the patients. CONCLUSION: Poor motivation in patients with brain injury may result from dysfunction in the mesolimbic/mesocortical dopaminergic circuitry, giving rise to associated deficiencies in reward responsiveness and frontal cognitive function. PMID:8774407

Bayesian estimation of optical properties of the human head via 3D structural MRI

NASA Astrophysics Data System (ADS)

Barnett, Alexander H.; Culver, Joseph P.; Sorensen, A. Gregory; Dale, Anders M.; Boas, David A.

2003-10-01

Knowledge of the baseline optical properties of the tissues of the human head is essential for absolute cerebral oximetry, and for quantitative studies of brain activation. In this work we numerically model the utility of signals from a small 6-optode time-resolved diffuse optical tomographic apparatus for inferring baseline scattering and absorption coefficients of the scalp, skull and brain, when complete geometric information is available from magnetic resonance imaging (MRI). We use an optical model where MRI-segmented tissues are assumed homogeneous. We introduce a noise model capturing both photon shot noise and forward model numerical accuracy, and use Bayesian inference to predict errorbars and correlations on the measurments. We also sample from the full posterior distribution using Markov chain Monte Carlo. We conclude that ~ 106 detected photons are sufficient to measure the brain"s scattering and absorption to a few percent. We present preliminary results using a fast multi-layer slab model, comparing the case when layer thicknesses are known versus unknown.

Causal effect of disconnection lesions on interhemispheric functional connectivity in rhesus monkeys

PubMed Central

O’Reilly, Jill X.; Croxson, Paula L.; Jbabdi, Saad; Sallet, Jerome; Noonan, MaryAnn P.; Mars, Rogier B.; Browning, Philip G.F.; Wilson, Charles R. E.; Mitchell, Anna S.; Miller, Karla L.; Rushworth, Matthew F. S.; Baxter, Mark G.

2013-01-01

In the absence of external stimuli or task demands, correlations in spontaneous brain activity (functional connectivity) reflect patterns of anatomical connectivity. Hence, resting-state functional connectivity has been used as a proxy measure for structural connectivity and as a biomarker for brain changes in disease. To relate changes in functional connectivity to physiological changes in the brain, it is important to understand how correlations in functional connectivity depend on the physical integrity of brain tissue. The causal nature of this relationship has been called into question by patient data suggesting that decreased structural connectivity does not necessarily lead to decreased functional connectivity. Here we provide evidence for a causal but complex relationship between structural connectivity and functional connectivity: we tested interhemispheric functional connectivity before and after corpus callosum section in rhesus monkeys. We found that forebrain commissurotomy severely reduced interhemispheric functional connectivity, but surprisingly, this effect was greatly mitigated if the anterior commissure was left intact. Furthermore, intact structural connections increased their functional connectivity in line with the hypothesis that the inputs to each node are normalized. We conclude that functional connectivity is likely driven by corticocortical white matter connections but with complex network interactions such that a near-normal pattern of functional connectivity can be maintained by just a few indirect structural connections. These surprising results highlight the importance of network-level interactions in functional connectivity and may cast light on various paradoxical findings concerning changes in functional connectivity in disease states. PMID:23924609

A method based on Monte Carlo simulations and voxelized anatomical atlases to evaluate and correct uncertainties on radiotracer accumulation quantitation in beta microprobe studies in the rat brain

NASA Astrophysics Data System (ADS)

Pain, F.; Dhenain, M.; Gurden, H.; Routier, A. L.; Lefebvre, F.; Mastrippolito, R.; Lanièce, P.

2008-10-01

The β-microprobe is a simple and versatile technique complementary to small animal positron emission tomography (PET). It relies on local measurements of the concentration of positron-labeled molecules. So far, it has been successfully used in anesthetized rats for pharmacokinetics experiments and for the study of brain energetic metabolism. However, the ability of the technique to provide accurate quantitative measurements using 18F, 11C and 15O tracers is likely to suffer from the contribution of 511 keV gamma rays background to the signal and from the contribution of positrons from brain loci surrounding the locus of interest. The aim of the present paper is to provide a method of evaluating several parameters, which are supposed to affect the quantification of recordings performed in vivo with this methodology. We have developed realistic voxelized phantoms of the rat whole body and brain, and used them as input geometries for Monte Carlo simulations of previous β-microprobe reports. In the context of realistic experiments (binding of 11C-Raclopride to D2 dopaminergic receptors in the striatum; local glucose metabolic rate measurement with 18F-FDG and H2O15 blood flow measurements in the somatosensory cortex), we have calculated the detection efficiencies and corresponding contribution of 511 keV gammas from peripheral organs accumulation. We confirmed that the 511 keV gammas background does not impair quantification. To evaluate the contribution of positrons from adjacent structures, we have developed β-Assistant, a program based on a rat brain voxelized atlas and matrices of local detection efficiencies calculated by Monte Carlo simulations for several probe geometries. This program was used to calculate the 'apparent sensitivity' of the probe for each brain structure included in the detection volume. For a given localization of a probe within the brain, this allows us to quantify the different sources of beta signal. Finally, since stereotaxic accuracy is crucial for quantification in most microprobe studies, the influence of stereotaxic positioning error was studied for several realistic experiments in favorable and unfavorable experimental situations (binding of 11C-Raclopride to D2 dopaminergic receptors in the striatum; binding of 18F-MPPF to 5HT1A receptors in the dorsal raphe nucleus).

Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge.

PubMed

Cash, David M; Frost, Chris; Iheme, Leonardo O; Ünay, Devrim; Kandemir, Melek; Fripp, Jurgen; Salvado, Olivier; Bourgeat, Pierrick; Reuter, Martin; Fischl, Bruce; Lorenzi, Marco; Frisoni, Giovanni B; Pennec, Xavier; Pierson, Ronald K; Gunter, Jeffrey L; Senjem, Matthew L; Jack, Clifford R; Guizard, Nicolas; Fonov, Vladimir S; Collins, D Louis; Modat, Marc; Cardoso, M Jorge; Leung, Kelvin K; Wang, Hongzhi; Das, Sandhitsu R; Yushkevich, Paul A; Malone, Ian B; Fox, Nick C; Schott, Jonathan M; Ourselin, Sebastien

2015-12-01

Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer's disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated "direct" measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer's disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: -1.4% to -2.2% (AD) and -0.35% to -0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: -1.5% to -7.0% (AD) and -0.4% to -1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods. Copyright © 2015. Published by Elsevier Inc.

Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge

PubMed Central

Cash, David M.; Frost, Chris; Iheme, Leonardo O.; Ünay, Devrim; Kandemir, Melek; Fripp, Jurgen; Salvado, Olivier; Bourgeat, Pierrick; Reuter, Martin; Fischl, Bruce; Lorenzi, Marco; Frisoni, Giovanni B.; Pennec, Xavier; Pierson, Ronald K.; Gunter, Jeffrey L.; Senjem, Matthew L.; Jack, Clifford R.; Guizard, Nicolas; Fonov, Vladimir S.; Collins, D. Louis; Modat, Marc; Cardoso, M. Jorge; Leung, Kelvin K.; Wang, Hongzhi; Das, Sandhitsu R.; Yushkevich, Paul A.; Malone, Ian B.; Fox, Nick C.; Schott, Jonathan M.; Ourselin, Sebastien

2015-01-01

Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer's disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated “direct” measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer's disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24 months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: − 1.4% to − 2.2% (AD) and − 0.35% to − 0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: − 1.5% to − 7.0% (AD) and − 0.4% to − 1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12 month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods. PMID:26275383

The Structural Connectivity Underpinning Language Aptitude, Working Memory, and IQ in the Perisylvian Language Network

ERIC Educational Resources Information Center

Xiang, Huadong; Dediu, Dan; Roberts, Leah; van Oort, Erik; Norris, David G.; Hagoort, Peter

2012-01-01

In this article, we report the results of a study on the relationship between individual differences in language learning aptitude and the structural connectivity of language pathways in the adult brain, the first of its kind. We measured four components of language aptitude ("vocabulary learning"; "sound recognition"; "sound-symbol…

Examining brain structures associated with the motive to achieve success and the motive to avoid failure: A voxel-based morphometry study.

PubMed

Ming, Dan; Chen, Qunlin; Yang, Wenjing; Chen, Rui; Wei, Dongtao; Li, Wenfu; Qiu, Jiang; Xu, Zhan; Zhang, Qinglin

2016-01-01

The motive to achieve success (MAS) and motive to avoid failure (MAF) are two different but classical kinds of achievement motivation. Though many functional magnetic resonance imaging studies have explored functional activation in motivation-related conditions, research has been silent as to the brain structures associated with individual differences in achievement motivation, especially with respect to MAS and MAF. In this study, the voxel-based morphometry method was used to uncover focal differences in brain structures related to MAS and MAF measured by the Mehrabian Achieving Tendency Scale in 353 healthy young Chinese adults. The results showed that the brain structures associated with individual differences in MAS and MAF were distinct. MAS was negatively correlated with regional gray matter volume (rGMV) in the medial prefrontal cortex (mPFC)/orbitofrontal cortex while MAF was negatively correlated with rGMV in the mPFC/subgenual cingulate gyrus. After controlling for mutual influences of MAS and MAF scores, MAS scores were found to be related to rGMV in the mPFC/orbitofrontal cortex and another cluster containing the parahippocampal gyrus and precuneus. These results may predict that compared with MAF, the generation process of MAS may be more complex and rational, thus in the real world, perhaps MAS is more beneficial to personal growth and guaranteeing the quality of task performance.

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

Revealing mesoscopic structural universality with diffusion

PubMed Central

Novikov, Dmitry S.; Jensen, Jens H.; Helpern, Joseph A.; Fieremans, Els

2014-01-01

Measuring molecular diffusion is widely used for characterizing materials and living organisms noninvasively. This characterization relies on relations between macroscopic diffusion metrics and structure at the mesoscopic scale commensurate with the diffusion length. Establishing such relations remains a fundamental challenge, hindering progress in materials science, porous media, and biomedical imaging. Here we show that the dynamical exponent in the time dependence of the diffusion coefficient distinguishes between the universality classes of the mesoscopic structural complexity. Our approach enables the interpretation of diffusion measurements by objectively selecting and modeling the most relevant structural features. As an example, the specific values of the dynamical exponent allow us to identify the relevant mesoscopic structure affecting MRI-measured water diffusion in muscles and in brain, and to elucidate the structural changes behind the decrease of diffusion coefficient in ischemic stroke. PMID:24706873

Brain Imaging and Blood Biomarker Abnormalities in Children With Autosomal Dominant Alzheimer Disease: A Cross-Sectional Study.

PubMed

Quiroz, Yakeel T; Schultz, Aaron P; Chen, Kewei; Protas, Hillary D; Brickhouse, Michael; Fleisher, Adam S; Langbaum, Jessica B; Thiyyagura, Pradeep; Fagan, Anne M; Shah, Aarti R; Muniz, Martha; Arboleda-Velasquez, Joseph F; Munoz, Claudia; Garcia, Gloria; Acosta-Baena, Natalia; Giraldo, Margarita; Tirado, Victoria; Ramírez, Dora L; Tariot, Pierre N; Dickerson, Bradford C; Sperling, Reisa A; Lopera, Francisco; Reiman, Eric M

2015-08-01

Brain imaging and fluid biomarkers are characterized in children at risk for autosomal dominant Alzheimer disease (ADAD). To characterize and compare structural magnetic resonance imaging (MRI), resting-state and task-dependent functional MRI, and plasma amyloid-β (Aβ) measurements in presenilin 1 (PSEN1) E280A mutation-carrying and noncarrying children with ADAD. Cross-sectional measures of structural and functional MRI and plasma Aβ assays were assessed in 18 PSEN1 E280A carriers and 19 noncarriers aged 9 to 17 years from a Colombian kindred with ADAD. Recruitment and data collection for this study were conducted at the University of Antioquia and the Hospital Pablo Tobon Uribe in Medellín, Colombia, between August 2011 and June 2012. All participants had blood sampling, structural MRI, and functional MRI during associative memory encoding and resting-state and cognitive assessments. Outcome measures included plasma Aβ1-42 concentrations and Aβ1-42:Aβ1-40 ratios, memory encoding-dependent activation changes, resting-state connectivity, and regional gray matter volumes. Structural and functional MRI data were compared using automated brain mapping algorithms and search regions related to AD. Similar to findings in adult mutation carriers, in the later preclinical and clinical stages of ADAD, mutation-carrying children were distinguished from control individuals by significantly higher plasma Aβ1-42 levels (mean [SD]: carriers, 18.8 [5.1] pg/mL and noncarriers, 13.1 [3.2] pg/mL; P < .001) and Aβ1-42:Aβ1-40 ratios (mean [SD]: carriers, 0.32 [0.06] and noncarriers, 0.21 [0.03]; P < .001), as well as less memory encoding task-related deactivation in parietal regions (eg, mean [SD] parameter estimates for the right precuneus were -0.590 [0.50] for noncarriers and -0.087 [0.38] for carriers; P < .005 uncorrected). Unlike carriers in the later stages, mutation-carrying children demonstrated increased functional connectivity of the posterior cingulate cortex with medial temporal lobe regions (mean [SD] parameter estimates were 0.038 [0.070] for noncarriers and 0.190 [0.057] for carriers), as well as greater gray matter volumes in temporal regions (eg, left parahippocampus; P < . 049, corrected for multiple comparisons). Children at genetic risk for ADAD have functional and structural brain changes and abnormal levels of plasma Aβ1-42. The extent to which the underlying brain changes are either neurodegenerative or developmental remains to be determined. This study provides additional information about the earliest known biomarker changes associated with ADAD.

Changes in Structural Connectivity Following a Cognitive Intervention in Children With Traumatic Brain Injury.

PubMed

Yuan, Weihong; Treble-Barna, Amery; Sohlberg, McKay M; Harn, Beth; Wade, Shari L

2017-02-01

Structural connectivity analysis based on graph theory and diffusion tensor imaging tractography is a novel method that quantifies the topological characteristics in the brain network. This study aimed to examine structural connectivity changes following the Attention Intervention and Management (AIM) program designed to improve attention and executive function (EF) in children with traumatic brain injury (TBI). Seventeen children with complicated mild to severe TBI (13.66 ± 2.68 years; >12 months postinjury) completed magnetic resonance imaging (MRI) and neurobehavioral measures at time 1, 10 of whom completed AIM and assessment at time 2. Eleven matched healthy comparison (HC) children (13.37 ± 2.08 years) completed MRI and neurobehavioral assessment at both time points, but did not complete AIM. Network characteristics were analyzed to quantify the structural connectivity before and after the intervention. Mixed model analyses showed that small-worldness was significantly higher in the TBI group than the HC group at time 1, and both small-worldness and normalized clustering coefficient decreased significantly at time 2 in the TBI group whereas the HC group remained relatively unchanged. Reductions in mean local efficiency were significantly correlated with improvements in verbal inhibition and both parent- and child-reported EF. Increased normalized characteristic path length was significantly correlated with improved sustained attention. The results provide preliminary evidence suggesting that graph theoretical analysis may be a sensitive tool in pediatric TBI for detecting ( a) abnormalities of structural connectivity in brain network and ( b) structural neuroplasticity associated with neurobehavioral improvement following a short-term intervention for attention and EF.

Composite technique for regional neurochemical studies: measurement of energy and neurotransmitter metabolites in single tissue sample.

PubMed

Djuricic, B M; Ueki, Y; Spatz, M

1985-06-01

A combined method is described for the determination of various metabolites from a single tissue sample of the brain. It comprises a quick inactivation of cerebral enzymes by microwave irradiation, easy separation of the desired brain regions, and perchloric acid extraction of tissue substances, which are assayed either by specific enzymatic techniques or by HPLC with electrochemical detection. The obtained values of most energy and neurotransmitter metabolites in the brain are in agreement with those reported using other methods. However, this technique, in contrast to the brain freezing in vitro or freeze-blowing, provides a more efficient procedure for rapid arrest of cerebral metabolism even in the deep brain structures and is therefore suitable for detection of early changes particularly those occurring in experimental pathological conditions such as ischemia.

Neurobiology of Schizophrenia: Search for the Elusive Correlation with Symptoms

PubMed Central

Mathalon, Daniel H.; Ford, Judith M.

2012-01-01

In the last half-century, human neuroscience methods provided a way to study schizophrenia in vivo, and established that it is associated with subtle abnormalities in brain structure and function. However, efforts to understand the neurobiological bases of the clinical symptoms that the diagnosis is based on have been largely unsuccessful. In this paper, we provide an overview of the conceptual and methodological obstacles that undermine efforts to link the severity of specific symptoms to specific neurobiological measures. These obstacles include small samples, questionable reliability and validity of measurements, medication confounds, failure to distinguish state and trait effects, correlation–causation ambiguity, and the absence of compelling animal models of specific symptoms to test mechanistic hypotheses derived from brain-symptom correlations. We conclude with recommendations to promote progress in establishing brain-symptom relationships. PMID:22654745

Traffic pollution exposure is associated with altered brain connectivity in school children.

PubMed

Pujol, Jesus; Martínez-Vilavella, Gerard; Macià, Dídac; Fenoll, Raquel; Alvarez-Pedrerol, Mar; Rivas, Ioar; Forns, Joan; Blanco-Hinojo, Laura; Capellades, Jaume; Querol, Xavier; Deus, Joan; Sunyer, Jordi

2016-04-01

Children are more vulnerable to the effects of environmental elements due to their active developmental processes. Exposure to urban air pollution has been associated with poorer cognitive performance, which is thought to be a result of direct interference with brain maturation. We aimed to assess the extent of such potential effects of urban pollution on child brain maturation using general indicators of vehicle exhaust measured in the school environment and a comprehensive imaging evaluation. A group of 263 children, aged 8 to 12 years, underwent MRI to quantify regional brain volumes, tissue composition, myelination, cortical thickness, neural tract architecture, membrane metabolites, functional connectivity in major neural networks and activation/deactivation dynamics during a sensory task. A combined measurement of elemental carbon and NO2 was used as a putative marker of vehicle exhaust. Air pollution exposure was associated with brain changes of a functional nature, with no evident effect on brain anatomy, structure or membrane metabolites. Specifically, a higher content of pollutants was associated with lower functional integration and segregation in key brain networks relevant to both inner mental processes (the default mode network) and stimulus-driven mental operations. Age and performance (motor response speed) both showed the opposite effect to that of pollution, thus indicating that higher exposure is associated with slower brain maturation. In conclusion, urban air pollution appears to adversely affect brain maturation in a critical age with changes specifically concerning the functional domain. Copyright © 2016 Elsevier Inc. All rights reserved.

Different Measures of Structural Similarity Tap Different Aspects of Visual Object Processing

PubMed Central

Gerlach, Christian

2017-01-01

The structural similarity of objects has been an important variable in explaining why some objects are easier to categorize at a superordinate level than to individuate, and also why some patients with brain injury have more difficulties in recognizing natural (structurally similar) objects than artifacts (structurally distinct objects). In spite of its merits as an explanatory variable, structural similarity is not a unitary construct, and it has been operationalized in different ways. Furthermore, even though measures of structural similarity have been successful in explaining task and category-effects, this has been based more on implication than on direct empirical demonstrations. Here, the direct influence of two different measures of structural similarity, contour overlap and within-item structural diversity, on object individuation (object decision) and superordinate categorization performance is examined. Both measures can account for performance differences across objects, but in different conditions. It is argued that this reflects differences between the measures in whether they tap: (i) global or local shape characteristics, and (ii) between- or within-category structural similarity. PMID:28861027

Individual differences in brain structure and resting brain function underlie cognitive styles: evidence from the Embedded Figures Test.

PubMed

Hao, Xin; Wang, Kangcheng; Li, Wenfu; Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Qinglin

2013-01-01

Cognitive styles can be characterized as individual differences in the way people perceive, think, solve problems, learn, and relate to others. Field dependence/independence (FDI) is an important and widely studied dimension of cognitive styles. Although functional imaging studies have investigated the brain activation of FDI cognitive styles, the combined structural and functional correlates with individual differences in a large sample have never been investigated. In the present study, we investigated the neural correlates of individual differences in FDI cognitive styles by analyzing the correlations between Embedded Figures Test (EFT) score and structural neuroimaging data [regional gray matter volume (rGMV) was assessed using voxel-based morphometry (VBM)]/functional neuroimaging data [resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF)] throughout the whole brain. Results showed that the increased rGMV in the left inferior parietal lobule (IPL) was associated with the EFT score, which might be the structural basis of effective local processing. Additionally, a significant positive correlation between ALFF and EFT score was found in the fronto-parietal network, including the left inferior parietal lobule (IPL) and the medial prefrontal cortex (mPFC). We speculated that the left IPL might be associated with superior feature identification, and mPFC might be related to cognitive inhibition of global processing bias. These results suggested that the underlying neuroanatomical and functional bases were linked to the individual differences in FDI cognitive styles and emphasized the important contribution of superior local processing ability and cognitive inhibition to field-independent style.

Individual Differences in Brain Structure and Resting Brain Function Underlie Cognitive Styles: Evidence from the Embedded Figures Test

PubMed Central

Hao, Xin; Wang, Kangcheng; Li, Wenfu; Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Qinglin

2013-01-01

Cognitive styles can be characterized as individual differences in the way people perceive, think, solve problems, learn, and relate to others. Field dependence/independence (FDI) is an important and widely studied dimension of cognitive styles. Although functional imaging studies have investigated the brain activation of FDI cognitive styles, the combined structural and functional correlates with individual differences in a large sample have never been investigated. In the present study, we investigated the neural correlates of individual differences in FDI cognitive styles by analyzing the correlations between Embedded Figures Test (EFT) score and structural neuroimaging data [regional gray matter volume (rGMV) was assessed using voxel-based morphometry (VBM)] / functional neuroimaging data [resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF)] throughout the whole brain. Results showed that the increased rGMV in the left inferior parietal lobule (IPL) was associated with the EFT score, which might be the structural basis of effective local processing. Additionally, a significant positive correlation between ALFF and EFT score was found in the fronto-parietal network, including the left inferior parietal lobule (IPL) and the medial prefrontal cortex (mPFC). We speculated that the left IPL might be associated with superior feature identification, and mPFC might be related to cognitive inhibition of global processing bias. These results suggested that the underlying neuroanatomical and functional bases were linked to the individual differences in FDI cognitive styles and emphasized the important contribution of superior local processing ability and cognitive inhibition to field-independent style. PMID:24348991

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Sustained effects of ecstasy on the human brain: a prospective neuroimaging study in novel users.

PubMed

de Win, Maartje M L; Jager, Gerry; Booij, Jan; Reneman, Liesbeth; Schilt, Thelma; Lavini, Cristina; Olabarriaga, Sílvia D; den Heeten, Gerard J; van den Brink, Wim

2008-11-01

Previous studies have suggested toxic effects of recreational ecstasy use on the serotonin system of the brain. However, it cannot be excluded that observed differences between users and non-users are the cause rather than the consequence of ecstasy use. As part of the Netherlands XTC Toxicity (NeXT) study, we prospectively assessed sustained effects of ecstasy use on the brain in novel ecstasy users using repeated measurements with a combination of different neuroimaging parameters of neurotoxicity. At baseline, 188 ecstasy-naive volunteers with high probability of first ecstasy use were examined. After a mean period of 17 months follow-up, neuroimaging was repeated in 59 incident ecstasy users and 56 matched persistent ecstasy-naives and their outcomes were compared. Neuroimaging included [(123)I]beta-carbomethoxy-3beta-(4-iodophenyl)tropane (CIT) SPECT to measure serotonin transporter densities as indicators of serotonergic function; (1)H-MR spectroscopy ((1)H-MRS) to measure brain metabolites as indicators of neuronal damage; diffusion tensor imaging (DTI) to measure the apparent diffusion coefficient and fractional anisotropy (FA) of the diffusional motion of water molecules in the brain as indicators of axonal integrity; and perfusion weighted imaging (PWI) to measure regional relative cerebral blood volume (rrCBV) which indicates brain perfusion. With this approach, both structural ((1)H-MRS and DTI) and functional ([(123)I]beta-CIT SPECT and PWI) aspects of neurotoxicity were combined. Compared to persistent ecstasy-naives, novel low-dose ecstasy users (mean 6.0, median 2.0 tablets) showed decreased rrCBV in the globus pallidus and putamen; decreased FA in thalamus and frontoparietal white matter; increased FA in globus pallidus; and increased apparent diffusion coefficient in the thalamus. No changes in serotonin transporter densities and brain metabolites were observed. These findings suggest sustained effects of ecstasy on brain microvasculature, white matter maturation and possibly axonal damage due to low dosages of ecstasy. Although we do not know yet whether these effects are reversible or not, we cannot exclude that ecstasy even in low doses is neurotoxic to the brain.

Functional connectivity and structural covariance between regions of interest can be measured more accurately using multivariate distance correlation.

PubMed

Geerligs, Linda; Cam-Can; Henson, Richard N

2016-07-15

Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on "distance correlation"; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across sessions, 2) more similar across participants, and 3) more robust to different sets of ROIs. Moreover, we found that the similarity between functional connectivity and structural covariance estimates was higher for distance correlation compared to Pearson correlation. We also explored the relative effects of different preprocessing options and motion artefacts on functional connectivity. Because distance correlation is easy to implement and fast to compute, it is a promising alternative to Pearson correlations for investigating ROI-based brain-wide connectivity patterns, for functional as well as structural data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Brain Metabolism Correlates of the Free and Cued Selective Reminding Test in Mild Cognitive Impairment.

PubMed

Caffarra, Paolo; Ghetti, Caterina; Ruffini, Livia; Spallazzi, Marco; Spotti, Annamaria; Barocco, Federica; Guzzo, Caterina; Marchi, Massimo; Gardini, Simona

2016-01-01

Free and Cued Selective Reminding Test (FCSRT) measures immediate and delayed episodic memory and cueing sensitivity and is suitable to detect prodromal Alzheimer's disease (AD). The present study aimed at investigating the segregation effect of FCSRT scores on brain metabolism of memory-related structures, usually affected by AD pathology, in the Mild Cognitive Impairment (MCI) stage. A cohort of forty-eight MCI patients underwent FCSRT and 18F-FDG-PET. Multiple regression analysis showed that Immediate Free Recall correlated with brain metabolism in the bilateral anterior cingulate and delayed free recall with the left anterior cingulate and medial frontal gyrus, whereas semantic cueing sensitivity with the left posterior cingulate. FCSRT in MCI is associated with neuro-functional activity of specific regions of memory-related structures connected to hippocampal formation, such as the cingulate cortex, usually damaged in AD.

Estimating intracranial volume using intracranial area in healthy children and those with childhood status epilepticus

PubMed Central

Piper, Rory J; Yoong, Michael M; Pujar, Suresh; Chin, Richard F

2014-01-01

Background Correcting volumetric measurements of brain structures for intracranial volume (ICV) is important in comparing volumes across subjects with different ICV. The aim of this study was to investigate whether intracranial area (ICA) reliably predicts actual ICV in a healthy pediatric cohort and in children with convulsive status epilepticus (CSE). Methods T1-weighted volumetric MRI was performed on 20 healthy children (control group), 10 with CSE with structurally normal MRI (CSE/MR-), and 12 with CSE with structurally abnormal MRI (CSE/MR+). ICA, using a mid-sagittal slice, and the actual ICV were measured. Results A high Spearman correlation was found between the ICA and ICV measurements in the control (r = 0.96; P < 0.0001), CSE/MR− (r = 0.93; P = 0.0003), and CSE/MR+ (r = 0.94; P < 0.0001) groups. On comparison of predicted and actual ICV, there was no significant difference in the CSE/MR− group (P = 0.77). However, the comparison between predicted and actual ICV was significantly different in the CSE/MR+ (P = 0.001) group. Our Bland–Altman plot showed that the ICA method consistently overestimated ICV in children in the CSE/MR+ group, especially in those with small ICV or widespread structural abnormalities. Conclusions After further validation, ICA measurement may be a reliable alternative to measuring actual ICV when correcting volume measurements for ICV, even in children with localized MRI abnormalities. Caution should be applied when the method is used in children with small ICV and those with multilobar brain pathology. PMID:25365798

Cognitive Function and Brain Structure in Persons With Type 2 Diabetes Mellitus After Intensive Lowering of Blood Pressure and Lipid Levels

PubMed Central

Williamson, Jeff D.; Launer, Lenore J.; Bryan, R. Nick; Coker, Laura H.; Lazar, Ronald M.; Gerstein, Hertzel C.; Murray, Anne M.; Sullivan, Mark D.; Horowitz, Karen R.; Ding, Jingzhong; Marcovina, Santica; Lovato, Laura; Lovato, James; Margolis, Karen L.; Davatzikos, Christos; Barzilay, Joshua; Ginsberg, Henry N.; Linz, Peter E.; Miller, Michael E.

2015-01-01

IMPORTANCE Persons with type 2 diabetes mellitus (T2DM) are at increased risk for decline in cognitive function, reduced brain volume, and increased white matter lesions in the brain. Poor control of blood pressure (BP) and lipid levels are risk factors for T2DM-related cognitive decline, but the effect of intensive treatment on brain function and structure is unknown. OBJECTIVE To examine whether intensive therapy for hypertension and combination therapy with a statin plus a fibrate reduces the risk of decline in cognitive function and total brain volume (TBV) in patients with T2DM. DESIGN, SETTING, AND PARTICIPANTS A North American multicenter clinical trial including 2977 participants without baseline clinical evidence of cognitive impairment or dementia and with hemoglobin A1c (HbA1c) levels less than 7.5% randomized to a systolic BP goal of less than 120 vs less than 140 mm Hg (n = 1439) or to a fibrate vs placebo in patients with low-density lipoprotein cholesterol levels less than 100 mg/dL (n = 1538). Participants were recruited from August 1, 2003, through October 31, 2005, with the final follow-up visit by June 30, 2009. MAIN OUTCOME MEASURES Cognition was assessed at baseline and 20 and 40 months. A subset of 503 participants underwent baseline and 40-month brain magnetic resonance imaging to assess for change in TBV and other structural measures of brain health. RESULTS Baseline mean HbA1c level was 8.3%; mean age, 62 years; and mean duration of T2DM, 10 years. At 40 months, no differences in cognitive function were found in the intensive BP-lowering trial or in the fibrate trial. At 40 months, TBV had declined more in the intensive vs standard BP-lowering group (difference, −4.4 [95% CI, −7.8 to −1.1] cm3; P = .01). Fibrate therapy had no effect on TBV compared with placebo. CONCLUSIONS AND RELEVANCE In participants with long-standing T2DM and at high risk for cardiovascular events, intensive BP control and fibrate therapy in the presence of controlled low-density lipoprotein cholesterol levels did not produce a measurable effect on cognitive decline at 40 months of follow-up. Intensive BP control was associated with greater decline in TBV at 40 months relative to standard therapy. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00000620 PMID:24493100

Aging and Visual Attention

PubMed Central

Madden, David J.

2007-01-01

Older adults are often slower and less accurate than are younger adults in performing visual-search tasks, suggesting an age-related decline in attentional functioning. Age-related decline in attention, however, is not entirely pervasive. Visual search that is based on the observer’s expectations (i.e., top-down attention) is relatively preserved as a function of adult age. Neuroimaging research suggests that age-related decline occurs in the structure and function of brain regions mediating the visual sensory input, whereas activation of regions in the frontal and parietal lobes is often greater for older adults than for younger adults. This increased activation may represent an age-related increase in the role of top-down attention during visual tasks. To obtain a more complete account of age-related decline and preservation of visual attention, current research is beginning to explore the relation of neuroimaging measures of brain structure and function to behavioral measures of visual attention. PMID:18080001

Structural Growth Trajectories and Rates of Change in the First 3 Months of Infant Brain Development

PubMed Central

Holland, Dominic; Chang, Linda; Ernst, Thomas M.; Curran, Megan; Buchthal, Steven D.; Alicata, Daniel; Skranes, Jon; Johansen, Heather; Hernandez, Antonette; Yamakawa, Robyn; Kuperman, Joshua M.; Dale, Anders M.

2016-01-01

IMPORTANCE The very early postnatal period witnesses extraordinary rates of growth, but structural brain development in this period has largely not been explored longitudinally. Such assessment may be key in detecting and treating the earliest signs of neurodevelopmental disorders. OBJECTIVE To assess structural growth trajectories and rates of change in the whole brain and regions of interest in infants during the first 3 months after birth. DESIGN, SETTING, AND PARTICIPANTS Serial structural T1-weighted and/or T2-weighted magnetic resonance images were obtained for 211 time points from 87 healthy term-born or term-equivalent preterm-born infants, aged 2 to 90 days, between October 5, 2007, and June 12, 2013. MAIN OUTCOMES AND MEASURES We segmented whole-brain and multiple subcortical regions of interest using a novel application of Bayesian-based methods. We modeled growth and rate of growth trajectories nonparametrically and assessed left-right asymmetries and sexual dimorphisms. RESULTS Whole-brain volume at birth was approximately one-third of healthy elderly brain volume, and did not differ significantly between male and female infants (347 388 mm3 and 335 509 mm3, respectively, P = .12). The growth rate was approximately 1%/d, slowing to 0.4%/d by the end of the first 3 months, when the brain reached just more than half of elderly adult brain volume. Overall growth in the first 90 days was 64%. There was a significant age-by-sex effect leading to widening separation in brain sizes with age between male and female infants (with male infants growing faster than females by 200.4 mm3/d, SE = 67.2, P = .003). Longer gestation was associated with larger brain size (2215 mm3/d, SE = 284, P = 4×10−13). The expected brain size of an infant born one week earlier than average was 5% smaller than average; at 90 days it will not have caught up, being 2% smaller than average. The cerebellum grew at the highest rate, more than doubling in 90 days, and the hippocampus grew at the slowest rate, increasing by 47% in 90 days. There was left-right asymmetry in multiple regions of interest, particularly the lateral ventricles where the left was larger than the right by 462 mm3 on average (approximately 5% of lateral ventricular volume at 2 months). We calculated volume-by-age percentile plots for assessing individual development. CONCLUSIONS AND RELEVANCE Normative trajectories for early postnatal brain structural development can be determined from magnetic resonance imaging and could be used to improve the detection of deviant maturational patterns indicative of neurodevelopmental disorders. PMID:25111045

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI)

PubMed Central

Hainsworth, A. H.; Lee, S.; Patel, A.; Poon, W. W.; Knight, A. E.

2018-01-01

Aims The spatial resolution of light microscopy is limited by the wavelength of visible light (the ‘diffraction limit’, approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Methods Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8–32 nm) and for SOFI (effective pixel size 80 nm). Results In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Conclusions Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. PMID:28696566

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI).

PubMed

Hainsworth, A H; Lee, S; Foot, P; Patel, A; Poon, W W; Knight, A E

2018-06-01

The spatial resolution of light microscopy is limited by the wavelength of visible light (the 'diffraction limit', approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8-32 nm) and for SOFI (effective pixel size 80 nm). In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. © 2017 British Neuropathological Society.

Analysis of the Metabolic and Structural Brain Changes in Patients With Torture-Related Post-Traumatic Stress Disorder (TR-PTSD) Using 18F-FDG PET and MRI

PubMed Central

Zandieh, Shahin; Bernt, Reinhard; Knoll, Peter; Wenzel, Thomas; Hittmair, Karl; Haller, Joerg; Hergan, Klaus; Mirzaei, Siroos

2016-01-01

Abstract Many people exposed to torture later suffer from torture-related post-traumatic stress disorder (TR-PTSD). The aim of this study was to analyze the morphologic and functional brain changes in patients with TR-PTSD using magnetic resonance imaging (MRI) and positron emission tomography (PET). This study evaluated 19 subjects. Thirteen subcortical brain structures were evaluated using FSL software. On the T1-weighted images, normalized brain volumes were measured using SIENAX software. The study compared the volume of the brain and 13 subcortical structures in 9 patients suffering from TR-PTSD after torture and 10 healthy volunteers (HV). Diffusion-weighted imaging (DWI) was performed in the transverse plane. In addition, the 18F-FDG PET data were evaluated to identify the activity of the elected regions. The mean left hippocampal volume for the TR-PTSD group was significantly lower than in the HV group (post hoc test (Bonferroni) P < 0.001). There was a significant difference between the gray matter volume of the patients with TR-PTSD and the HV group (post hoc test (Bonferroni) P < 0.001). The TR-PTSD group showed low significant expansion of the ventricles in contrast to the HV group (post hoc test (Bonferroni) P < 0.001). Diffusion-weighted imaging revealed significant differences in the right frontal lobe and the left occipital lobe between the TR-PTSD and HV group (post hoc test (Bonferroni) P < 0.001). Moderate hypometabolism was noted in the occipital lobe in 6 of the 9 patients with TR-PTSD, in the temporal lobe in 1 of the 9 patients, and in the caudate nucleus in 5 of the 9 patients. In 2 cases, additional hypometabolism was observed in the posterior cingulate cortex and in the parietal and frontal lobes. The findings from this study show that TR-PTSD might have a deleterious influence on a set of specific brain structures. This study also demonstrated that PET combined with MRI is sensitive in detecting possible metabolic and structural brain changes in TR-PTSD. PMID:27082610

Analysis of the Metabolic and Structural Brain Changes in Patients With Torture-Related Post-Traumatic Stress Disorder (TR-PTSD) Using ¹⁸F-FDG PET and MRI.

PubMed

Zandieh, Shahin; Bernt, Reinhard; Knoll, Peter; Wenzel, Thomas; Hittmair, Karl; Haller, Joerg; Hergan, Klaus; Mirzaei, Siroos

2016-04-01

Many people exposed to torture later suffer from torture-related post-traumatic stress disorder (TR-PTSD). The aim of this study was to analyze the morphologic and functional brain changes in patients with TR-PTSD using magnetic resonance imaging (MRI) and positron emission tomography (PET). This study evaluated 19 subjects. Thirteen subcortical brain structures were evaluated using FSL software. On the T1-weighted images, normalized brain volumes were measured using SIENAX software. The study compared the volume of the brain and 13 subcortical structures in 9 patients suffering from TR-PTSD after torture and 10 healthy volunteers (HV). Diffusion-weighted imaging (DWI) was performed in the transverse plane. In addition, the 18F-FDG PET data were evaluated to identify the activity of the elected regions. The mean left hippocampal volume for the TR-PTSD group was significantly lower than in the HV group (post hoc test (Bonferroni) P < 0.001). There was a significant difference between the gray matter volume of the patients with TR-PTSD and the HV group (post hoc test (Bonferroni) P < 0.001). The TR-PTSD group showed low significant expansion of the ventricles in contrast to the HV group (post hoc test (Bonferroni) P < 0.001). Diffusion-weighted imaging revealed significant differences in the right frontal lobe and the left occipital lobe between the TR-PTSD and HV group (post hoc test (Bonferroni) P < 0.001). Moderate hypometabolism was noted in the occipital lobe in 6 of the 9 patients with TR-PTSD, in the temporal lobe in 1 of the 9 patients, and in the caudate nucleus in 5 of the 9 patients. In 2 cases, additional hypometabolism was observed in the posterior cingulate cortex and in the parietal and frontal lobes. The findings from this study show that TR-PTSD might have a deleterious influence on a set of specific brain structures. This study also demonstrated that PET combined with MRI is sensitive in detecting possible metabolic and structural brain changes in TR-PTSD.

[The Application of Magnetic Resonance Imaging in Alzheimer's Disease].

PubMed

Matsuda, Hiroshi

2017-07-01

In Alzheimer's disease (AD), magnetic resonance imaging (MRI) is essential for early diagnosis, differential diagnosis, and evaluation of disease progression. In structural MRI, the automatic diagnosis of atrophy by computers, even when it is not visually noticeable, is possible in daily clinical practice. Furthermore, subfield volumetric measurements of the medial temporal structures, as well as longitudinal volume measurements with high accuracy, have been developed and are useful for calculating the needed sample size in clinical trials. In addition to detecting local atrophy, graph theory has been applied to structural MRI for evaluation of alterations of the brain networks potentially affected in AD.

Adiposity is associated with structural properties of the adolescent brain.

PubMed

Schwartz, Deborah H; Dickie, Erin; Pangelinan, Melissa M; Leonard, Gabriel; Perron, Michel; Pike, G Bruce; Richer, Louis; Veillette, Suzanne; Pausova, Zdenka; Paus, Tomáš

2014-12-01

Obesity, a major risk factor for cardiometabolic disease, is associated with variations in a number of structural properties in the adult brain, as assessed with magnetic resonance imaging (MRI). In this study, we investigated the cross-sectional relationship between visceral fat (VF), total body fat (TBF) and three MRI parameters in the brains of typically developing adolescents: (i) T1-weighted (T1W) signal intensity; (ii) T1W signal contrast between white matter (WM) and gray matter (GM); and (iii) magnetization transfer ratio (MTR). In a community-based sample of 970 adolescents (12-18 years old, 466 males), VF was quantified using MRI, and total body fat was measured using a multifrequency bioimpedance. T1W images of the brain were used to determine signal intensity in lobar GM and WM, as well as WM:GM signal contrast. A magnetization transfer (MT) sequence of MT(ON) and MT(OFF) was used to obtain MTR in GM and WM. We found that both larger volumes of VF and more TBF were independently associated with higher signal intensity in WM and higher WM:GM signal contrast, as well as higher MTR in both GM and WM. These relationships were independent of a number of potential confounders, including age, sex, puberty stage, household income and height. Our results suggest that both visceral fat and fat deposited elsewhere in the body are associated independently with structural properties of the adolescent brain. We speculate that these relationships suggest the presence of adiposity-related variations in phospholipid composition of brain lipids. Copyright © 2014. Published by Elsevier Inc.

Oxidative modification of lipoic acid by HNE in Alzheimer disease brain.

PubMed

Hardas, Sarita S; Sultana, Rukhsana; Clark, Amy M; Beckett, Tina L; Szweda, Luke I; Murphy, M Paul; Butterfield, D Allan

2013-01-01

Alzheimer disease (AD) is an age-related neurodegenerative disease characterized by the presence of three pathological hallmarks: synapse loss, extracellular senile plaques (SP) and intracellular neurofibrillary tangles (NFTs). The major component of SP is amyloid β-peptide (Aβ), which has been shown to induce oxidative stress. The AD brain shows increased levels of lipid peroxidation products, including 4-hydroxy-2-nonenal (HNE). HNE can react covalently with Cys, His, or Lys residues on proteins, altering structure and function of the latter. In the present study we measured the levels of the HNE-modified lipoic acid in brain of subjects with AD and age-matched controls. Lipoic acid is a key co-factor for a number of proteins including pyruvate dehydrogenase and α-ketoglutarate dehydrogenase, key complexes for cellular energetics. We observed a significant decrease in the levels of HNE-lipoic acid in the AD brain compared to that of age-matched controls. To investigate this phenomenon further, the levels and activity of lipoamide dehydrogenase (LADH) were measured in AD and control brains. Additionally, LADH activities were measured after in-vitro HNE-treatment to mice brains. Both LADH levels and activities were found to be significantly reduced in AD brain compared to age-matched control. HNE-treatment also reduced the LADH activity in mice brain. These data are consistent with a two-hit hypothesis of AD: oxidative stress leads to lipid peroxidation that, in turn, causes oxidative dysfunction of key energy-related complexes in mitochondria, triggering neurodegeneration. This study is consonant with the notion that lipoic acid supplementation could be a potential treatment for the observed loss of cellular energetics in AD and potentiate the antioxidant defense system to prevent or delay the oxidative stress in and progression of this devastating dementing disorder.

Antidepressant Effects of Electroconvulsive Therapy Correlate With Subgenual Anterior Cingulate Activity and Connectivity in Depression

PubMed Central

Liu, Yi; Du, Lian; Li, Yongmei; Liu, Haixia; Zhao, Wenjing; Liu, Dan; Zeng, Jinkun; Li, Xingbao; Fu, Yixiao; Qiu, Haitang; Li, Xirong; Qiu, Tian; Hu, Hua; Meng, Huaqing; Luo, Qinghua

2015-01-01

Abstract The mechanisms underlying the effects of electroconvulsive therapy (ECT) in major depressive disorder (MDD) are not fully understood. Resting-state functional magnetic resonance imaging (rs-fMRI) is a new tool to study the effects of brain stimulation interventions, particularly ECT. The authors aim to investigate the mechanisms of ECT in MDD by rs-fMRI. They used rs-fMRI to measure functional changes in the brain of first-episode, treatment-naive MDD patients (n = 23) immediately before and then following 8 ECT sessions (brief-pulse square-wave apparatus, bitemporal). They also computed voxel-wise amplitude of low-frequency fluctuation (ALFF) as a measure of regional brain activity and selected the left subgenual anterior cingulate cortex (sgACC) to evaluate functional connectivity between the sgACC and other brain regions. Increased regional brain activity measured by ALFF mainly in the left sgACC following ECT. Functional connectivity of the left sgACC increased in the ipsilateral parahippocampal gyrus, pregenual ACC, contralateral middle temporal pole, and orbitofrontal cortex. Importantly, reduction in depressive symptoms were negatively correlated with increased ALFF in the left sgACC and left hippocampus, and with distant functional connectivity between the left sgACC and contralateral middle temporal pole. That is, across subjects, as depression improved, regional brain activity in sgACC and its functional connectivity increased in the brain. Eight ECT sessions in MDD patients modulated activity in the sgACC and its networks. The antidepressant effects of ECT were negatively correlated with sgACC brain activity and connectivity. These findings suggest that sgACC-associated prefrontal-limbic structures are associated with the therapeutic effects of ECT in MDD. PMID:26559309

Neuropsychological function in type 2 diabetes mellitus.

PubMed

Nici, Janice; Hom, Jim

2018-05-04

Type 2 diabetes mellitus (DM) is a major and growing health problem. Brain-related effects of type 2 DM have been studied in several ways over the past few decades. Results have shown effects on brain structure, incidence of dementia, and impairment of various cognitive functions. The present study examined a sample of clinically-referred patients with type 2 DM and compared them with a sample of control patients who were matched on a pairwise basis on age, education, and gender. Each patient was tested using a comprehensive, integrated neuropsychological test battery. Results showed a pattern of generalized and specific neuropsychological dysfunction affecting a broad range of neurocognitive and sensorimotor abilities. However, no differences were found on measures of attention/concentration, memory, or abstract reasoning. Nevertheless, the DM group consistently performed worse on all measures. The DM group's score on a summary measure of neuropsychological function (GNDS) reflected moderate brain-related impairment. A neurocognitive profile is identified that may help clinicians understand their DM patients.

Physiological and psychological individual differences influence resting brain function measured by ASL perfusion.

PubMed

Kano, M; Coen, S J; Farmer, A D; Aziz, Q; Williams, S C R; Alsop, D C; Fukudo, S; O'Gorman, R L

2014-09-01

Effects of physiological and/or psychological inter-individual differences on the resting brain state have not been fully established. The present study investigated the effects of individual differences in basal autonomic tone and positive and negative personality dimensions on resting brain activity. Whole-brain resting cerebral perfusion images were acquired from 32 healthy subjects (16 males) using arterial spin labeling perfusion MRI. Neuroticism and extraversion were assessed with the Eysenck Personality Questionnaire-Revised. Resting autonomic activity was assessed using a validated measure of baseline cardiac vagal tone (CVT) in each individual. Potential associations between the perfusion data and individual CVT (27 subjects) and personality score (28 subjects) were tested at the level of voxel clusters by fitting a multiple regression model at each intracerebral voxel. Greater baseline perfusion in the dorsal anterior cingulate cortex (ACC) and cerebellum was associated with lower CVT. At a corrected significance threshold of p < 0.01, strong positive correlations were observed between extraversion and resting brain perfusion in the right caudate, brain stem, and cingulate gyrus. Significant negative correlations between neuroticism and regional cerebral perfusion were identified in the left amygdala, bilateral insula, ACC, and orbitofrontal cortex. These results suggest that individual autonomic tone and psychological variability influence resting brain activity in brain regions, previously shown to be associated with autonomic arousal (dorsal ACC) and personality traits (amygdala, caudate, etc.) during active task processing. The resting brain state may therefore need to be taken into account when interpreting the neurobiology of individual differences in structural and functional brain activity.

Is balance performance reduced after mild traumatic brain injury?: Interim analysis from chronic effects of neurotrauma consortium (CENC) multi-centre study.

PubMed

Walker, William C; Nowak, Kayla J; Kenney, Kimbra; Franke, Laura Manning; Eapen, Blessen C; Skop, Karen; Levin, Harvey; Agyemang, Amma A; Tate, David F; Wilde, Elisabeth A; Hinds, Sidney; Nolen, Tracy L

2018-06-12

Determine if mild traumatic brain injury (mTBI) history is associated with balance disturbances. Chronic Effects of Neurotrauma Consortium (CENC) centres. The CENC multi-centre study enrols post-9/11 era Service Members and Veterans with combat exposure. This sample (n = 322) consisted of enrolees completing initial evaluation by September 2016 at the three sites conducting computerized dynamic post-urography (CDP) testing. Observational study with cross-sectional analyses using structural equation modelling. Comprehensive structured interviews were used to diagnose all lifetime mild traumatic brain injuries (mTBIs). The outcome, Sensory Organization Test (SOT), was measured on CDP dual-plate force platform. Other studied variables were measured by structured interviews, record review and questionnaires. The overall positive/negative mTBI classification did not have a significant effect on the composite equilibrium score. However, the repetitive mTBI classification showed lower scores for participants with ≥ 3 mTBI versus 1-2 lifetime mTBIs. For repetitive mTBI, pain interference acted as a mediator for the indirect effect, and a direct effect was evident on some sensory condition equilibrium scores. These findings show that repeated mTBI, partially mediated by pain, may lead to later balance disturbances among military combatants. Further study of CDP outcomes within this accruing cohort is warranted.

Cortical Structures Associated With Sports Participation in Children: A Population-Based Study.

PubMed

López-Vicente, Mónica; Tiemeier, Henning; Wildeboer, Andrea; Muetzel, Ryan L; Verhulst, Frank C; Jaddoe, Vincent W V; Sunyer, Jordi; White, Tonya

2017-01-01

We studied cortical morphology in relation to sports participation and type of sport using a large sample of healthy children (n = 911). Sports participation data was collected through a parent-reported questionnaire. Magnetic resonance scans were acquired, and different morphological brain features were quantified. Global volumetric measures were not associated with sports participation. We observed thicker cortex in motor and premotor areas associated with sports participation. In boys, team sports participation, relative to individual sports, was related to thinner cortex in prefrontal brain areas involved in the regulation of behaviors. This study showed a relationship between sports participation and brain maturation.

Specification and estimation of sources of bias affecting neurological studies in PET/MR with an anatomical brain phantom

NASA Astrophysics Data System (ADS)

Teuho, J.; Johansson, J.; Linden, J.; Saunavaara, V.; Tolvanen, T.; Teräs, M.

2014-01-01

Selection of reconstruction parameters has an effect on the image quantification in PET, with an additional contribution from a scanner-specific attenuation correction method. For achieving comparable results in inter- and intra-center comparisons, any existing quantitative differences should be identified and compensated for. In this study, a comparison between PET, PET/CT and PET/MR is performed by using an anatomical brain phantom, to identify and measure the amount of bias caused due to differences in reconstruction and attenuation correction methods especially in PET/MR. Differences were estimated by using visual, qualitative and quantitative analysis. The qualitative analysis consisted of a line profile analysis for measuring the reproduction of anatomical structures and the contribution of the amount of iterations to image contrast. The quantitative analysis consisted of measurement and comparison of 10 anatomical VOIs, where the HRRT was considered as the reference. All scanners reproduced the main anatomical structures of the phantom adequately, although the image contrast on the PET/MR was inferior when using a default clinical brain protocol. Image contrast was improved by increasing the amount of iterations from 2 to 5 while using 33 subsets. Furthermore, a PET/MR-specific bias was detected, which resulted in underestimation of the activity values in anatomical structures closest to the skull, due to the MR-derived attenuation map that ignores the bone. Thus, further improvements for the PET/MR reconstruction and attenuation correction could be achieved by optimization of RAMLA-specific reconstruction parameters and implementation of bone to the attenuation template.

Music mnemonics aid Verbal Memory and Induce Learning – Related Brain Plasticity in Multiple Sclerosis

PubMed Central

Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker

2014-01-01

Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during music-assisted learning. Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG) in alpha and beta frequency bands in 54 patients with MS. The study sample was randomly divided into two groups, either hearing a spoken or a musical (sung) presentation of Rey’s auditory verbal learning test. We defined the “learning-related synchronization” (LRS) as the percent change in EEG spectral power from the first time the word was presented to the average of the subsequent word encoding trials. LRS differed significantly between the music and the spoken conditions in low alpha and upper beta bands. Patients in the music condition showed overall better word memory and better word order memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. The evidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization in prefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicit in musical stimuli enhances “deep encoding” during verbal learning and sharpens the timing of neural dynamics in brain networks degraded by demyelination in MS. PMID:24982626

Atlas based brain volumetry: How to distinguish regional volume changes due to biological or physiological effects from inherent noise of the methodology.

PubMed

Opfer, Roland; Suppa, Per; Kepp, Timo; Spies, Lothar; Schippling, Sven; Huppertz, Hans-Jürgen

2016-05-01

Fully-automated regional brain volumetry based on structural magnetic resonance imaging (MRI) plays an important role in quantitative neuroimaging. In clinical trials as well as in clinical routine multiple MRIs of individual patients at different time points need to be assessed longitudinally. Measures of inter- and intrascanner variability are crucial to understand the intrinsic variability of the method and to distinguish volume changes due to biological or physiological effects from inherent noise of the methodology. To measure regional brain volumes an atlas based volumetry (ABV) approach was deployed using a highly elastic registration framework and an anatomical atlas in a well-defined template space. We assessed inter- and intrascanner variability of the method in 51 cognitively normal subjects and 27 Alzheimer dementia (AD) patients from the Alzheimer's Disease Neuroimaging Initiative by studying volumetric results of repeated scans for 17 compartments and brain regions. Median percentage volume differences of scan-rescans from the same scanner ranged from 0.24% (whole brain parenchyma in healthy subjects) to 1.73% (occipital lobe white matter in AD), with generally higher differences in AD patients as compared to normal subjects (e.g., 1.01% vs. 0.78% for the hippocampus). Minimum percentage volume differences detectable with an error probability of 5% were in the one-digit percentage range for almost all structures investigated, with most of them being below 5%. Intrascanner variability was independent of magnetic field strength. The median interscanner variability was up to ten times higher than the intrascanner variability. Copyright © 2016 Elsevier Inc. All rights reserved.

Deep brain optical measurements of cell type-specific neural activity in behaving mice.

PubMed

Cui, Guohong; Jun, Sang Beom; Jin, Xin; Luo, Guoxiang; Pham, Michael D; Lovinger, David M; Vogel, Steven S; Costa, Rui M

2014-01-01

Recent advances in genetically encoded fluorescent sensors enable the monitoring of cellular events from genetically defined groups of neurons in vivo. In this protocol, we describe how to use a time-correlated single-photon counting (TCSPC)-based fiber optics system to measure the intensity, emission spectra and lifetime of fluorescent biosensors expressed in deep brain structures in freely moving mice. When combined with Cre-dependent selective expression of genetically encoded Ca(2+) indicators (GECIs), this system can be used to measure the average neural activity from a specific population of cells in mice performing complex behavioral tasks. As an example, we used viral expression of GCaMPs in striatal projection neurons (SPNs) and recorded the fluorescence changes associated with calcium spikes from mice performing a lever-pressing operant task. The whole procedure, consisting of virus injection, behavior training and optical recording, takes 3-4 weeks to complete. With minor adaptations, this protocol can also be applied to recording cellular events from other cell types in deep brain regions, such as dopaminergic neurons in the ventral tegmental area. The simultaneously recorded fluorescence signals and behavior events can be used to explore the relationship between the neural activity of specific brain circuits and behavior.

Effects of induced placental and fetal growth restriction, size at birth and early neonatal growth on behavioural and brain structural lateralization in sheep.

PubMed

Hunter, Damien Seth; Hazel, Susan J; Kind, Karen L; Liu, Hong; Marini, Danila; Giles, Lynne C; De Blasio, Miles J; Owens, Julie A; Pitcher, Julia B; Gatford, Kathryn L

2017-09-01

Poor perinatal growth in humans results in asymmetrical grey matter loss in fetuses and infants and increased functional and behavioural asymmetry, but specific contributions of pre- and postnatal growth are unclear. We therefore compared strength and direction of lateralization in obstacle avoidance and maze exit preference tasks in offspring of placentally restricted (PR: 10M, 13F) and control (CON: 23M, 17F) sheep pregnancies at 18 and 40 weeks of age, and examined gross brain structure of the prefrontal cortex at 52 weeks of age (PR: 14M, 18F; CON: 23M, 25F). PR did not affect lateralization direction, but 40-week-old PR females had greater lateralization strength than CON (P = .021). Behavioural lateralization measures were not correlated with perinatal growth. PR did not alter brain morphology. In males, cross-sectional areas of the prefrontal cortex and left hemisphere correlated positively with skull width at birth, and white matter area correlated positively with neonatal growth rate of the skull (all P < .05). These studies reinforce the need to include progeny of both sexes in future studies of neurodevelopmental programming, and suggest that restricting in utero growth has relatively mild effects on gross brain structural or behavioural lateralization in sheep.

Dynamics of brain activity in motor and frontal cortical areas during music listening: a magnetoencephalographic study.

PubMed

Popescu, Mihai; Otsuka, Asuka; Ioannides, Andreas A

2004-04-01

There are formidable problems in studying how 'real' music engages the brain over wide ranges of temporal scales extending from milliseconds to a lifetime. In this work, we recorded the magnetoencephalographic signal while subjects listened to music as it unfolded over long periods of time (seconds), and we developed and applied methods to correlate the time course of the regional brain activations with the dynamic aspects of the musical sound. We showed that frontal areas generally respond with slow time constants to the music, reflecting their more integrative mode; motor-related areas showed transient-mode responses to fine temporal scale structures of the sound. The study combined novel analysis techniques designed to capture and quantify fine temporal sequencing from the authentic musical piece (characterized by a clearly defined rhythm and melodic structure) with the extraction of relevant features from the dynamics of the regional brain activations. The results demonstrated that activity in motor-related structures, specifically in lateral premotor areas, supplementary motor areas, and somatomotor areas, correlated with measures of rhythmicity derived from the music. These correlations showed distinct laterality depending on how the musical performance deviated from the strict tempo of the music score, that is, depending on the musical expression.