Neuroimaging of Cerebrovascular Disease in the Aging Brain

PubMed Central

Gupta, Ajay; Nair, Sreejit; Schweitzer, Andrew D.; Kishore, Sirish; Johnson, Carl E.; Comunale, Joseph P.; Tsiouris, Apostolos J.; Sanelli, Pina C.

2012-01-01

Cerebrovascular disease remains a significant public health burden with its greatest impact on the elderly population. Advances in neuroimaging techniques allow detailed and sophisticated evaluation of many manifestations of cerebrovascular disease in the brain parenchyma as well as in the intracranial and extracranial vasculature. These tools continue to contribute to our understanding of the multifactorial processes that occur in the age-dependent development of cerebrovascular disease. Structural abnormalities related to vascular disease in the brain and vessels have been well characterized with CT and MRI based techniques. We review some of the pathophysiologic mechanisms in the aging brain and cerebral vasculature and the related structural abnormalities detectable on neuroimaging, including evaluation of age-related white matter changes, atherosclerosis of the cerebral vasculature, and cerebral infarction. In addition, newer neuroimaging techniques, such as diffusion tensor imaging, perfusion techniques, and assessment of cerebrovascular reserve, are also reviewed, as these techniques can detect physiologic alterations which complement the morphologic changes that cause cerebrovascular disease in the aging brain.Further investigation of these advanced imaging techniques has potential application to the understanding and diagnosis of cerebrovascular disease in the elderly. PMID:23185721

Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's disease neuroimaging initiative.

PubMed

Gomar, Jesus J; Bobes-Bascaran, Maria T; Conejero-Goldberg, Concepcion; Davies, Peter; Goldberg, Terry E

2011-09-01

Biomarkers have become increasingly important in understanding neurodegenerative processes associated with Alzheimer disease. Markers include regional brain volumes, cerebrospinal fluid measures of pathological Aβ1-42 and total tau, cognitive measures, and individual risk factors. To determine the discriminative utility of different classes of biomarkers and cognitive markers by examining their ability to predict a change in diagnostic status from mild cognitive impairment to Alzheimer disease. Longitudinal study. We analyzed the Alzheimer's Disease Neuroimaging Initiative database to study patients with mild cognitive impairment who converted to Alzheimer disease (n = 116) and those who did not convert (n = 204) within a 2-year period. We determined the predictive utility of 25 variables from all classes of markers, biomarkers, and risk factors in a series of logistic regression models and effect size analyses. The Alzheimer's Disease Neuroimaging Initiative public database. Primary outcome measures were odds ratios, pseudo- R(2)s, and effect sizes. In comprehensive stepwise logistic regression models that thus included variables from all classes of markers, the following baseline variables predicted conversion within a 2-year period: 2 measures of delayed verbal memory and middle temporal lobe cortical thickness. In an effect size analysis that examined rates of decline, change scores for biomarkers were modest for 2 years, but a change in an everyday functional activities measure (Functional Assessment Questionnaire) was considerably larger. Decline in scores on the Functional Assessment Questionnaire and Trail Making Test, part B, accounted for approximately 50% of the predictive variance in conversion from mild cognitive impairment to Alzheimer disease. Cognitive markers at baseline were more robust predictors of conversion than most biomarkers. Longitudinal analyses suggested that conversion appeared to be driven less by changes in the neurobiologic

Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative.

PubMed

Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; Decarli, Charles S; Dale, Anders M; Carmichael, Owen W; Tosun, Duygu; Weiner, Michael W

2010-05-01

Functions of the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present ("ADNI-GO") and future ("ADNI-2," if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled "ADNI-1" subjects who are followed up longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor-specific pilot sub-studies of arterial spin-labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications. Copyright 2010 The Alzheimer

Multivariate Protein Signatures of Pre-Clinical Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Plasma Proteome Dataset

PubMed Central

Johnstone, Daniel; Milward, Elizabeth A.; Berretta, Regina; Moscato, Pablo

2012-01-01

Background Recent Alzheimer's disease (AD) research has focused on finding biomarkers to identify disease at the pre-clinical stage of mild cognitive impairment (MCI), allowing treatment to be initiated before irreversible damage occurs. Many studies have examined brain imaging or cerebrospinal fluid but there is also growing interest in blood biomarkers. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has generated data on 190 plasma analytes in 566 individuals with MCI, AD or normal cognition. We conducted independent analyses of this dataset to identify plasma protein signatures predicting pre-clinical AD. Methods and Findings We focused on identifying signatures that discriminate cognitively normal controls (n = 54) from individuals with MCI who subsequently progress to AD (n = 163). Based on p value, apolipoprotein E (APOE) showed the strongest difference between these groups (p = 2.3×10−13). We applied a multivariate approach based on combinatorial optimization ((α,β)-k Feature Set Selection), which retains information about individual participants and maintains the context of interrelationships between different analytes, to identify the optimal set of analytes (signature) to discriminate these two groups. We identified 11-analyte signatures achieving values of sensitivity and specificity between 65% and 86% for both MCI and AD groups, depending on whether APOE was included and other factors. Classification accuracy was improved by considering “meta-features,” representing the difference in relative abundance of two analytes, with an 8-meta-feature signature consistently achieving sensitivity and specificity both over 85%. Generating signatures based on longitudinal rather than cross-sectional data further improved classification accuracy, returning sensitivities and specificities of approximately 90%. Conclusions Applying these novel analysis approaches to the powerful and well-characterized ADNI dataset has identified sets of

Perspective: The Alzheimer's Disease Neuroimaging Initiative and the role and contributions of the Private Partner Scientific Board (PPSB).

PubMed

Liu, Enchi; Luthman, Johan; Cedarbaum, Jesse M; Schmidt, Mark E; Cole, Patricia E; Hendrix, James; Carrillo, Maria C; Jones-Davis, Dorothy; Tarver, Erika; Novak, Gerald; De Santi, Susan; Soares, Holly D; Potter, William Z; Siemers, Eric; Schwarz, Adam J

2015-07-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) Private Partner Scientific Board (PPSB) is comprised of representatives of private, for-profit entities (including pharmaceutical, biotechnology, diagnostics, imaging companies, and imaging contract research organizations), and nonprofit organizations that provide financial and scientific support to ADNI through the Foundation for the National Institutes of Health. The PPSB serves as an independent, open, and precompetitive forum in which all private sector and not-for-profit partners in ADNI can collaborate, share information, and offer scientific and private-sector perspectives and expertise on issues relating to the ADNI project. In this article, we review and highlight the role, activities, and contributions of the PPSB within the ADNI project, and provide a perspective on remaining unmet needs and future directions. Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Treatment With Cholinesterase Inhibitors and Memantine of Patients in the Alzheimer’s Disease Neuroimaging Initiative

PubMed Central

Schneider, Lon S.; Insel, Philip S.; Weiner, Michael W.

2011-01-01

Objectives To assess the clinical characteristics and course of patients with mild cognitive impairment (MCI) and mild Alzheimer disease (AD) treated with cholinesterase inhibitors (ChEIs) and memantine hydrochloride. Design Cohort study. Setting The 59 recruiting sites for the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants Outpatients with MCI and AD in ADNI. Main Outcome Measures The AD Assessment Scale–cognitive subscale (ADAS-cog), Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR) scale, and Functional Activities Questionnaire (FAQ). Results A total of 177 (44.0%) of 402 MCI patients and 159 (84.6%) of 188 mild-AD patients were treated with ChEIs and 11.4% of MCI patients and 45.7% of AD patients with memantine at entry. Mild-cognitive-impairment patients who received ChEIs with or without memantine were more impaired, showed greater decline in scores, and progressed to dementia sooner than patients who did not receive ChEIs. Alzheimer-disease patients who received ChEIs and memantine took them longer, were more functionally impaired, and showed greater decline on the MMSE and CDR (but not on the ADAS-cog or FAQ) than those who received ChEIs only. Conclusions Academic physicians frequently prescribe ChEIs and memantine earlier than indicated in the US Food and Drug Administration–approved labeling to patients who are relatively more severely impaired or who are rapidly progressing toward cognitive impairment. The use of these medications in ADNI is associated with clinical decline and may affect the interpretation of clinical trial outcomes. Study Registration clinicalTrials.gov Identifier: NCT00106899 PMID:21220675

Neuroimaging Studies Illustrate the Commonalities Between Ageing and Brain Diseases.

PubMed

Cole, James H

2018-07-01

The lack of specificity in neuroimaging studies of neurological and psychiatric diseases suggests that these different diseases have more in common than is generally considered. Potentially, features that are secondary effects of different pathological processes may share common neurobiological underpinnings. Intriguingly, many of these mechanisms are also observed in studies of normal (i.e., non-pathological) brain ageing. Different brain diseases may be causing premature or accelerated ageing to the brain, an idea that is supported by a line of "brain ageing" research that combines neuroimaging data with machine learning analysis. In reviewing this field, I conclude that such observations could have important implications, suggesting that we should shift experimental paradigm: away from characterizing the average case-control brain differences resulting from a disease toward methods that place individuals in their age-appropriate context. This will also lead naturally to clinical applications, whereby neuroimaging can contribute to a personalized-medicine approach to improve brain health. © 2018 WILEY Periodicals, Inc.

Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative.

PubMed

Carmichael, Owen; Schwarz, Christopher; Drucker, David; Fletcher, Evan; Harvey, Danielle; Beckett, Laurel; Jack, Clifford R; Weiner, Michael; DeCarli, Charles

2010-11-01

To evaluate relationships between magnetic resonance imaging (MRI)-based measures of white matter hyperintensities (WMHs), measured at baseline and longitudinally, and 1-year cognitive decline using a large convenience sample in a clinical trial design with a relatively mild profile of cardiovascular risk factors. Convenience sample in a clinical trial design. A total of 804 participants in the Alzheimer Disease Neuroimaging Initiative who received MRI scans, cognitive testing, and clinical evaluations at baseline, 6-month follow-up, and 12-month follow-up visits. For each scan, WMHs were detected automatically on coregistered sets of T1, proton density, and T2 MRI images using a validated method. Mixed-effects regression models evaluated relationships between risk factors for WMHs, WMH volume, and change in outcome measures including Mini-Mental State Examination (MMSE), Alzheimer Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Clinical Dementia Rating Scale sum of boxes scores. Covariates in these models included race, sex, years of education, age, apolipoprotein E genotype, baseline clinical diagnosis (cognitively normal, mild cognitive impairment, or Alzheimer disease), cardiovascular risk score, and MRI-based hippocampal and brain volumes. Higher baseline WMH volume was associated with greater subsequent 1-year increase in ADAS-Cog and decrease in MMSE scores. Greater WMH volume at follow-up was associated with greater ADAS-Cog and lower MMSE scores at follow-up. Higher baseline age and cardiovascular risk score and more impaired baseline clinical diagnosis were associated with higher baseline WMH volume. White matter hyperintensity volume predicts 1-year cognitive decline in a relatively healthy convenience sample that was similar to clinical trial samples, and therefore should be considered as a covariate of interest at baseline and longitudinally in future AD treatment trials.

Medication for Alzheimer's disease and associated fall hazard: a retrospective cohort study from the Alzheimer's Disease Neuroimaging Initiative.

PubMed

Epstein, Noam U; Guo, Rong; Farlow, Martin R; Singh, Jaswinder P; Fisher, Morris

2014-02-01

Falls are common in the elderly, especially in those with cognitive impairment. The elderly are often treated with several medications, which may have both beneficial and deleterious effects. The use and type of medication in Alzheimer's disease (AD) patients and association with falls is limited. We examined the association between falls and medication use in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Diagnosis, demographics, medication use, apolipoprotein E4 allele status and functional activity level at baseline were gathered for 810 participants enrolled in the ADNI, including healthy controls and subjects with mild cognitive impairment or Alzheimer's. Reports detailing adverse event falls were tabulated. Baseline characteristics were compared between subjects with and without one or more falls. Cox proportional hazards models were conducted to evaluate the association between subject characteristics and hazard of the first fall. Age (p < 0.0001), Functional Activities Questionnaire (p = 0.035), Beers List (p = 0.0477) and medications for treating cognitive symptoms of Alzheimer's (p = 0.0019) were associated with hazard of fall in the univariate model. In the final multivariate model, after adjusting for covariates, Alzheimer's medication use (p = 0.0005) was associated with hazard of fall. Medication was changed by the clinician after an adverse fall event in 9% of the falls. About 7% of the falls were reported as serious adverse events and 6% were reported to be severe. We found a significant association between the use of symptomatic medication treating cognitive symptoms in AD and hazard of fall after adjusting for age and Beers List medication use. Additional pharmacovigilance of the association between falls and Alzheimer's medication use is warranted.

CATEGORICAL AND CORRELATIONAL ANALYSES OF BASELINE FLUORODEOXYGLUCOSE POSITRON EMISSION TOMOGRAPHY IMAGES FROM THE ALZHEIMER’S DISEASE NEUROIMAGING INITIATIVE (ADNI)

PubMed Central

Langbaum, Jessica B.S.; Chen, Kewei; Lee, Wendy; Reschke, Cole; Bandy, Dan; Fleisher, Adam S.; Alexander, Gene E.; Foster, Norman L.; Weiner, Michael W.; Koeppe, Robert A.; Jagust, William J.; Reiman, Eric M.

2010-01-01

In mostly small single-center studies, Alzheimer’s disease (AD) is associated with characteristic and progressive reductions in fluorodeoxyglucose positron emission tomography (PET) measurements of the regional cerebral metabolic rate for glucose (CMRgl). The AD Neuroimaging Initiative (ADNI) is acquiring FDG PET, volumetric magnetic resonance imaging, and other biomarker measurements in a large longitudinal multi-center study of initially mildly affected probable AD (pAD) patients, amnestic mild cognitive impairment (aMCI) patients, who are at increased AD risk, and cognitively normal controls (NC), and we are responsible for analyzing the PET images using statistical parametric mapping (SPM). Here we compare baseline CMRgl measurements from 74 pAD patients and 142 aMCI patients to those from 82 NC, we correlate CMRgl with categorical and continuous measures of clinical disease severity, and we compare apolipoprotein E (APOE) ε4 carriers to non-carriers in each of these subject groups. In comparison with NC, the pAD and aMCI groups each had significantly lower CMRgl bilaterally in posterior cingulate, precuneus, parietotemporal and frontal cortex. Similar reductions were observed when categories of disease severity or lower Mini-Mental State Exam (MMSE) scores were correlated with lower CMRgl. However, when analyses were restricted to the pAD patients, lower MMSE scores were significantly correlated with lower left frontal and temporal CMRgl. These findings from a large, multi-site study support previous single-site findings, supports the characteristic pattern of baseline CMRgl reductions in AD and aMCI patients, as well as preferential anterior CMRgl reductions after the onset of AD dementia. PMID:19349228

Reference standard space hippocampus labels according to the European Alzheimer's Disease Consortium-Alzheimer's Disease Neuroimaging Initiative harmonized protocol: Utility in automated volumetry.

PubMed

Wolf, Dominik; Bocchetta, Martina; Preboske, Gregory M; Boccardi, Marina; Grothe, Michel J

2017-08-01

A harmonized protocol (HarP) for manual hippocampal segmentation on magnetic resonance imaging (MRI) has recently been developed by an international European Alzheimer's Disease Consortium-Alzheimer's Disease Neuroimaging Initiative project. We aimed at providing consensual certified HarP hippocampal labels in Montreal Neurological Institute (MNI) standard space to serve as reference in automated image analyses. Manual HarP tracings on the high-resolution MNI152 standard space template of four expert certified HarP tracers were combined to obtain consensual bilateral hippocampus labels. Utility and validity of these reference labels is demonstrated in a simple atlas-based morphometry approach for automated calculation of HarP-compliant hippocampal volumes within SPM software. Individual tracings showed very high agreement among the four expert tracers (pairwise Jaccard indices 0.82-0.87). Automatically calculated hippocampal volumes were highly correlated (r L/R  = 0.89/0.91) with gold standard volumes in the HarP benchmark data set (N = 135 MRIs), with a mean volume difference of 9% (standard deviation 7%). The consensual HarP hippocampus labels in the MNI152 template can serve as a reference standard for automated image analyses involving MNI standard space normalization. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

PubMed Central

Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Liu, Enchi; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Schmidt, Mark E.; Shaw, Leslie; Shen, Li; Siuciak, Judith A.; Soares, Holly; Toga, Arthur W.; Trojanowski, John Q.

2014-01-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates

Graphical Neuroimaging Informatics: Application to Alzheimer’s Disease

PubMed Central

Bowman, Ian; Joshi, Shantanu H.; Greer, Vaughan

2013-01-01

The Informatics Visualization for Neuroimaging (INVIZIAN) framework allows one to graphically display image and meta-data information from sizeable collections of neuroimaging data as a whole using a dynamic and compelling user interface. Users can fluidly interact with an entire collection of cortical surfaces using only their mouse. In addition, users can cluster and group brains according in multiple ways for subsequent comparison using graphical data mining tools. In this article, we illustrate the utility of INVIZIAN for simultaneous exploration and mining a large collection of extracted cortical surface data arising in clinical neuroimaging studies of patients with Alzheimer’s Disease, mild cognitive impairment, as well as healthy control subjects. Alzheimer’s Disease is particularly interesting due to the wide-spread effects on cortical architecture and alterations of volume in specific brain areas associated with memory. We demonstrate INVIZIAN’s ability to render multiple brain surfaces from multiple diagnostic groups of subjects, showcase the interactivity of the system, and showcase how INVIZIAN can be employed to generate hypotheses about the collection of data which would be suitable for direct access to the underlying raw data and subsequent formal statistical analysis. Specifically, we use INVIZIAN show how cortical thickness and hippocampal volume differences between group are evident even in the absence of more formal hypothesis testing. In the context of neurological diseases linked to brain aging such as AD, INVIZIAN provides a unique means for considering the entirety of whole brain datasets, look for interesting relationships among them, and thereby derive new ideas for further research and study. PMID:24203652

The Alzheimer’s Disease Neuroimaging Initiative: A review of papers published since its inception

PubMed Central

Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Liu, Enchi; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Schmidt, Mark E.; Shaw, Leslie; Siuciak, Judith A.; Soares, Holly; Toga, Arthur W.; Trojanowski, John Q.

2012-01-01

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD and 200 normal controls and $67 million funding was provided by both the public and private sectors including the National Institutes on Aging, thirteen pharmaceutical companies and two Foundations that provided support through the Foundation for NIH (FNIH). This article reviews all papers published since the inception of the initiative and summarizes the results as of February, 2011. The major accomplishments of ADNI have been 1) the development of standardized methods for clinical, magnetic resonance imaging (MRI) and positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in a multi-center setting; 2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control, MCI and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β amyloid (Aβ) cascade [1] and tau mediated neurodegeneration hypotheses for AD while brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; 3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities including MRI, FDG-PET, CSF biomarkers and clinical tests; 4) the development of methods for the early detection of AD. CSF biomarkers, Aβ42 and tau as well as amyloid PET may reflect the earliest steps in AD pathology in mildly or even non-symptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; 5) the improvement of clinical trial efficiency through the identification of subjects most

Ventricular enlargement as a possible measure of Alzheimer's disease progression validated using the Alzheimer's disease neuroimaging initiative database

PubMed Central

Nestor, Sean M.; Rupsingh, Raul; Borrie, Michael; Smith, Matthew; Accomazzi, Vittorio; Wells, Jennie L.; Fogarty, Jennifer

2008-01-01

Ventricular enlargement may be an objective and sensitive measure of neuropathological change associated with mild cognitive impairment (MCI) and Alzheimer's disease (AD), suitable to assess disease progression for multi-centre studies. This study compared (i) ventricular enlargement after six months in subjects with MCI, AD and normal elderly controls (NEC) in a multi-centre study, (ii) volumetric and cognitive changes between Apolipoprotein E genotypes, (iii) ventricular enlargement in subjects who progressed from MCI to AD, and (iv) sample sizes for multi-centre MCI and AD studies based on measures of ventricular enlargement. Three dimensional T1-weighted MRI and cognitive measures were acquired from 504 subjects (NEC n = 152, MCI n = 247 and AD n = 105) participating in the multi-centre Alzheimer's Disease Neuroimaging Initiative. Cerebral ventricular volume was quantified at baseline and after six months using semi-automated software. For the primary analysis of ventricle and neurocognitive measures, between group differences were evaluated using an analysis of covariance, and repeated measures t-tests were used for within group comparisons. For secondary analyses, all groups were dichotomized for Apolipoprotein E genotype based on the presence of an ε4 polymorphism. In addition, the MCI group was dichotomized into those individuals who progressed to a clinical diagnosis of AD, and those subjects that remained stable with MCI after six months. Group differences on neurocognitive and ventricle measures were evaluated by independent t-tests. General sample size calculations were computed for all groups derived from ventricle measurements and neurocognitive scores. The AD group had greater ventricular enlargement compared to both subjects with MCI (P = 0.0004) and NEC (P < 0.0001), and subjects with MCI had a greater rate of ventricular enlargement compared to NEC (P = 0.0001). MCI subjects that progressed to clinical AD after six months had greater ventricular

Combinations of Multiple Neuroimaging Markers using Logistic Regression for Auxiliary Diagnosis of Alzheimer Disease and Mild Cognitive Impairment.

PubMed

Mao, Nini; Liu, Yunting; Chen, Kewei; Yao, Li; Wu, Xia

2018-06-05

Multiple neuroimaging modalities have been developed providing various aspects of information on the human brain. Used together and properly, these complementary multimodal neuroimaging data integrate multisource information which can facilitate a diagnosis and improve the diagnostic accuracy. In this study, 3 types of brain imaging data (sMRI, FDG-PET, and florbetapir-PET) were fused in the hope to improve diagnostic accuracy, and multivariate methods (logistic regression) were applied to these trimodal neuroimaging indices. Then, the receiver-operating characteristic (ROC) method was used to analyze the outcomes of the logistic classifier, with either each index, multiples from each modality, or all indices from all 3 modalities, to investigate their differential abilities to identify the disease. With increasing numbers of indices within each modality and across modalities, the accuracy of identifying Alzheimer disease (AD) increases to varying degrees. For example, the area under the ROC curve is above 0.98 when all the indices from the 3 imaging data types are combined. Using a combination of different indices, the results confirmed the initial hypothesis that different biomarkers were potentially complementary, and thus the conjoint analysis of multiple information from multiple sources would improve the capability to identify diseases such as AD and mild cognitive impairment. © 2018 S. Karger AG, Basel.

Disease progression model for Clinical Dementia Rating–Sum of Boxes in mild cognitive impairment and Alzheimer’s subjects from the Alzheimer’s Disease Neuroimaging Initiative

PubMed Central

Samtani, Mahesh N; Raghavan, Nandini; Novak, Gerald; Nandy, Partha; Narayan, Vaibhav A

2014-01-01

Background The objective of this analysis was to develop a nonlinear disease progression model, using an expanded set of covariates that captures the longitudinal Clinical Dementia Rating Scale–Sum of Boxes (CDR–SB) scores. These were derived from the Alzheimer’s Disease Neuroimaging Initiative ADNI-1 study, of 301 Alzheimer’s disease and mild cognitive impairment patients who were followed for 2–3 years. Methods The model describes progression rate and baseline disease score as a function of covariates. The covariates that were tested fell into five groups: a) hippocampal volume; b) serum and cerebrospinal fluid (CSF) biomarkers; c) demographics and apolipoprotein Epsilon 4 (ApoE4) allele status; d) baseline cognitive tests; and e) disease state and comedications. Results Covariates associated with baseline disease severity were disease state, hippocampal volume, and comedication use. Disease progression rate was influenced by baseline CSF biomarkers, Trail-Making Test part A score, delayed logical memory test score, and current level of impairment as measured by CDR–SB. The rate of disease progression was dependent on disease severity, with intermediate scores around the inflection point score of 10 exhibiting high disease progression rate. The CDR–SB disease progression rate in a typical patient, with late mild cognitive impairment and mild Alzheimer’s disease, was estimated to be approximately 0.5 and 1.4 points/year, respectively. Conclusions In conclusion, this model describes disease progression in terms of CDR–SB changes in patients and its dependency on novel covariates. The CSF biomarkers included in the model discriminate mild cognitive impairment subjects as progressors and nonprogressors. Therefore, the model may be utilized for optimizing study designs, through patient population enrichment and clinical trial simulations. PMID:24926196

Relationships between cognitive performance, neuroimaging, and vascular disease: the DHS-Mind Study

PubMed Central

Hsu, Fang-Chi; Raffield, Laura M.; Hugenschmidt, Christina E.; Cox, Amanda; Xu, Jianzhao; Carr, J. Jeffery; Freedman, Barry I.; Maldjian, Joseph A.; Williamson, Jeff D.; Bowden, Donald W.

2015-01-01

Background Type 2 diabetes mellitus increases risk for cognitive decline and dementia; elevated burdens of vascular disease are hypothesized to contribute to this risk. These relationships were examined in the Diabetes Heart Study-Mind using a battery of cognitive tests, neuroimaging measures, and subclinical cardiovascular disease (CVD) burden assessed by coronary artery calcified plaque (CAC). We hypothesized that CAC would attenuate the association between neuroimaging measures and cognition performance. Methods Associations were examined using marginal models in this family-based cohort of 572 European Americans from 263 families. All models were adjusted for age, gender, education, type 2 diabetes, and hypertension, with some neuroimaging measures additionally adjusted for intracranial volume. Results Higher total brain volume (TBV) was associated with better performance on the Digit Symbol Substitution Task (DSST) and Semantic Fluency (both p≤7.0 x 10−4). Higher gray matter volume (GMV) was associated with better performance on the Modified Mini-Mental State Examination and Semantic Fluency (both p≤9.0 x 10−4). Adjusting for CAC caused minimal changes to the results. Conclusions Relationships exist between neuroimaging measures and cognitive performance in a type 2 diabetes-enriched European American cohort. Associations were minimally attenuated after adjusting for subclinical CVD. Additional work is needed to understand how subclinical CVD burden interacts with other factors and impacts relationships between neuroimaging and cognitive testing measures. PMID:26185004

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer's disease neuroimaging initiative.

PubMed

Yao, Xiaohui; Yan, Jingwen; Ginda, Michael; Börner, Katy; Saykin, Andrew J; Shen, Li

2017-01-01

Alzheimer's disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

PubMed

Weiner, Michael W; Veitch, Dallas P; Aisen, Paul S; Beckett, Laurel A; Cairns, Nigel J; Cedarbaum, Jesse; Green, Robert C; Harvey, Danielle; Jack, Clifford R; Jagust, William; Luthman, Johan; Morris, John C; Petersen, Ronald C; Saykin, Andrew J; Shaw, Leslie; Shen, Li; Schwarz, Adam; Toga, Arthur W; Trojanowski, John Q

2015-06-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, �

Medication for Alzheimer’s Disease and Associated Fall Hazard: a Retrospective Cohort Study from the Alzheimer’s Disease Neuro-Imaging Initiative

PubMed Central

Epstein, Noam U.; Guo, Rong; Farlow, Martin R.; Singh, Jaswinder P.; Fisher, Morris

2014-01-01

Background Falls are common in the elderly, especially in those with cognitive impairment. The elderly are often treated with several medications which may have both beneficial and deleterious effects. The use and type of medication in Alzheimer’s patients and association with falls is limited. Objective We examined the association between falls and medication use in the Alzheimer’s Disease Neuro-Imaging Initiative (ADNI). Methods Diagnosis, demographics, medication use, apolipoprotein E4 allele status and functional activity level at baseline were gathered for 810 participants enrolled in ADNI including healthy controls and subjects with mild cognitive impairment or Alzheimer’s. Adverse event fall reports were tabulated. Baseline characteristics were compared between subjects with and without one or more falls. Cox proportional hazards models were conducted to evaluate the association between subject characteristics and hazard of first fall. Results Age (p<0.0001), functional activities questionnaire (p=0.035), Beers list (p=0.0477) and medications for treating cognitive symptoms of Alzheimer’s (p=0.0019) were associated with hazard of fall in the univariate model. In the final multivariate model, after adjusting for covariates, Alzheimer’s medication use (p=0.0005) was associated with hazard of fall. Medication was changed after an adverse fall event by the clinician in 9% of the falls. About 7% of the falls were reported as serious adverse events and 6% were reported to be severe. Conclusion We found a significant association between use of symptomatic medication treating cognitive symptoms in Alzheimer’s disease and hazard of fall after adjusting for age and Beers list medication use. Additional pharmaco-vigilance of the association between falls and Alzheimer’s medication use is warranted. PMID:24357133

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set.

PubMed

Park, Ji Eun; Park, Bumwoo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Oh, Joo Young; Lee, Jae-Hong; Roh, Jee Hoon; Shim, Woo Hyun

2017-01-01

To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal ( p < 0.001) and supramarginal gyrus ( p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set

PubMed Central

Park, Ji Eun; Park, Bumwoo; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Oh, Joo Young; Lee, Jae-Hong; Roh, Jee Hoon; Shim, Woo Hyun

2017-01-01

Objective To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Materials and Methods Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Results Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Conclusion Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease. PMID:29089831

Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

PubMed

Crane, Paul K; Carle, Adam; Gibbons, Laura E; Insel, Philip; Mackin, R Scott; Gross, Alden; Jones, Richard N; Mukherjee, Shubhabrata; Curtis, S McKay; Harvey, Danielle; Weiner, Michael; Mungas, Dan

2012-12-01

We sought to develop and evaluate a composite memory score from the neuropsychological battery used in the Alzheimer's Disease (AD) Neuroimaging Initiative (ADNI). We used modern psychometric approaches to analyze longitudinal Rey Auditory Verbal Learning Test (RAVLT, 2 versions), AD Assessment Schedule - Cognition (ADAS-Cog, 3 versions), Mini-Mental State Examination (MMSE), and Logical Memory data to develop ADNI-Mem, a composite memory score. We compared RAVLT and ADAS-Cog versions, and compared ADNI-Mem to RAVLT recall sum scores, four ADAS-Cog-derived scores, the MMSE, and the Clinical Dementia Rating Sum of Boxes. We evaluated rates of decline in normal cognition, mild cognitive impairment (MCI), and AD, ability to predict conversion from MCI to AD, strength of association with selected imaging parameters, and ability to differentiate rates of decline between participants with and without AD cerebrospinal fluid (CSF) signatures. The second version of the RAVLT was harder than the first. The ADAS-Cog versions were of similar difficulty. ADNI-Mem was slightly better at detecting change than total RAVLT recall scores. It was as good as or better than all of the other scores at predicting conversion from MCI to AD. It was associated with all our selected imaging parameters for people with MCI and AD. Participants with MCI with an AD CSF signature had somewhat more rapid decline than did those without. This paper illustrates appropriate methods for addressing the different versions of word lists, and demonstrates the additional power to be gleaned with a psychometrically sound composite memory score.

How random is the random forest? Random forest algorithm on the service of structural imaging biomarkers for Alzheimer's disease: from Alzheimer's disease neuroimaging initiative (ADNI) database.

PubMed

Dimitriadis, Stavros I; Liparas, Dimitris

2018-06-01

Neuroinformatics is a fascinating research field that applies computational models and analytical tools to high dimensional experimental neuroscience data for a better understanding of how the brain functions or dysfunctions in brain diseases. Neuroinformaticians work in the intersection of neuroscience and informatics supporting the integration of various sub-disciplines (behavioural neuroscience, genetics, cognitive psychology, etc.) working on brain research. Neuroinformaticians are the pathway of information exchange between informaticians and clinicians for a better understanding of the outcome of computational models and the clinical interpretation of the analysis. Machine learning is one of the most significant computational developments in the last decade giving tools to neuroinformaticians and finally to radiologists and clinicians for an automatic and early diagnosis-prognosis of a brain disease. Random forest (RF) algorithm has been successfully applied to high-dimensional neuroimaging data for feature reduction and also has been applied to classify the clinical label of a subject using single or multi-modal neuroimaging datasets. Our aim was to review the studies where RF was applied to correctly predict the Alzheimer's disease (AD), the conversion from mild cognitive impairment (MCI) and its robustness to overfitting, outliers and handling of non-linear data. Finally, we described our RF-based model that gave us the 1 st position in an international challenge for automated prediction of MCI from MRI data.

2014 Update of the Alzheimer’s Disease Neuroimaging Initiative: A review of papers published since its inception

PubMed Central

Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Cedarbaum, Jesse; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Luthman, Johan; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie; Shen, Li; Schwarz, Adam; Toga, Arthur W.; Trojanowski, John Q.

2016-01-01

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer’s Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, �

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer’s disease neuroimaging initiative

PubMed Central

Yao, Xiaohui; Yan, Jingwen; Ginda, Michael; Börner, Katy; Saykin, Andrew J.

2017-01-01

Background Alzheimer’s disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. Methods Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. Results During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. Conclusions Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI

Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer's disease.

PubMed

Nho, Kwangsik; Kim, Sungeun; Horgusluoglu, Emrin; Risacher, Shannon L; Shen, Li; Kim, Dokyoon; Lee, Seunggeun; Foroud, Tatiana; Shaw, Leslie M; Trojanowski, John Q; Aisen, Paul S; Petersen, Ronald C; Jack, Clifford R; Weiner, Michael W; Green, Robert C; Toga, Arthur W; Saykin, Andrew J

2017-05-24

The APOE ε4 allele is the most significant common genetic risk factor for late-onset Alzheimer's disease (LOAD). The region surrounding APOE on chromosome 19 has also shown consistent association with LOAD. However, no common variants in the region remain significant after adjusting for APOE genotype. We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) and neuroimaging biomarkers of LOAD. Whole genome sequencing (WGS) was performed on 817 blood DNA samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sequence data from 757 non-Hispanic Caucasian participants was used in the present analysis. We extracted all rare variants (MAF (minor allele frequency) < 0.05) within a 312 kb window in APOE's vicinity encompassing 12 genes. We assessed CSF and neuroimaging (MRI and PET) biomarkers as LOAD-related quantitative endophenotypes. Gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). A total of 3,334 rare variants (MAF < 0.05) were found within the APOE region. Among them, 72 rare non-synonymous variants were observed. Eight genes spanning the APOE region were significantly associated with CSF Aβ 1-42 (p < 1.0 × 10 -3 ). After controlling for APOE genotype and adjusting for multiple comparisons, 4 genes (CBLC, BCAM, APOE, and RELB) remained significant. Whole-brain surface-based analysis identified highly significant clusters associated with rare variants of CBLC in the temporal lobe region including the entorhinal cortex, as well as frontal lobe regions. Whole-brain voxel-wise analysis of amyloid PET identified significant clusters in the bilateral frontal and parietal lobes showing associations of rare variants of RELB with cortical amyloid burden. Rare variants within genes spanning the APOE region are significantly associated with LOAD-related CSF Aβ 1-42 and neuroimaging biomarkers after adjusting for APOE genotype

Ethical and Legal Implications of the Methodological Crisis in Neuroimaging.

PubMed

Kellmeyer, Philipp

2017-10-01

Currently, many scientific fields such as psychology or biomedicine face a methodological crisis concerning the reproducibility, replicability, and validity of their research. In neuroimaging, similar methodological concerns have taken hold of the field, and researchers are working frantically toward finding solutions for the methodological problems specific to neuroimaging. This article examines some ethical and legal implications of this methodological crisis in neuroimaging. With respect to ethical challenges, the article discusses the impact of flawed methods in neuroimaging research in cognitive and clinical neuroscience, particularly with respect to faulty brain-based models of human cognition, behavior, and personality. Specifically examined is whether such faulty models, when they are applied to neurological or psychiatric diseases, could put patients at risk, and whether this places special obligations on researchers using neuroimaging. In the legal domain, the actual use of neuroimaging as evidence in United States courtrooms is surveyed, followed by an examination of ways that the methodological problems may create challenges for the criminal justice system. Finally, the article reviews and promotes some promising ideas and initiatives from within the neuroimaging community for addressing the methodological problems.

Aging, neurodegenerative disease, and traumatic brain injury: the role of neuroimaging.

PubMed

Esopenko, Carrie; Levine, Brian

2015-02-15

Traumatic brain injury (TBI) is a highly prevalent condition with significant effects on cognition and behavior. While the acute and sub-acute effects of TBI recover over time, relatively little is known about the long-term effects of TBI in relation to neurodegenerative disease. This issue has recently garnered a great deal of attention due to publicity surrounding chronic traumatic encephalopathy (CTE) in professional athletes, although CTE is but one of several neurodegenerative disorders associated with a history of TBI. Here, we review the literative on neurodegenerative disorders linked to remote TBI. We also review the evidence for neuroimaging changes associated with unhealthy brain aging in the context of remote TBI. We conclude that neuroimaging biomarkers have significant potential to increase understanding of the mechanisms of unhealthy brain aging and neurodegeneration following TBI, with potential for identifying those at risk for unhealthy brain aging prior to the clinical manifestation of neurodegenerative disease.

Longitudinal Neuroimaging Hippocampal Markers for Diagnosing Alzheimer's Disease.

PubMed

Platero, Carlos; Lin, Lin; Tobar, M Carmen

2018-05-21

Hippocampal atrophy measures from magnetic resonance imaging (MRI) are powerful tools for monitoring Alzheimer's disease (AD) progression. In this paper, we introduce a longitudinal image analysis framework based on robust registration and simultaneous hippocampal segmentation and longitudinal marker classification of brain MRI of an arbitrary number of time points. The framework comprises two innovative parts: a longitudinal segmentation and a longitudinal classification step. The results show that both steps of the longitudinal pipeline improved the reliability and the accuracy of the discrimination between clinical groups. We introduce a novel approach to the joint segmentation of the hippocampus across multiple time points; this approach is based on graph cuts of longitudinal MRI scans with constraints on hippocampal atrophy and supported by atlases. Furthermore, we use linear mixed effect (LME) modeling for differential diagnosis between clinical groups. The classifiers are trained from the average residue between the longitudinal marker of the subjects and the LME model. In our experiments, we analyzed MRI-derived longitudinal hippocampal markers from two publicly available datasets (Alzheimer's Disease Neuroimaging Initiative, ADNI and Minimal Interval Resonance Imaging in Alzheimer's Disease, MIRIAD). In test/retest reliability experiments, the proposed method yielded lower volume errors and significantly higher dice overlaps than the cross-sectional approach (volume errors: 1.55% vs 0.8%; dice overlaps: 0.945 vs 0.975). To diagnose AD, the discrimination ability of our proposal gave an area under the receiver operating characteristic (ROC) curve (AUC) [Formula: see text] 0.947 for the control vs AD, AUC [Formula: see text] 0.720 for mild cognitive impairment (MCI) vs AD, and AUC [Formula: see text] 0.805 for the control vs MCI.

Data sharing in neuroimaging research

PubMed Central

Poline, Jean-Baptiste; Breeze, Janis L.; Ghosh, Satrajit; Gorgolewski, Krzysztof; Halchenko, Yaroslav O.; Hanke, Michael; Haselgrove, Christian; Helmer, Karl G.; Keator, David B.; Marcus, Daniel S.; Poldrack, Russell A.; Schwartz, Yannick; Ashburner, John; Kennedy, David N.

2012-01-01

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging. PMID:22493576

Knowledge-driven binning approach for rare variant association analysis: application to neuroimaging biomarkers in Alzheimer's disease.

PubMed

Kim, Dokyoon; Basile, Anna O; Bang, Lisa; Horgusluoglu, Emrin; Lee, Seunggeun; Ritchie, Marylyn D; Saykin, Andrew J; Nho, Kwangsik

2017-05-18

Rapid advancement of next generation sequencing technologies such as whole genome sequencing (WGS) has facilitated the search for genetic factors that influence disease risk in the field of human genetics. To identify rare variants associated with human diseases or traits, an efficient genome-wide binning approach is needed. In this study we developed a novel biological knowledge-based binning approach for rare-variant association analysis and then applied the approach to structural neuroimaging endophenotypes related to late-onset Alzheimer's disease (LOAD). For rare-variant analysis, we used the knowledge-driven binning approach implemented in Bin-KAT, an automated tool, that provides 1) binning/collapsing methods for multi-level variant aggregation with a flexible, biologically informed binning strategy and 2) an option of performing unified collapsing and statistical rare variant analyses in one tool. A total of 750 non-Hispanic Caucasian participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort who had both WGS data and magnetic resonance imaging (MRI) scans were used in this study. Mean bilateral cortical thickness of the entorhinal cortex extracted from MRI scans was used as an AD-related neuroimaging endophenotype. SKAT was used for a genome-wide gene- and region-based association analysis of rare variants (MAF (minor allele frequency) < 0.05) and potential confounding factors (age, gender, years of education, intracranial volume (ICV) and MRI field strength) for entorhinal cortex thickness were used as covariates. Significant associations were determined using FDR adjustment for multiple comparisons. Our knowledge-driven binning approach identified 16 functional exonic rare variants in FANCC significantly associated with entorhinal cortex thickness (FDR-corrected p-value < 0.05). In addition, the approach identified 7 evolutionary conserved regions, which were mapped to FAF1, RFX7, LYPLAL1 and GOLGA3, significantly associated

The Co-evolution of Neuroimaging and Psychiatric Neurosurgery.

PubMed

Dyster, Timothy G; Mikell, Charles B; Sheth, Sameer A

2016-01-01

The role of neuroimaging in psychiatric neurosurgery has evolved significantly throughout the field's history. Psychiatric neurosurgery initially developed without the benefit of information provided by modern imaging modalities, and thus lesion targets were selected based on contemporary theories of frontal lobe dysfunction in psychiatric disease. However, by the end of the 20th century, the availability of structural and functional magnetic resonance imaging (fMRI) allowed for the development of mechanistic theories attempting to explain the anatamofunctional basis of these disorders, as well as the efficacy of stereotactic neuromodulatory treatments. Neuroimaging now plays a central and ever-expanding role in the neurosurgical management of psychiatric disorders, by influencing the determination of surgical candidates, allowing individualized surgical targeting and planning, and identifying network-level changes in the brain following surgery. In this review, we aim to describe the coevolution of psychiatric neurosurgery and neuroimaging, including ways in which neuroimaging has proved useful in elucidating the therapeutic mechanisms of neuromodulatory procedures. We focus on ablative over stimulation-based procedures given their historical precedence and the greater opportunity they afford for post-operative re-imaging, but also discuss important contributions from the deep brain stimulation (DBS) literature. We conclude with a discussion of how neuroimaging will transition the field of psychiatric neurosurgery into the era of precision medicine.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.

PubMed

Weiner, Michael W; Veitch, Dallas P; Aisen, Paul S; Beckett, Laurel A; Cairns, Nigel J; Green, Robert C; Harvey, Danielle; Jack, Clifford R; Jagust, William; Morris, John C; Petersen, Ronald C; Saykin, Andrew J; Shaw, Leslie M; Toga, Arthur W; Trojanowski, John Q

2017-04-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015. We used standard searches to find publications using ADNI data. (1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and

Dopamine Transporter Neuroimaging as an Enrichment Biomarker in Early Parkinson's Disease Clinical Trials: A Disease Progression Modeling Analysis

PubMed Central

Nicholas, Timothy; Tsai, Kuenhi; Macha, Sreeraj; Sinha, Vikram; Stone, Julie; Corrigan, Brian; Bani, Massimo; Muglia, Pierandrea; Watson, Ian A.; Kern, Volker D.; Sheveleva, Elena; Marek, Kenneth; Stephenson, Diane T.; Romero, Klaus

2017-01-01

Abstract Given the recognition that disease‐modifying therapies should focus on earlier Parkinson's disease stages, trial enrollment based purely on clinical criteria poses significant challenges. The goal herein was to determine the utility of dopamine transporter neuroimaging as an enrichment biomarker in early motor Parkinson's disease clinical trials. Patient‐level longitudinal data of 672 subjects with early‐stage Parkinson's disease in the Parkinson's Progression Markers Initiative (PPMI) observational study and the Parkinson Research Examination of CEP‐1347 Trial (PRECEPT) clinical trial were utilized in a linear mixed‐effects model analysis. The rate of worsening in the motor scores between subjects with or without a scan without evidence of dopamine transporter deficit was different both statistically and clinically. The average difference in the change from baseline of motor scores at 24 months between biomarker statuses was –3.16 (90% confidence interval [CI] = –0.96 to –5.42) points. Dopamine transporter imaging could identify subjects with a steeper worsening of the motor scores, allowing trial enrichment and 24% reduction of sample size. PMID:28749580

Biotin-responsive basal ganglia disease: neuroimaging features before and after treatment.

PubMed

Kassem, H; Wafaie, A; Alsuhibani, S; Farid, T

2014-10-01

Biotin-responsive basal ganglia disease is an autosomal recessive neurometabolic disorder presenting with subacute encephalopathy that can cause death if left untreated. The purpose of this study is to assess the neuroimaging and clinical features of the disease before and after treatment with biotin. We retrospectively reviewed the clinical, laboratory, and neuroimaging features of 15 genetically-proved Middle Eastern cases of biotin-responsive basal ganglia disease. Brain MR imaging was done at the onset of symptoms in all cases and within 2-8 weeks after biotin and thiamine therapy in 14 patients. The MR imaging datasets were analyzed according to lesion location, extent, and distribution. Brain MR imaging showed bilateral lesions in the caudate nuclei with complete or partial involvement of the putamen and sparing of the globus pallidus in all cases. In 80%, discrete abnormal signals were observed in the mesencephalon, cerebral cortical-subcortical regions, and thalami. In 53%, when the disease was advanced, patchy deep white matter affection was found. The cerebellum was involved in 13.3%. The signal abnormality of the mesencephalon, cortex, and white matter disappeared after treatment whereas the caudate and putamen necrosis persisted in all patients, including those who became asymptomatic. Biotin-responsive basal ganglia disease is a treatable underdiagnosed disease. It should be suspected in pediatric patients with unexplained encephalopathy whose brain MR imaging shows bilateral and symmetric lesions in the caudate heads and putamen, with or without involvement of mesencephalon, thalami, and cortical-subcortical regions, as the therapeutic trial of biotin and thiamine can be lifesaving. © 2014 by American Journal of Neuroradiology.

Ethics Analysis of Neuroimaging in Alzheimer’s Disease

PubMed Central

Illes, J.; Rosen, A.; Greicius, M.; Racine, E.

2009-01-01

This article focuses on the prospects and ethics of using neuroimaging to predict Alzheimer’s disease (AD). It is motivated by consideration of the historical roles of science in medicine and society, and considerations specifically contemporary of capabilities in imaging and aging, and the benefits and hope they bring. A general consensus is that combinations of imaging methods will ultimately be most fruitful in predicting disease. Their roll-out into translational practice will not be free of complexity, however, as culture and values differ in terms of what defines benefit and risk, who will benefit and who is at risk, what methods must be in place to assure the maximum safety, comfort, and protection of subjects and patients, and educational and policy needs. Proactive planning for the ethical and societal implications of predicting diseases of the aging brain is critical and will benefit all stakeholders— researchers, patients and families, health care providers, and policy makers. PMID:17413029

Dopamine Transporter Neuroimaging as an Enrichment Biomarker in Early Parkinson's Disease Clinical Trials: A Disease Progression Modeling Analysis.

PubMed

Conrado, Daniela J; Nicholas, Timothy; Tsai, Kuenhi; Macha, Sreeraj; Sinha, Vikram; Stone, Julie; Corrigan, Brian; Bani, Massimo; Muglia, Pierandrea; Watson, Ian A; Kern, Volker D; Sheveleva, Elena; Marek, Kenneth; Stephenson, Diane T; Romero, Klaus

2018-01-01

Given the recognition that disease-modifying therapies should focus on earlier Parkinson's disease stages, trial enrollment based purely on clinical criteria poses significant challenges. The goal herein was to determine the utility of dopamine transporter neuroimaging as an enrichment biomarker in early motor Parkinson's disease clinical trials. Patient-level longitudinal data of 672 subjects with early-stage Parkinson's disease in the Parkinson's Progression Markers Initiative (PPMI) observational study and the Parkinson Research Examination of CEP-1347 Trial (PRECEPT) clinical trial were utilized in a linear mixed-effects model analysis. The rate of worsening in the motor scores between subjects with or without a scan without evidence of dopamine transporter deficit was different both statistically and clinically. The average difference in the change from baseline of motor scores at 24 months between biomarker statuses was -3.16 (90% confidence interval [CI] = -0.96 to -5.42) points. Dopamine transporter imaging could identify subjects with a steeper worsening of the motor scores, allowing trial enrichment and 24% reduction of sample size. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.

PubMed

Ramanan, Vijay K; Kim, Sungeun; Holohan, Kelly; Shen, Li; Nho, Kwangsik; Risacher, Shannon L; Foroud, Tatiana M; Mukherjee, Shubhabrata; Crane, Paul K; Aisen, Paul S; Petersen, Ronald C; Weiner, Michael W; Saykin, Andrew J

2012-12-01

Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions.

Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative.

PubMed

Russo, María J; Campos, Jorge; Vázquez, Silvia; Sevlever, Gustavo; Allegri, Ricardo F

2017-01-01

Background: Ongoing research is focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to Alzheimer's disease (AD). We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up. Methods: A total of 397 amnestic-MCI subjects from Alzheimer's disease Neuroimaging Initiative were included. Logistic regression modeling was done to assess the predictive value of all RAVLT measures, risk factors such as age, sex, education, APOE genotype, and CSF biomarkers for progression to AD. Estimating adjusted odds ratios was used to determine which variables would produce an optimal predictive model, and whether adding tests of interaction between the RAVLT Delayed Recall and recognition measures (traditional score and d-prime) would improve prediction of the conversion from a-MCI to AD. Results: 112 (28.2%) subjects developed dementia and 285 (71.8%) subjects did not. Of the all included variables, CSF Aβ1-42 levels, RAVLT Delayed Recall, and the combination of RAVLT Delayed Recall and d-prime were predictive of progression to AD (χ 2 = 38.23, df = 14, p < 0.001). Conclusions: The combination of RAVLT Delayed Recall and d-prime measures may be predictor of conversion from MCI to AD in the ADNI cohort, especially in combination with amyloid biomarkers. A predictive model to help identify individuals at-risk for dementia should include not only traditional episodic memory measures (delayed recall or recognition), but also additional variables (d-prime) that allow the homogenization of the assessment procedures in the diagnosis of MCI.

Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative

PubMed Central

Russo, María J.; Campos, Jorge; Vázquez, Silvia; Sevlever, Gustavo; Allegri, Ricardo F.; Weiner, Michael W.

2017-01-01

Background: Ongoing research is focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to Alzheimer's disease (AD). We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up. Methods: A total of 397 amnestic-MCI subjects from Alzheimer's disease Neuroimaging Initiative were included. Logistic regression modeling was done to assess the predictive value of all RAVLT measures, risk factors such as age, sex, education, APOE genotype, and CSF biomarkers for progression to AD. Estimating adjusted odds ratios was used to determine which variables would produce an optimal predictive model, and whether adding tests of interaction between the RAVLT Delayed Recall and recognition measures (traditional score and d-prime) would improve prediction of the conversion from a-MCI to AD. Results: 112 (28.2%) subjects developed dementia and 285 (71.8%) subjects did not. Of the all included variables, CSF Aβ1-42 levels, RAVLT Delayed Recall, and the combination of RAVLT Delayed Recall and d-prime were predictive of progression to AD (χ2 = 38.23, df = 14, p < 0.001). Conclusions: The combination of RAVLT Delayed Recall and d-prime measures may be predictor of conversion from MCI to AD in the ADNI cohort, especially in combination with amyloid biomarkers. A predictive model to help identify individuals at-risk for dementia should include not only traditional episodic memory measures (delayed recall or recognition), but also additional variables (d-prime) that allow the homogenization of the assessment procedures in the diagnosis of MCI. PMID:28344552

Choosing Wisely: A Neurosurgical Perspective on Neuroimaging for Headaches

PubMed Central

Hawasli, Ammar H.; Chicoine, Michael R.; Dacey, Ralph G.

2016-01-01

Multiple national initiatives seek to curb spending in order to address increasing health care costs in the United States. The Choosing Wisely® initiative is one popular initiative that focuses on reducing health care spending by setting guidelines to limit tests and procedures requested by patients and ordered by physicians. To reduce spending on neuroimaging, the Choosing Wisely® initiative and other organizations have offered guidelines to limit neuroimaging for headaches. Although the intentions are laudable, these guidelines are inconsistent with the neurosurgeon’s experience with brain tumor patients. If adopted by governing or funding organizations, these guidelines threaten to negatively impact the care and outcomes of patients with brain tumors, who frequently present with minimal symptoms or isolated headaches syndromes. As we grapple with the difficult conflict between evidence-based cost-cutting guidelines and individualized patient-tailored medicine, a physician must carefully balance the costs and benefits of discretionary services such as neuroimaging for headaches. By participating in the development of validated clinical decision rules on neuroimaging for headaches, neurosurgeons can advocate for their patients and improve their patients’ outcomes. PMID:25255253

Neuropathologic assessment of participants in two multi-center longitudinal observational studies: the Alzheimer Disease Neuroimaging Initiative (ADNI) and the Dominantly Inherited Alzheimer Network (DIAN).

PubMed

Cairns, Nigel J; Perrin, Richard J; Franklin, Erin E; Carter, Deborah; Vincent, Benjamin; Xie, Mingqiang; Bateman, Randall J; Benzinger, Tammie; Friedrichsen, Karl; Brooks, William S; Halliday, Glenda M; McLean, Catriona; Ghetti, Bernardino; Morris, John C

2015-08-01

It has been hypothesized that the relatively rare autosomal dominant Alzheimer disease (ADAD) may be a useful model of the more frequent, sporadic, late-onset AD (LOAD). Individuals with ADAD have a predictable age at onset and the biomarker profile of ADAD participants in the preclinical stage may be used to predict disease progression and clinical onset. However, the extent to which the pathogenesis and neuropathology of ADAD overlaps with that of LOAD is equivocal. To address this uncertainty, two multicenter longitudinal observational studies, the Alzheimer Disease Neuroimaging Initiative (ADNI) and the Dominantly Inherited Alzheimer Network (DIAN), leveraged the expertise and resources of the existing Knight Alzheimer Disease Research Center (ADRC) at Washington University School of Medicine, St. Louis, Missouri, USA, to establish a Neuropathology Core (NPC). The ADNI/DIAN-NPC is systematically examining the brains of all participants who come to autopsy at the 59 ADNI sites in the USA and Canada and the 14 DIAN sites in the USA (eight), Australia (three), UK (one) and Germany (two). By 2014, 41 ADNI and 24 DIAN autopsies (involving nine participants and 15 family members) had been performed. The autopsy rate in the ADNI cohort in the most recent year was 93% (total since NPC inception: 70%). In summary, the ADNI/DIAN NPC has implemented a standard protocol for all sites to solicit permission for brain autopsy and to send brain tissue to the NPC for a standardized, uniform and state-of-the-art neuropathologic assessment. The benefit to ADNI and DIAN of the implementation of the NPC is very clear. The NPC provides final "gold standard" neuropathological diagnoses and data against which the antecedent observations and measurements of ADNI and DIAN can be compared. © 2015 Japanese Society of Neuropathology.

Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration

PubMed Central

Wardlaw, Joanna M; Smith, Eric E; Biessels, Geert J; Cordonnier, Charlotte; Fazekas, Franz; Frayne, Richard; Lindley, Richard I; O'Brien, John T; Barkhof, Frederik; Benavente, Oscar R; Black, Sandra E; Brayne, Carol; Breteler, Monique; Chabriat, Hugues; DeCarli, Charles; de Leeuw, Frank-Erik; Doubal, Fergus; Duering, Marco; Fox, Nick C; Greenberg, Steven; Hachinski, Vladimir; Kilimann, Ingo; Mok, Vincent; Oostenbrugge, Robert van; Pantoni, Leonardo; Speck, Oliver; Stephan, Blossom C M; Teipel, Stefan; Viswanathan, Anand; Werring, David; Chen, Christopher; Smith, Colin; van Buchem, Mark; Norrving, Bo; Gorelick, Philip B; Dichgans, Martin

2013-01-01

Summary Cerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE). PMID:23867200

An unusual neuroimaging finding and response to immunotherapy in a child with genetically confirmed vanishing white matter disease.

PubMed

Singh, Rahul Raman; Livingston, John; Lim, Ming; Berry, Ian R; Siddiqui, Ata

2017-03-01

We present an unusual neuroimaging finding in a young girl with genetically confirmed vanishing white matter disease and a possible response to immunotherapy. 2.5 yr old girl, presented with acute onset unsteadiness and encephalopathy following a viral illness. MRI showed global symmetric white matter abnormality, with symmetric enhancement of cranial nerves (III and V) and of cervical and lumbar roots. She received immunotherapy for her encephalopathic illness with white matter changes. Follow up neuroimaging showed resolution of white matter edema and resolution of the change in the brainstem. Genetic testing confirmed a diagnosis of vanishing white matter disease (VWMD). Craniospinal nerve enhancement and possible response to immunotherapy has not been described in vanishing white matter disease. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

The Complexity of Clinical Huntington's Disease: Developments in Molecular Genetics, Neuropathology and Neuroimaging Biomarkers.

PubMed

Tippett, Lynette J; Waldvogel, Henry J; Snell, Russell G; Vonsattel, Jean-Paul; Young, Anne B; Faull, Richard L M

2017-01-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder characterised by extensive neuronal loss in the striatum and cerebral cortex, and a triad of clinical symptoms affecting motor, cognitive/behavioural and mood functioning. The mutation causing HD is an expansion of a CAG tract in exon 1 of the HTT gene. This chapter provides a multifaceted overview of the clinical complexity of HD. We explore recent directions in molecular genetics including the identification of loci that are genetic modifiers of HD that could potentially reveal therapeutic targets beyond the HTT gene transcript and protein. The variability of clinical symptomatology in HD is considered alongside recent findings of variability in cellular and neurochemical changes in the striatum and cerebral cortex in human brain. We review evidence from structural neuroimaging methods of progressive changes of striatum, cerebral cortex and white matter in pre-symptomatic and symptomatic HD, with a particular focus on the potential identification of neuroimaging biomarkers that could be used to test promising disease-specific and modifying treatments. Finally we provide an overview of completed clinical trials in HD and future therapeutic developments.

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.

PubMed

Dimitriadis, S I; Liparas, Dimitris; Tsolaki, Magda N

2018-05-15

In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI. Based on preprocessed MRI images from the organizers of a neuroimaging challenge, 3 we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme. In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition. The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature. Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of analgesics on executive function and memory in the Alzheimer's Disease Neuroimaging Initiative Database.

PubMed

Doan, Lisa; Choi, Daniel; Kline, Richard

2017-10-01

Pain is common in older adults but may be undertreated in part due to concerns about medication toxicity. Analgesics may affect cognition. In this retrospective cohort study, we used the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to examine the interaction of cognitive status and medications, especially non-steroidal anti-inflammatory drugs (NSAIDs). We hypothesized NSAID use would be associated with cognition and that this could be mediated through changes in brain structure. In this post hoc analysis of the ADNI database, subjects were selected by searching the "concurrent medications log" for analgesic medications. Subjects were included if the analgesic was listed on the medication log prior to enrollment in ADNI and throughout the study. Subjects taking analgesics, particularly NSAIDs, at each study visit were compared to control subjects taking no analgesics. Using descriptive statistics as well as univariate, multivariate and repeated measure ANOVA, we explored the relationship between NSAID use and scores for executive function and memory related cognitive activities. We further took advantage of the extensive magnetic resonance imaging (MRI) data available in ADNI to test whether cognitive change was associated with brain structure. The multitude of imaging variables was compressed into a small number of features (five eigenvectors (EV)) using principal component analysis. There were 87 NSAID users, 373 controls, and 71 taking other analgesics. NSAID use was associated with higher executive function scores for cognitively normal (NL) subjects as well as subjects with mild cognitive impairment (MCI). NSAID use was also associated with higher memory scores, but for NL females only. We analysed MRI data using principal component analysis to generate a set of five EVs. Examining NL and MCI subjects, one EV had significantly larger values in subjects taking NSAIDs versus control. This EV was one of two EVs which significantly correlated with

Coexisting cerebral infarction in Alzheimer's disease is associated with fast dementia progression: applying the National Institute for Neurological Disorders and Stroke/Association Internationale pour la Recherche et l'Enseignement en Neurosciences Neuroimaging Criteria in Alzheimer's Disease with Concomitant Cerebral Infarction.

PubMed

Sheng, Bun; Cheng, Lik Fai; Law, Chun Bon; Li, Ho Lun; Yeung, Kwan Mo; Lau, Kwok Kwong

2007-06-01

To determine whether patients with Alzheimer's disease (AD) and coexisting cerebral infarction (CI) that satisfy the National Institute for Neurological Disorders and Stroke/Association Internationale pour la Recherche et l'Enseignement en Neurosciences (NINDS-AIREN) neuroimaging criteria for vascular dementia (VaD) progress faster than those who do not satisfy the neuroimaging criteria. Retrospective cohort study. Multidisciplinary memory clinic in a tertiary hospital. One hundred thirty consecutive patients with AD, with or without CI, followed up regularly for more than 1 year. The patients were classified according to the distribution and severity of CI as defined according to the NINDS-AIREN neuroimaging criteria into those with AD and no CI (AD-N), those with AD and CI not fulfilling neuroimaging criteria (AD-I), and those with AD and CI fulfilling neuroimaging criteria (AD-V), and their differences in dementia progression were tested. The loss of independence, indicated by institution admission or a clinical dementia rating (CDR) score of 3, was defined as the endpoint for a poor outcome. The mean age was 75.8, and 68.5% were women. The initial Mini-Mental State Examination (MMSE) score was 15.3+/-0.4, and the average duration of follow up was 30.4 months. Fifty-four patients had reached study endpoint at the time of analysis. AD-V (hazard ratio (HR)=3.1, 95% confidence interval (CI)=1.2-8.2), use of psychotropic drugs (HR=2.7, 95% CI=1.1-6.4), and initial MMSE score (HR=0.9, 95% CI=0.8-1.0) were independent predictors of poor outcome in the Cox regression model. In AD, co-occurrence of CI with distribution and severity as defined in the NINDS-AIREN neuroimaging criteria for VaD is associated with faster dementia progression.

Effect of Education on Alzheimer's Disease-Related Neuroimaging Biomarkers in Healthy Controls, and Participants with Mild Cognitive Impairment and Alzheimer's Disease: A Cross-Sectional Study.

PubMed

Wada, Masataka; Noda, Yoshihiro; Shinagawa, Shunichiro; Chung, Jun Ku; Sawada, Kyosuke; Ogyu, Kamiyu; Tarumi, Ryosuke; Tsugawa, Sakiko; Miyazaki, Takahiro; Yamagata, Bun; Graff-Guerrero, Ariel; Mimura, Masaru; Nakajima, Shinichiro

2018-01-01

Cognitive reserve is the acquired capacity reflecting a functional brain adaptability/flexibility in the context of aging. Educational attainment is thought to be among the most important factors that contribute to cognitive reserve. The aim of this study is to investigate the relationships among duration of education and Alzheimer's disease (AD) related neuroimaging biomarkers such as amyloid-β deposition, glucose metabolism, and brain volumes in each stage of AD. We reanalyzed a part of the datasets of the Alzheimer's Disease Neuroimaging Initiative. Participants were between 55 and 90 years of age and diagnosed as one of the following: healthy controls (HC), mild cognitive impairment (MCI), or AD. Multiple regression analyses were conducted to examine the relationships among duration of education and amyloid-β deposition (n = 825), brain metabolism (n = 1,304), and brain volumes (n = 1,606) among three groups using data for 18F-Florbetapir (AV-45) imaging, fludeoxyglucose (FDG) positron emission tomography, and T1-weighted magnetic resonance imaging. Duration of education had no correlations with amyloid-β deposition or brain metabolism in any groups. However, duration of education was positively associated with the total brain volume only in participants with MCI. Our findings suggest that education may exert a protective effect on total brain volume in the MCI stage but not in HC or AD. Thus, education may play an important role in preventing the onset of dementia through brain reserve in MCI.

Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review.

PubMed

Sarica, Alessia; Cerasa, Antonio; Quattrone, Aldo

2017-01-01

Objective: Machine learning classification has been the most important computational development in the last years to satisfy the primary need of clinicians for automatic early diagnosis and prognosis. Nowadays, Random Forest (RF) algorithm has been successfully applied for reducing high dimensional and multi-source data in many scientific realms. Our aim was to explore the state of the art of the application of RF on single and multi-modal neuroimaging data for the prediction of Alzheimer's disease. Methods: A systematic review following PRISMA guidelines was conducted on this field of study. In particular, we constructed an advanced query using boolean operators as follows: ("random forest" OR "random forests") AND neuroimaging AND ("alzheimer's disease" OR alzheimer's OR alzheimer) AND (prediction OR classification) . The query was then searched in four well-known scientific databases: Pubmed, Scopus, Google Scholar and Web of Science. Results: Twelve articles-published between the 2007 and 2017-have been included in this systematic review after a quantitative and qualitative selection. The lesson learnt from these works suggest that when RF was applied on multi-modal data for prediction of Alzheimer's disease (AD) conversion from the Mild Cognitive Impairment (MCI), it produces one of the best accuracies to date. Moreover, the RF has important advantages in terms of robustness to overfitting, ability to handle highly non-linear data, stability in the presence of outliers and opportunity for efficient parallel processing mainly when applied on multi-modality neuroimaging data, such as, MRI morphometric, diffusion tensor imaging, and PET images. Conclusions: We discussed the strengths of RF, considering also possible limitations and by encouraging further studies on the comparisons of this algorithm with other commonly used classification approaches, particularly in the early prediction of the progression from MCI to AD.

A Neuroimaging Web Services Interface as a Cyber Physical System for Medical Imaging and Data Management in Brain Research: Design Study.

PubMed

Lizarraga, Gabriel; Li, Chunfei; Cabrerizo, Mercedes; Barker, Warren; Loewenstein, David A; Duara, Ranjan; Adjouadi, Malek

2018-04-26

Structural and functional brain images are essential imaging modalities for medical experts to study brain anatomy. These images are typically visually inspected by experts. To analyze images without any bias, they must be first converted to numeric values. Many software packages are available to process the images, but they are complex and difficult to use. The software packages are also hardware intensive. The results obtained after processing vary depending on the native operating system used and its associated software libraries; data processed in one system cannot typically be combined with data on another system. The aim of this study was to fulfill the neuroimaging community’s need for a common platform to store, process, explore, and visualize their neuroimaging data and results using Neuroimaging Web Services Interface: a series of processing pipelines designed as a cyber physical system for neuroimaging and clinical data in brain research. Neuroimaging Web Services Interface accepts magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and functional magnetic resonance imaging. These images are processed using existing and custom software packages. The output is then stored as image files, tabulated files, and MySQL tables. The system, made up of a series of interconnected servers, is password-protected and is securely accessible through a Web interface and allows (1) visualization of results and (2) downloading of tabulated data. All results were obtained using our processing servers in order to maintain data validity and consistency. The design is responsive and scalable. The processing pipeline started from a FreeSurfer reconstruction of Structural magnetic resonance imaging images. The FreeSurfer and regional standardized uptake value ratio calculations were validated using Alzheimer’s Disease Neuroimaging Initiative input images, and the results were posted at the Laboratory of Neuro Imaging data archive. Notable

A Neuroimaging Web Services Interface as a Cyber Physical System for Medical Imaging and Data Management in Brain Research: Design Study

PubMed Central

2018-01-01

Background Structural and functional brain images are essential imaging modalities for medical experts to study brain anatomy. These images are typically visually inspected by experts. To analyze images without any bias, they must be first converted to numeric values. Many software packages are available to process the images, but they are complex and difficult to use. The software packages are also hardware intensive. The results obtained after processing vary depending on the native operating system used and its associated software libraries; data processed in one system cannot typically be combined with data on another system. Objective The aim of this study was to fulfill the neuroimaging community’s need for a common platform to store, process, explore, and visualize their neuroimaging data and results using Neuroimaging Web Services Interface: a series of processing pipelines designed as a cyber physical system for neuroimaging and clinical data in brain research. Methods Neuroimaging Web Services Interface accepts magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and functional magnetic resonance imaging. These images are processed using existing and custom software packages. The output is then stored as image files, tabulated files, and MySQL tables. The system, made up of a series of interconnected servers, is password-protected and is securely accessible through a Web interface and allows (1) visualization of results and (2) downloading of tabulated data. Results All results were obtained using our processing servers in order to maintain data validity and consistency. The design is responsive and scalable. The processing pipeline started from a FreeSurfer reconstruction of Structural magnetic resonance imaging images. The FreeSurfer and regional standardized uptake value ratio calculations were validated using Alzheimer’s Disease Neuroimaging Initiative input images, and the results were posted at the Laboratory of

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

Functional neuroimaging of extraversion-introversion.

PubMed

Lei, Xu; Yang, Tianliang; Wu, Taoyu

2015-12-01

Neuroimaging techniques such as functional magnetic resonance imaging and positron emission tomography have provided an unprecedented neurobiological perspective for research on personality traits. Evidence from task-related neuroimaging has shown that extraversion is associated with activations in regions of the anterior cingulate cortex, dorsolateral prefrontal cortex, middle temporal gyrus and the amygdala. Currently, resting-state neuroimaging is being widely used in cognitive neuroscience. Initial exploration of extraversion has revealed correlations with the medial prefrontal cortex, anterior cingulate cortex, insular cortex, and the precuneus. Recent research work has indicated that the long-range temporal dependence of the resting-state spontaneous oscillation has high test-retest reliability. Moreover, the long-range temporal dependence of the resting-state networks is highly correlated with personality traits, and this can be used for the prediction of extraversion. As the long-range temporal dependence reflects real-time information updating in individuals, this method may provide a new approach to research on personality traits.

[How to start a neuroimaging study].

PubMed

Narumoto, Jin

2012-06-01

In order to help researchers understand how to start a neuroimaging study, several tips are described in this paper. These include 1) Choice of an imaging modality, 2) Statistical method, and 3) Interpretation of the results. 1) There are several imaging modalities available in clinical research. Advantages and disadvantages of each modality are described. 2) Statistical Parametric Mapping, which is the most common statistical software for neuroimaging analysis, is described in terms of parameter setting in normalization and level of significance. 3) In the discussion section, the region which shows a significant difference between patients and normal controls should be discussed in relation to the neurophysiology of the disease, making reference to previous reports from neuroimaging studies in normal controls, lesion studies and animal studies. A typical pattern of discussion is described.

Pseudotumoral hemicerebellitis as a mimicker of Lhermitte-Duclos disease in children: does neuroimaging help to differentiate them?

PubMed

Bosemani, Thangamadhan; Steinlin, Maja; Toelle, Sandra P; Beck, Jürgen; Boltshauser, Eugen; Huisman, Thierry A G M; Poretti, Andrea

2016-05-01

The clinical presentation and neuroimaging findings of children with pseudotumoral hemicerebellitis (PTHC) and Lhermitte-Duclos disease (LDD) may be very similar. The differentiation between these entities, however, is important because their management and prognosis are different. We report on three children with PTHC. For all three children, in the acute situation, the differentiation between PTHC and LDD was challenging. A review of the literature shows that a detailed evaluation of conventional and neuroimaging data may help to differentiate between these two entities. A striated folial pattern, brainstem involvement, and prominent veins surrounding the thickened cerebellar foliae on susceptibility weighted imaging favor LDD, while post-contrast enhancement and an increased choline peak on (1)H-Magnetic resonance spectroscopy suggest PTHC.

GPU Accelerated Browser for Neuroimaging Genomics.

PubMed

Zigon, Bob; Li, Huang; Yao, Xiaohui; Fang, Shiaofen; Hasan, Mohammad Al; Yan, Jingwen; Moore, Jason H; Saykin, Andrew J; Shen, Li

2018-04-25

Neuroimaging genomics is an emerging field that provides exciting opportunities to understand the genetic basis of brain structure and function. The unprecedented scale and complexity of the imaging and genomics data, however, have presented critical computational bottlenecks. In this work we present our initial efforts towards building an interactive visual exploratory system for mining big data in neuroimaging genomics. A GPU accelerated browsing tool for neuroimaging genomics is created that implements the ANOVA algorithm for single nucleotide polymorphism (SNP) based analysis and the VEGAS algorithm for gene-based analysis, and executes them at interactive rates. The ANOVA algorithm is 110 times faster than the 4-core OpenMP version, while the VEGAS algorithm is 375 times faster than its 4-core OpenMP counter part. This approach lays a solid foundation for researchers to address the challenges of mining large-scale imaging genomics datasets via interactive visual exploration.

GM2-Gangliosidosis (Sandhoff and Tay Sachs disease): Diagnosis and Neuroimaging Findings (An Iranian Pediatric Case Series).

PubMed

Karimzadeh, Parvaneh; Jafari, Narjes; Nejad Biglari, Habibeh; Jabbeh Dari, Sayena; Ahmad Abadi, Farzad; Alaee, Mohammad-Reza; Nemati, Hamid; Saket, Sasan; Tonekaboni, Seyed Hasan; Taghdiri, Mohammad-Mahdi; Ghofrani, Mohammad

2014-01-01

GM2-Gangliosidosis disease is a rare autosomal recessive genetic disorder that includes two disorders (Tay-Sachs and Sandhoff disease).These disorders cause a progressive deterioration of nerve cells and inherited deficiency in creating hexosaminidases A, B, and AB. Patients who were diagnosed withGM2-Gangliosidosis in the Neurology Department of Mofid Children's Hospital in Tehran, Iran from October 2009 to February 2014were included in our study. The disorder was confirmed by neurometabolic and enzyme level detection of hexosaminidases A, B, and AB in reference to Wagnester Laboratory in Germany. We assessed age, gender, past medical history, developmental status, clinical manifestations, and neuroimaging findings of 9 patients with Sandhoff disease and 9 with Tay Sachs disease. 83% of our patients were the offspring of consanguineous marriages. All of them had a developmental disorder as a chief complaint. 38%of patients had a history of developmental delay or regression and 22% had seizures. The patients with Sandhoff and Tay Sachs disease were followed for approximately 5 years and the follow-up showed all patients were bedridden or had expired due to refractory seizures, pneumonia aspiration, or swallowing disorders. Neuro-imaging findings included bilateral thalamic involvement, brain atrophy, and hypo myelination in near half of our patients (48%). According to the results of this study, we suggest that cherry-red spots, hyperacusis, refractory seizures, and relative parents in children with developmental delay and/or regression should be considered for assessment of GM2-Gangliosidosis disease.

Neuroimaging findings in pediatric sports-related concussion.

PubMed

Ellis, Michael J; Leiter, Jeff; Hall, Thomas; McDonald, Patrick J; Sawyer, Scott; Silver, Norm; Bunge, Martin; Essig, Marco

2015-09-01

The goal in this review was to summarize the results of clinical neuroimaging studies performed in patients with sports-related concussion (SRC) who were referred to a multidisciplinar ypediatric concussion program. The authors conducted a retrospective review of medical records and neuroimaging findings for all patients referred to a multidisciplinary pediatric concussion program between September 2013 and July 2014. Inclusion criteria were as follows: 1) age ≤ 19 years; and 2) physician-diagnosed SRC. All patients underwent evaluation and follow-up by the same neurosurgeon. The 2 outcomes examined in this review were the frequency of neuroimaging studies performed in this population (including CT and MRI) and the findings of those studies. Clinical indications for neuroimaging and the impact of neuroimaging findings on clinical decision making were summarized where available. This investigation was approved by the local institutional ethics review board. A total of 151 patients (mean age 14 years, 59% female) were included this study. Overall, 36 patients (24%) underwent neuroimaging studies, the results of which were normal in 78% of cases. Sixteen percent of patients underwent CT imaging; results were normal in 79% of cases. Abnormal CT findings included the following: arachnoid cyst (1 patient), skull fracture (2 patients), suspected intracranial hemorrhage (1 patient), and suspected hemorrhage into an arachnoid cyst (1 patient). Eleven percent of patients underwent MRI; results were normal in 75% of cases. Abnormal MRI findings included the following: intraparenchymal hemorrhage and sylvian fissure arachnoid cyst (1 patient); nonhemorrhagic contusion (1 patient); demyelinating disease (1 patient); and posterior fossa arachnoid cyst, cerebellar volume loss, and nonspecific white matter changes (1 patient). Results of clinical neuroimaging studies are normal in the majority of pediatric patients with SRC. However, in selected cases neuroimaging can provide

Exploring APOE genotype effects on Alzheimer's disease risk and amyloid β burden in individuals with subjective cognitive decline: The FundacioACE Healthy Brain Initiative (FACEHBI) study baseline results.

PubMed

Moreno-Grau, Sonia; Rodríguez-Gómez, Octavio; Sanabria, Ángela; Pérez-Cordón, Alba; Sánchez-Ruiz, Domingo; Abdelnour, Carla; Valero, Sergi; Hernández, Isabel; Rosende-Roca, Maitée; Mauleón, Ana; Vargas, Liliana; Lafuente, Asunción; Gil, Silvia; Santos-Santos, Miguel Ángel; Alegret, Montserrat; Espinosa, Ana; Ortega, Gemma; Guitart, Marina; Gailhajanet, Anna; de Rojas, Itziar; Sotolongo-Grau, Óscar; Ruiz, Susana; Aguilera, Nuria; Papasey, Judith; Martín, Elvira; Peleja, Esther; Lomeña, Francisco; Campos, Francisco; Vivas, Assumpta; Gómez-Chiari, Marta; Tejero, Miguel Ángel; Giménez, Joan; Serrano-Ríos, Manuel; Orellana, Adelina; Tárraga, Lluís; Ruiz, Agustín; Boada, Mercè

2018-05-01

Subjective cognitive decline (SCD) has been proposed as a potential preclinical stage of Alzheimer's disease (AD). Nevertheless, the genetic and biomarker profiles of SCD individuals remain mostly unexplored. We evaluated apolipoprotein E (APOE) ε4's effect in the risk of presenting SCD, using the Fundacio ACE Healthy Brain Initiative (FACEHBI) SCD cohort and Spanish controls, and performed a meta-analysis addressing the same question. We assessed the relationship between APOE dosage and brain amyloid burden in the FACEHBI SCD and Alzheimer's Disease Neuroimaging Initiative cohorts. Analysis of the FACEHBI cohort and the meta-analysis demonstrated SCD individuals presented higher allelic frequencies of APOE ε4 with respect to controls. APOE dosage explained 9% (FACEHBI cohort) and 11% (FACEHBI and Alzheimer's Disease Neuroimaging Initiative cohorts) of the variance of cerebral amyloid levels. The FACEHBI sample presents APOE ε4 enrichment, suggesting that a pool of AD patients is nested in our sample. Cerebral amyloid levels are partially explained by the APOE allele dosage, suggesting that other genetic or epigenetic factors are involved in this AD endophenotype. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Structural and Functional Neuroimaging of Visual Hallucinations in Lewy Body Disease: A Systematic Literature Review

PubMed Central

Cagnin, Annachiara; Bandmann, Oliver; Venneri, Annalena

2017-01-01

Patients with Lewy body disease (LBD) frequently experience visual hallucinations (VH), well-formed images perceived without the presence of real stimuli. The structural and functional brain mechanisms underlying VH in LBD are still unclear. The present review summarises the current literature on the neural correlates of VH in LBD, namely Parkinson’s disease (PD), and dementia with Lewy bodies (DLB). Following a systematic literature search, 56 neuroimaging studies of VH in PD and DLB were critically reviewed and evaluated for quality assessment. The main structural neuroimaging results on VH in LBD revealed grey matter loss in frontal areas in patients with dementia, and parietal and occipito-temporal regions in PD without dementia. Parietal and temporal hypometabolism was also reported in hallucinating PD patients. Disrupted functional connectivity was detected especially in the default mode network and fronto-parietal regions. However, evidence on structural and functional connectivity is still limited and requires further investigation. The current literature is in line with integrative models of VH suggesting a role of attention and perception deficits in the development of VH. However, despite the close relationship between VH and cognitive impairment, its associations with brain structure and function have been explored only by a limited number of studies. PMID:28714891

Multimodal neuroimaging of male and female brain structure in health and disease across the life span

PubMed Central

Thompson, Paul M.

2016-01-01

Sex differences in brain development and aging are important to identify, as they may help to understand risk factors and outcomes in brain disorders that are more prevalent in one sex compared with the other. Brain imaging techniques have advanced rapidly in recent years, yielding detailed structural and functional maps of the living brain. Even so, studies are often limited in sample size, and inconsistent findings emerge, one example being varying findings regarding sex differences in the size of the corpus callosum. More recently, large‐scale neuroimaging consortia such as the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium have formed, pooling together expertise, data, and resources from hundreds of institutions around the world to ensure adequate power and reproducibility. These initiatives are helping us to better understand how brain structure is affected by development, disease, and potential modulators of these effects, including sex. This review highlights some established and disputed sex differences in brain structure across the life span, as well as pitfalls related to interpreting sex differences in health and disease. We also describe sex‐related findings from the ENIGMA consortium, and ongoing efforts to better understand sex differences in brain circuitry. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc. PMID:27870421

Neuroimaging and Fetal Alcohol Spectrum Disorders

ERIC Educational Resources Information Center

Norman, Andria L.; Crocker, Nicole; Mattson, Sarah N.; Riley, Edward P.

2009-01-01

The detrimental effects of prenatal alcohol exposure on the developing brain include structural brain anomalies as well as cognitive and behavioral deficits. Initial neuroimaging studies of fetal alcohol spectrum disorders (FASD) using magnetic resonance imaging (MRI) confirmed previous autopsy reports of overall reduction in brain volume and…

The Shepherd's Crook Sign: A New Neuroimaging Pareidolia in Joubert Syndrome.

PubMed

Manley, Andrew T; Maertens, Paul M

2015-01-01

By pareidolically recognizing specific patterns indicative of particular diseases, neuroimagers reinforce their mnemonic strategies and improve their neuroimaging diagnostic skills. Joubert Syndrome (JS) is an autosomal recessive disorder characterized clinically by mental retardation, episodes of abnormal deep and rapid breathing, abnormal eye movements, and ataxia. Many neuroimaging signs characteristic of JS have been reported. In retrospective case study, two consanguineous neonates diagnosed with JS were evaluated with brain magnetic resonance imaging (MRI), computed tomography (CT), and neurosonography. Both cranial ultrasound and MRI of the brain showed the characteristic molar tooth sign. There was a shepherd's crook in the sagittal views of the posterior fossa where the shaft of the crook is made by the brainstem and the pons. The arc of the crook is made by the abnormal superior cerebellar peduncle and cerebellar hemisphere. By ultrasound, the shepherd's crook sign was seen through the posterior fontanelle only. CT imaging also showed the shepherd's crook sign. Neuroimaging diagnosis of JS, which already involves the pareidolical recognition of specific patterns indicative of the disease, can be improved by recognition of the shepherd's crook sign on MRI, CT, and cranial ultrasound. Copyright © 2014 by the American Society of Neuroimaging.

Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline

PubMed Central

Dinov, Ivo; Lozev, Kamen; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Zamanyan, Alen; Chakrapani, Shruthi; Van Horn, John; Parker, D. Stott; Magsipoc, Rico; Leung, Kelvin; Gutman, Boris; Woods, Roger; Toga, Arthur

2010-01-01

Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges—management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu. PMID:20927408

Near-Infrared Neuroimaging with NinPy

PubMed Central

Strangman, Gary E.; Zhang, Quan; Zeffiro, Thomas

2009-01-01

There has been substantial recent growth in the use of non-invasive optical brain imaging in studies of human brain function in health and disease. Near-infrared neuroimaging (NIN) is one of the most promising of these techniques and, although NIN hardware continues to evolve at a rapid pace, software tools supporting optical data acquisition, image processing, statistical modeling, and visualization remain less refined. Python, a modular and computationally efficient development language, can support functional neuroimaging studies of diverse design and implementation. In particular, Python's easily readable syntax and modular architecture allow swift prototyping followed by efficient transition to stable production systems. As an introduction to our ongoing efforts to develop Python software tools for structural and functional neuroimaging, we discuss: (i) the role of non-invasive diffuse optical imaging in measuring brain function, (ii) the key computational requirements to support NIN experiments, (iii) our collection of software tools to support NIN, called NinPy, and (iv) future extensions of these tools that will allow integration of optical with other structural and functional neuroimaging data sources. Source code for the software discussed here will be made available at www.nmr.mgh.harvard.edu/Neural_SystemsGroup/software.html. PMID:19543449

Multimodal neuroimaging of male and female brain structure in health and disease across the life span.

PubMed

Jahanshad, Neda; Thompson, Paul M

2017-01-02

Sex differences in brain development and aging are important to identify, as they may help to understand risk factors and outcomes in brain disorders that are more prevalent in one sex compared with the other. Brain imaging techniques have advanced rapidly in recent years, yielding detailed structural and functional maps of the living brain. Even so, studies are often limited in sample size, and inconsistent findings emerge, one example being varying findings regarding sex differences in the size of the corpus callosum. More recently, large-scale neuroimaging consortia such as the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium have formed, pooling together expertise, data, and resources from hundreds of institutions around the world to ensure adequate power and reproducibility. These initiatives are helping us to better understand how brain structure is affected by development, disease, and potential modulators of these effects, including sex. This review highlights some established and disputed sex differences in brain structure across the life span, as well as pitfalls related to interpreting sex differences in health and disease. We also describe sex-related findings from the ENIGMA consortium, and ongoing efforts to better understand sex differences in brain circuitry. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.

PubMed

Cole, James H; Franke, Katja

2017-12-01

The brain changes as we age and these changes are associated with functional deterioration and neurodegenerative disease. It is vital that we better understand individual differences in the brain ageing process; hence, techniques for making individualised predictions of brain ageing have been developed. We present evidence supporting the use of neuroimaging-based 'brain age' as a biomarker of an individual's brain health. Increasingly, research is showing how brain disease or poor physical health negatively impacts brain age. Importantly, recent evidence shows that having an 'older'-appearing brain relates to advanced physiological and cognitive ageing and the risk of mortality. We discuss controversies surrounding brain age and highlight emerging trends such as the use of multimodality neuroimaging and the employment of 'deep learning' methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

High Frequency of Neuroimaging Abnormalities Among Pediatric Patients With Sepsis Who Undergo Neuroimaging.

PubMed

Sandquist, Mary K; Clee, Mark S; Patel, Smruti K; Howard, Kelli A; Yunger, Toni; Nagaraj, Usha D; Jones, Blaise V; Fei, Lin; Vadivelu, Sudhakar; Wong, Hector R

2017-07-01

This study was intended to describe and correlate the neuroimaging findings in pediatric patients after sepsis. Retrospective chart review. Single tertiary care PICU. Patients admitted to Cincinnati Children's Hospital Medical Center with a discharge diagnosis of sepsis or septic shock between 2004 and 2013 were crossmatched with patients who underwent neuroimaging during the same time period. All neuroimaging studies that occurred during or subsequent to a septic event were reviewed, and all new imaging findings were recorded and classified. As many patients experienced multiple septic events and/or had multiple neuroimaging studies after sepsis, our statistical analysis utilized the most recent or "final" imaging study available for each patient so that only brain imaging findings that persisted were included. A total of 389 children with sepsis and 1,705 concurrent or subsequent neuroimaging studies were included in the study. Median age at first septic event was 3.4 years (interquartile range, 0.7-11.5). Median time from first sepsis event to final neuroimaging was 157 days (interquartile range, 10-1,054). The most common indications for final imaging were follow-up (21%), altered mental status (18%), and fever/concern for infection (15%). Sixty-three percentage (n = 243) of final imaging studies demonstrated abnormal findings, the most common of which were volume loss (39%) and MRI signal and/or CT attenuation abnormalities (21%). On multivariable logistic regression, highest Pediatric Risk of Mortality score and presence of oncologic diagnosis/organ transplantation were independently associated with any abnormal final neuroimaging study findings (odds ratio, 1.032; p = 0.048 and odds ratio, 1.632; p = 0.041), although early timing of neuroimaging demonstrated a negative association (odds ratio, 0.606; p = 0.039). The most common abnormal finding of volume loss was independently associated with highest Pediatric Risk of Mortality score (odds ratio, 1.037; p

Neuroimaging of epilepsy

PubMed Central

Cendes, Fernando; Theodore, William H.; Brinkmann, Benjamin H.; Sulc, Vlastimil; Cascino, Gregory D.

2017-01-01

Imaging is pivotal in the evaluation and management of patients with seizure disorders. Elegant structural neuroimaging with magnetic resonance imaging (MRI) may assist in determining the etiology of focal epilepsy and demonstrating the anatomical changes associated with seizure activity. The high diagnostic yield of MRI to identify the common pathological findings in individuals with focal seizures including mesial temporal sclerosis, vascular anomalies, low-grade glial neoplasms and malformations of cortical development has been demonstrated. Positron emission tomography (PET) is the most commonly performed interictal functional neuroimaging technique that may reveal a focal hypometabolic region concordant with seizure onset. Single photon emission computed tomography (SPECT) studies may assist performance of ictal neuroimaging in patients with pharmacoresistant focal epilepsy being considered for neurosurgical treatment. This chapter highlights neuroimaging developments and innovations, and provides a comprehensive overview of the imaging strategies used to improve the care and management of people with epilepsy. PMID:27430454

Changes in Brain Lateralization in Patients with Mild Cognitive Impairment and Alzheimer's Disease: A Resting-State Functional Magnetic Resonance Study from Alzheimer's Disease Neuroimaging Initiative.

PubMed

Liu, Hao; Zhang, Lele; Xi, Qian; Zhao, Xiaohu; Wang, Fei; Wang, Xiangbin; Men, Weiwei; Lin, Qixiang

2018-01-01

To detect changes in brain lateralization in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) using resting-state functional magnetic resonance imaging (fMRI). Data from 61 well-matched right-handed subjects were obtained from the Alzheimer's Disease Neuroimaging Initiative, including 19 healthy controls (HCs), 25 patients with MCI, and 17 patients with AD. First, we divided 256 pairs of seed regions from each hemisphere covering the entire cerebral gray matter. Then, we used the intrinsic laterality index (iLI) approach to quantify the functional laterality using fMRI. One-way ANOVA was employed to estimate the differences in iLI among the three groups. The sum, number and mean value of the iLI were calculated within the thresholds of 0 < |iLI| < 0.2, 0.2 ≤ |iLI| < 0.4, 0.4 ≤ |iLI| < 0.8, and |iLI| ≥ 0.8, to explore the changes in the lateralization of resting-state brain function in patients with MCI and AD. One-way ANOVA revealed that the iLIs of the three groups were significantly different. The HCs showed a significant leftward interhemispheric difference within |iLI| ≥ 0.8. Compared with the HCs, the patients with MCI manifested a distinct abnormal rightward interhemispheric asymmetry, mainly within the thresholds of 0.2 ≤ |iLI| < 0.4 and 0.4 ≤ |iLI| < 0.8; in the patients with AD, the normal leftward lateralization that was observed in the HCs disappeared, and an abnormal rightward laterality was expressed within 0.4 ≤ |iLI| < 0.8. By directly comparing the patients with MCI with the patients with AD, an exclusive abnormal rightward laterality was observed in the patients with MCI within the 0.2 ≤ |iLI| < 0.4 threshold, and the normal leftward asymmetry vanished in the patients with AD within the |iLI| ≥ 0.8 threshold. Global brain lateralization was different among three groups. The abnormal rightward dominance observed in the patients with MCI

Second-opinion interpretations of neuroimaging studies by oncologic neuroradiologists can help reduce errors in cancer care.

PubMed

Hatzoglou, Vaios; Omuro, Antonio M; Haque, Sofia; Khakoo, Yasmin; Ganly, Ian; Oh, Jung Hun; Shukla-Dave, Amita; Fatovic, Robin; Gaal, Joshua; Holodny, Andrei I

2016-09-01

The purpose of this study was to investigate the utility and clinical impact of second-opinion interpretations of outside neuroimaging studies by oncologic neuroradiologists at a National Cancer Institute-designated cancer center. We performed a retrospective analysis of initial outside and second-opinion radiology reports from 300 computed tomography and magnetic resonance imaging studies and identified cases with discrepancies between the two reports. An adult neuro-oncologist, pediatric neuro-oncologist, and head and neck surgeon reviewed each pair of discrepant reports based on their area of expertise, patient age, and the type of study performed. The clinicians were blinded to the origin of each report and recorded whether the differences in the reports would have led to a change in patient management and/or disease staging. Histopathologic analysis, clinical assessment, and/or minimum 3-month imaging follow-up served as the reference standards to establish which of the 2 reports was correct. Among the 283 cases that met our study criteria, there were 55 neuroimaging studies with disagreements (19%) between the initial outside report and second-opinion interpretation. Patient management and/or disease stage would have been altered in 42 of 283 cases (15%) based on report differences as determined by the 2 neuro-oncologists and the surgeon participating in the study. Sufficient follow-up was available in 35 of 42 cases (83%). The second-opinion interpretation was correct 100% of the time (35/35). Second-opinion interpretations of neuroimaging studies by subspecialized oncologic neuroradiologists provide added value by reducing error and optimizing the care of cancer patients. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2708-2714. © 2016 American Cancer Society. © 2016 American Cancer Society.

Neuroimaging for psychotherapy research: Current trends

PubMed Central

WEINGARTEN, CAROL P.; STRAUMAN, TIMOTHY J.

2014-01-01

Objective This article reviews neuroimaging studies that inform psychotherapy research. An introduction to neuroimaging methods is provided as background for the increasingly sophisticated breadth of methods and findings appearing in psychotherapy research. Method We compiled and assessed a comprehensive list of neuroimaging studies of psychotherapy outcome, along with selected examples of other types of studies that also are relevant to psychotherapy research. We emphasized magnetic resonance imaging (MRI) since it is the dominant neuroimaging modality in psychological research. Results We summarize findings from neuroimaging studies of psychotherapy outcome, including treatment for depression, obsessive-compulsive disorder (OCD), and schizophrenia. Conclusions The increasing use of neuroimaging methods in the study of psychotherapy continues to refine our understanding of both outcome and process. We suggest possible directions for future neuroimaging studies in psychotherapy research. PMID:24527694

Similarities and Differences in Neuroimaging.

PubMed

Sun, Yan-Kun; Sun, Yan; Lin, Xiao; Lu, Lin; Shi, Jie

2017-01-01

Addiction is a chronically relapsing disease characterized by drug intoxication, craving, bingeing, and withdrawal with loss of control. An increasing number of studies have indicated that non-substance addiction, like internet addiction and pathological gambling, share clinical, phenomenological, and biological features with substance addiction. With the development of imaging technology in the past three decades, neuroimaging studies have provided information on the neurobiological effects, and revealed neurochemical and functional changes in the brains of both drug-addicted and non-substance addicted subjects. Imaging techniques play a more critical role in understanding the neuronal processes of addiction and will lead the direction in future research for medication development of addiction treatment, especially for non-substance addiction, which shares an increasing percentage of addiction disorder. This article will review the similarities and differences between substance and non-substance addiction based on neuroimaging studies that may provide clues for future study on these two main kinds of addiction, especially the growing non-substance addiction.

[Pedophilia: contribution of neurology and neuroimaging techniques].

PubMed

Fonteille, V; Cazala, F; Moulier, V; Stoléru, S

2012-12-01

Pedophilia is characterized by a persistent sexual interest of an adult for prepubescent children. The development of neuroimaging techniques such as functional Magnetic Resonance Imaging (fMRI) is starting to clarify the cerebral basis of disorders of sexual behavior such as pedophilia, which had been previously suggested by case studies. To review structural and functional neuroimaging studies of pedophilia. An exhaustive consultation of PubMed and Ovid databases was conducted. We obtained 19 articles presented in the present review of the literature. Case studies have demonstrated various changes of sexual behavior in relation to brain lesions, including the late appearance in adults of a sexual attraction to prepubescent children. In most cases of pedophilia associated with brain lesions, these lesions were located in frontal or in temporal regions. Structural neuroimaging studies have compared pedophiles with healthy subjects and tried to relate pedophilia to anatomical differences between these two groups. The location of structural changes is inconsistent across studies. Recent functional neuroimaging studies have also attempted to investigate the cerebral correlates of pedophilia. Results suggest that the activation pattern found in pedophiles in response to pictures of prepubescent nude girls or boys is similar to the pattern observed in healthy subjects in response to pictures of adult nude women or men. However, regions that become more activated in patients than in healthy controls in response to the presentation of pictures of children vary across studies. Studies that have begun to investigate the cerebral correlates of pedophilia demonstrate that it is possible to explore them through neuroimaging techniques. These initial results have to be confirmed by new studies backed with objective measurements of sexual arousal such as phallometry. Copyright © 2012 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Systematic Redaction for Neuroimage Data

PubMed Central

Matlock, Matt; Schimke, Nakeisha; Kong, Liang; Macke, Stephen; Hale, John

2013-01-01

In neuroscience, collaboration and data sharing are undermined by concerns over the management of protected health information (PHI) and personal identifying information (PII) in neuroimage datasets. The HIPAA Privacy Rule mandates measures for the preservation of subject privacy in neuroimaging studies. Unfortunately for the researcher, the management of information privacy is a burdensome task. Wide scale data sharing of neuroimages is challenging for three primary reasons: (i) A dearth of tools to systematically expunge PHI/PII from neuroimage data sets, (ii) a facility for tracking patient identities in redacted datasets has not been produced, and (iii) a sanitization workflow remains conspicuously absent. This article describes the XNAT Redaction Toolkit—an integrated redaction workflow which extends a popular neuroimage data management toolkit to remove PHI/PII from neuroimages. Quickshear defacing is also presented as a complementary technique for deidentifying the image data itself. Together, these tools improve subject privacy through systematic removal of PII/PHI. PMID:24179597

Neuroimaging Week: A Novel, Engaging, and Effective Curriculum for Teaching Neuroimaging to Junior Psychiatric Residents

ERIC Educational Resources Information Center

Downar, Jonathan; Krizova, Adriana; Ghaffar, Omar; Zaretsky, Ari

2010-01-01

Objective: Neuroimaging techniques are increasingly important in psychiatric research and clinical practice, but few postgraduate psychiatry programs offer formal training in neuroimaging. To address this need, the authors developed a course to prepare psychiatric residents to use neuroimaging techniques effectively in independent practice.…

Pathogenesis and neuroimaging of cerebral large and small vessel disease in type 2 diabetes: A possible link between cerebral and retinal microvascular abnormalities.

PubMed

Umemura, Toshitaka; Kawamura, Takahiko; Hotta, Nigishi

2017-03-01

Diabetes patients have more than double the risk of ischemic stroke compared with non-diabetic individuals, and its neuroimaging characteristics have important clinical implications. To understand the pathophysiology of ischemic stroke in diabetes, it is important to focus not only on the stroke subtype, but also on the size and location of the occlusive vessels. Specifically, ischemic stroke in diabetes patients might be attributed to both large and small vessels, and intracranial internal carotid artery disease and small infarcts of the posterior circulation often occur. An additional feature is that asymptomatic lacunar infarctions are often seen in the basal ganglia and brain stem on brain magnetic resonance imaging. In particular, cerebral small vessel disease (SVD), including lacunar infarctions, white matter lesions and cerebral microbleeds, has been shown to be associated not only with stroke incidence, but also with the development and progression of dementia and diabetic microangiopathy. However, the pathogenesis of cerebral SVD is not fully understood. In addition, data on the association between neuroimaging findings of the cerebral SVD and diabetes are limited. Recently, the clinical importance of the link between cerebral SVD and retinal microvascular abnormalities has been a topic of considerable interest. Several clinical studies have shown that retinal microvascular abnormalities are closely related to cerebral SVD, suggesting that retinal microvascular abnormalities might be pathophysiologically linked to ischemic cerebral SVD. We review the literature relating to the pathophysiology and neuroimaging of cerebrovascular disease in diabetes, and discuss the problems based on the concept of cerebral large and small vessel disease. © 2016 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

What do people with dementia and their carers want to know about neuroimaging for dementia?

PubMed

Featherstone, Hannah; Butler, Marie-Louise; Ciblis, Aurelia; Bokde, Arun L; Mullins, Paul G; McNulty, Jonathan P

2017-05-01

Neuroimaging forms an important part of dementia diagnosis. Provision of information on neuroimaging to people with dementia and their carers may aid understanding of the pathological, physiological and psychosocial changes of the disease, and increase understanding of symptoms. This qualitative study aimed to investigate participants' knowledge of the dementia diagnosis pathway, their understanding of neuroimaging and its use in diagnosis, and to determine content requirements for a website providing neuroimaging information. Structured interviews and a focus group were conducted with carers and people with dementia. The findings demonstrate an unmet need for information on neuroimaging both before and after the examination. Carers were keen to know about neuroimaging at a practical and technical level to help avoid diagnosis denial. People with dementia requested greater information, but with a caveat to avoid overwhelming detail, and were less likely to favour an Internet resource.

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories.

PubMed

Neu, Scott C; Crawford, Karen L; Toga, Arthur W

2012-01-01

Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead.

Neuroimaging and Drug Taking in Primates Abbreviated title: Neuroimaging and Drug taking

PubMed Central

Murnane, Kevin S.; Howell, Leonard L.

2011-01-01

Rationale Neuroimaging techniques have led to significant advances in our understanding of the neurobiology of drug-taking and the treatment of drug addiction in humans. Neuroimaging approaches provide a powerful translational approach that can link findings from humans and laboratory animals. Objective This review describes the utility of neuroimaging toward understanding the neurobiological basis of drug taking, and documents the close concordance that can be achieved among neuroimaging, neurochemical and behavioral endpoints. Results The study of drug interactions with dopamine and serotonin transporters in vivo has identified pharmacological mechanisms of action associated with the abuse liability of stimulants. Neuroimaging has identified the extended limbic system, including the prefrontal cortex and anterior cingulate, as important neuronal circuitry that underlies drug taking. The ability to conduct within-subject, longitudinal assessments of brain chemistry and neuronal function has enhanced our efforts to document long-term changes in dopamine D2 receptors, monoamine transporters, and prefrontal metabolism due to chronic drug exposure. Dysregulation of dopamine function and brain metabolic changes in areas involved in reward circuitry have been linked to drug-taking behavior, cognitive impairment and treatment response. Conclusions Experimental designs employing neuroimaging should consider well-documented determinants of drug taking, including pharmacokinetic considerations, subject history and environmental variables. Methodological issues to consider include limited molecular probes, lack of neurochemical specificity in brain activation studies, and the potential influence of anesthetics in animal studies. Nevertheless, these integrative approaches should have important implications for understanding drug-taking behavior and the treatment of drug addiction. PMID:21360099

[Functional neuroimaging in the diagnosis of patients with Parkinsonism: Update and recommendations for clinical use].

PubMed

Arbizu, J; Luquin, M R; Abella, J; de la Fuente-Fernández, R; Fernandez-Torrón, R; García-Solís, D; Garrastachu, P; Jiménez-Hoyuela, J M; Llaneza, M; Lomeña, F; Lorenzo-Bosquet, C; Martí, M J; Martinez-Castrillo, J C; Mir, P; Mitjavila, M; Ruiz-Martínez, J; Vela, L

2014-01-01

Functional Neuroimaging has been traditionally used in research for patients with different Parkinsonian syndromes. However, the emergence of commercial radiotracers together with the availability of single photon emission computed tomography (SPECT) and, more recently, positron emission tomography (PET) have made them available for clinical practice. Particularly, the development of clinical evidence achieved by functional neuroimaging techniques over the past two decades have motivated a progressive inclusion of several biomarkers in the clinical diagnostic criteria for neurodegenerative diseases that occur with Parkinsonism. However, the wide range of radiotracers designed to assess the involvement of different pathways in the neurodegenerative process underlying Parkinsonian syndromes (dopaminergic nigrostriatal pathway integrity, basal ganglia and cortical neuronal activity, myocardial sympathetic innervation), and the different neuroimaging techniques currently available (scintigraphy, SPECT and PET), have generated some controversy concerning the best neuroimaging test that should be indicated for the differential diagnosis of Parkinsonism. In this article, a panel of nuclear medicine and neurology experts has evaluated the functional neuroimaging techniques emphazising practical considerations related to the diagnosis of patients with uncertain origin parkinsonism and the assessment Parkinson's disease progression. Copyright © 2014 Elsevier España, S.L. and SEMNIM. All rights reserved.

The neuroimaging of sacred values.

PubMed

Vilarroya, Oscar; Hilferty, Joseph

2013-09-01

Sacred (or protected) values (SVs) constitute core beliefs that define primary reference groups. There is significant research on SVs at a behavioral level, but their neural underpinnings are just beginning to be discovered. In this paper, we highlight the current state of neuroimaging research concerning SVs. Given that SVs are considered to be strongly motivated by moral principles, we first provide an outline of the neural circuits that have been found to be involved in moral cognition. We then review various neuroimaging studies that have explored the notion of SVs. Specifically, we concentrate on neuroimaging studies dealing with intergroup bias and those that focus on social norms, since these are two basic dimensions of SVs that have been studied with neuroimaging techniques. Finally, we review two studies that have directly addressed SVs with neuroimaging techniques, and we offer suggestions for further avenues of study. © 2013 New York Academy of Sciences.

Neuroimaging training among neuropsychologists: A survey of the state of current training and recommendations for trainees

PubMed Central

Benitez, Andreana; Hassenstab, Jason; Bangen, Katherine J.

2013-01-01

Neuroimaging has gained widespread use in neuropsychological research and practice. However, there are neither established guidelines on how neuropsychologists might become competent researchers or consumers of neuroimaging data, nor any published studies describing the state of neuroimaging training among neuropsychologists. We report the results of two online surveys, one of 13 expert neuropsychologist-neuroimagers, whose responses informed the formulation of a second, larger survey to neuropsychologists-at-large that were a random selection of a third of the members of the International Neuropsychological Society and American Academy of Clinical Neuropsychology. 237 doctoral-level neuropsychologists, or 15.3% of potential participants, provided complete responses. Most respondents (69.2%) received training in neuroimaging, mostly at the post-doctoral level, largely through independent study, clinical conferences, instruction by clinical supervisors, and individualized mentoring, on topics such as neuroimaging modalities in neurology, neuroanatomy, and the appropriate information to glean from neuroradiology reports. Of the remaining respondents who did not receive training in neuroimaging, 64.4% indicated that such training would be very or extremely beneficial to one’s career as a neuropsychologist. Both neuropsychologist-neuroimagers and neuropsychologists-at-large provided specific recommendations for training. Findings from this initial effort will guide trainees who seek to develop competence in neuroimaging, and inform future formulations of neuropsychological training. PMID:24215451

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories

PubMed Central

Neu, Scott C.; Crawford, Karen L.; Toga, Arthur W.

2012-01-01

Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead. PMID:22470336

Neural modeling and functional neuroimaging.

PubMed

Horwitz, B; Sporns, O

1994-01-01

Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America. Copyright © 1994 Wiley-Liss, Inc.

Nervous System Injury and Neuroimaging of Zika Virus Infection.

PubMed

Wu, Shanshan; Zeng, Yu; Lerner, Alexander; Gao, Bo; Law, Meng

2018-01-01

In 2016, World Health Organization announced Zika virus infection and its neurological sequalae are a public health emergency of global scope. Preliminary studies have confirmed a relationship between Zika virus infection and certain neurological disorders, including microcephaly and Guillain-Barre syndrome (GBS). The neuroimaging features of microcephaly secondary to Zika virus infection include calcifications at the junction of gray-white matter and subcortical white matter with associated cortical abnormalities, diminution of white matter, large ventricles with or without hydrocephalus, cortical malformations, hypoplasia of cerebellum and brainstem, and enlargement of cerebellomedullary cistern. Contrast enhancement of the cauda equine nerve roots is the typical neuroimaging finding of GBS associated with Zika virus. This review describes the nervous system disorders and associated imaging findings seen in Zika virus infection, with the aim to improve the understanding of this disease. Imaging plays a key role on accurate diagnosis and prognostic evaluation of this disease.

Neuroimaging and Other Biomarkers for Alzheimer's Disease: The Changing Landscape of Early Detection

PubMed Central

Risacher, Shannon L.; Saykin, Andrew J.

2014-01-01

The goal of this review is to provide an overview of biomarkers for Alzheimer's disease (AD), with emphasis on neuroimaging and cerebrospinal fluid (CSF) biomarkers. We first review biomarker changes in patients with late-onset AD, including findings from studies using structural and functional magnetic resonance imaging (MRI), advanced MRI techniques (diffusion tensor imaging, magnetic resonance spectroscopy, perfusion), positron emission tomography with fluorodeoxyglucose, amyloid tracers, and other neurochemical tracers, and CSF protein levels. Next, we evaluate findings from these biomarkers in preclinical and prodromal stages of AD including mild cognitive impairment (MCI) and pre-MCI conditions conferring elevated risk. We then discuss related findings in patients with dominantly inherited AD. We conclude with a discussion of the current theoretical framework for the role of biomarkers in AD and emergent directions for AD biomarker research. PMID:23297785

Gray matter atrophy in patients with mild cognitive impairment/Alzheimer's disease over the course of developing delusions.

PubMed

Fischer, Corinne E; Ting, Windsor Kwan-Chun; Millikin, Colleen P; Ismail, Zahinoor; Schweizer, Tom A

2016-01-01

We conducted a neuroimaging analysis to understand the neuroanatomical correlates of gray matter loss in a group of mild cognitive impairment and early Alzheimer's disease patients who developed delusions. With data collected as part of the Alzheimer's Disease Neuroimaging Initiative, we conducted voxel-based morphometry to determine areas of gray matter change in the same Alzheimer's Disease Neuroimaging Initiative participants, before and after they developed delusions. We identified 14 voxel clusters with significant gray matter decrease in patient scans post-delusional onset, correcting for multiple comparisons (false discovery rate, p < 0.05). Major areas of difference included the right and left insulae, left precuneus, the right and left cerebellar culmen, the left superior temporal gyrus, the right posterior cingulate, the right thalamus, and the left parahippocampal gyrus. Although contrary to our initial predictions of enhanced right frontal atrophy, our preliminary work identifies several neuroanatomical areas, including the cerebellum and left posterior hemisphere, which may be involved in delusional development in these patients. Copyright © 2015 John Wiley & Sons, Ltd.

Visualization and unsupervised predictive clustering of high-dimensional multimodal neuroimaging data.

PubMed

Mwangi, Benson; Soares, Jair C; Hasan, Khader M

2014-10-30

Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data. We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm. t-SNE was evaluated against classical principal component analysis. Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders. Copyright © 2014 Elsevier B.V. All rights reserved.

Examining the relationship between head trauma and neurodegenerative disease: A review of epidemiology, pathology and neuroimaging techniques

PubMed Central

Sundman, Mark H; Hall, Eric E; Chen, Nan-kuei

2014-01-01

Traumatic brain injuries (TBI) are induced by sudden acceleration-deceleration and/or rotational forces acting on the brain. Diffuse axonal injury (DAI) has been identified as one of the chief underlying causes of morbidity and mortality in head trauma incidents. DAIs refer to microscopic white matter (WM) injuries as a result of shearing forces that induce pathological and anatomical changes within the brain, which potentially contribute to significant impairments later in life. These microscopic injuries are often unidentifiable by the conventional computed tomography (CT) and magnetic resonance (MR) scans employed by emergency departments to initially assess head trauma patients and, as a result, TBIs are incredibly difficult to diagnose. The impairments associated with TBI may be caused by secondary mechanisms that are initiated at the moment of injury, but often have delayed clinical presentations that are difficult to assess due to the initial misdiagnosis. As a result, the true consequences of these head injuries may go unnoticed at the time of injury and for many years thereafter. The purpose of this review is to investigate these consequences of TBI and their potential link to neurodegenerative disease (ND). This review will summarize the current epidemiological findings, the pathological similarities, and new neuroimaging techniques that may help delineate the relationship between TBI and ND. Lastly, this review will discuss future directions and propose new methods to overcome the limitations that are currently impeding research progress. It is imperative that improved techniques are developed to adequately and retrospectively assess TBI history in patients that may have been previously undiagnosed in order to increase the validity and reliability across future epidemiological studies. The authors introduce a new surveillance tool (Retrospective Screening of Traumatic Brain Injury Questionnaire, RESTBI) to address this concern. PMID:25324979

An expanded role for neuroimaging in the evaluation of memory impairment

PubMed Central

Desikan, Rahul S.; Rafii, Michael S.; Brewer, James B.; Hess, Christopher P.

2014-01-01

Alzheimer’s disease (AD) affects millions of people worldwide. The neuropathologic process underlying AD begins years, if not decades, before the onset of memory decline. Recent advances in neuroimaging suggest that it is now possible to detect AD-associated neuropathological changes well before dementia onset. Here, we evaluate the role of recently developed in vivo biomarkers in the clinical evaluation of AD. We discuss how assessment strategies might incorporate neuroimaging markers to better inform patients, families and clinicians when memory impairment prompts a search for diagnosis and management options. PMID:23764728

Nervous System Injury and Neuroimaging of Zika Virus Infection

PubMed Central

Wu, Shanshan; Zeng, Yu; Lerner, Alexander; Gao, Bo; Law, Meng

2018-01-01

In 2016, World Health Organization announced Zika virus infection and its neurological sequalae are a public health emergency of global scope. Preliminary studies have confirmed a relationship between Zika virus infection and certain neurological disorders, including microcephaly and Guillain–Barre syndrome (GBS). The neuroimaging features of microcephaly secondary to Zika virus infection include calcifications at the junction of gray–white matter and subcortical white matter with associated cortical abnormalities, diminution of white matter, large ventricles with or without hydrocephalus, cortical malformations, hypoplasia of cerebellum and brainstem, and enlargement of cerebellomedullary cistern. Contrast enhancement of the cauda equine nerve roots is the typical neuroimaging finding of GBS associated with Zika virus. This review describes the nervous system disorders and associated imaging findings seen in Zika virus infection, with the aim to improve the understanding of this disease. Imaging plays a key role on accurate diagnosis and prognostic evaluation of this disease. PMID:29740383

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

PubMed

Portugal, Liana C L; Rosa, Maria João; Rao, Anil; Bebko, Genna; Bertocci, Michele A; Hinze, Amanda K; Bonar, Lisa; Almeida, Jorge R C; Perlman, Susan B; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A; Ciuffetelli, Gary; Rodriguez, Eric; Forbes, Erika E; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Arnold, Eugene L; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Pereira, Mirtes; Oliveira, Leticia; Phillips, Mary L; Mourao-Miranda, Janaina

2016-01-01

High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included

Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls

PubMed Central

Arbabshirani, Mohammad R.; Plis, Sergey; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there are extensive evidences showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

PubMed

Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing; Calhoun, Vince D

2017-01-15

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need

Visual Systems for Interactive Exploration and Mining of Large-Scale Neuroimaging Data Archives

PubMed Central

Bowman, Ian; Joshi, Shantanu H.; Van Horn, John D.

2012-01-01

While technological advancements in neuroimaging scanner engineering have improved the efficiency of data acquisition, electronic data capture methods will likewise significantly expedite the populating of large-scale neuroimaging databases. As they do and these archives grow in size, a particular challenge lies in examining and interacting with the information that these resources contain through the development of compelling, user-driven approaches for data exploration and mining. In this article, we introduce the informatics visualization for neuroimaging (INVIZIAN) framework for the graphical rendering of, and dynamic interaction with the contents of large-scale neuroimaging data sets. We describe the rationale behind INVIZIAN, detail its development, and demonstrate its usage in examining a collection of over 900 T1-anatomical magnetic resonance imaging (MRI) image volumes from across a diverse set of clinical neuroimaging studies drawn from a leading neuroimaging database. Using a collection of cortical surface metrics and means for examining brain similarity, INVIZIAN graphically displays brain surfaces as points in a coordinate space and enables classification of clusters of neuroanatomically similar MRI images and data mining. As an initial step toward addressing the need for such user-friendly tools, INVIZIAN provides a highly unique means to interact with large quantities of electronic brain imaging archives in ways suitable for hypothesis generation and data mining. PMID:22536181

Mind-Body Practices and the Adolescent Brain: Clinical Neuroimaging Studies

PubMed Central

Sharma, Anup; Newberg, Andrew B

2016-01-01

Background Mind-Body practices constitute a large and diverse group of practices that can substantially affect neurophysiology in both healthy individuals and those with various psychiatric disorders. In spite of the growing literature on the clinical and physiological effects of mind-body practices, very little is known about their impact on central nervous system (CNS) structure and function in adolescents with psychiatric disorders. Method This overview highlights findings in a select group of mind-body practices including yoga postures, yoga breathing techniques and meditation practices. Results Mind-body practices offer novel therapeutic approaches for adolescents with psychiatric disorders. Findings from these studies provide insights into the design and implementation of neuroimaging studies for adolescents with psychiatric disorders. Conclusions Clinical neuroimaging studies will be critical in understanding how different practices affect disease pathogenesis and symptomatology in adolescents. Neuroimaging of mind-body practices on adolescents with psychiatric disorders will certainly be an open and exciting area of investigation. PMID:27347478

Mind-Body Practices and the Adolescent Brain: Clinical Neuroimaging Studies.

PubMed

Sharma, Anup; Newberg, Andrew B

Mind-Body practices constitute a large and diverse group of practices that can substantially affect neurophysiology in both healthy individuals and those with various psychiatric disorders. In spite of the growing literature on the clinical and physiological effects of mind-body practices, very little is known about their impact on central nervous system (CNS) structure and function in adolescents with psychiatric disorders. This overview highlights findings in a select group of mind-body practices including yoga postures, yoga breathing techniques and meditation practices. Mind-body practices offer novel therapeutic approaches for adolescents with psychiatric disorders. Findings from these studies provide insights into the design and implementation of neuroimaging studies for adolescents with psychiatric disorders. Clinical neuroimaging studies will be critical in understanding how different practices affect disease pathogenesis and symptomatology in adolescents. Neuroimaging of mind-body practices on adolescents with psychiatric disorders will certainly be an open and exciting area of investigation.

Recognition and treatment of Alzheimer's disease: a case-based review.

PubMed

Marseille, Dana M; Silverman, Daniel H S

2006-01-01

Early recognition and treatment initiation are pivotal in managing Alzheimer's disease (AD). Once a diagnosis of AD is made, a treatment plan is developed and should include treatment initiation with cholinesterase inhibitors (ChEIs) to improve cognition, management of comorbid conditions, and treat behavioral symptoms. Caregiver compliance is integral to AD treatment success. The purpose of this report is to present two real case studies of "suspected" AD or related dementia and stress the significance of early and accurate diagnosis in disease management. In case 1, a caregiver reports gradual but progressive loss of memory, and the patient himself complains of memory impairment. Neuroimaging analysis confirms "typical " AD. In case 2, initiation of ChEI therapy is followed by substantial clinical improvement in the face of a complex medical picture, and neuroimaging revealing more neurodegenerative changes than could be accounted for by "pure" AD.

Neuroimaging Endophenotypes in Autism Spectrum Disorder

PubMed Central

Mahajan, Rajneesh; Mostofsky, Stewart H.

2015-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has a strong genetic basis, and is heterogeneous in its etiopathogenesis and clinical presentation. Neuroimaging studies, in concert with neuropathological and clinical research, have been instrumental in delineating trajectories of development in children with ASD. Structural neuroimaging has revealed ASD to be a disorder with general and regional brain enlargement, especially in the frontotemporal cortices, while functional neuroimaging studies have highlighted diminished connectivity, especially between frontal-posterior regions. The diverse and specific neuroimaging findings may represent potential neuroendophenotypes, and may offer opportunities to further understand the etiopathogenesis of ASD, predict treatment response and lead to the development of new therapies. PMID:26234701

Brain dysfunction behind functional symptoms: neuroimaging and somatoform, conversive, and dissociative disorders.

PubMed

García-Campayo, Javier; Fayed, Nicolas; Serrano-Blanco, Antoni; Roca, Miquel

2009-03-01

Neuroimaging research in psychiatry has been increasing exponentially in recent years, yet many psychiatrists are relatively unfamiliar with this field. This article summarizes the findings of the most relevant research articles on the neuroimaging of somatoform, conversive, and dissociative disorders published from January 2007 through June 2008. Neuroimaging findings summarized here include alterations of stress regulation and coping in somatoform pain disorders, the importance of catastrophizing in somatization disorder, and the relevance of a history of physical/sexual abuse in irritable bowel syndrome. Regarding fibromyalgia, three of the most significant advances have been the impossibility of differentiating primary and concomitant fibromyalgia in the presence of quiescent underlying disease, the role of hippocampal dysfunction, and the possibility that fibromyalgia may be characterized as an aging process. In dissociative disorders, the high levels of elaborative memory encoding and the reduced size of the parietal lobe are highlighted. The most promising clinical consequence of these studies, in addition to improving knowledge about the etiology of these illnesses, is the possibility of using neuroimaging findings to identify subgroups of patients, which could allow treatments to be tailored.

Testing for association with multiple traits in generalized estimation equations, with application to neuroimaging data.

PubMed

Zhang, Yiwei; Xu, Zhiyuan; Shen, Xiaotong; Pan, Wei

2014-08-01

There is an increasing need to develop and apply powerful statistical tests to detect multiple traits-single locus associations, as arising from neuroimaging genetics and other studies. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI), in addition to genome-wide single nucleotide polymorphisms (SNPs), thousands of neuroimaging and neuropsychological phenotypes as intermediate phenotypes for Alzheimer's disease, have been collected. Although some classic methods like MANOVA and newly proposed methods may be applied, they have their own limitations. For example, MANOVA cannot be applied to binary and other discrete traits. In addition, the relationships among these methods are not well understood. Importantly, since these tests are not data adaptive, depending on the unknown association patterns among multiple traits and between multiple traits and a locus, these tests may or may not be powerful. In this paper we propose a class of data-adaptive weights and the corresponding weighted tests in the general framework of generalized estimation equations (GEE). A highly adaptive test is proposed to select the most powerful one from this class of the weighted tests so that it can maintain high power across a wide range of situations. Our proposed tests are applicable to various types of traits with or without covariates. Importantly, we also analytically show relationships among some existing and our proposed tests, indicating that many existing tests are special cases of our proposed tests. Extensive simulation studies were conducted to compare and contrast the power properties of various existing and our new methods. Finally, we applied the methods to an ADNI dataset to illustrate the performance of the methods. We conclude with the recommendation for the use of the GEE-based Score test and our proposed adaptive test for their high and complementary performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Neuroimaging of Central Sensitivity Syndromes: Key Insights from the Scientific Literature

PubMed Central

Walitt, Brian; Čeko, Marta; Gracely, John L.; Gracely, Richard H.

2016-01-01

Central sensitivity syndromes are characterized by distressing symptoms, such as pain and fatigue, in the absence of clinically obvious pathology. The scientific underpinnings of these disorders are not currently known. Modern neuroimaging techniques promise new insights into mechanisms mediating these postulated syndromes. We review the results of neuroimaging applied to five central sensitivity syndromes: fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, temporomandibular joint disorder, and vulvodynia syndrome. Neuroimaging studies of basal metabolism, anatomic constitution, molecular constituents, evoked neural activity, and treatment effect are compared across all of these syndromes. Evoked sensory paradigms reveal sensory augmentation to both painful and non-painful stimulation. This is a transformative observation for these syndromes, which were historically considered to be completely of hysterical or feigned in origin. However, whether sensory augmentation represents the cause of these syndromes, a predisposing factor, an endophenotype, or an epiphenomenon cannot be discerned from the current literature. Further, the result from cross-sectional neuroimaging studies of basal activity, anatomy, and molecular constituency are extremely heterogeneous within and between the syndromes. A defining neuroimaging “signature” cannot be discerned for any of the particular syndromes or for an over-arching central sensitization mechanism common to all of the syndromes. Several issues confound initial attempts to meaningfully measure treatment effects in these syndromes. At this time, the existence of “central sensitivity syndromes” is based more soundly on clinical and epidemiological evidence. A coherent picture of a “central sensitization” mechanism that bridges across all of these syndromes does not emerge from the existing scientific evidence. PMID:26717948

Functional neuroimaging in psychiatry.

PubMed Central

Fu, C H; McGuire, P K

1999-01-01

Functional neuroimaging is one of the most powerful means available for investigating the pathophysiology of psychiatric disorders. In this review, we shall focus on the different ways that it can be employed to this end, describing the major findings in the field in the context of different methodological approaches. We will also discuss practical issues that are particular to studying psychiatric disorders and the potential contribution of functional neuroimaging to future psychiatric research. PMID:10466156

Introduction and overview of the special issue "Brain imaging and aging": The new era of neuroimaging in aging research.

PubMed

Furukawa, Katsutoshi; Ishiki, Aiko; Tomita, Naoki; Onaka, Yuta; Saito, Haruka; Nakamichi, Tomoko; Hara, Kazunari; Kusano, Yusuke; Ebara, Masamune; Arata, Yuki; Sakota, Miku; Miyazawa, Isabelle; Totsune, Tomoko; Okinaga, Shoji; Okamura, Nobuyuki; Kudo, Yukitsuka; Arai, Hiroyuki

2016-09-01

It is well known that the brain is one of the organs particularly affected by aging in terms of function, relative to the gastrointestinal tract and liver, which exhibit less functional decline. There is also a wide range of age-related neurological disorders such as stroke, Alzheimer's disease, and Parkinson's disease. Therefore, it is very important to understand the relationship between functional age-related change and neurological dysfunction. Neuroimaging techniques including magnetic resonance imaging and positron emission tomography have been significantly improved over recent years. Many physicians and researchers have investigated various mechanisms of age-related cerebral change and associated neurological disorders using neuroimaging techniques. In this special issue of Ageing Research Reviews, we focus on cerebral- and neuro-imaging, which are a range of tools used to visualize structure, functions, and pathogenic molecules in the nervous system. In addition, we summarize several review articles about the history, present values, and future perspectives of neuroimaging modalities. Copyright © 2016 Elsevier B.V. All rights reserved.

[Physiopathology of autobiographical memory in aging: episodic and semantic distinction, clinical findings and neuroimaging studies].

PubMed

Piolino, Pascale; Martinelli, Pénélope; Viard, Armelle; Noulhiane, Marion; Eustache, Francis; Desgranges, Béatrice

2010-01-01

From an early age, autobiographical memory models our feeling of identity and continuity. It grows throughout lifetime with our experiences and is built up from general self-knowledge and specific memories. The study of autobiographical memory depicts the dynamic and reconstructive features of this type of long-term memory, combining both semantic and episodic aspects, its strength and fragility. In this article, we propose to illustrate the properties of autobiographical memory from the field of cognitive psychology, neuropsychology and neuroimaging research through the analysis of the mechanisms of disturbance in normal and Alzheimer's disease. We show that the cognitive and neural bases of autobiographical memory are distinct in both cases. In normal aging, autobiographical memory retrieval is mainly dependent on frontal/executive function and on sense of reexperiencing specific context connected to hippocampal regions regardless of memory remoteness. In Alzheimer's disease, autobiographical memory deficit, characterized by a Ribot's temporal gradient, is connected to different regions according to memory remoteness. Our functional neuroimaging results suggest that patients at the early stage can compensate for their massive deficit of episodic recent memories correlated to hippocampal alteration with over general remote memories related to prefrontal regions. On the whole, the research findings allowed initiating new autobiographical memory studies by comparing normal and pathological aging and developing cognitive methods of memory rehabilitation in patients based on preserved personal semantic capacity. © Société de Biologie, 2010.

Neuroimaging essentials in essential tremor: A systematic review

PubMed Central

Sharifi, Sarvi; Nederveen, Aart J.; Booij, Jan; van Rootselaar, Anne-Fleur

2014-01-01

Background Essential tremor is regarded to be a disease of the central nervous system. Neuroimaging is a rapidly growing field with potential benefits to both diagnostics and research. The exact role of imaging techniques with respect to essential tremor in research and clinical practice is not clear. A systematic review of the different imaging techniques in essential tremor is lacking in the literature. Methods We performed a systematic literature search combining the terms essential tremor and familial tremor with the following keywords: imaging, MRI, VBM, DWI, fMRI, PET and SPECT, both in abbreviated form as well as in full form. We summarize and discuss the quality and the external validity of each study and place the results in the context of existing knowledge regarding the pathophysiology of essential tremor. Results A total of 48 neuroimaging studies met our search criteria, roughly divided into 19 structural and 29 functional and metabolic studies. The quality of the studies varied, especially concerning inclusion criteria. Functional imaging studies indicated cerebellar hyperactivity during rest and during tremor. The studies also pointed to the involvement of the thalamus, the inferior olive and the red nucleus. Structural studies showed less consistent results. Discussion and conclusion Neuroimaging techniques in essential tremor give insight into the pathophysiology of essential tremor indicating the involvement of the cerebellum as the most consistent finding. GABAergic dysfunction might be a major premise in the pathophysiological hypotheses. Inconsistencies between studies can be partly explained by the inclusion of heterogeneous patient groups. Improvement of scientific research requires more stringent inclusion criteria and application of advanced analysis techniques. Also, the use of multimodal neuroimaging techniques is a promising development in movement disorders research. Currently, the role of imaging techniques in essential tremor in daily

Gray Matter Pathology in MS: Neuroimaging and Clinical Correlations

PubMed Central

Honce, Justin Morris

2013-01-01

It is abundantly clear that there is extensive gray matter pathology occurring in multiple sclerosis. While attention to gray matter pathology was initially limited to studies of autopsy specimens and biopsies, the development of new MRI techniques has allowed assessment of gray matter pathology in vivo. Current MRI techniques allow the direct visualization of gray matter demyelinating lesions, the quantification of diffuse damage to normal appearing gray matter, and the direct measurement of gray matter atrophy. Gray matter demyelination (both focal and diffuse) and gray matter atrophy are found in the very earliest stages of multiple sclerosis and are progressive over time. Accumulation of gray matter damage has substantial impact on the lives of multiple sclerosis patients; a growing body of the literature demonstrates correlations between gray matter pathology and various measures of both clinical disability and cognitive impairment. The effect of disease modifying therapies on the rate accumulation of gray matter pathology in MS has been investigated. This review focuses on the neuroimaging of gray matter pathology in MS, the effect of the accumulation of gray matter pathology on clinical and cognitive disability, and the effect of disease-modifying agents on various measures of gray matter damage. PMID:23878736

Systematic review with meta-analysis: neuroimaging in hepatitis C chronic infection.

PubMed

Oriolo, G; Egmond, E; Mariño, Z; Cavero, M; Navines, R; Zamarrenho, L; Solà, R; Pujol, J; Bargallo, N; Forns, X; Martin-Santos, R

2018-05-01

Chronic hepatitis C is considered a systemic disease because of extra-hepatic manifestations. Neuroimaging has been employed in hepatitis C virus-infected patients to find in vivo evidence of central nervous system alterations. Systematic review and meta-analysis of neuroimaging research in chronic hepatitis C treatment naive patients, or patients previously treated without sustained viral response, to study structural and functional brain impact of hepatitis C. Using PRISMA guidelines a database search was conducted from inception up until 1 May 2017 for peer-reviewed studies on structural or functional neuroimaging assessment of chronic hepatitis C patients without cirrhosis or encephalopathy, with control group. Meta-analyses were performed when possible. The final sample comprised 25 studies (magnetic resonance spectroscopy [N = 12], perfusion weighted imaging [N = 1], positron emission tomography [N = 3], single-photon emission computed tomography [N = 4], functional connectivity in resting state [N = 1], diffusion tensor imaging [N = 2] and structural magnetic resonance imaging [N = 2]). The whole sample was of 509 chronic hepatitis C patients, with an average age of 41.5 years old and mild liver disease. A meta-analysis of magnetic resonance spectroscopy studies showed increased levels of choline/creatine ratio (mean difference [MD] 0.12, 95% confidence interval [CI] 0.06-0.18), creatine (MD 0.85, 95% CI 0.42-1.27) and glutamate plus glutamine (MD 1.67, 95% CI 0.39-2.96) in basal ganglia and increased levels of choline/creatine ratio in centrum semiovale white matter (MD 0.13, 95% CI 0.07-0.19) in chronic hepatitis C patients compared with healthy controls. Photon emission tomography studies meta-analyses did not find significant differences in PK11195 binding potential in cortical and subcortical regions of chronic hepatitis C patients compared with controls. Correlations were observed between various neuroimaging alterations and

Neuroimaging correlates of neuropsychiatric symptoms in Alzheimer's disease: a review of 20 years of research.

PubMed

Boublay, N; Schott, A M; Krolak-Salmon, P

2016-10-01

Assessing morphological, perfusion and metabolic brain changes preceding or associated with neuropsychiatric symptoms (NPSs) will help in the understanding of pathophysiological underlying processes in Alzheimer's disease (AD). This review aimed to highlight the main findings on significant associations between neuroimaging and NPSs, the pathophysiology to elucidate possible underlying mechanisms, and methodological issues to aid future research. Research papers published from January 1990 to October 2015 were identified in the databases PsycInfo, Embase, PubMed and Medline, using key words related to NPSs and imaging techniques. In addition to a semi-systematic search in the databases, we also performed hand searches based on reported citations identified to be of interest. Delusions, apathy and depression symptoms were particularly associated with brain changes in AD. The majority of studies disclosed an association between frontal lobe structural and/or metabolic changes and NPSs, implicating, interestingly, for all 12 NPSs studied, the anterior cingulate cortex although temporal, subcortical and parietal regions, and insula were also involved. Given the high degree of connectivity of these brain areas, frontal change correlates of NPSs may help in the understanding of neural network participation. This review also highlights crucial methodological issues that may reduce the heterogeneity of results to enable progress on the pathophysiological mechanisms and aid research on NPS treatments in AD. Based on a broad review of the current literature, a global brain pattern to support the huge heterogeneity of neuroimaging correlates of NPSs in AD and methodological strategies are suggested to help direct future research. © 2016 EAN.

Multimodal neuroimaging in presurgical evaluation of drug-resistant epilepsy☆

PubMed Central

Zhang, Jing; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Mei, Shanshan; Liu, Qingzhu; Li, Yunlin

2013-01-01

Intracranial EEG (icEEG) monitoring is critical in epilepsy surgical planning, but it has limitations. The advances of neuroimaging have made it possible to reveal epileptic abnormalities that could not be identified previously and improve the localization of the seizure focus and the vital cortex. A frequently asked question in the field is whether non-invasive neuroimaging could replace invasive icEEG or reduce the need for icEEG in presurgical evaluation. This review considers promising neuroimaging techniques in epilepsy presurgical assessment in order to address this question. In addition, due to large variations in the accuracies of neuroimaging across epilepsy centers, multicenter neuroimaging studies are reviewed, and there is much need for randomized controlled trials (RCTs) to better reveal the utility of presurgical neuroimaging. The results of multiple studies indicate that non-invasive neuroimaging could not replace invasive icEEG in surgical planning especially in non-lesional or extratemporal lobe epilepsies, but it could reduce the need for icEEG in certain cases. With technical advances, multimodal neuroimaging may play a greater role in presurgical evaluation to reduce the costs and risks of epilepsy surgery, and provide surgical options for more patients with drug-resistant epilepsy. PMID:24282678

Neuroimaging Field Methods Using Functional Near Infrared Spectroscopy (NIRS) Neuroimaging to Study Global Child Development: Rural Sub-Saharan Africa.

PubMed

Jasińska, Kaja K; Guei, Sosthène

2018-02-02

Portable neuroimaging approaches provide new advances to the study of brain function and brain development with previously inaccessible populations and in remote locations. This paper shows the development of field functional Near Infrared Spectroscopy (fNIRS) imaging to the study of child language, reading, and cognitive development in a rural village setting of Côte d'Ivoire. Innovation in methods and the development of culturally appropriate neuroimaging protocols allow a first-time look into the brain's development and children's learning outcomes in understudied environments. This paper demonstrates protocols for transporting and setting up a mobile laboratory, discusses considerations for field versus laboratory neuroimaging, and presents a guide for developing neuroimaging consent procedures and building meaningful long-term collaborations with local government and science partners. Portable neuroimaging methods can be used to study complex child development contexts, including the impact of significant poverty and adversity on brain development. The protocol presented here has been developed for use in Côte d'Ivoire, the world's primary source of cocoa, and where reports of child labor in the cocoa sector are common. Yet, little is known about the impact of child labor on brain development and learning. Field neuroimaging methods have the potential to yield new insights into such urgent issues, and the development of children globally.

Auditory neuroimaging with fMRI and PET.

PubMed

Talavage, Thomas M; Gonzalez-Castillo, Javier; Scott, Sophie K

2014-01-01

For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. This article is part of a Special Issue entitled Human Auditory Neuroimaging. Copyright © 2013 Elsevier B.V. All rights reserved.

Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury

PubMed Central

Bigler, Erin D.

2016-01-01

The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology

Quantitative Neuroimaging Software for Clinical Assessment of Hippocampal Volumes on MR Imaging

PubMed Central

Ahdidan, Jamila; Raji, Cyrus A.; DeYoe, Edgar A.; Mathis, Jedidiah; Noe, Karsten Ø.; Rimestad, Jens; Kjeldsen, Thomas K.; Mosegaard, Jesper; Becker, James T.; Lopez, Oscar

2015-01-01

Background: Multiple neurological disorders including Alzheimer’s disease (AD), mesial temporal sclerosis, and mild traumatic brain injury manifest with volume loss on brain MRI. Subtle volume loss is particularly seen early in AD. While prior research has demonstrated the value of this additional information from quantitative neuroimaging, very few applications have been approved for clinical use. Here we describe a US FDA cleared software program, NeuroreaderTM, for assessment of clinical hippocampal volume on brain MRI. Objective: To present the validation of hippocampal volumetrics on a clinical software program. Method: Subjects were drawn (n = 99) from the Alzheimer Disease Neuroimaging Initiative study. Volumetric brain MR imaging was acquired in both 1.5 T (n = 59) and 3.0 T (n = 40) scanners in participants with manual hippocampal segmentation. Fully automated hippocampal segmentation and measurement was done using a multiple atlas approach. The Dice Similarity Coefficient (DSC) measured the level of spatial overlap between NeuroreaderTM and gold standard manual segmentation from 0 to 1 with 0 denoting no overlap and 1 representing complete agreement. DSC comparisons between 1.5 T and 3.0 T scanners were done using standard independent samples T-tests. Results: In the bilateral hippocampus, mean DSC was 0.87 with a range of 0.78–0.91 (right hippocampus) and 0.76–0.91 (left hippocampus). Automated segmentation agreement with manual segmentation was essentially equivalent at 1.5 T (DSC = 0.879) versus 3.0 T (DSC = 0.872). Conclusion: This work provides a description and validation of a software program that can be applied in measuring hippocampal volume, a biomarker that is frequently abnormal in AD and other neurological disorders. PMID:26484924

Neuromarketing: the hope and hype of neuroimaging in business.

PubMed

Ariely, Dan; Berns, Gregory S

2010-04-01

The application of neuroimaging methods to product marketing - neuromarketing - has recently gained considerable popularity. We propose that there are two main reasons for this trend. First, the possibility that neuroimaging will become cheaper and faster than other marketing methods; and second, the hope that neuroimaging will provide marketers with information that is not obtainable through conventional marketing methods. Although neuroimaging is unlikely to be cheaper than other tools in the near future, there is growing evidence that it may provide hidden information about the consumer experience. The most promising application of neuroimaging methods to marketing may come before a product is even released - when it is just an idea being developed.

Intergenerational Neuroimaging of Human Brain Circuitry

PubMed Central

Ho, Tiffany C.; Sanders, Stephan J.; Gotlib, Ian H.; Hoeft, Fumiko

2016-01-01

Neuroscientists are increasingly using advanced neuroimaging methods to elucidate the intergenerational transmission of human brain circuitry. This new line of work promises to shed insight into the ontogeny of complex behavioral traits, including psychiatric disorders, and possible mechanisms of transmission. Here, we highlight recent intergenerational neuroimaging studies and provide recommendations for future work. PMID:27623194

[Neuroimaging follow-up of cerebral aneurysms treated with endovascular techniques].

PubMed

Delgado, F; Saiz, A; Hilario, A; Murias, E; San Román Manzanera, L; Lagares Gomez-Abascal, A; Gabarrós, A; González García, A

2014-01-01

There are no specific recommendations in clinical guidelines about the best time, imaging tests, or intervals for following up patients with intracranial aneurysms treated with endovascular techniques. We reviewed the literature, using the following keywords to search in the main medical databases: cerebral aneurysm, coils, endovascular procedure, and follow-up. Within the Cerebrovascular Disease Group of the Spanish Society of Neuroradiology, we aimed to propose recommendations and an orientative protocol based on the scientific evidence for using neuroimaging to monitor intracranial aneurysms that have been treated with endovascular techniques. We aimed to specify the most appropriate neuroimaging techniques, the interval, the time of follow-up, and the best approach to defining the imaging findings, with the ultimate goal of improving clinical outcomes while optimizing and rationalizing the use of available resources. Copyright © 2013 SERAM. Published by Elsevier Espana. All rights reserved.

The Washington University Central Neuroimaging Data Archive

PubMed Central

Gurney, Jenny; Olsen, Timothy; Flavin, John; Ramaratnam, Mohana; Archie, Kevin; Ransford, James; Herrick, Rick; Wallace, Lauren; Cline, Jeanette; Horton, Will; Marcus, Daniel S

2016-01-01

Since the early 2000’s, much of the neuroimaging work at Washington University (WU) has been facilitated by the Central Neuroimaging Data Archive (CNDA), an XNAT-based imaging informatics system. The CNDA is uniquely related to XNAT, as it served as the original codebase for the XNAT open source platform. The CNDA hosts data acquired in over 1000 research studies, encompassing 36,000 subjects and more than 60,000 imaging sessions. Most imaging modalities used in modern human research are represented in the CNDA, including magnetic resonance (MR), positron emission tomography (PET), computed tomography (CT), nuclear medicine (NM), computed radiography (CR), digital radiography (DX), and ultrasound (US). However, the majority of the imaging data in the CNDA are MR and PET of the human brain. Currently, about 20% of the total imaging data in the CNDA is available by request to external researchers. CNDA’s available data includes large sets of imaging sessions and in some cases clinical, psychometric, tissue, or genetic data acquired in the study of Alzheimer’s disease, brain metabolism, cancer, HIV, sickle cell anemia, and Tourette syndrome. PMID:26439514

Neuromarketing: the hope and hype of neuroimaging in business

PubMed Central

Ariely, Dan; Berns, Gregory S.

2010-01-01

The application of neuroimaging methods to product marketing — neuromarketing — has recently gained considerable popularity. We propose that there are two main reasons for this trend. First, the possibility that neuroimaging will become cheaper and faster than other marketing methods; and second, the hope that neuroimaging will provide marketers with information that is not obtainable through conventional marketing methods. Although neuroimaging is unlikely to be cheaper than other tools in the near future, there is growing evidence that it may provide hidden information about the consumer experience. The most promising application of neuroimaging methods to marketing may come before a product is even released — when it is just an idea being developed. PMID:20197790

A very simple, re-executable neuroimaging publication

PubMed Central

Ghosh, Satrajit S.; Poline, Jean-Baptiste; Keator, David B.; Halchenko, Yaroslav O.; Thomas, Adam G.; Kessler, Daniel A.; Kennedy, David N.

2017-01-01

Reproducible research is a key element of the scientific process. Re-executability of neuroimaging workflows that lead to the conclusions arrived at in the literature has not yet been sufficiently addressed and adopted by the neuroimaging community. In this paper, we document a set of procedures, which include supplemental additions to a manuscript, that unambiguously define the data, workflow, execution environment and results of a neuroimaging analysis, in order to generate a verifiable re-executable publication. Re-executability provides a starting point for examination of the generalizability and reproducibility of a given finding. PMID:28781753

Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.

PubMed

Fu, Cynthia H Y; Costafreda, Sergi G

2013-09-01

Neuroimaging research has substantiated the functional and structural abnormalities underlying psychiatric disorders but has, thus far, failed to have a significant impact on clinical practice. Recently, neuroimaging-based diagnoses and clinical predictions derived from machine learning analysis have shown significant potential for clinical translation. This review introduces the key concepts of this approach, including how the multivariate integration of patterns of brain abnormalities is a crucial component. We survey recent findings that have potential application for diagnosis, in particular early and differential diagnoses in Alzheimer disease and schizophrenia, and the prediction of clinical response to treatment in depression. We discuss the specific clinical opportunities and the challenges for developing biomarkers for psychiatry in the absence of a diagnostic gold standard. We propose that longitudinal outcomes, such as early diagnosis and prediction of treatment response, offer definite opportunities for progress. We propose that efforts should be directed toward clinically challenging predictions in which neuroimaging may have added value, compared with the existing standard assessment. We conclude that diagnostic and prognostic biomarkers will be developed through the joint application of expert psychiatric knowledge in addition to advanced methods of analysis.

A panel of clinical and neuropathological features of cerebrovascular disease through the novel neuroimaging methods

PubMed Central

Alves, Gilberto Sousa; de Carvalho, Luiza de Amorim; Sudo, Felipe Kenji; Briand, Lucas; Laks, Jerson; Engelhardt, Eliasz

2017-01-01

ABSTRACT. The last decade has witnessed substantial progress in acquiring diagnostic biomarkers for the diagnostic workup of cerebrovascular disease (CVD). Advanced neuroimaging methods not only provide a strategic contribution for the differential diagnosis of vascular dementia (VaD) and vascular cognitive impairment (VCI), but also help elucidate the pathophysiological mechanisms ultimately leading to small vessel disease (SVD) throughout its course. Objective: In this review, the novel imaging methods, both structural and metabolic, were summarized and their impact on the diagnostic workup of age-related CVD was analysed. Methods: An electronic search between January 2010 and 2017 was carried out on PubMed/MEDLINE, Institute for Scientific Information Web of Knowledge and EMBASE. Results: The use of full functional multimodality in simultaneous Magnetic Resonance (MR)/Positron emission tomography (PET) may potentially improve the clinical characterization of VCI-VaD; for structural imaging, MRI at 3.0 T enables higher-resolution scanning with greater imaging matrices, thinner slices and more detail on the anatomical structure of vascular lesions. Conclusion: Although the importance of most of these techniques in the clinical setting has yet to be recognized, there is great expectancy in achieving earlier and more refined therapeutic interventions for the effective management of VCI-VaD. PMID:29354214

Neuroimaging evaluation in refractory epilepsy

PubMed Central

Granados, Ana M; Orejuela, Juan F

2015-01-01

Purpose To describe the application of neuroimaging analysis, compared to neuropsychological tests and video-electroencephalogram, for the evaluation of refractory epilepsy in a reference centre in Cali, Colombia. Methods Between March 2013 and November 2014, 29 patients, 19 men and 10 women, aged 9–65 years and with refractory epilepsy, were assessed by structural and functional magnetic resonance imaging while performing tasks related to language, verbal and non-verbal memory. Also, volumetric evaluation was performed. A 1.5 Tesla magnetic resonance imaging scanner was used in all cases. Results Neuroimaging evaluation identified 13 patients with mesial temporal sclerosis. The remaining patients were classified as: 10 patients with neoplastic masses, two patients with cortical atrophy, two patients with scarring lesions and two patients with non-structural aetiology. Among patients with mesial temporal sclerosis, comparison between techniques for lateralising the epileptogenic foci was made; the κ index between functional magnetic resonance imaging and hippocampi volumetry was κ = 1.00, agreement between neuroimaging and video-electroencephalogram was good (κ = 0.78) and comparison with a neuropsychological test was mild (κ = 0.24). Conclusions Neuroimaging studies allow the assessment of functional and structural damage related to epileptogenic lesions and foci, and are helpful to select surgical treatment, conduct intraoperative neuronavigation techniques, predict surgical deficits and evaluate patient recovery. PMID:26427897

Update on the MRI Core of the Alzheimer's Disease Neuroimaging Initiative

PubMed Central

Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; DeCarli, Charles S; Dale, Anders M; Weiner, Michael W

2010-01-01

Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications. PMID:20451869

A Review on the Bioinformatics Tools for Neuroimaging

PubMed Central

MAN, Mei Yen; ONG, Mei Sin; Mohamad, Mohd Saberi; DERIS, Safaai; SULONG, Ghazali; YUNUS, Jasmy; CHE HARUN, Fauzan Khairi

2015-01-01

Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system. PMID:27006633

The behavioural/dysexecutive variant of Alzheimer’s disease: clinical, neuroimaging and pathological features

PubMed Central

Pijnenburg, Yolande A. L.; Perry, David C.; Cohn-Sheehy, Brendan I.; Scheltens, Nienke M. E.; Vogel, Jacob W.; Kramer, Joel H.; van der Vlies, Annelies E.; Joie, Renaud La; Rosen, Howard J.; van der Flier, Wiesje M.; Grinberg, Lea T.; Rozemuller, Annemieke J.; Huang, Eric J.; van Berckel, Bart N. M.; Miller, Bruce L.; Barkhof, Frederik; Jagust, William J.; Scheltens, Philip; Seeley, William W.; Rabinovici, Gil D.

2015-01-01

A ‘frontal variant of Alzheimer’s disease’ has been described in patients with predominant behavioural or dysexecutive deficits caused by Alzheimer’s disease pathology. The description of this rare Alzheimer’s disease phenotype has been limited to case reports and small series, and many clinical, neuroimaging and neuropathological characteristics are not well understood. In this retrospective study, we included 55 patients with Alzheimer’s disease with a behavioural-predominant presentation (behavioural Alzheimer’s disease) and a neuropathological diagnosis of high-likelihood Alzheimer’s disease (n = 17) and/or biomarker evidence of Alzheimer’s disease pathology (n = 44). In addition, we included 29 patients with autopsy/biomarker-defined Alzheimer’s disease with a dysexecutive-predominant syndrome (dysexecutive Alzheimer’s disease). We performed structured chart reviews to ascertain clinical features. First symptoms were more often cognitive (behavioural Alzheimer’s disease: 53%; dysexecutive Alzheimer’s disease: 83%) than behavioural (behavioural Alzheimer’s disease: 25%; dysexecutive Alzheimer’s disease: 3%). Apathy was the most common behavioural feature, while hyperorality and perseverative/compulsive behaviours were less prevalent. Fifty-two per cent of patients with behavioural Alzheimer’s disease met diagnostic criteria for possible behavioural-variant frontotemporal dementia. Overlap between behavioural and dysexecutive Alzheimer’s disease was modest (9/75 patients). Sixty per cent of patients with behavioural Alzheimer’s disease and 40% of those with the dysexecutive syndrome carried at least one APOE ε4 allele. We also compared neuropsychological test performance and brain atrophy (applying voxel-based morphometry) with matched autopsy/biomarker-defined typical (amnestic-predominant) Alzheimer’s disease (typical Alzheimer’s disease, n = 58), autopsy-confirmed/Alzheimer’s disease biomarker-negative behavioural

Cognitive neuroimaging: cognitive science out of the armchair.

PubMed

de Zubicaray, Greig I

2006-04-01

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.

Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning.

PubMed

Janssen, Ronald J; Mourão-Miranda, Janaina; Schnack, Hugo G

2018-04-22

Psychiatric prognosis is a difficult problem. Making a prognosis requires looking far into the future, as opposed to making a diagnosis, which is concerned with the current state. During the follow-up period, many factors will influence the course of the disease. Combined with the usually scarcer longitudinal data and the variability in the definition of outcomes/transition, this makes prognostic predictions a challenging endeavor. Employing neuroimaging data in this endeavor introduces the additional hurdle of high dimensionality. Machine-learning techniques are especially suited to tackle this challenging problem. This review starts with a brief introduction to machine learning in the context of its application to clinical neuroimaging data. We highlight a few issues that are especially relevant for prediction of outcome and transition using neuroimaging. We then review the literature that discusses the application of machine learning for this purpose. Critical examination of the studies and their results with respect to the relevant issues revealed the following: 1) there is growing evidence for the prognostic capability of machine-learning-based models using neuroimaging; and 2) reported accuracies may be too optimistic owing to small sample sizes and the lack of independent test samples. Finally, we discuss options to improve the reliability of (prognostic) prediction models. These include new methodologies and multimodal modeling. Paramount, however, is our conclusion that future work will need to provide properly (cross-)validated accuracy estimates of models trained on sufficiently large datasets. Nevertheless, with the technological advances enabling acquisition of large databases of patients and healthy subjects, machine learning represents a powerful tool in the search for psychiatric biomarkers. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Childhood-Onset Schizophrenia: Insights from Neuroimaging Studies

ERIC Educational Resources Information Center

Gogtay, Nitin; Rapoport, Judith L.

2008-01-01

The use of longitudinal neuroimaging to study the developmental perspectives of brain pathology in children with childhood-onset schizophrenia (COS) is described. Structural neuroimaging is capable of providing evidence of neurobiological specificity of COS to distinguish it from other brain abnormalities seen in neuropsychiatric illnesses like…

Auditory Neuroimaging with fMRI and PET

PubMed Central

Talavage, Thomas M.; Gonzalez-Castillo, Javier; Scott, Sophie K.

2013-01-01

For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. PMID:24076424

Neuroimaging findings in treatment-resistant schizophrenia: a systematic review

PubMed Central

Nakajima, Shinichiro; Takeuchi, Hiroyoshi; Plitman, Eric; Fervaha, Gagan; Gerretsen, Philip; Caravaggio, Fernando; Chung, Jun Ku; Iwata, Yusuke; Remington, Gary; Graff-Guerrero, Ariel

2015-01-01

Background Recent developments in neuroimaging have advanced understanding biological mechanisms underlying schizophrenia. However, neuroimaging correlates of treatment-resistant schizophrenia (TRS) and superior effects of clozapine on TRS remain unclear. Methods Systematic search was performed to identify neuroimaging characteristics unique to TRS and ultra-resistant schizophrenia (i.e. clozapine-resistant [URS]), and clozapine's efficacy in TRS using Embase, Medline, and PsychInfo. Search terms included (schizophreni*) and (resistan* OR refractory OR clozapine) and (ASL OR CT OR DTI OR FMRI OR MRI OR MRS OR NIRS OR PET OR SPECT). Results 25 neuroimaging studies have investigated TRS and effects of clozapine. Only 5 studies have compared TRS and non-TRS, collectively providing no replicated neuroimaging finding specific to TRS. Studies comparing TRS and healthy controls suggest hypometabolism in the prefrontal cortex, hypermetabolism in the basal ganglia, and structural anomalies in the corpus callosum contribute to TRS. Clozapine may increase prefrontal hypoactivation in TRS although this was not related to clinical improvement; in contrast, evidence has suggested a link between clozapine efficacy and decreased metabolism in the basal ganglia and thalamus. Conclusion Existing literature does not elucidate neuroimaging correlates specific to TRS or URS, which, if present, might also shed light on clozapine's efficacy in TRS. This said, leads from other lines of investigation, including the glutamatergic system can prove useful in guiding future neuroimaging studies focused on, in particular, the frontocortical-basal ganglia-thalamic circuits. Critical to the success of this work will be precise subtyping of study subjects based on treatment response/nonresponse and the use of multimodal neuroimaging. PMID:25684554

Neuroimaging in mental health care: voices in translation

PubMed Central

Borgelt, Emily L.; Buchman, Daniel Z.; Illes, Judy

2012-01-01

Images of brain function, popularly called “neuroimages,” have become a mainstay of contemporary communication about neuroscience and mental health. Paralleling media coverage of neuroimaging research and the high visibility of clinics selling scans is pressure from sponsors to move basic research about brain function along the translational pathway. Indeed, neuroimaging may offer benefits to mental health care: early or tailored intervention, opportunities for education and planning, and access to resources afforded by objectification of disorder. However, risks of premature technology transfer, such as misinterpretation, misrepresentation, and increased stigmatization, could compromise patient care. The insights of stakeholder groups about neuroimaging for mental health care are a largely untapped resource of information and guidance for translational efforts. We argue that the insights of key stakeholders—including researchers, healthcare providers, patients, and families—have an essential role to play upstream in professional, critical, and ethical discourse surrounding neuroimaging in mental health. Here we integrate previously orthogonal lines of inquiry involving stakeholder research to describe the translational landscape as well as challenges on its horizon. PMID:23097640

Turner Syndrome: Neuroimaging Findings--Structural and Functional

ERIC Educational Resources Information Center

Mullaney, Ronan; Murphy, Declan

2009-01-01

Neuroimaging studies of Turner syndrome can advance our understanding of the X chromosome in brain development, and the modulatory influence of endocrine factors. There is increasing evidence from neuroimaging studies that TX individuals have significant differences in the anatomy, function, and metabolism of a number of brain regions; including…

Neuroimaging of Cognitive Load in Instructional Multimedia

ERIC Educational Resources Information Center

Whelan, Robert R.

2007-01-01

This paper reviews research literature on cognitive load measurement in learning and neuroimaging, and describes a mapping between the main elements of cognitive load theory and findings in functional neuroanatomy. It is argued that these findings may lead to the improved measurement of cognitive load using neuroimaging. The paper describes how…

Computer-assisted initial diagnosis of rare diseases

PubMed Central

Piñol, Marc; Vilaplana, Jordi; Teixidó, Ivan; Cruz, Joaquim; Comas, Jorge; Vilaprinyo, Ester; Sorribas, Albert

2016-01-01

Introduction. Most documented rare diseases have genetic origin. Because of their low individual frequency, an initial diagnosis based on phenotypic symptoms is not always easy, as practitioners might never have been exposed to patients suffering from the relevant disease. It is thus important to develop tools that facilitate symptom-based initial diagnosis of rare diseases by clinicians. In this work we aimed at developing a computational approach to aid in that initial diagnosis. We also aimed at implementing this approach in a user friendly web prototype. We call this tool Rare Disease Discovery. Finally, we also aimed at testing the performance of the prototype. Methods. Rare Disease Discovery uses the publicly available ORPHANET data set of association between rare diseases and their symptoms to automatically predict the most likely rare diseases based on a patient’s symptoms. We apply the method to retrospectively diagnose a cohort of 187 rare disease patients with confirmed diagnosis. Subsequently we test the precision, sensitivity, and global performance of the system under different scenarios by running large scale Monte Carlo simulations. All settings account for situations where absent and/or unrelated symptoms are considered in the diagnosis. Results. We find that this expert system has high diagnostic precision (≥80%) and sensitivity (≥99%), and is robust to both absent and unrelated symptoms. Discussion. The Rare Disease Discovery prediction engine appears to provide a fast and robust method for initial assisted differential diagnosis of rare diseases. We coupled this engine with a user-friendly web interface and it can be freely accessed at http://disease-discovery.udl.cat/. The code and most current database for the whole project can be downloaded from https://github.com/Wrrzag/DiseaseDiscovery/tree/no_classifiers. PMID:27547534

Neuroimaging and Research into Second Language Acquisition

ERIC Educational Resources Information Center

Sabourin, Laura

2009-01-01

Neuroimaging techniques are becoming not only more and more sophisticated but are also coming to be increasingly accessible to researchers. One thing that one should take note of is the potential of neuroimaging research within second language acquisition (SLA) to contribute to issues pertaining to the plasticity of the adult brain and to general…

Big Data and Neuroimaging.

PubMed

Webb-Vargas, Yenny; Chen, Shaojie; Fisher, Aaron; Mejia, Amanda; Xu, Yuting; Crainiceanu, Ciprian; Caffo, Brian; Lindquist, Martin A

2017-12-01

Big Data are of increasing importance in a variety of areas, especially in the biosciences. There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas. Importantly, statisticians and statistical thinking have a major role to play in creating meaningful progress in this arena. We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big Data problems. We use the field of statistical neuroimaging to demonstrate these points. As such, this paper covers several applications and novel methodological developments of Big Data tools applied to neuroimaging data.

The clinical value of large neuroimaging data sets in Alzheimer's disease.

PubMed

Toga, Arthur W

2012-02-01

Rapid advances in neuroimaging and cyberinfrastructure technologies have brought explosive growth in the Web-based warehousing, availability, and accessibility of imaging data on a variety of neurodegenerative and neuropsychiatric disorders and conditions. There has been a prolific development and emergence of complex computational infrastructures that serve as repositories of databases and provide critical functionalities such as sophisticated image analysis algorithm pipelines and powerful three-dimensional visualization and statistical tools. The statistical and operational advantages of collaborative, distributed team science in the form of multisite consortia push this approach in a diverse range of population-based investigations. Copyright © 2012 Elsevier Inc. All rights reserved.

The Status of the Quality Control in Acupuncture-Neuroimaging Studies

PubMed Central

Qiu, Ke; Jing, Miaomiao; Liu, Xiaoyan; Gao, Feifei; Liang, Fanrong; Zeng, Fang

2016-01-01

Using neuroimaging techniques to explore the central mechanism of acupuncture gains increasing attention, but the quality control of acupuncture-neuroimaging study remains to be improved. We searched the PubMed Database during 1995 to 2014. The original English articles with neuroimaging scan performed on human beings were included. The data involved quality control including the author, sample size, characteristics of the participant, neuroimaging technology, and acupuncture intervention were extracted and analyzed. The rigorous inclusion and exclusion criteria are important guaranty for the participants' homogeneity. The standard operation process of acupuncture and the stricter requirement for acupuncturist play significant role in quality control. More attention should be paid to the quality control in future studies to improve the reproducibility and reliability of the acupuncture-neuroimaging studies. PMID:27242911

Molecular neuroimaging of emotional decision-making.

PubMed

Takahashi, Hidehiko

2013-04-01

With the dissemination of non-invasive human neuroimaging techniques such as fMRI and the advancement of cognitive science, neuroimaging studies focusing on emotions and social cognition have become established. Along with this advancement, behavioral economics taking emotional and social factors into account for economic decisions has been merged with neuroscientific studies, and this interdisciplinary approach is called neuroeconomics. Past neuroeconomics studies have demonstrated that subcortical emotion-related brain structures play an important role in "irrational" decision-making. The research field that investigates the role of central neurotransmitters in this process is worthy of further development. Here, we provide an overview of recent molecular neuroimaging studies to further the understanding of the neurochemical basis of "irrational" or emotional decision-making and the future direction, including clinical implications, of the field. Copyright © 2013 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Structural neuroimaging in neuropsychology: History and contemporary applications.

PubMed

Bigler, Erin D

2017-11-01

Neuropsychology's origins began long before there were any in vivo methods to image the brain. That changed with the advent of computed tomography in the 1970s and magnetic resonance imaging in the early 1980s. Now computed tomography and magnetic resonance imaging are routinely a part of neuropsychological investigations with an increasing number of sophisticated methods for image analysis. This review examines the history of neuroimaging utilization in neuropsychological investigations, highlighting the basic methods that go into image quantification and the various metrics that can be derived. Neuroimaging methods and limitations for identify what constitutes a lesion are discussed. Likewise, the influence of various demographic and developmental factors that influence quantification of brain structure are reviewed. Neuroimaging is an integral part of 21st Century neuropsychology. The importance of neuroimaging to advancing neuropsychology is emphasized. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Adult bacterial meningitis-a quality registry study: earlier treatment and favourable outcome if initial management by infectious diseases physicians.

PubMed

Grindborg, Ö; Naucler, P; Sjölin, J; Glimåker, M

2015-06-01

Acute bacterial meningitis (ABM) is challenging for the admitting physician because it is a rare but fulminant disease, usually presenting without typical symptoms, and rapid treatment is pivotal. The purpose of this study was to evaluate the effect of initial management by infectious diseases (ID) physicians vs. non-ID physicians. A total of 520 consecutive adults (>17 years old), 110 with initial ID management and 410 with non-ID management, registered in the Swedish quality registry for community-acquired ABM January 2008 to December 2013, were analysed retrospectively. Primary outcome was appropriate treatment with antibiotics and corticosteroids <1 hour from admission. Secondary analyses were mortality during hospital stay and persisting neurological and hearing deficits at follow-up after 2 to 6 months. Differences in diagnostic treatment sequences also were analysed. Appropriate treatment <1 hour from admission was achieved significantly more often (41%) by ID physicians vs. non-ID physicians (24%) with an odds ratio (OR) of 2.4 (95% confidence interval [CI]: 1.40 to 4.14; p < 0.01) adjusted for confounders. The door-to-antibiotic time was significantly shorter, and significantly more patients were administered corticosteroids together with the first doses of antibiotics in the ID group. A trend of decreased mortality (4.5% vs. 8.0%) and sequelae at follow-up (24% vs. 44%; adjusted OR 0.55: 95% CI 0.31 to 1.00; p 0.05) were observed in the ID group vs. the non-ID group. Antibiotics were started without prior neuroimaging more often in the ID group (86% vs. 57%; p < 0.001). Initial management at the emergency department by ID physicians is associated with earlier appropriate treatment, more appropriate diagnostic treatment sequences and favourable outcome. Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Targeting neuronal dysfunction in schizophrenia with nicotine: Evidence from neurophysiology to neuroimaging

PubMed Central

Smucny, Jason; Tregellas, Jason R

2018-01-01

Patients with schizophrenia self-administer nicotine at rates higher than is self-administered for any other psychiatric illness. Although the reasons are unclear, one hypothesis suggests that nicotine is a form of ‘self-medication’ in order to restore normal levels of nicotinic signaling and target abnormalities in neuronal function associated with cognitive processes. This brief review discusses evidence from neurophysiological and neuroimaging studies in schizophrenia patients that nicotinic agonists may effectively target dysfunctional neuronal circuits in the illness. Evidence suggests that nicotine significantly modulates a number of these circuits, although relatively few studies have used modern neuroimaging techniques (e.g. functional magnetic resonance imaging (fMRI)) to examine the effects of nicotinic drugs on disease-related neurobiology. The neuronal effects of nicotine and other nicotinic agonists in schizophrenia remain a priority for psychiatry research. PMID:28441884

A Significant Proportion of Pediatric Morphea En Coup De Sabre and Parry-Romberg Syndrome Patients Have Neuroimaging Findings

PubMed Central

Chiu, Yvonne E.; Vora, Sheetal; Kwon, Eun-Kyung M.; Maheshwari, Mohit

2012-01-01

Background/Objectives En coup de sabre (ECDS) and Parry-Romberg syndrome (PRS) are variants of linear morphea on the head and neck that can be associated with neurologic manifestations. Intracranial abnormalities on computed tomography (CT) and magnetic resonance imaging (MRI) can be present in a significant proportion of patients. Methods We describe 32 pediatric patients from our institution with ECDS or PRS, in whom neuroimaging was performed in 21 cases. We also review 51 additional patients from the literature. Results Nineteen percent of the children at our institution had intracranial abnormalities on MRI, half of whom were asymptomatic. Hyperintensities on T2-weighted sequences were the most common finding, present in all patients who had intracranial abnormalities on MRI. Seizures and headaches were the most common neurologic symptom, affecting 13% and 9% of our population, respectively. The presence of neurologic symptoms was not correlated with neuroimaging abnormalities as 2 asymptomatic patients had marked MRI findings, while the MRI was abnormal in only 2/9 symptomatic patients. Similarly, the severity of the superficial disease did not predict neurologic involvement; a patient with subtle skin involvement had striking MRI findings and seizures while another patient with a bony defect had no brain parenchymal involvement. Conclusions Neurologic symptoms and neuroimaging abnormalities are found in a surprisingly substantial percentage of children with ECDS and PRS. Early recognition of neurologic involvement is necessary as it affects treatment choices. As clinical predictors of intracranial abnormalities are poor, strong consideration should be given to obtaining an MRI prior to treatment initiation to assist in management decisions and establish a baseline examination. PMID:23106674

Cognitive Neuroimaging: Cognitive Science out of the Armchair

ERIC Educational Resources Information Center

de Zubicaray, Greig I.

2006-01-01

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some…

Machine learning for neuroimaging with scikit-learn.

PubMed

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

Machine learning for neuroimaging with scikit-learn

PubMed Central

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388

Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

PubMed Central

Sweet, Jennifer A.; Pace, Jonathan; Girgis, Fady; Miller, Jonathan P.

2016-01-01

Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS. PMID:27445709

Pituitary gland in psychiatric disorders: a review of neuroimaging findings.

PubMed

Atmaca, Murad

2014-08-01

In this paper, it was reviewed neuroimaging results of the pituitary gland in psychiatric disorders, particularly schizophrenia, mood disorders, anxiety disorders, and somatoform disorders. The author made internet search in detail by using PubMed database including the period between 1980 and 2012 October. It was included in the articles in English, Turkish and French languages on pituitary gland in psychiatric disorders through structural or functional neuroimaging results. After searching mentioned in the Methods section in detail, investigations were obtained on pituitary gland neuroimaging in a variety of psychiatric disorders. There have been so limited investigations on pituitary neuroimaging in psychiatric disorders including major psychiatric illnesses like schizophrenia and mood disorders. Current findings are so far from the generalizability of the results. For this reason, it is required to perform much more neuroimaging studies of pituitary gland in all psychiatric disorders to reach the diagnostic importance of measuring it.

Providing traceability for neuroimaging analyses.

PubMed

McClatchey, Richard; Branson, Andrew; Anjum, Ashiq; Bloodsworth, Peter; Habib, Irfan; Munir, Kamran; Shamdasani, Jetendr; Soomro, Kamran

2013-09-01

With the increasingly digital nature of biomedical data and as the complexity of analyses in medical research increases, the need for accurate information capture, traceability and accessibility has become crucial to medical researchers in the pursuance of their research goals. Grid- or Cloud-based technologies, often based on so-called Service Oriented Architectures (SOA), are increasingly being seen as viable solutions for managing distributed data and algorithms in the bio-medical domain. For neuroscientific analyses, especially those centred on complex image analysis, traceability of processes and datasets is essential but up to now this has not been captured in a manner that facilitates collaborative study. Few examples exist, of deployed medical systems based on Grids that provide the traceability of research data needed to facilitate complex analyses and none have been evaluated in practice. Over the past decade, we have been working with mammographers, paediatricians and neuroscientists in three generations of projects to provide the data management and provenance services now required for 21st century medical research. This paper outlines the finding of a requirements study and a resulting system architecture for the production of services to support neuroscientific studies of biomarkers for Alzheimer's disease. The paper proposes a software infrastructure and services that provide the foundation for such support. It introduces the use of the CRISTAL software to provide provenance management as one of a number of services delivered on a SOA, deployed to manage neuroimaging projects that have been studying biomarkers for Alzheimer's disease. In the neuGRID and N4U projects a Provenance Service has been delivered that captures and reconstructs the workflow information needed to facilitate researchers in conducting neuroimaging analyses. The software enables neuroscientists to track the evolution of workflows and datasets. It also tracks the outcomes of

The Role of Functional Neuroimaging in Pre-Surgical Epilepsy Evaluation

PubMed Central

Pittau, Francesca; Grouiller, Frédéric; Spinelli, Laurent; Seeck, Margitta; Michel, Christoph M.; Vulliemoz, Serge

2014-01-01

The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy. PMID:24715886

White matter hyperintensities and cerebral amyloidosis: necessary and sufficient for clinical expression of Alzheimer disease?

PubMed

Provenzano, Frank A; Muraskin, Jordan; Tosto, Giuseppe; Narkhede, Atul; Wasserman, Ben T; Griffith, Erica Y; Guzman, Vanessa A; Meier, Irene B; Zimmerman, Molly E; Brickman, Adam M

2013-04-01

Current hypothetical models emphasize the importance of β-amyloid in Alzheimer disease (AD) pathogenesis, although amyloid alone is not sufficient to account for the dementia syndrome. The impact of small-vessel cerebrovascular disease, visualized as white matter hyperintensities (WMHs) on magnetic resonance imaging scans, may be a key factor that contributes independently to AD presentation. To determine the impact of WMHs and Pittsburgh Compound B (PIB) positron-emission tomography-derived amyloid positivity on the clinical expression of AD. Baseline PIB-positron-emission tomography values were downloaded from the Alzheimer's Disease Neuroimaging Initiative database. Total WMH volume was derived on accompanying structural magnetic resonance imaging data. We examined whether PIB positivity and total WMHs predicted diagnostic classification of patients with AD (n = 20) and control subjects (n = 21). A second analysis determined whether WMHs discriminated between those with and without the clinical diagnosis of AD among those who were classified as PIB positive (n = 28). A third analysis examined whether WMHs, in addition to PIB status, could be used to predict future risk for AD among subjects with mild cognitive impairment (n = 59). The Alzheimer's Disease Neuroimaging Initiative public database. The study involved data from 21 normal control subjects, 59 subjects with mild cognitive impairment, and 20 participants with clinically defined AD from the Alzheimer Disease's Neuroimaging Initiative database. Clinical AD diagnosis and WMH volume. Pittsburgh Compound B positivity and increased total WMH volume independently predicted AD diagnosis. Among PIB-positive subjects, those diagnosed as having AD had greater WMH volume than normal control subjects. Among subjects with mild cognitive impairment, both WMH and PIB status at baseline conferred risk for future diagnosis of AD. White matter hyperintensities contribute to the presentation of AD and, in the context of

Terminology development towards harmonizing multiple clinical neuroimaging research repositories.

PubMed

Turner, Jessica A; Pasquerello, Danielle; Turner, Matthew D; Keator, David B; Alpert, Kathryn; King, Margaret; Landis, Drew; Calhoun, Vince D; Potkin, Steven G; Tallis, Marcelo; Ambite, Jose Luis; Wang, Lei

2015-07-01

Data sharing and mediation across disparate neuroimaging repositories requires extensive effort to ensure that the different domains of data types are referred to by commonly agreed upon terms. Within the SchizConnect project, which enables querying across decentralized databases of neuroimaging, clinical, and cognitive data from various studies of schizophrenia, we developed a model for each data domain, identified common usable terms that could be agreed upon across the repositories, and linked them to standard ontological terms where possible. We had the goal of facilitating both the current user experience in querying and future automated computations and reasoning regarding the data. We found that existing terminologies are incomplete for these purposes, even with the history of neuroimaging data sharing in the field; and we provide a model for efforts focused on querying multiple clinical neuroimaging repositories.

Terminology development towards harmonizing multiple clinical neuroimaging research repositories

PubMed Central

Turner, Jessica A.; Pasquerello, Danielle; Turner, Matthew D.; Keator, David B.; Alpert, Kathryn; King, Margaret; Landis, Drew; Calhoun, Vince D.; Potkin, Steven G.; Tallis, Marcelo; Ambite, Jose Luis; Wang, Lei

2015-01-01

Data sharing and mediation across disparate neuroimaging repositories requires extensive effort to ensure that the different domains of data types are referred to by commonly agreed upon terms. Within the SchizConnect project, which enables querying across decentralized databases of neuroimaging, clinical, and cognitive data from various studies of schizophrenia, we developed a model for each data domain, identified common usable terms that could be agreed upon across the repositories, and linked them to standard ontological terms where possible. We had the goal of facilitating both the current user experience in querying and future automated computations and reasoning regarding the data. We found that existing terminologies are incomplete for these purposes, even with the history of neuroimaging data sharing in the field; and we provide a model for efforts focused on querying multiple clinical neuroimaging repositories. PMID:26688838

Addison disease - diagnosis and initial management.

PubMed

O'Connell, Susan; Siafarikas, Aris

2010-11-01

Adrenal insufficiency is a rare disease caused by either primary adrenal failure (Addison disease) or by impairment of the hypothalamic-pituitary-adrenal axis. Steroid replacement therapy normalises quality of life, however, adherence can be problematic. This article provides information on adrenal insufficiency focusing on awareness of initial symptoms and on risk scenarios, emergency management and baseline investigations, complete investigations and long term management. Early recognition of adrenal insufficiency is essential to avoid associated morbidity and mortality. Initial diagnosis and decision to treat are based on history and physical examination. Appropriate management includes emergency resuscitation and steroid administration. Initial investigations can include sodium, potassium and blood glucose levels. However, complete investigations can be deferred. Specialist advice should be obtained and long term management includes a Team Care Arrangement. For patients, an emergency plan and emergency identification are essential.

A Review of Neuroimaging Findings in Repetitive Brain Trauma

PubMed Central

Koerte, Inga K.; Lin, Alexander P.; Willems, Anna; Muehlmann, Marc; Hufschmidt, Jakob; Coleman, Michael J.; Green, Isobel; Liao, Huijun; Tate, David F.; Wilde, Elisabeth A.; Pasternak, Ofer; Bouix, Sylvain; Rathi, Yogesh; Bigler, Erin D.; Stern, Robert A.; Shenton, Martha E.

2017-01-01

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease confirmed at post-mortem. Those at highest risk are professional athletes who participate in contact sports and military personnel who are exposed to repetitive blast events. All neuropathologically-confirmed CTE cases, to date, have had a history of repetitive head impacts. This suggests that repetitive head impacts may be necessary for the initiation of the pathogenetic cascade that, in some cases, leads to CTE. Importantly, while all CTE appears to result from repetitive brain trauma, not all repetitive brain trauma results in CTE. Magnetic resonance imaging has great potential for understanding better the underlying mechanisms of repetitive brain trauma. In this review we provide an overview of advanced imaging techniques currently used to investigate brain anomalies. We also provide an overview of neuroimaging findings in those exposed to repetitive head impacts in the acute/subacute and chronic phase of injury and in more neurodegenerative phases of injury, as well as in military personnel exposed to repetitive head impacts. Finally, we discuss future directions for research that will likely lead to a better understanding of the underlying mechanisms separating those who recover from repetitive brain trauma versus those who go on to develop CTE. PMID:25904047

Recent neuroimaging, neurophysiological, and neuropathological advances for the understanding of NPC

PubMed Central

Benussi, Alberto; Cotelli, Maria Sofia; Padovani, Alessandro; Borroni, Barbara

2018-01-01

Niemann–Pick disease type C (NPC) is a rare autosomal recessive lysosomal storage disorder with extensive biological, molecular, and clinical heterogeneity. Recently, numerous studies have tried to shed light on the pathophysiology of the disease, highlighting possible disease pathways common to other neurodegenerative disorders, such as Alzheimer’s disease and frontotemporal dementia, and identifying possible candidate biomarkers for disease staging and response to treatment. Miglustat, which reversibly inhibits glycosphingolipid synthesis, has been licensed in the European Union and elsewhere for the treatment of NPC in both children and adults. A number of ongoing clinical trials might hold promise for the development of new treatments for NPC. The objective of the present work is to review and evaluate recent literature data in order to highlight the latest neuroimaging, neurophysiological, and neuropathological advances for the understanding of NPC pathophysiology. Furthermore, ongoing developments in disease-modifying treatments will be briefly discussed. PMID:29511534

Neuropsychological and neuroimaging underpinnings of schizoaffective disorder: a systematic review.

PubMed

Madre, M; Canales-Rodríguez, E J; Ortiz-Gil, J; Murru, A; Torrent, C; Bramon, E; Perez, V; Orth, M; Brambilla, P; Vieta, E; Amann, B L

2016-07-01

The neurobiological basis and nosological status of schizoaffective disorder remains elusive and controversial. This study provides a systematic review of neurocognitive and neuroimaging findings in the disorder. A comprehensive literature search was conducted via PubMed, ScienceDirect, Scopus and Web of Knowledge (from 1949 to 31st March 2015) using the keyword 'schizoaffective disorder' and any of the following terms: 'neuropsychology', 'cognition', 'structural neuroimaging', 'functional neuroimaging', 'multimodal', 'DTI' and 'VBM'. Only studies that explicitly examined a well defined sample, or subsample, of patients with schizoaffective disorder were included. Twenty-two of 43 neuropsychological and 19 of 51 neuroimaging articles fulfilled inclusion criteria. We found a general trend towards schizophrenia and schizoaffective disorder being related to worse cognitive performance than bipolar disorder. Grey matter volume loss in schizoaffective disorder is also more comparable to schizophrenia than to bipolar disorder which seems consistent across further neuroimaging techniques. Neurocognitive and neuroimaging abnormalities in schizoaffective disorder resemble more schizophrenia than bipolar disorder. This is suggestive for schizoaffective disorder being a subtype of schizophrenia or being part of the continuum spectrum model of psychosis, with schizoaffective disorder being more skewed towards schizophrenia than bipolar disorder. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Towards structured sharing of raw and derived neuroimaging data across existing resources

PubMed Central

Keator, D.B.; Helmer, K.; Steffener, J.; Turner, J.A.; Van Erp, T.G.M.; Gadde, S.; Ashish, N.; Burns, G.A.; Nichols, B.N.

2013-01-01

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery. PMID:23727024

Neuroimaging of Human Balance Control: A Systematic Review

PubMed Central

Wittenberg, Ellen; Thompson, Jessica; Nam, Chang S.; Franz, Jason R.

2017-01-01

This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control. PMID:28443007

Imperial College near infrared spectroscopy neuroimaging analysis framework.

PubMed

Orihuela-Espina, Felipe; Leff, Daniel R; James, David R C; Darzi, Ara W; Yang, Guang-Zhong

2018-01-01

This paper describes the Imperial College near infrared spectroscopy neuroimaging analysis (ICNNA) software tool for functional near infrared spectroscopy neuroimaging data. ICNNA is a MATLAB-based object-oriented framework encompassing an application programming interface and a graphical user interface. ICNNA incorporates reconstruction based on the modified Beer-Lambert law and basic processing and data validation capabilities. Emphasis is placed on the full experiment rather than individual neuroimages as the central element of analysis. The software offers three types of analyses including classical statistical methods based on comparison of changes in relative concentrations of hemoglobin between the task and baseline periods, graph theory-based metrics of connectivity and, distinctively, an analysis approach based on manifold embedding. This paper presents the different capabilities of ICNNA in its current version.

Functional neuroimaging: technical, logical, and social perspectives.

PubMed

Aguirre, Geoffrey K

2014-01-01

Neuroscientists have long sought to study the dynamic activity of the human brain-what's happening in the brain, that is, while people are thinking, feeling, and acting. Ideally, an inside look at brain function would simultaneously and continuously measure the biochemical state of every cell in the central nervous system. While such a miraculous method is science fiction, a century of progress in neuroimaging technologies has made such simultaneous and continuous measurement a plausible fiction. Despite this progress, practitioners of modern neuroimaging struggle with two kinds of limitations: those that attend the particular neuroimaging methods we have today and those that would limit any method of imaging neural activity, no matter how powerful. In this essay, I consider the liabilities and potential of techniques that measure human brain activity. I am concerned here only with methods that measure relevant physiologic states of the central nervous system and relate those measures to particular mental states. I will consider in particular the preeminent method of functional neuroimaging: BOLD fMRI. While there are several practical limits on the biological information that current technologies can measure, these limits-as important as they are-are minor in comparison to the fundamental logical restraints on the conclusions that can be drawn from brain imaging studies. © 2014 by The Hastings Center.

COPPADIS-2015 (COhort of Patients with PArkinson's DIsease in Spain, 2015), a global--clinical evaluations, serum biomarkers, genetic studies and neuroimaging--prospective, multicenter, non-interventional, long-term study on Parkinson's disease progression.

PubMed

Santos-García, Diego; Mir, Pablo; Cubo, Esther; Vela, Lydia; Rodríguez-Oroz, Mari Cruz; Martí, Maria José; Arbelo, José Matías; Infante, Jon; Kulisevsky, Jaime; Martínez-Martín, Pablo

2016-02-25

Parkinson's disease (PD) is a progressive neurodegenerative disorder causing motor and non-motor symptoms that can affect independence, social adjustment and the quality of life (QoL) of both patients and caregivers. Studies designed to find diagnostic and/or progression biomarkers of PD are needed. We describe here the study protocol of COPPADIS-2015 (COhort of Patients with PArkinson's DIsease in Spain, 2015), an integral PD project based on four aspects/concepts: 1) PD as a global disease (motor and non-motor symptoms); 2) QoL and caregiver issues; 3) Biomarkers; 4) Disease progression. Observational, descriptive, non-interventional, 5-year follow-up, national (Spain), multicenter (45 centers from 15 autonomous communities), evaluation study. Specific goals: (1) detailed study (clinical evaluations, serum biomarkers, genetic studies and neuroimaging) of a population of PD patients from different areas of Spain, (2) comparison with a control group and (3) follow-up for 5 years. COPPADIS-2015 has been specifically designed to assess 17 proposed objectives. approximately 800 non-dementia PD patients, 600 principal caregivers and 400 control subjects. Study evaluations: (1) baseline includes motor assessment (e.g., Unified Parkinson's Disease Rating Scale part III), non-motor symptoms (e.g., Non-Motor Symptoms Scale), cognition (e.g., Parkinson's Disease Cognitive Rating Scale), mood and neuropsychiatric symptoms (e.g., Neuropsychiatric Inventory), disability, QoL (e.g., 39-item Parkinson's disease Quality of Life Questionnaire Summary-Index) and caregiver status (e.g., Zarit Caregiver Burden Inventory); (2) follow-up includes annual (patients) or biannual (caregivers and controls) evaluations. Serum biomarkers (S-100b protein, TNF-α, IL-1, IL-2, IL-6, vitamin B12, methylmalonic acid, homocysteine, uric acid, C-reactive protein, ferritin, iron) and brain MRI (volumetry, tractography and MTAi [Medial Temporal Atrophy Index]), at baseline and at the end of follow

Advanced Neuroimaging in Traumatic Brain Injury

PubMed Central

Edlow, Brian L.; Wu, Ona

2013-01-01

Advances in structural and functional neuroimaging have occurred at a rapid pace over the past two decades. Novel techniques for measuring cerebral blood flow, metabolism, white matter connectivity, and neural network activation have great potential to improve the accuracy of diagnosis and prognosis for patients with traumatic brain injury (TBI), while also providing biomarkers to guide the development of new therapies. Several of these advanced imaging modalities are currently being implemented into clinical practice, whereas others require further development and validation. Ultimately, for advanced neuroimaging techniques to reach their full potential and improve clinical care for the many civilians and military personnel affected by TBI, it is critical for clinicians to understand the applications and methodological limitations of each technique. In this review, we examine recent advances in structural and functional neuroimaging and the potential applications of these techniques to the clinical care of patients with TBI. We also discuss pitfalls and confounders that should be considered when interpreting data from each technique. Finally, given the vast amounts of advanced imaging data that will soon be available to clinicians, we discuss strategies for optimizing data integration, visualization and interpretation. PMID:23361483

Associations between Verbal Learning Slope and Neuroimaging Markers across the Cognitive Aging Spectrum.

PubMed

Gifford, Katherine A; Phillips, Jeffrey S; Samuels, Lauren R; Lane, Elizabeth M; Bell, Susan P; Liu, Dandan; Hohman, Timothy J; Romano, Raymond R; Fritzsche, Laura R; Lu, Zengqi; Jefferson, Angela L

2015-07-01

A symptom of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a flat learning profile. Learning slope calculation methods vary, and the optimal method for capturing neuroanatomical changes associated with MCI and early AD pathology is unclear. This study cross-sectionally compared four different learning slope measures from the Rey Auditory Verbal Learning Test (simple slope, regression-based slope, two-slope method, peak slope) to structural neuroimaging markers of early AD neurodegeneration (hippocampal volume, cortical thickness in parahippocampal gyrus, precuneus, and lateral prefrontal cortex) across the cognitive aging spectrum [normal control (NC); (n=198; age=76±5), MCI (n=370; age=75±7), and AD (n=171; age=76±7)] in ADNI. Within diagnostic group, general linear models related slope methods individually to neuroimaging variables, adjusting for age, sex, education, and APOE4 status. Among MCI, better learning performance on simple slope, regression-based slope, and late slope (Trial 2-5) from the two-slope method related to larger parahippocampal thickness (all p-values<.01) and hippocampal volume (p<.01). Better regression-based slope (p<.01) and late slope (p<.01) were related to larger ventrolateral prefrontal cortex in MCI. No significant associations emerged between any slope and neuroimaging variables for NC (p-values ≥.05) or AD (p-values ≥.02). Better learning performances related to larger medial temporal lobe (i.e., hippocampal volume, parahippocampal gyrus thickness) and ventrolateral prefrontal cortex in MCI only. Regression-based and late slope were most highly correlated with neuroimaging markers and explained more variance above and beyond other common memory indices, such as total learning. Simple slope may offer an acceptable alternative given its ease of calculation.

Neuroimaging and Recovery of Language in Aphasia

PubMed Central

Thompson, Cynthia K.; den Ouden, Dirk-Bart

2010-01-01

The use of functional neuroimaging techniques has advanced what is known about the neural mechanisms used to support language processing in aphasia resulting from brain damage. This paper highlights recent findings derived from neuroimaging studies focused on neuroplasticity of language networks, the role of the left and right hemispheres in this process, and studies examining how treatment affects the neurobiology of recovery. We point out variability across studies as well as factors related to this variability, and we emphasize challenges that remain for research. PMID:18957184

Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges

PubMed Central

2018-01-01

Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ. PMID:29324666

The coordinate-based meta-analysis of neuroimaging data.

PubMed

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E; Johnson, Timothy D

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research.

The coordinate-based meta-analysis of neuroimaging data

PubMed Central

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E.; Johnson, Timothy D.

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research. PMID:29545671

Neuroimaging studies of social cognition in schizophrenia.

PubMed

Fujiwara, Hironobu; Yassin, Walid; Murai, Toshiya

2015-05-01

Impaired social cognition is considered a core contributor to unfavorable psychosocial functioning in schizophrenia. Rather than being a unitary process, social cognition is a collection of multifaceted processes that recruit multiple brain structures, thus structural and functional neuroimaging techniques are ideal methodologies for revealing the underlying pathophysiology of impaired social cognition. Many neuroimaging studies have suggested that in addition to white-matter deficits, schizophrenia is associated with decreased gray-matter volume in multiple brain areas, especially fronto-temporal and limbic regions. However, few schizophrenia studies have examined associations between brain abnormalities and social cognitive disabilities. During the last decade, we have investigated structural brain abnormalities in schizophrenia using high-resolution magnetic resonance imaging, and our findings have been confirmed by us and others. By assessing different types of social cognitive abilities, structural abnormalities in multiple brain regions have been found to be associated with disabilities in social cognition, such as recognition of facial emotion, theory of mind, and empathy. These structural deficits have also been associated with alexithymia and quality of life in ways that are closely related to the social cognitive disabilities found in schizophrenia. Here, we overview a series of neuroimaging studies from our laboratory that exemplify current research into this topic, and discuss how it can be further tackled using recent advances in neuroimaging technology. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.

Functional neuroimaging of emotional learning and autonomic reactions.

PubMed

Peper, Martin; Herpers, Martin; Spreer, Joachim; Hennig, Jürgen; Zentner, Josef

2006-06-01

This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.

Neuroimaging in psychiatric pharmacogenetics research: the promise and pitfalls.

PubMed

Falcone, Mary; Smith, Ryan M; Chenoweth, Meghan J; Bhattacharjee, Abesh Kumar; Kelsoe, John R; Tyndale, Rachel F; Lerman, Caryn

2013-11-01

The integration of research on neuroimaging and pharmacogenetics holds promise for improving treatment for neuropsychiatric conditions. Neuroimaging may provide a more sensitive early measure of treatment response in genetically defined patient groups, and could facilitate development of novel therapies based on an improved understanding of pathogenic mechanisms underlying pharmacogenetic associations. This review summarizes progress in efforts to incorporate neuroimaging into genetics and treatment research on major psychiatric disorders, such as schizophrenia, major depressive disorder, bipolar disorder, attention-deficit/hyperactivity disorder, and addiction. Methodological challenges include: performing genetic analyses in small study populations used in imaging studies; inclusion of patients with psychiatric comorbidities; and the extensive variability across studies in neuroimaging protocols, neurobehavioral task probes, and analytic strategies. Moreover, few studies use pharmacogenetic designs that permit testing of genotype × drug effects. As a result of these limitations, few findings have been fully replicated. Future studies that pre-screen participants for genetic variants selected a priori based on drug metabolism and targets have the greatest potential to advance the science and practice of psychiatric treatment.

Neuroimaging of the Periaqueductal Gray: State of the Field

PubMed Central

Linnman, Clas; Moulton, Eric A.; Barmettler, Gabi; Becerra, Lino; Borsook, David

2011-01-01

This review and meta-analysis aims at summarizing and integrating the human neuroimaging studies that report periaqueductal gray (PAG) involvement; 250 original manuscripts on human neuroimaging of the PAG were identified. A narrative review and meta-analysis using activation likelihood estimates is included. Behaviors covered include pain and pain modulation, anxiety, bladder and bowel function and autonomic regulation. Methods include structural and functional magnetic resonance imaging, functional connectivity measures, diffusion weighted imaging and positron emission tomography. Human neuroimaging studies in healthy and clinical populations largely confirm the animal literature indicating that the PAG is involved in homeostatic regulation of salient functions such as pain, anxiety and autonomic function. Methodological concerns in the current literature, including resolution constraints, imaging artifacts and imprecise neuroanatomical labeling are discussed, and future directions are proposed. A general conclusion is that PAG neuroimaging is a field with enormous potential to translate animal data onto human behaviors, but with some growing pains that can and need to be addressed in order to add to our understanding of the neurobiology of this key region. PMID:22197740

Neuroimaging in human MDMA (Ecstasy) users.

PubMed

Cowan, Ronald L; Roberts, Deanne M; Joers, James M

2008-10-01

MDMA (3,4 methylenedioxymethamphetamine) has been used by millions of people worldwide as a recreational drug. The terms "MDMA" and "Ecstasy" are often used synonymously, but it is important to note that the purity of Ecstasy sold as MDMA is not certain. MDMA use is of public health concern, not so much because MDMA produces a common or severe dependence syndrome, but rather because rodent and nonhuman primate studies have indicated that MDMA (when administered at certain dosages and intervals) can cause long-lasting reductions in markers of brain serotonin (5-HT) that appear specific to fine-diameter axons arising largely from the dorsal raphe nucleus (DR). Given the popularity of MDMA, the potential for the drug to produce long-lasting or permanent 5-HT axon damage or loss, and the widespread role of 5-HT function in the brain, there is a great need for a better understanding of brain function in human users of this drug. To this end, neuropsychological, neuroendocrine, and neuroimaging studies have all suggested that human MDMA users may have long-lasting changes in brain function consistent with 5-HT toxicity. Data from animal models leads to testable hypotheses regarding MDMA's effects on the human brain. Because neuropsychological and neuroimaging findings have focused on the neocortex, a cortical model is developed to provide a context for designing and interpreting neuroimaging studies in MDMA users. Aspects of the model are supported by the available neuroimaging data, but there are controversial findings in some areas and most findings have not been replicated across different laboratories and using different modalities. This paper reviews existing findings in the context of a cortical model and suggests directions for future research.

Functional neuroimaging in epileptic encephalopathies.

PubMed

Siniatchkin, Michael; Capovilla, Giuseppe

2013-11-01

Epileptic encephalopathies (EEs) represent a group of severe epileptic disorders associated with cognitive and behavioral disturbances. The mechanisms of cognitive disability in EEs remain unclear. This review summarized neuroimaging studies that have tried to describe specific fingerprints of brain activation in EE. Although the epileptic activity can be generated individually in different brain regions, it seems likely that the activity propagates in a syndrome-specific way. In some EEs, the epileptiform discharges were associated with an interruption of activity in the default mode network. In another EE, other mechanisms seem to underlie cognitive disability associated with epileptic activity, for example, abnormal connectivity pattern or interfering activity in the thalamocortical network. Further neuroimaging studies are needed to investigate the short-term and long-term impact of epileptic activity on cognition and development. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Exploration and Modulation of Brain Network Interactions with Noninvasive Brain Stimulation in Combination with Neuroimaging

PubMed Central

Shafi, Mouhsin M.; Westover, M. Brandon; Fox, Michael D.; Pascual-Leone, Alvaro

2012-01-01

Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language, and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to noninvasively alter brain activity, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional MRI, PET and EEG, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner. PMID:22429242

Effects of traumatic brain injury and posttraumatic stress disorder on development of Alzheimer's disease in Vietnam Veterans using the Alzheimer's Disease Neuroimaging Initiative: Preliminary Report.

PubMed

Weiner, Michael W; Harvey, Danielle; Hayes, Jacqueline; Landau, Susan M; Aisen, Paul S; Petersen, Ronald C; Tosun, Duygu; Veitch, Dallas P; Jack, Clifford R; Decarli, Charles; Saykin, Andrew J; Grafman, Jordan; Neylanthe, Thomas C

2017-06-01

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) have previously been reported to be associated with increased risk of Alzheimer's disease (AD). We are using biomarkers to study Vietnam Veterans with/without mild cognitive impairment with a history of at least one TBI and/or ongoing PTSD to determine whether these contribute to the development of AD. Potential subjects identified by Veterans Administration records underwent an initial telephone screen. Consented subjects underwent clinical evaluation, lumbar puncture, structural MRI and amyloid PET scans. We observed worse cognitive functioning in PTSD and TBI + PTSD groups, worse global cognitive functioning in the PTSD group, lower superior parietal volume in the TBI + PTSD group, and lower amyloid positivity in the PTSD group, but not the TBI group compared to controls without TBI/PTSD. Medial temporal lobe atrophy was not increased in the PTSD and/or TBI groups. Preliminary results do not indicate that TBI or PTSD increase the risk for AD measured by amyloid PET. Additional recruitment, longitudinal follow-up, and tau PET scans will provide more information in the future.

Presymptomatic and longitudinal neuroimaging in neurodegeneration--from snapshots to motion picture: a systematic review.

PubMed

Schuster, Christina; Elamin, Marwa; Hardiman, Orla; Bede, Peter

2015-10-01

Recent quantitative neuroimaging studies have been successful in capturing phenotype and genotype-specific changes in dementia syndromes, amyotrophic lateral sclerosis, Parkinson's disease and other neurodegenerative conditions. However, the majority of imaging studies are cross-sectional, despite the obvious superiority of longitudinal study designs in characterising disease trajectories, response to therapy, progression rates and evaluating the presymptomatic phase of neurodegenerative conditions. The aim of this work is to perform a systematic review of longitudinal imaging initiatives in neurodegeneration focusing on methodology, optimal statistical models, follow-up intervals, attrition rates, primary study outcomes and presymptomatic studies. Longitudinal imaging studies were identified from 'PubMed' and reviewed from 1990 to 2014. The search terms 'longitudinal', 'MRI', 'presymptomatic' and 'imaging' were utilised in combination with one of the following degenerative conditions; Alzheimer's disease, amyotrophic lateral sclerosis/motor neuron disease, frontotemporal dementia, Huntington's disease, multiple sclerosis, Parkinson's disease, ataxia, HIV, alcohol abuse/dependence. A total of 423 longitudinal imaging papers and 103 genotype-based presymptomatic studies were identified and systematically reviewed. Imaging techniques, follow-up intervals and attrition rates showed significant variation depending on the primary diagnosis. Commonly used statistical models included analysis of annualised percentage change, mixed and random effect models, and non-linear cumulative models with acceleration-deceleration components. Although longitudinal imaging studies have the potential to provide crucial insights into the presymptomatic phase and natural trajectory of neurodegenerative processes a standardised design is required to enable meaningful data interpretation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under

CBRAIN: a web-based, distributed computing platform for collaborative neuroimaging research.

PubMed

Sherif, Tarek; Rioux, Pierre; Rousseau, Marc-Etienne; Kassis, Nicolas; Beck, Natacha; Adalat, Reza; Das, Samir; Glatard, Tristan; Evans, Alan C

2014-01-01

The Canadian Brain Imaging Research Platform (CBRAIN) is a web-based collaborative research platform developed in response to the challenges raised by data-heavy, compute-intensive neuroimaging research. CBRAIN offers transparent access to remote data sources, distributed computing sites, and an array of processing and visualization tools within a controlled, secure environment. Its web interface is accessible through any modern browser and uses graphical interface idioms to reduce the technical expertise required to perform large-scale computational analyses. CBRAIN's flexible meta-scheduling has allowed the incorporation of a wide range of heterogeneous computing sites, currently including nine national research High Performance Computing (HPC) centers in Canada, one in Korea, one in Germany, and several local research servers. CBRAIN leverages remote computing cycles and facilitates resource-interoperability in a transparent manner for the end-user. Compared with typical grid solutions available, our architecture was designed to be easily extendable and deployed on existing remote computing sites with no tool modification, administrative intervention, or special software/hardware configuration. As October 2013, CBRAIN serves over 200 users spread across 53 cities in 17 countries. The platform is built as a generic framework that can accept data and analysis tools from any discipline. However, its current focus is primarily on neuroimaging research and studies of neurological diseases such as Autism, Parkinson's and Alzheimer's diseases, Multiple Sclerosis as well as on normal brain structure and development. This technical report presents the CBRAIN Platform, its current deployment and usage and future direction.

Acute pediatric encephalitis neuroimaging: single-institution series as part of the California encephalitis project.

PubMed

Bykowski, Julie; Kruk, Peter; Gold, Jeffrey J; Glaser, Carol A; Sheriff, Heather; Crawford, John R

2015-06-01

Diagnosing pediatric encephalitis is challenging because of varied clinical presentation, nonspecific neuroimaging features, and rare confirmation of causality. We reviewed acute neuroimaging of children with clinically suspected encephalitis to identify findings that may correlate with etiology and length of stay. Imaging of 141 children with clinically suspected encephalitis as part of The California Encephalitis Project from 2005 to 2012 at a single institution was reviewed to compare the extent of neuroimaging abnormalities to patient age, gender, length of stay, and unknown, possible, or confirmed pathogen. Scan review was blinded and categorized by extent and distribution of abnormal findings. Abnormal findings were evident on 23% (22/94) of computed tomography and 50% (67/134) of magnetic resonance imaging studies in the acute setting. Twenty children with normal admission computed tomography had abnormal findings on magnetic resonance imaging performed within 2 days. Length of stay was significantly longer among children with abnormal acute magnetic resonance imaging (P < 0.001) and correlated with increased complexity (Spearman rho = 0.4, P < 0.001) categorized as: no imaging abnormality, meningeal enhancement and/or focal nonenhancing lesion, multifocal lesions, confluent lesions, and lesions plus diffusion restriction, hemorrhage, or hydrocephalus. There was no correlation between neuroimaging findings and an identifiable pathogen (P = 0.8). Abnormal magnetic resonance imaging findings are more common than abnormal computed tomography findings in pediatric encephalitis. Increasing complexity of magnetic resonance imaging findings correlated with disease severity as evidenced by longer length of stay, but were not specific for an identifiable pathogen using a standardized diagnostic encephalitis panel. Copyright © 2015 Elsevier Inc. All rights reserved.

Neuroimaging with functional near infrared spectroscopy: From formation to interpretation

NASA Astrophysics Data System (ADS)

Herrera-Vega, Javier; Treviño-Palacios, Carlos G.; Orihuela-Espina, Felipe

2017-09-01

Functional Near Infrared Spectroscopy (fNIRS) is gaining momentum as a functional neuroimaging modality to investigate the cerebral hemodynamics subsequent to neural metabolism. As other neuroimaging modalities, it is neuroscience's tool to understand brain systems functions at behaviour and cognitive levels. To extract useful knowledge from functional neuroimages it is critical to understand the series of transformations applied during the process of the information retrieval and how they bound the interpretation. This process starts with the irradiation of the head tissues with infrared light to obtain the raw neuroimage and proceeds with computational and statistical analysis revealing hidden associations between pixels intensities and neural activity encoded to end up with the explanation of some particular aspect regarding brain function.To comprehend the overall process involved in fNIRS there is extensive literature addressing each individual step separately. This paper overviews the complete transformation sequence through image formation, reconstruction and analysis to provide an insight of the final functional interpretation.

A simple tool for neuroimaging data sharing

PubMed Central

Haselgrove, Christian; Poline, Jean-Baptiste; Kennedy, David N.

2014-01-01

Data sharing is becoming increasingly common, but despite encouragement and facilitation by funding agencies, journals, and some research efforts, most neuroimaging data acquired today is still not shared due to political, financial, social, and technical barriers to sharing data that remain. In particular, technical solutions are few for researchers that are not a part of larger efforts with dedicated sharing infrastructures, and social barriers such as the time commitment required to share can keep data from becoming publicly available. We present a system for sharing neuroimaging data, designed to be simple to use and to provide benefit to the data provider. The system consists of a server at the International Neuroinformatics Coordinating Facility (INCF) and user tools for uploading data to the server. The primary design principle for the user tools is ease of use: the user identifies a directory containing Digital Imaging and Communications in Medicine (DICOM) data, provides their INCF Portal authentication, and provides identifiers for the subject and imaging session. The user tool anonymizes the data and sends it to the server. The server then runs quality control routines on the data, and the data and the quality control reports are made public. The user retains control of the data and may change the sharing policy as they need. The result is that in a few minutes of the user’s time, DICOM data can be anonymized and made publicly available, and an initial quality control assessment can be performed on the data. The system is currently functional, and user tools and access to the public image database are available at http://xnat.incf.org/. PMID:24904398

Identifying Treatment Response of Sertraline in a Teenager with Selective Mutism using Electrophysiological Neuroimaging

PubMed Central

Eugene, Andy R.; Masiak, Jolanta

2016-01-01

Background Selective Mutism is described as the inability to verbally express oneself in anxiety provoking social situations and may result in awkward social interactions in school-aged children. In this case-report we present the baseline electrophysiological neuroimaging results and after treatment with Sertraline for 6-weeks. Methods A 20-channel EEG event-related potential recording was acquired during an internal voice task at baseline prior to the initiation of 50mg of Sertraline and then repeated 6-weeks after treatment with Sertraline. EEG signals were processed for movement, eye-blink, and muscle artifacts and ERP signal averaging was completed. ERPs were analyzed using Standard Low Resolution Brain Electromagnetic Tomography (sLORETA). Results At baseline, Sertraline increased the neuronal activation in the middle temporal gyrus and the anterior cingulate gyrus from baseline in the patient following 6-weeks of treatment. Conclusion Our findings suggest that electrophysiological neuroimaging may provide a creative approach for personalizing medicine by providing insight to the pharmacodynamics of antidepressants. PMID:27468379

Identifying Treatment Response of Sertraline in a Teenager with Selective Mutism using Electrophysiological Neuroimaging.

PubMed

Eugene, Andy R; Masiak, Jolanta

2016-06-01

Selective Mutism is described as the inability to verbally express oneself in anxiety provoking social situations and may result in awkward social interactions in school-aged children. In this case-report we present the baseline electrophysiological neuroimaging results and after treatment with Sertraline for 6-weeks. A 20-channel EEG event-related potential recording was acquired during an internal voice task at baseline prior to the initiation of 50mg of Sertraline and then repeated 6-weeks after treatment with Sertraline. EEG signals were processed for movement, eye-blink, and muscle artifacts and ERP signal averaging was completed. ERPs were analyzed using Standard Low Resolution Brain Electromagnetic Tomography (sLORETA). At baseline, Sertraline increased the neuronal activation in the middle temporal gyrus and the anterior cingulate gyrus from baseline in the patient following 6-weeks of treatment. Our findings suggest that electrophysiological neuroimaging may provide a creative approach for personalizing medicine by providing insight to the pharmacodynamics of antidepressants.

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

Neuroimaging: A Window to the Neurological Foundations of Learning and Behavior in Children.

ERIC Educational Resources Information Center

Lyon, G. Reid, Ed.; Rumsey, Judith M., Ed.

This book presents 11 papers on the use of neuroimaging technology in brain-related disorders. The text contains full-color neuroimaging scans and provides both theoretical and methodological explanations of the various neuroimaging techniques and their application to developmental disorders in children. The papers are grouped into three sections,…

Neuroimaging of Fear-Associated Learning

PubMed Central

Greco, John A; Liberzon, Israel

2016-01-01

Fear conditioning has been commonly used as a model of emotional learning in animals and, with the introduction of functional neuroimaging techniques, has proven useful in establishing the neurocircuitry of emotional learning in humans. Studies of fear acquisition suggest that regions such as amygdala, insula, anterior cingulate cortex, and hippocampus play an important role in acquisition of fear, whereas studies of fear extinction suggest that the amygdala is also crucial for safety learning. Extinction retention testing points to the ventromedial prefrontal cortex as an essential region in the recall of the safety trace, and explicit learning of fear and safety associations recruits additional cortical and subcortical regions. Importantly, many of these findings have implications in our understanding of the pathophysiology of psychiatric disease. Recent studies using clinical populations have lent insight into the changes in regional activity in specific disorders, and treatment studies have shown how pharmaceutical and other therapeutic interventions modulate brain activation during emotional learning. Finally, research investigating individual differences in neurotransmitter receptor genotypes has highlighted the contribution of these systems in fear-associated learning. PMID:26294108

Imaging genetics approach to predict progression of Parkinson's diseases.

PubMed

Mansu Kim; Seong-Jin Son; Hyunjin Park

2017-07-01

Imaging genetics is a tool to extract genetic variants associated with both clinical phenotypes and imaging information. The approach can extract additional genetic variants compared to conventional approaches to better investigate various diseased conditions. Here, we applied imaging genetics to study Parkinson's disease (PD). We aimed to extract significant features derived from imaging genetics and neuroimaging. We built a regression model based on extracted significant features combining genetics and neuroimaging to better predict clinical scores of PD progression (i.e. MDS-UPDRS). Our model yielded high correlation (r = 0.697, p <; 0.001) and low root mean squared error (8.36) between predicted and actual MDS-UPDRS scores. Neuroimaging (from 123 I-Ioflupane SPECT) predictors of regression model were computed from independent component analysis approach. Genetic features were computed using image genetics approach based on identified neuroimaging features as intermediate phenotypes. Joint modeling of neuroimaging and genetics could provide complementary information and thus have the potential to provide further insight into the pathophysiology of PD. Our model included newly found neuroimaging features and genetic variants which need further investigation.

Seeing responsibility: can neuroimaging teach us anything about moral and legal responsibility?

PubMed

Wasserman, David; Johnston, Josephine

2014-01-01

As imaging technologies help us understand the structure and function of the brain, providing insight into human capabilities as basic as vision and as complex as memory, and human conditions as impairing as depression and as fraught as psychopathy, some have asked whether they can also help us understand human agency. Specifically, could neuroimaging lead us to reassess the socially significant practice of assigning and taking responsibility? While responsibility itself is not a psychological process open to investigation through neuroimaging, decision-making is. Over the past decade, different researchers and scholars have sought to use neuroimaging (or the results of neuroimaging studies) to investigate what is going on in the brain when we make decisions. The results of this research raise the question whether neuroscience-especially now that it includes neuroimaging-can and should alter our understandings of responsibility and our related practice of holding people responsible. It is this question that we investigate here. © 2014 by The Hastings Center.

Neuroimaging: beginning to appreciate its complexities.

PubMed

Parens, Erik; Johnston, Josephine

2014-01-01

For over a century, scientists have sought to see through the protective shield of the human skull and into the living brain. Today, an array of technologies allows researchers and clinicians to create astonishingly detailed images of our brain's structure as well as colorful depictions of the electrical and physiological changes that occur within it when we see, hear, think and feel. These technologies-and the images they generate-are an increasingly important tool in medicine and science. Given the role that neuroimaging technologies now play in biomedical research, both neuroscientists and nonexperts should aim to be as clear as possible about how neuroimages are made and what they can-and cannot-tell us. Add to this that neuroimages have begun to be used in courtrooms at both the determination of guilt and sentencing stages, that they are being employed by marketers to refine advertisements and develop new products, that they are being sold to consumers for the diagnosis of mental disorders and for the detection of lies, and that they are being employed in arguments about the nature (or absence) of powerful concepts like free will and personhood, and the need for citizens to have a basic understanding of how this technology works and what it can and cannot tell us becomes even more pressing. © 2014 by The Hastings Center.

The impacts of cognitive-behavioral therapy on the treatment of phobic disorders measured by functional neuroimaging techniques: a systematic review.

PubMed

Galvao-de Almeida, Amanda; Araujo Filho, Gerardo Maria de; Berberian, Arthur de Almeida; Trezsniak, Clarissa; Nery-Fernandes, Fabiana; Araujo Neto, Cesar Augusto; Jackowski, Andrea Parolin; Miranda-Scippa, Angela; Oliveira, Irismar Reis de

2013-01-01

Functional neuroimaging techniques represent fundamental tools in the context of translational research integrating neurobiology, psychopathology, neuropsychology, and therapeutics. In addition, cognitive-behavioral therapy (CBT) has proven its efficacy in the treatment of anxiety disorders and may be useful in phobias. The literature has shown that feelings and behaviors are mediated by specific brain circuits, and changes in patterns of interaction should be associated with cerebral alterations. Based on these concepts, a systematic review was conducted aiming to evaluate the impact of CBT on phobic disorders measured by functional neuroimaging techniques. A systematic review of the literature was conducted including studies published between January 1980 and April 2012. Studies written in English, Spanish or Portuguese evaluating changes in the pattern of functional neuroimaging before and after CBT in patients with phobic disorders were included. The initial search strategy retrieved 45 studies. Six of these studies met all inclusion criteria. Significant deactivations in the amygdala, insula, thalamus and hippocampus, as well as activation of the medial orbitofrontal cortex, were observed after CBT in phobic patients when compared with controls. In spite of their technical limitations, neuroimaging techniques provide neurobiological support for the efficacy of CBT in the treatment of phobic disorders. Further studies are needed to confirm this conclusion.

Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures

PubMed Central

Ye, Zheng; Rae, Charlotte L.; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle‐Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R.; Maxwell, Helen; Sahakian, Barbara J.; Barker, Roger A.; Robbins, Trevor W.

2016-01-01

Abstract Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double‐blind randomized three‐way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion‐weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave‐one‐out cross‐validation (LOOCV) to predict patients’ responses in terms of improved stopping efficiency. We identified two optimal models: (1) a “clinical” model that predicted the response of an individual patient with 77–79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion‐weighted imaging scan; and (2) a “mechanistic” model that explained the behavioral response with 85% accuracy for each drug, using drug‐induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. Hum Brain Mapp 37:1026–1037

Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.

PubMed

Aine, C J; Bockholt, H J; Bustillo, J R; Cañive, J M; Caprihan, A; Gasparovic, C; Hanlon, F M; Houck, J M; Jung, R E; Lauriello, J; Liu, J; Mayer, A R; Perrone-Bizzozero, N I; Posse, S; Stephen, J M; Turner, J A; Clark, V P; Calhoun, Vince D

2017-10-01

In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network's collaborative informatics and neuroimaging suite (COINS).

Responsible Reporting: Neuroimaging News in the Age of Responsible Research and Innovation.

PubMed

de Jong, Irja Marije; Kupper, Frank; Arentshorst, Marlous; Broerse, Jacqueline

2016-08-01

Besides offering opportunities in both clinical and non-clinical domains, the application of novel neuroimaging technologies raises pressing dilemmas. 'Responsible Research and Innovation' (RRI) aims to stimulate research and innovation activities that take ethical and social considerations into account from the outset. We previously identified that Dutch neuroscientists interpret "responsible innovation" as educating the public on neuroimaging technologies via the popular press. Their aim is to mitigate (neuro)hype, an aim shared with the wider emerging RRI community. Here, we present results of a media-analysis undertaken to establish whether the body of articles in the Dutch popular press presents balanced conversations on neuroimaging research to the public. We found that reporting was mostly positive and framed in terms of (healthcare) progress. There was rarely a balance between technology opportunities and limitations, and even fewer articles addressed societal or ethical aspects of neuroimaging research. Furthermore, neuroimaging metaphors seem to favour oversimplification. Current reporting is therefore more likely to enable hype than to mitigate it. How can neuroscientists, given their self-ascribed social responsibility, address this conundrum? We make a case for a collective and shared responsibility among neuroscientists, journalists and other stakeholders, including funders, committed to responsible reporting on neuroimaging research.

Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition

PubMed Central

Zhan, Liang; Liu, Yashu; Wang, Yalin; Zhou, Jiayu; Jahanshad, Neda; Ye, Jieping; Thompson, Paul M.

2015-01-01

Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying brain imaging biomarkers that help to automatically differentiate stages of Alzheimer's disease. Here, we focused on brain structural networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying different stages of Alzheimer's disease. PMID:26257601

Linking Essential Tremor to the Cerebellum-Neuroimaging Evidence.

PubMed

Cerasa, Antonio; Quattrone, Aldo

2016-06-01

Essential tremor (ET) is the most common pathological tremor disorder in the world, and post-mortem evidence has shown that the cerebellum is the most consistent area of pathology in ET. In the last few years, advanced neuroimaging has tried to confirm this evidence. The aim of the present review is to discuss to what extent the evidence provided by this field of study may be generalised. We performed a systematic literature search combining the terms ET with the following keywords: MRI, VBM, MRS, DTI, fMRI, PET and SPECT. We summarised and discussed each study and placed the results in the context of existing knowledge regarding the cerebellar involvement in ET. A total of 51 neuroimaging studies met our search criteria, roughly divided into 19 structural and 32 functional studies. Despite clinical and methodological differences, both functional and structural imaging studies showed similar findings but without defining a clear topography of neurodegeneration. Indeed, the vast majority of studies found functional and structural abnormalities in several parts of the anterior and posterior cerebellar lobules, but it remains to be established to what degree these neural changes contribute to clinical symptoms of ET. Currently, advanced neuroimaging has confirmed the involvement of the cerebellum in pathophysiological processes of ET, although a high variability in results persists. For this reason, the translation of this knowledge into daily clinical practice is again partially limited, although new advanced multivariate neuroimaging approaches (machine-learning) are proving interesting changes of perspective.

Chronic behavior disturbance and neurocognitive deficits in neuro-Behcet's disease: a case study.

PubMed

Fisher, Caroline A; Sewell, Katherine; Baker, Amy

2016-06-01

Behcet's disease is a vasculitis and multisystem inflammatory syndrome. Neurological abnormalities occur in a subset of patients. This report presents a case of neuro-Behcet's disease characterized by an initial onset of behavior changes prior to diagnosis, which evolved into a chronic behavioral syndrome. Neuroimaging investigations revealed progressive periventricular white matter and brainstem atrophy and lesions in the basal ganglia and deep white matter tracts, while neuropsychological investigations revealed reductions in information processing, executive functioning, and memory. The case indicates that behavior changes may be the first symptoms to emerge in Behcet's, before other defining features of the disease.

Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?

PubMed

Madhyastha, Tara M; Koh, Natalie; Day, Trevor K M; Hernández-Fernández, Moises; Kelley, Austin; Peterson, Daniel J; Rajan, Sabreena; Woelfer, Karl A; Wolf, Jonathan; Grabowski, Thomas J

2017-01-01

The contribution of this paper is to identify and describe current best practices for using Amazon Web Services (AWS) to execute neuroimaging workflows "in the cloud." Neuroimaging offers a vast set of techniques by which to interrogate the structure and function of the living brain. However, many of the scientists for whom neuroimaging is an extremely important tool have limited training in parallel computation. At the same time, the field is experiencing a surge in computational demands, driven by a combination of data-sharing efforts, improvements in scanner technology that allow acquisition of images with higher image resolution, and by the desire to use statistical techniques that stress processing requirements. Most neuroimaging workflows can be executed as independent parallel jobs and are therefore excellent candidates for running on AWS, but the overhead of learning to do so and determining whether it is worth the cost can be prohibitive. In this paper we describe how to identify neuroimaging workloads that are appropriate for running on AWS, how to benchmark execution time, and how to estimate cost of running on AWS. By benchmarking common neuroimaging applications, we show that cloud computing can be a viable alternative to on-premises hardware. We present guidelines that neuroimaging labs can use to provide a cluster-on-demand type of service that should be familiar to users, and scripts to estimate cost and create such a cluster.

Classical hallucinogens and neuroimaging: A systematic review of human studies: Hallucinogens and neuroimaging.

PubMed

Dos Santos, Rafael G; Osório, Flávia L; Crippa, José Alexandre S; Hallak, Jaime E C

2016-12-01

Serotonergic hallucinogens produce alterations of perceptions, mood, and cognition, and have anxiolytic, antidepressant, and antiaddictive properties. These drugs act as agonists of frontocortical 5-HT 2A receptors, but the neural basis of their effects are not well understood. Thus, we conducted a systematic review of neuroimaging studies analyzing the effects of serotonergic hallucinogens in man. Studies published in the PubMed, Lilacs, and SciELO databases until 12 April 2016 were included using the following keywords: "ayahuasca", "DMT", "psilocybin", "LSD", "mescaline" crossed one by one with the terms "mri", "fmri", "pet", "spect", "imaging" and "neuroimaging". Of 279 studies identified, 25 were included. Acute effects included excitation of frontolateral/frontomedial cortex, medial temporal lobe, and occipital cortex, and inhibition of the default mode network. Long-term use was associated with thinning of the posterior cingulate cortex, thickening of the anterior cingulate cortex, and decreased neocortical 5-HT 2A receptor binding. Despite the high methodological heterogeneity and the small sample sizes, the results suggest that hallucinogens increase introspection and positive mood by modulating brain activity in the fronto-temporo-parieto-occipital cortex. Copyright © 2016 Elsevier Ltd. All rights reserved.

CBRAIN: a web-based, distributed computing platform for collaborative neuroimaging research

PubMed Central

Sherif, Tarek; Rioux, Pierre; Rousseau, Marc-Etienne; Kassis, Nicolas; Beck, Natacha; Adalat, Reza; Das, Samir; Glatard, Tristan; Evans, Alan C.

2014-01-01

The Canadian Brain Imaging Research Platform (CBRAIN) is a web-based collaborative research platform developed in response to the challenges raised by data-heavy, compute-intensive neuroimaging research. CBRAIN offers transparent access to remote data sources, distributed computing sites, and an array of processing and visualization tools within a controlled, secure environment. Its web interface is accessible through any modern browser and uses graphical interface idioms to reduce the technical expertise required to perform large-scale computational analyses. CBRAIN's flexible meta-scheduling has allowed the incorporation of a wide range of heterogeneous computing sites, currently including nine national research High Performance Computing (HPC) centers in Canada, one in Korea, one in Germany, and several local research servers. CBRAIN leverages remote computing cycles and facilitates resource-interoperability in a transparent manner for the end-user. Compared with typical grid solutions available, our architecture was designed to be easily extendable and deployed on existing remote computing sites with no tool modification, administrative intervention, or special software/hardware configuration. As October 2013, CBRAIN serves over 200 users spread across 53 cities in 17 countries. The platform is built as a generic framework that can accept data and analysis tools from any discipline. However, its current focus is primarily on neuroimaging research and studies of neurological diseases such as Autism, Parkinson's and Alzheimer's diseases, Multiple Sclerosis as well as on normal brain structure and development. This technical report presents the CBRAIN Platform, its current deployment and usage and future direction. PMID:24904400

Integration of a neuroimaging processing pipeline into a pan-canadian computing grid

NASA Astrophysics Data System (ADS)

Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.

2012-02-01

The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.

The 100 most-cited articles in neuroimaging: A bibliometric analysis.

PubMed

Kim, Hye Jeong; Yoon, Dae Young; Kim, Eun Soo; Lee, Kwanseop; Bae, Jong Seok; Lee, Ju-Hun

2016-10-01

The purpose of our study was to identify and characterize the 100 most-cited articles in neuroimaging. Based on the database of Journal Citation Reports, we selected 669 journals that were considered as potential outlets for neuroimaging articles. The Web of Science search tools were used to identify the 100 most-cited articles relevant to neuroimaging within the selected journals. The following information was recorded for each article: publication year, journal, category and impact factor of journal, number of citations, number of annual citations, authorship, department, institution, country, article type, imaging technique used, and topic. The 100 most-cited articles in neuroimaging were published between 1980 and 2012, with 1995-2004 producing 69 articles. Citations ranged from 4384 to 673 and annual citations ranged from 313.1 to 24.9. The majority of articles were published in radiology/imaging journals (n=75), originated in the United States (n=58), were original articles (n=63), used MRI as imaging modality (n=85), and dealt with imaging technique (n=45). The Oxford Centre for Functional Magnetic Resonance Imaging of the Brain at John Radcliffe Hospital (n=10) was the leading institutions and Karl J. Friston (n=11) was the most prolific author. Our study presents a detailed list and an analysis of the 100 most-cited articles in the field of neuroimaging, which provides an insight into historical developments and allows for recognition of the important advances in this field. Copyright © 2016 Elsevier Inc. All rights reserved.

Legionnaire's disease surveillance programme (initial survey analysis).

PubMed

O'Neill, K

1990-08-01

In Australia, approximately 150 cases of Legionnaire's Disease are reported annually. Untreated, the mortality rate is estimated at 20%. Australia's largest Legionnaire's Disease epidemic broke out in Wollongong (New South Wales) back in 1987, where some 45 cases required hospitalization and 10 of these died. Local Health Authorities have been advised to conduct initial surveys of their particular municipalities to locate all known water cooling towers and evaporative condensers to establish maintenance standards on such units to overcome possible future outbreaks of this disease with significant mortality.

Cardiac Complications, Earlier Treatment, and Initial Disease Severity in Kawasaki Disease.

PubMed

Abrams, Joseph Y; Belay, Ermias D; Uehara, Ritei; Maddox, Ryan A; Schonberger, Lawrence B; Nakamura, Yosikazu

2017-09-01

To assess if observed higher observed risks of cardiac complications for patients with Kawasaki disease (KD) treated earlier may reflect bias due to confounding from initial disease severity, as opposed to any negative effect of earlier treatment. We used data from Japanese nationwide KD surveys from 1997 to 2004. Receipt of additional intravenous immunoglobulin (IVIG) (data available all years) or any additional treatment (available for 2003-2004) were assessed as proxies for initial disease severity. We determined associations between earlier or later IVIG treatment (defined as receipt of IVIG on days 1-4 vs days 5-10 of illness) and cardiac complications by stratifying by receipt of additional treatment or by using logistic modeling to control for the effect of receiving additional treatment. A total of 48 310 patients with KD were included in the analysis. In unadjusted analysis, earlier IVIG treatment was associated with a higher risk for 4 categories of cardiac complications, including all major cardiac complications (risk ratio, 1.10; 95% CI, 1.06-1.15). Stratifying by receipt of additional treatment removed this association, and earlier IVIG treatment became protective against all major cardiac complications when controlling for any additional treatment in logistic regressions (OR, 0.90; 95% CI, 0.80-1.00). Observed higher risks of cardiac complications among patients with KD receiving IVIG treatment on days 1-4 of the illness are most likely due to underlying higher initial disease severity, and patients with KD should continue to be treated with IVIG as early as possible. Published by Elsevier Inc.

Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

PubMed

Gorgolewski, Krzysztof; Burns, Christopher D; Madison, Cindee; Clark, Dav; Halchenko, Yaroslav O; Waskom, Michael L; Ghosh, Satrajit S

2011-01-01

Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; http://nipy.org/nipype), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for

Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python

PubMed Central

Gorgolewski, Krzysztof; Burns, Christopher D.; Madison, Cindee; Clark, Dav; Halchenko, Yaroslav O.; Waskom, Michael L.; Ghosh, Satrajit S.

2011-01-01

Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; http://nipy.org/nipype), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for

Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?

PubMed Central

Madhyastha, Tara M.; Koh, Natalie; Day, Trevor K. M.; Hernández-Fernández, Moises; Kelley, Austin; Peterson, Daniel J.; Rajan, Sabreena; Woelfer, Karl A.; Wolf, Jonathan; Grabowski, Thomas J.

2017-01-01

The contribution of this paper is to identify and describe current best practices for using Amazon Web Services (AWS) to execute neuroimaging workflows “in the cloud.” Neuroimaging offers a vast set of techniques by which to interrogate the structure and function of the living brain. However, many of the scientists for whom neuroimaging is an extremely important tool have limited training in parallel computation. At the same time, the field is experiencing a surge in computational demands, driven by a combination of data-sharing efforts, improvements in scanner technology that allow acquisition of images with higher image resolution, and by the desire to use statistical techniques that stress processing requirements. Most neuroimaging workflows can be executed as independent parallel jobs and are therefore excellent candidates for running on AWS, but the overhead of learning to do so and determining whether it is worth the cost can be prohibitive. In this paper we describe how to identify neuroimaging workloads that are appropriate for running on AWS, how to benchmark execution time, and how to estimate cost of running on AWS. By benchmarking common neuroimaging applications, we show that cloud computing can be a viable alternative to on-premises hardware. We present guidelines that neuroimaging labs can use to provide a cluster-on-demand type of service that should be familiar to users, and scripts to estimate cost and create such a cluster. PMID:29163119

Clinical neuroimaging in the preterm infant: Diagnosis and prognosis.

PubMed

Hinojosa-Rodríguez, Manuel; Harmony, Thalía; Carrillo-Prado, Cristina; Van Horn, John Darrell; Irimia, Andrei; Torgerson, Carinna; Jacokes, Zachary

2017-01-01

Perinatal care advances emerging over the past twenty years have helped to diminish the mortality and severe neurological morbidity of extremely and very preterm neonates (e.g., cystic Periventricular Leukomalacia [c-PVL] and Germinal Matrix Hemorrhage - Intraventricular Hemorrhage [GMH-IVH grade 3-4/4]; 22 to < 32 weeks of gestational age, GA). However, motor and/or cognitive disabilities associated with mild-to-moderate white and gray matter injury are frequently present in this population (e.g., non-cystic Periventricular Leukomalacia [non-cystic PVL], neuronal-axonal injury and GMH-IVH grade 1-2/4). Brain research studies using magnetic resonance imaging (MRI) report that 50% to 80% of extremely and very preterm neonates have diffuse white matter abnormalities (WMA) which correspond to only the minimum grade of severity. Nevertheless, mild-to-moderate diffuse WMA has also been associated with significant affectations of motor and cognitive activities. Due to increased neonatal survival and the intrinsic characteristics of diffuse WMA, there is a growing need to study the brain of the premature infant using non-invasive neuroimaging techniques sensitive to microscopic and/or diffuse lesions. This emerging need has led the scientific community to try to bridge the gap between concepts or ideas from different methodologies and approaches; for instance, neuropathology, neuroimaging and clinical findings. This is evident from the combination of intense pre-clinical and clinicopathologic research along with neonatal neurology and quantitative neuroimaging research. In the following review, we explore literature relating the most frequently observed neuropathological patterns with the recent neuroimaging findings in preterm newborns and infants with perinatal brain injury. Specifically, we focus our discussions on the use of neuroimaging to aid diagnosis, measure morphometric brain damage, and track long-term neurodevelopmental outcomes.

Neuroimaging, a new tool for investigating the effects of early diet on cognitive and brain development

PubMed Central

Isaacs, Elizabeth B.

2013-01-01

Nutrition is crucial to the initial development of the central nervous system (CNS), and then to its maintenance, because both depend on dietary intake to supply the elements required to develop and fuel the system. Diet in early life is often seen in the context of “programming” where a stimulus occurring during a vulnerable period can have long-lasting or even lifetime effects on some aspect of the organism's structure or function. Nutrition was first shown to be a programming stimulus for growth, and then for cognitive behavior, in animal studies that were able to employ methods that allowed the demonstration of neural effects of early nutrition. Such research raised the question of whether nutrition could also programme cognition/brain structure in humans. Initial studies of cognitive effects were observational, usually conducted in developing countries where the presence of confounding factors made it difficult to interpret the role of nutrition in the cognitive deficits that were seen. Attributing causality to nutrition required randomized controlled trials (RCTs) and these, often in developed countries, started to appear around 30 years ago. Most demonstrated convincingly that early nutrition could affect subsequent cognition. Until the advent of neuroimaging techniques that allowed in vivo examination of the brain, however, we could determine very little about the neural effects of early diet in humans. The combination of well-designed trials with neuroimaging tools means that we are now able to pose and answer questions that would have seemed impossible only recently. This review discusses various neuroimaging methods that are suitable for use in nutrition studies, while pointing out some of the limitations that they may have. The existing literature is small, but examples of studies that have used these methods are presented. Finally, some considerations that have arisen from previous studies, as well as suggestions for future research, are discussed

Uncovering the etiology of conversion disorder: insights from functional neuroimaging

PubMed Central

Ejareh dar, Maryam; Kanaan, Richard AA

2016-01-01

Conversion disorder (CD) is a syndrome of neurological symptoms arising without organic cause, arguably in response to emotional stress, but the exact neural substrates of these symptoms and the underlying mechanisms remain poorly understood with the hunt for a biological basis afoot for centuries. In the past 15 years, novel insights have been gained with the advent of functional neuroimaging studies in patients suffering from CDs in both motor and nonmotor domains. This review summarizes recent functional neuroimaging studies including functional magnetic resonance imaging (fMRI), single photon emission computerized tomography (SPECT), and positron emission tomography (PET) to see whether they bring us closer to understanding the etiology of CD. Convergent functional neuroimaging findings suggest alterations in brain circuits that could point to different mechanisms for manifesting functional neurological symptoms, in contrast with feigning or healthy controls. Abnormalities in emotion processing and in emotion-motor processing suggest a diathesis, while differential reactions to certain stressors implicate a specific response to trauma. No comprehensive theory emerges from these clues, and all results remain preliminary, but functional neuroimaging has at least given grounds for hope that a model for CD may soon be found. PMID:26834476

Functional Neuroimaging in Psychopathy.

PubMed

Del Casale, Antonio; Kotzalidis, Georgios D; Rapinesi, Chiara; Di Pietro, Simone; Alessi, Maria Chiara; Di Cesare, Gianluigi; Criscuolo, Silvia; De Rossi, Pietro; Tatarelli, Roberto; Girardi, Paolo; Ferracuti, Stefano

2015-01-01

Psychopathy is associated with cognitive and affective deficits causing disruptive, harmful and selfish behaviour. These have considerable societal costs due to recurrent crime and property damage. A better understanding of the neurobiological bases of psychopathy could improve therapeutic interventions, reducing the related social costs. To analyse the major functional neural correlates of psychopathy, we reviewed functional neuroimaging studies conducted on persons with this condition. We searched the PubMed database for papers dealing with functional neuroimaging and psychopathy, with a specific focus on how neural functional changes may correlate with task performances and human behaviour. Psychopathy-related behavioural disorders consistently correlated with dysfunctions in brain areas of the orbitofrontal-limbic (emotional processing and somatic reaction to emotions; behavioural planning and responsibility taking), anterior cingulate-orbitofrontal (correct assignment of emotional valence to social stimuli; violent/aggressive behaviour and challenging attitude) and prefrontal-temporal-limbic (emotional stimuli processing/response) networks. Dysfunctional areas more consistently included the inferior frontal, orbitofrontal, dorsolateral prefrontal, ventromedial prefrontal, temporal (mainly the superior temporal sulcus) and cingulated cortices, the insula, amygdala, ventral striatum and other basal ganglia. Emotional processing and learning, and several social and affective decision-making functions are impaired in psychopathy, which correlates with specific changes in neural functions. © 2015 S. Karger AG, Basel.

Neuroimaging Data Sharing on the Neuroinformatics Database Platform

PubMed Central

Book, Gregory A; Stevens, Michael; Assaf, Michal; Glahn, David; Pearlson, Godfrey D

2015-01-01

We describe the Neuroinformatics Database (NiDB), an open-source database platform for archiving, analysis, and sharing of neuroimaging data. Data from the multi-site projects Autism Brain Imaging Data Exchange (ABIDE), Bipolar-Schizophrenia Network on Intermediate Phenotypes parts one and two (B-SNIP1, B-SNIP2), and Monetary Incentive Delay task (MID) are available for download from the public instance of NiDB, with more projects sharing data as it becomes available. As demonstrated by making several large datasets available, NiDB is an extensible platform appropriately suited to archive and distribute shared neuroimaging data. PMID:25888923

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Linking neuroimaging signals to behavioral responses in single cases: Challenges and opportunities.

PubMed

Sander, Tilmann H; Zhou, Bin

2016-09-01

Despite rapid progress both in psychology and neuroimaging, there is still a convergence gap between the results of these two scientific disciplines. This is particularly unsatisfactory, as the variability between single subjects needs to be understood both for basic science and for patient diagnostics in, for example, the field of age-related cognitive changes. Active and passive behaviors are the observables in psychology and can be studied alone or in combination with the neuroimaging approach. Various physical signatures of brain activity are the observables in neuroimaging and can be measured concurrent with behaviors. Despite the intrinsic relationship between behaviors and the corresponding neuroimaging patterns and the obvious advantages in integrating behavioral and neuroimaging measurements, the results of combined studies can be difficult to interpret. Experiments are often optimized to yield either a novel behavioral or a novel physiological result, but rarely designed for a better match between the two. Since integrating the results is probably a key to future progress in clinical psychology and basic research, an attempt is made here to identify some difficulties and to provide some ideas for future research. © 2016 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis

PubMed Central

2011-01-01

Background A variety of neuroimaging software packages have been released from various laboratories worldwide, and many researchers use these packages in combination. Though most of these software packages are freely available, some people find them difficult to install and configure because they are mostly based on UNIX-like operating systems. We developed a live USB-bootable Linux package named "Lin4Neuro." This system includes popular neuroimaging analysis tools. The user interface is customized so that even Windows users can use it intuitively. Results The boot time of this system was only around 40 seconds. We performed a benchmark test of inhomogeneity correction on 10 subjects of three-dimensional T1-weighted MRI scans. The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive. We also installed Lin4Neuro on a virtualization software package that emulates the Linux environment on a Windows-based operation system. Although the processing speed was slower than that under other conditions, it remained comparable. Conclusions With Lin4Neuro in one's hand, one can access neuroimaging software packages easily, and immediately focus on analyzing data. Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis. It also provides a practical means of sharing analysis environments across sites. PMID:21266047

Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis.

PubMed

Nemoto, Kiyotaka; Dan, Ippeita; Rorden, Christopher; Ohnishi, Takashi; Tsuzuki, Daisuke; Okamoto, Masako; Yamashita, Fumio; Asada, Takashi

2011-01-25

A variety of neuroimaging software packages have been released from various laboratories worldwide, and many researchers use these packages in combination. Though most of these software packages are freely available, some people find them difficult to install and configure because they are mostly based on UNIX-like operating systems. We developed a live USB-bootable Linux package named "Lin4Neuro." This system includes popular neuroimaging analysis tools. The user interface is customized so that even Windows users can use it intuitively. The boot time of this system was only around 40 seconds. We performed a benchmark test of inhomogeneity correction on 10 subjects of three-dimensional T1-weighted MRI scans. The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive. We also installed Lin4Neuro on a virtualization software package that emulates the Linux environment on a Windows-based operation system. Although the processing speed was slower than that under other conditions, it remained comparable. With Lin4Neuro in one's hand, one can access neuroimaging software packages easily, and immediately focus on analyzing data. Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis. It also provides a practical means of sharing analysis environments across sites.

Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

PubMed Central

Jie, Biao; Gao, Wei; Wang, Qian; Wee, Chong-Yaw

2014-01-01

Rapid advances in neuroimaging techniques have provided an efficient and noninvasive way for exploring the structural and functional connectivity of the human brain. Quantitative measurement of abnormality of brain connectivity in patients with neurodegenerative diseases, such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD), have also been widely reported, especially at a group level. Recently, machine learning techniques have been applied to the study of AD and MCI, i.e., to identify the individuals with AD/MCI from the healthy controls (HCs). However, most existing methods focus on using only a single property of a connectivity network, although multiple network properties, such as local connectivity and global topological properties, can potentially be used. In this paper, by employing multikernel based approach, we propose a novel connectivity based framework to integrate multiple properties of connectivity network for improving the classification performance. Specifically, two different types of kernels (i.e., vector-based kernel and graph kernel) are used to quantify two different yet complementary properties of the network, i.e., local connectivity and global topological properties. Then, multikernel learning (MKL) technique is adopted to fuse these heterogeneous kernels for neuroimaging classification. We test the performance of our proposed method on two different data sets. First, we test it on the functional connectivity networks of 12 MCI and 25 HC subjects. The results show that our method achieves significant performance improvement over those using only one type of network property. Specifically, our method achieves a classification accuracy of 91.9%, which is 10.8% better than those by single network-property-based methods. Then, we test our method for gender classification on a large set of functional connectivity networks with 133 infants scanned at birth, 1 year, and 2 years, also demonstrating very promising results. PMID

Brain glucose metabolism during hypoglycemia in type 1 diabetes: insights from functional and metabolic neuroimaging studies.

PubMed

Rooijackers, Hanne M M; Wiegers, Evita C; Tack, Cees J; van der Graaf, Marinette; de Galan, Bastiaan E

2016-02-01

Hypoglycemia is the most frequent complication of insulin therapy in patients with type 1 diabetes. Since the brain is reliant on circulating glucose as its main source of energy, hypoglycemia poses a threat for normal brain function. Paradoxically, although hypoglycemia commonly induces immediate decline in cognitive function, long-lasting changes in brain structure and cognitive function are uncommon in patients with type 1 diabetes. In fact, recurrent hypoglycemia initiates a process of habituation that suppresses hormonal responses to and impairs awareness of subsequent hypoglycemia, which has been attributed to adaptations in the brain. These observations sparked great scientific interest into the brain's handling of glucose during (recurrent) hypoglycemia. Various neuroimaging techniques have been employed to study brain (glucose) metabolism, including PET, fMRI, MRS and ASL. This review discusses what is currently known about cerebral metabolism during hypoglycemia, and how findings obtained by functional and metabolic neuroimaging techniques contributed to this knowledge.

[Recent progress of neuroimaging studies on sleeping brain].

PubMed

Sasaki, Yuka

2012-06-01

Although sleep is a familiar phenomenon, its functions are yet to be elucidated. Understanding these functions of sleep is an important focus area in neuroscience. Electroencephalography (EEG) has been the predominantly used method in human sleep research but does not provide detailed spatial information about brain activation during sleep. To supplement the spatial information provided by this method, researchers have started using a combination of EEG and various advanced neuroimaging techniques that have been recently developed, including positron emission tomography (PET) and magnetic resonance imaging (MRI). In this paper, we will review the recent progress in sleep studies, especially studies that have used such advanced neuroimaging techniques. First, we will briefly introduce several neuroimaging techniques available for use in sleep studies. Next, we will review the spatiotemporal brain activation patterns during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep, the dynamics of functional connectivity during sleep, and the consolidation of learning and memory during sleep; studies on the neural correlates of dreams, which have not yet been identified, will also be discussed. Lastly, possible directions for future research in this area will be discussed.

Neuroimaging correlates of aggression in schizophrenia: an update.

PubMed

Hoptman, Matthew J; Antonius, Daniel

2011-03-01

Aggression in schizophrenia is associated with poor treatment outcomes, hospital admissions, and stigmatization of patients. As such it represents an important public health issue. This article reviews recent neuroimaging studies of aggression in schizophrenia, focusing on PET/single photon emission computed tomography and MRI methods. The neuroimaging literature on aggression in schizophrenia is in a period of development. This is attributable in part to the heterogeneous nature and basis of that aggression. Radiological methods have consistently shown reduced activity in frontal and temporal regions. MRI brain volumetric studies have been less consistent, with some studies finding increased volumes of inferior frontal structures, and others finding reduced volumes in aggressive individuals with schizophrenia. Functional MRI studies have also had inconsistent results, with most finding reduced activity in inferior frontal and temporal regions, but some also finding increased activity in other regions. Some studies have made a distinction between types of aggression in schizophrenia in the context of antisocial traits, and this appears to be useful in understanding the neuroimaging literature. Frontal and temporal abnormalities appear to be a consistent feature of aggression in schizophrenia, but their precise nature likely differs because of the heterogeneous nature of that behavior.

Spinal Cord Lesions in Congenital Toxoplasmosis Demonstrated with Neuroimaging, Including Their Successful Treatment in an Adult.

PubMed

Burrowes, Delilah; Boyer, Kenneth; Swisher, Charles N; Noble, A Gwendolyn; Sautter, Mari; Heydemann, Peter; Rabiah, Peter; Lee, Daniel; McLeod, Rima

2012-03-01

Neuroimaging studies for persons in the National Collaborative Chicago-Based Congenital Toxoplasmosis Study (NCCCTS) with symptoms and signs referable to the spinal cord were reviewed. Three infants had symptomatic spinal cord lesions, another infant a Chiari malformation, and another infant a symptomatic peri-spinal cord lipoma. One patient had an unusual history of prolonged spinal cord symptoms presenting in middle age. Neuroimaging was used to establish her diagnosis and response to treatment. This 43 year-old woman with congenital toxoplasmosis developed progressive leg spasticity, weakness, numbness, difficulty walking, and decreased visual acuity and color vision without documented re-activation of her chorioretinal disease. At 52 years of age, spinal cord lesions in locations correlating with her symptoms and optic atrophy were diagnosed with 3 Tesla MRI scan. Treatment with pyrimethamine and sulfadiazine decreased her neurologic symptoms, improved her neurologic examination, and resolved her enhancing spinal cord lesions seen on MRI.

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

Robust regression for large-scale neuroimaging studies.

PubMed

Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

2015-05-01

Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Survival after initial diagnosis of Alzheimer disease.

PubMed

Larson, Eric B; Shadlen, Marie-Florence; Wang, Li; McCormick, Wayne C; Bowen, James D; Teri, Linda; Kukull, Walter A

2004-04-06

Alzheimer disease is an increasingly common condition in older people. Knowledge of life expectancy after the diagnosis of Alzheimer disease and of associations of patient characteristics with survival may help planning for future care. To investigate the course of Alzheimer disease after initial diagnosis and examine associations hypothesized to correlate with survival among community-dwelling patients with Alzheimer disease. Prospective observational study. An Alzheimer disease patient registry from a base population of 23 000 persons age 60 years and older in the Group Health Cooperative, Seattle, Washington. 521 newly recognized persons with Alzheimer disease enrolled from 1987 to 1996 in an Alzheimer disease patient registry. Baseline measurements included patient demographic features, Mini-Mental State Examination score, Blessed Dementia Rating Scale score, duration since reported onset of symptoms, associated symptoms, comorbid conditions, and selected signs. Survival was the outcome of interest. The median survival from initial diagnosis was 4.2 years for men and 5.7 years for women with Alzheimer disease. Men had poorer survival across all age groups compared with females. Survival was decreased in all age groups compared with the life expectancy of the U.S. population. Predictors of mortality based on proportional hazards models included a baseline Mini-Mental State Examination score of 17 or less, baseline Blessed Dementia Rating Scale score of 5.0 or greater, presence of frontal lobe release signs, presence of extrapyramidal signs, gait disturbance, history of falls, congestive heart failure, ischemic heart disease, and diabetes at baseline. The base population, although typical of the surrounding Seattle community, may not be representative of other, more diverse populations. In this sample of community-dwelling elderly persons who received a diagnosis of Alzheimer disease, survival duration was shorter than predicted on the basis of U.S. population

Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer's disease patients.

PubMed

Son, Seong-Jin; Kim, Jonghoon; Park, Hyunjin

2017-01-01

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer's disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint.

Neuroimaging and Anxiety: the Neural Substrates of Pathological and Non-pathological Anxiety.

PubMed

Taylor, James M; Whalen, Paul J

2015-06-01

Advances in the use of noninvasive neuroimaging to study the neural correlates of pathological and non-pathological anxiety have shone new light on the underlying neural bases for both the development and manifestation of anxiety. This review summarizes the most commonly observed neural substrates of the phenotype of anxiety. We focus on the neuroimaging paradigms that have shown promise in exposing this relevant brain circuitry. In this way, we offer a broad overview of how anxiety is studied in the neuroimaging laboratory and the key findings that offer promise for future research and a clearer understanding of anxiety.

Reading the Freudian theory of sexual drives from a functional neuroimaging perspective

PubMed Central

Stoléru, Serge

2014-01-01

One of the essential tasks of neuropsychoanalysis is to investigate the neural correlates of sexual drives. Here, we consider the four defining characteristics of sexual drives as delineated by Freud: their pressure, aim, object, and source. We systematically examine the relations between these characteristics and the four-component neurophenomenological model that we have proposed based on functional neuroimaging studies, which comprises a cognitive, a motivational, an emotional and an autonomic/neuroendocrine component. Functional neuroimaging studies of sexual arousal (SA) have thrown a new light on the four fundamental characteristics of sexual drives by identifying their potential neural correlates. While these studies are essentially consistent with the Freudian model of drives, the main difference emerging between the functional neuroimaging perspective on sexual drives and the Freudian theory relates to the source of drives. From a functional neuroimaging perspective, sources of sexual drives, conceived by psychoanalysis as processes of excitation occurring in a peripheral organ, do not seem, at least in adult subjects, to be an essential part of the determinants of SA. It is rather the central processing of visual or genital stimuli that gives to these stimuli their sexually arousing and sexually pleasurable character. Finally, based on functional neuroimaging results, some possible improvements to the psychoanalytic theory of sexual drives are suggested. PMID:24672467

Red flag findings in children with headaches: Prevalence and association with emergency department neuroimaging.

PubMed

Tsze, Daniel S; Ochs, Julie B; Gonzalez, Ariana E; Dayan, Peter S

2018-01-01

Background Clinicians appear to obtain emergent neuroimaging for children with headaches based on the presence of red flag findings. However, little data exists regarding the prevalence of these findings in emergency department populations, and whether the identification of red flag findings is associated with potentially unnecessary emergency department neuroimaging. Objectives We aimed to determine the prevalence of red flag findings and their association with neuroimaging in otherwise healthy children presenting with headaches to the emergency department. Our secondary aim was to determine the prevalence of emergent intracranial abnormalities in this population. Methods A prospective cohort study of otherwise healthy children 2-17 years of age presenting to an urban pediatric emergency department with non-traumatic headaches was undertaken. Emergency department physicians completed a standardized form to document headache descriptors and characteristics, associated symptoms, and physical and neurological exam findings. Children who did not receive emergency department neuroimaging received 4-month telephone follow-up. Outcomes included emergency department neuroimaging and the presence of emergent intracranial abnormalities. Results We enrolled 224 patients; 197 (87.9%) had at least one red flag finding on history. Several red flag findings were reported by more than a third of children, including: Headache waking from sleep (34.8%); headache present with or soon after waking (39.7%); or headaches increasing in frequency, duration and severity (40%, 33.1%, and 46.3%). Thirty-three percent of children received emergency department neuroimaging. The prevalence of emergent intracranial abnormalities was 1% (95% CI 0.1, 3.6). Abnormal neurological exam, extreme pain intensity of presenting headache, vomiting, and positional symptoms were independently associated with emergency department neuroimaging. Conclusions Red flag findings are common in children presenting

Energy landscape analysis of neuroimaging data

NASA Astrophysics Data System (ADS)

Ezaki, Takahiro; Watanabe, Takamitsu; Ohzeki, Masayuki; Masuda, Naoki

2017-05-01

Computational neuroscience models have been used for understanding neural dynamics in the brain and how they may be altered when physiological or other conditions change. We review and develop a data-driven approach to neuroimaging data called the energy landscape analysis. The methods are rooted in statistical physics theory, in particular the Ising model, also known as the (pairwise) maximum entropy model and Boltzmann machine. The methods have been applied to fitting electrophysiological data in neuroscience for a decade, but their use in neuroimaging data is still in its infancy. We first review the methods and discuss some algorithms and technical aspects. Then, we apply the methods to functional magnetic resonance imaging data recorded from healthy individuals to inspect the relationship between the accuracy of fitting, the size of the brain system to be analysed and the data length. This article is part of the themed issue `Mathematical methods in medicine: neuroscience, cardiology and pathology'.

Brain imaging and cognitive dysfunctions in Huntington's disease

PubMed Central

Montoya, Alonso; Price, Bruce H.; Menear, Matthew; Lepage, Martin

2006-01-01

Recent decades have seen tremendous growth in our understanding of the cognitive dysfunctions observed in Huntington's disease (HD). Advances in neuroimaging have contributed greatly to this growth. We reviewed the role that structural and functional neuroimaging techniques have played in elucidating the cerebral bases of the cognitive deficits associated with HD. We conducted a computer-based search using PubMed and PsycINFO databases to retrieve studies of patients with HD published between 1965 and December 2004 that reported measures on cognitive tasks and used neuroimaging techniques. Structural neuroimaging has provided important evidence of morphological brain changes in HD. Striatal and cortical atrophy are the most common findings, and they correlate with cognitive deficits in attention, working memory and executive functions. Functional studies have also demonstrated correlations between striatal dysfunction and cognitive performance. Striatal hypoperfusion and decreased glucose utilization correlate with executive dysfunction. Hypometabolism also occurs throughout the cerebral cortex and correlates with performance on recognition memory, language and perceptual tests. Measures of presynaptic and postsynaptic dopamine biochemistry have also correlated with measurements of episodic memory, speed of processing and executive functioning. Aided by the results of numerous neuroimaging studies, it is becoming increasingly clear that cognitive deficits in HD involve abnormal connectivity between the basal ganglia and cortical areas. In the future, neuroimaging techniques may shed the most light on the pathophysiology of HD by defining neurodegenerative disease phenotypes as a valuable tool for knowing when patients become “symptomatic,” having been in a gene-positive presymptomatic state, and as a biomarker in following the disease, thereby providing a prospect for improved patient care. PMID:16496032

Translational Immunoimaging and Neuroimaging Demonstrate Corneal Neuroimmune Crosstalk.

PubMed

Hamrah, Pedram; Seyed-Razavi, Yashar; Yamaguchi, Takefumi

2016-11-01

Corneal immunoimaging and neuroimaging approaches facilitate in vivo analyses of the cornea, including high-resolution imaging of corneal immune cells and nerves. This approach facilitates the analyses of underlying immune and nerve alterations not detected by clinical slit-lamp examination alone. In this review, we describe recent work performed in our translational ocular immunology center with a focus on "bench-to-bedside" and "bedside-to-bench" research. The ability to visualize dendritiform immune cells (DCs) in patients with laser in vivo confocal microscopy (IVCM), recently discovered in the central murine cornea, has allowed us to demonstrate their utility as a potential surrogate biomarker for inflammatory ocular surface diseases. This biomarker for inflammation allows the measurement of therapeutic efficacy of anti-inflammatory drugs and its utility as an endpoint in clinical trials with high interobserver agreement. IVCM image analyses from our studies has demonstrated a significant increase in DC density and size in ocular disease, a positive correlation between DC density and clinical signs and symptoms of disease and pro-inflammatory tear cytokines, and a strong negative correlation between DC density and subbasal nerve density. In conjunction with preclinical research investigating the inflammatory state in a partial or fully denervated cornea, our results indicated that corneal nerves are directly involved in the regulation of homeostasis and immune privilege in the cornea.

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients

PubMed Central

Son, Seong-Jin; Kim, Jonghoon

2017-01-01

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer’s disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint. PMID:28333946

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

PubMed

Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

Towards a model-based cognitive neuroscience of stopping - a neuroimaging perspective.

PubMed

Sebastian, Alexandra; Forstmann, Birte U; Matzke, Dora

2018-07-01

Our understanding of the neural correlates of response inhibition has greatly advanced over the last decade. Nevertheless the specific function of regions within this stopping network remains controversial. The traditional neuroimaging approach cannot capture many processes affecting stopping performance. Despite the shortcomings of the traditional neuroimaging approach and a great progress in mathematical and computational models of stopping, model-based cognitive neuroscience approaches in human neuroimaging studies are largely lacking. To foster model-based approaches to ultimately gain a deeper understanding of the neural signature of stopping, we outline the most prominent models of response inhibition and recent advances in the field. We highlight how a model-based approach in clinical samples has improved our understanding of altered cognitive functions in these disorders. Moreover, we show how linking evidence-accumulation models and neuroimaging data improves the identification of neural pathways involved in the stopping process and helps to delineate these from neural networks of related but distinct functions. In conclusion, adopting a model-based approach is indispensable to identifying the actual neural processes underlying stopping. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Incidental Findings in Neuroimaging: Ethical and Medicolegal Considerations

PubMed Central

Leung, Lawrence

2013-01-01

With the rapid advances in neurosciences in the last three decades, there has been an exponential increase in the use of neuroimaging both in basic sciences and clinical research involving human subjects. During routine neuroimaging, incidental findings that are not part of the protocol or scope of research agenda can occur and they often pose a challenge as to how they should be handled to abide by the medicolegal principles of research ethics. This paper reviews the issue from various ethical (do no harm, general duty to rescue, and mutual benefits and owing) and medicolegal perspectives (legal liability, fiduciary duties, Law of Tort, and Law of Contract) with a suggested protocol of approach. PMID:26317093

Incidental Findings in Neuroimaging: Ethical and Medicolegal Considerations.

PubMed

Leung, Lawrence

2013-01-01

With the rapid advances in neurosciences in the last three decades, there has been an exponential increase in the use of neuroimaging both in basic sciences and clinical research involving human subjects. During routine neuroimaging, incidental findings that are not part of the protocol or scope of research agenda can occur and they often pose a challenge as to how they should be handled to abide by the medicolegal principles of research ethics. This paper reviews the issue from various ethical (do no harm, general duty to rescue, and mutual benefits and owing) and medicolegal perspectives (legal liability, fiduciary duties, Law of Tort, and Law of Contract) with a suggested protocol of approach.

Genetic Testing and Neuroimaging: Trading off Benefit and Risk for Youth with Mental Illness

PubMed Central

Lee, Grace; Mizgalewicz, Ania; Borgelt, Emily; Illes, Judy

2015-01-01

According to the World Health Organization, mental illness is one of the leading causes of disability worldwide. The first onset of mental illness usually occurs during childhood or adolescence. Neuroimaging and genetic testing have been invaluable in research on behavioral and intentional disorders, particularly with their potential to lead to improved diagnostic and predictive capabilities and to decrease the associated burdens of disease. The present study focused specifically the perspectives of mental health providers on the role of neuroimaging and genetic testing in clinical practice with children and adolescents. We interviewed 38 psychiatrists, psychologists, and allied mental health professionals who work primarily with youth about their receptivity towards either the use of neuroimaging or genetic testing. Interviews probed the role they foresee for these modalities for prediction, diagnosis, and treatment planning, and the benefits and risks they anticipate. Practitioners anticipated three major benefits associated with clinical introduction of imaging and genetic testing in the mental health care for youth: (1) improved understanding of illness, (2) more accurate diagnosis than available through conventional clinical examination, and (3) validation of treatment plans. They also perceived three major risks: (1) potential adverse impacts on employment and insurance as adolescents reach adulthood, (2) misuse or misinterpretation of the imaging or genetic data, and (3) infringements on self-esteem or self-motivation. Movement of brain imaging and genetic testing into clinical care will require a delicate balance of biology and respect for autonomy in the still-evolving cognitive and affective world of young individuals. PMID:26949737

Genetic Testing and Neuroimaging for Youth at Risk for Mental Illness: Trading off Benefit and Risk.

PubMed

Lee, Grace; Mizgalewicz, Ania; Borgelt, Emily; Illes, Judy

2015-01-01

According to the World Health Organization, mental illness is one of the leading causes of disability worldwide. The first onset of mental illness usually occurs during childhood or adolescence, with nearly 12 million diagnosed cases in the United States alone. Neuroimaging and genetic testing have been invaluable in research on behavioral, affective, and attentional disorders, particularly with their potential predictive capabilities, and ability to improve diagnosis and to decrease the associated burdens of disease. The present study focused specifically the perspectives of mental health providers on the role of neuroimaging and genetic testing in clinical practice with children and adolescents. We interviewed 38 psychiatrists, psychologists, and allied mental health professionals who work primarily with youth about their receptivity toward either the use of neuroimaging or genetic testing. Interviews probed the role they foresee for these modalities for prediction, diagnosis, treatment planning, and the benefits and risks they anticipate. Practitioners anticipated three major benefits associated with clinical introduction of imaging and genetic testing in the mental health care for youth: (1) improved understanding of the brain and mental illness, (2) more accurate diagnosis than available through conventional clinical examination, and (3) legitimization of treatment plans. They also perceived three major risks: (1) misuse or misinterpretation of the imaging or genetic data, (2) potential adverse impacts on employment and insurance as adolescents reach adulthood, and (3) infringements on self-esteem or self-motivation. The nature of the interview questions focused on the future of neuroimaging and genetic testing testing research in the context of clinical neuroscience. Therefore, the responses from interview participants are based on anticipated rather than actual experience. Continued expansion of brain imaging and genetic testing into clinical care will

Neuroimaging of Pain: Human Evidence and Clinical Relevance of Central Nervous System Processes and Modulation.

PubMed

Martucci, Katherine T; Mackey, Sean C

2018-06-01

Neuroimaging research has demonstrated definitive involvement of the central nervous system in the development, maintenance, and experience of chronic pain. Structural and functional neuroimaging has helped elucidate central nervous system contributors to chronic pain in humans. Neuroimaging of pain has provided a tool for increasing our understanding of how pharmacologic and psychologic therapies improve chronic pain. To date, findings from neuroimaging pain research have benefitted clinical practice by providing clinicians with an educational framework to discuss the biopsychosocial nature of pain with patients. Future advances in neuroimaging-based therapeutics (e.g., transcranial magnetic stimulation, real-time functional magnetic resonance imaging neurofeedback) may provide additional benefits for clinical practice. In the future, with standardization and validation, brain imaging could provide objective biomarkers of chronic pain, and guide treatment for personalized pain management. Similarly, brain-based biomarkers may provide an additional predictor of perioperative prognoses.

Neuroimaging Insights into the Pathophysiology of Sleep Disorders

PubMed Central

Desseilles, Martin; Dang-Vu, Thanh; Schabus, Manuel; Sterpenich, Virginie; Maquet, Pierre; Schwartz, Sophie

2008-01-01

Neuroimaging methods can be used to investigate whether sleep disorders are associated with specific changes in brain structure or regional activity. However, it is still unclear how these new data might improve our understanding of the pathophysiology underlying adult sleep disorders. Here we review functional brain imaging findings in major intrinsic sleep disorders (i.e., idiopathic insomnia, narcolepsy, and obstructive sleep apnea) and in abnormal motor behavior during sleep (i.e., periodic limb movement disorder and REM sleep behavior disorder). The studies reviewed include neuroanatomical assessments (voxel-based morphometry, magnetic resonance spectroscopy), metabolic/functional investigations (positron emission tomography, single photon emission computed tomography, functional magnetic resonance imaging), and ligand marker measurements. Based on the current state of the research, we suggest that brain imaging is a useful approach to assess the structural and functional correlates of sleep impairments as well as better understand the cerebral consequences of various therapeutic approaches. Modern neuroimaging techniques therefore provide a valuable tool to gain insight into possible pathophysiological mechanisms of sleep disorders in adult humans. Citation: Desseilles M; Dang-Vu TD; Schabus M; Sterpenich V; Maquet P; Schwartz S. Neuroimaging insights into the pathophysiology of sleep disorders. SLEEP 2008;31(6):777–794. PMID:18548822

Neuroimaging Findings of Zika Virus-Associated Neurologic Complications in Adults.

PubMed

Hygino da Cruz, L C; Nascimento, O J M; Lopes, F P P L; da Silva, I R F

2018-05-17

When the first suspected cases of neurologic disorders associated with the Zika virus were noticed in Brazil in late 2015, several studies had been conducted to understand the pathophysiology of the disease and its associated complications. In addition to its well-established association with microcephaly in neonates, the Zika virus infection has also been suggested to trigger other severe neurologic complications in adults, such as Guillain-Barré syndrome, radiculomyelitis, and meningoencephalitis. Hence, the Zika virus should be deemed a global threat that can cause devastating neurologic complications among individuals in all age ranges. The aim of this review was to further describe neuroimaging findings of Zika virus infection and associated neurologic complications found in adults. © 2018 by American Journal of Neuroradiology.

Sharing brain mapping statistical results with the neuroimaging data model

PubMed Central

Maumet, Camille; Auer, Tibor; Bowring, Alexander; Chen, Gang; Das, Samir; Flandin, Guillaume; Ghosh, Satrajit; Glatard, Tristan; Gorgolewski, Krzysztof J.; Helmer, Karl G.; Jenkinson, Mark; Keator, David B.; Nichols, B. Nolan; Poline, Jean-Baptiste; Reynolds, Richard; Sochat, Vanessa; Turner, Jessica; Nichols, Thomas E.

2016-01-01

Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html. PMID:27922621

MULTI-SOURCE FEATURE LEARNING FOR JOINT ANALYSIS OF INCOMPLETE MULTIPLE HETEROGENEOUS NEUROIMAGING DATA

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2012-01-01

Analysis of incomplete data is a big challenge when integrating large-scale brain imaging datasets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. In this paper, we address this problem by proposing an incomplete Multi-Source Feature (iMSF) learning method where all the samples (with at least one available data source) can be used. To illustrate the proposed approach, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 NC), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithm. Depending on the problem being solved, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. To build a practical and robust system, we construct a classifier ensemble by combining our method with four other methods for missing value estimation. Comprehensive experiments with various parameters show that our proposed iMSF method and the ensemble model yield stable and promising results. PMID:22498655

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

PubMed Central

Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

Evaluation of multi-modal, multi-site neuroimaging measures in Huntington's disease: Baseline results from the PADDINGTON study☆

PubMed Central

Hobbs, Nicola Z.; Cole, James H.; Farmer, Ruth E.; Rees, Elin M.; Crawford, Helen E.; Malone, Ian B.; Roos, Raymund A.C.; Sprengelmeyer, Reiner; Durr, Alexandra; Landwehrmeyer, Bernhard; Scahill, Rachael I.; Tabrizi, Sarah J.; Frost, Chris

2012-01-01

Background Macro- and micro-structural neuroimaging measures provide valuable information on the pathophysiology of Huntington's disease (HD) and are proposed as biomarkers. Despite theoretical advantages of microstructural measures in terms of sensitivity to pathology, there is little evidence directly comparing the two. Methods 40 controls and 61 early HD subjects underwent 3 T MRI (T1- and diffusion-weighted), as part of the PADDINGTON study. Macrostructural volumetrics were obtained for the whole brain, caudate, putamen, corpus callosum (CC) and ventricles. Microstructural diffusion metrics of fractional anisotropy (FA), mean-, radial- and axial-diffusivity (MD, RD, AD) were computed for white matter (WM), CC, caudate and putamen. Group differences were examined adjusting for age, gender and site. A formal comparison of effect sizes determined which modality and metrics provided a statistically significant advantage over others. Results Macrostructural measures showed decreased regional and global volume in HD (p < 0.001); except the ventricles which were enlarged (p < 0.01). In HD, FA was increased in the deep grey-matter structures (p < 0.001), and decreased in the WM (CC, p = 0.035; WM, p = 0.053); diffusivity metrics (MD, RD, AD) were increased for all brain regions (p < 0.001). The largest effect sizes were for putamen volume, caudate volume and putamen diffusivity (AD, RD and MD); each was significantly larger than those for all other metrics (p < 0.05). Conclusion The highest performing macro- and micro-structural metrics had similar sensitivity to HD pathology quantified via effect sizes. Region-of-interest may be more important than imaging modality, with deep grey-matter regions outperforming the CC and global measures, for both volume and diffusivity. FA appears to be relatively insensitive to disease effects. PMID:24179770

High-throughput neuroimaging-genetics computational infrastructure

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

2014-01-01

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize

Functional Neuro-Imaging and Post-Traumatic Olfactory Impairment

PubMed Central

Roberts, Richard J.; Sheehan, William; Thurber, Steven; Roberts, Mary Ann

2010-01-01

Objective: To evaluate via a research literature survey the anterior neurological significance of decreased olfactory functioning following traumatic brain injuries. Materials and Methods: A computer literature review was performed to locate all functional neuro-imaging studies on patients with post-traumatic anosmia and other olfactory deficits. Results: A convergence of findings from nine functional neuro-imaging studies indicating evidence for reduced metabolic activity at rest or relative hypo-perfusion during olfactory activations. Hypo-activation of the prefrontal regions was apparent in all nine post-traumatic samples, with three samples yielding evidence of reduced activity in the temporal regions as well. Conclusions: The practical ramifications include the reasonable hypothesis that a total anosmic head trauma patient likely has frontal lobe involvement. PMID:21716782

Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications.

PubMed

Goldstein, Rita Z; Volkow, Nora D

2011-10-20

The loss of control over drug intake that occurs in addiction was initially believed to result from disruption of subcortical reward circuits. However, imaging studies in addictive behaviours have identified a key involvement of the prefrontal cortex (PFC) both through its regulation of limbic reward regions and its involvement in higher-order executive function (for example, self-control, salience attribution and awareness). This Review focuses on functional neuroimaging studies conducted in the past decade that have expanded our understanding of the involvement of the PFC in drug addiction. Disruption of the PFC in addiction underlies not only compulsive drug taking but also accounts for the disadvantageous behaviours that are associated with addiction and the erosion of free will.

Using neuroimaging to understand the cortical mechanisms of auditory selective attention

PubMed Central

Lee, Adrian KC; Larson, Eric; Maddox, Ross K; Shinn-Cunningham, Barbara G

2013-01-01

Over the last four decades, a range of different neuroimaging tools have been used to study human auditory attention, spanning from classic event-related potential studies using electroencephalography to modern multimodal imaging approaches (e.g., combining anatomical information based on magnetic resonance imaging with magneto- and electroencephalography). This review begins by exploring the different strengths and limitations inherent to different neuroimaging methods, and then outlines some common behavioral paradigms that have been adopted to study auditory attention. We argue that in order to design a neuroimaging experiment that produces interpretable, unambiguous results, the experimenter must not only have a deep appreciation of the imaging technique employed, but also a sophisticated understanding of perception and behavior. Only with the proper caveats in mind can one begin to infer how the cortex supports a human in solving the “cocktail party” problem. PMID:23850664

Neuroimaging the interaction of mind and metabolism in humans

PubMed Central

D’Agostino, Alexandra E.; Small, Dana M.

2012-01-01

Hormonal and metabolic signals interact with neural circuits orchestrating behavior to guide food intake. Neuroimaging techniques such as functional magnetic resonance imaging (fMRI) enable the identification of where in the brain particular mental processes like desire, satiety and pleasure occur. Once these neural circuits are described it then becomes possible to determine how metabolic and hormonal signals can alter brain response to influence psychological states and decision-making processes to guide intake. Here, we provide an overview of the contributions of functional neuroimaging to the understanding of how subjective and neural responses to food and food cues interact with metabolic/hormonal factors. PMID:24024114

Brain mapping in cognitive disorders: a multidisciplinary approach to learning the tools and applications of functional neuroimaging

PubMed Central

Kelley, Daniel J; Johnson, Sterling C

2007-01-01

Background With rapid advances in functional imaging methods, human studies that feature functional neuroimaging techniques are increasing exponentially and have opened a vast arena of new possibilities for understanding brain function and improving the care of patients with cognitive disorders in the clinical setting. There is a growing need for medical centers to offer clinically relevant functional neuroimaging courses that emphasize the multifaceted and multidisciplinary nature of this field. In this paper, we describe the implementation of a functional neuroimaging course focusing on cognitive disorders that might serve as a model for other medical centers. We identify key components of an active learning course design that impact student learning gains in methods and issues pertaining to functional neuroimaging that deserve consideration when optimizing the medical neuroimaging curriculum. Methods Learning gains associated with the course were assessed using polychoric correlation analysis of responses to the SALG (Student Assessment of Learning Gains) instrument. Results Student gains in the functional neuroimaging of cognition as assessed by the SALG instrument were strongly associated with several aspects of the course design. Conclusion Our implementation of a multidisciplinary and active learning functional neuroimaging course produced positive learning outcomes. Inquiry-based learning activities and an online learning environment contributed positively to reported gains. This functional neuroimaging course design may serve as a useful model for other medical centers. PMID:17953758

Ensemble Sparse Classification of Alzheimer’s Disease

PubMed Central

Liu, Manhua; Zhang, Daoqiang; Shen, Dinggang

2012-01-01

The high-dimensional pattern classification methods, e.g., support vector machines (SVM), have been widely investigated for analysis of structural and functional brain images (such as magnetic resonance imaging (MRI)) to assist the diagnosis of Alzheimer’s disease (AD) including its prodromal stage, i.e., mild cognitive impairment (MCI). Most existing classification methods extract features from neuroimaging data and then construct a single classifier to perform classification. However, due to noise and small sample size of neuroimaging data, it is challenging to train only a global classifier that can be robust enough to achieve good classification performance. In this paper, instead of building a single global classifier, we propose a local patch-based subspace ensemble method which builds multiple individual classifiers based on different subsets of local patches and then combines them for more accurate and robust classification. Specifically, to capture the local spatial consistency, each brain image is partitioned into a number of local patches and a subset of patches is randomly selected from the patch pool to build a weak classifier. Here, the sparse representation-based classification (SRC) method, which has shown effective for classification of image data (e.g., face), is used to construct each weak classifier. Then, multiple weak classifiers are combined to make the final decision. We evaluate our method on 652 subjects (including 198 AD patients, 225 MCI and 229 normal controls) from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using MR images. The experimental results show that our method achieves an accuracy of 90.8% and an area under the ROC curve (AUC) of 94.86% for AD classification and an accuracy of 87.85% and an AUC of 92.90% for MCI classification, respectively, demonstrating a very promising performance of our method compared with the state-of-the-art methods for AD/MCI classification using MR images. PMID:22270352

Neural Correlates of Visual Perceptual Expertise: Evidence from Cognitive Neuroscience Using Functional Neuroimaging

ERIC Educational Resources Information Center

Gegenfurtner, Andreas; Kok, Ellen M.; van Geel, Koos; de Bruin, Anique B. H.; Sorger, Bettina

2017-01-01

Functional neuroimaging is a useful approach to study the neural correlates of visual perceptual expertise. The purpose of this paper is to review the functional-neuroimaging methods that have been implemented in previous research in this context. First, we will discuss research questions typically addressed in visual expertise research. Second,…

Statistical Challenges in "Big Data" Human Neuroimaging.

PubMed

Smith, Stephen M; Nichols, Thomas E

2018-01-17

Smith and Nichols discuss "big data" human neuroimaging studies, with very large subject numbers and amounts of data. These studies provide great opportunities for making new discoveries about the brain but raise many new analytical challenges and interpretational risks. Copyright © 2017 Elsevier Inc. All rights reserved.

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Neuroimaging in human MDMA (Ecstasy) users: A cortical model

PubMed Central

Cowan, Ronald L; Roberts, Deanne M; Joers, James M

2009-01-01

MDMA (3,4 methylenedioxymethamphetamine) has been used by millions of people worldwide as a recreational drug. MDMA and Ecstasy are often used synonymously but it is important to note that the purity of Ecstasy sold as MDMA is not certain. MDMA use is of public health concern, not so much because MDMA produces a common or severe dependence syndrome, but rather because rodent and non-human primate studies have indicated that MDMA (when administered at certain dosages and intervals) can cause long-lasting reductions in markers of brain serotonin (5-HT) that appear specific to fine diameter axons arising largely from the dorsal raphe nucleus (DR). Given the popularity of MDMA, the potential for the drug to produce long-lasting or permanent 5-HT axon damage or loss, and the widespread role of 5-HT function in the brain, there is a great need for a better understanding of brain function in human users of this drug. To this end, neuropsychological, neuroendocrine, and neuroimaging studies have all suggested that human MDMA users may have long-lasting changes in brain function consistent with 5-HT toxicity. Data from animal models leads to testable hypotheses regarding MDMA effects on the human brain. Because neuropsychological and neuroimaging findings have focused on the neocortex, a cortical model is developed to provide context for designing and interpreting neuroimaging studies in MDMA users. Aspects of the model are supported by the available neuroimaging data but there are controversial findings in some areas and most findings have not been replicated across different laboratories and using different modalities. This paper reviews existing findings in the context of a cortical model and suggests directions for future research. PMID:18991874

[Neuroimaging and Blood Biomarkers in Functional Prognosis after Stroke].

PubMed

Branco, João Paulo; Costa, Joana Santos; Sargento-Freitas, João; Oliveira, Sandra; Mendes, Bruno; Laíns, Jorge; Pinheiro, João

2016-11-01

Stroke remains one of the leading causes of morbidity and mortality around the world and it is associated with an important long-term functional disability. Some neuroimaging resources and certain peripheral blood or cerebrospinal fluid proteins can give important information about etiology, therapeutic approach, follow-up and functional prognosis in acute ischemic stroke patients. However, among the scientific community, there is currently more interest in the stroke vital prognosis over the functional prognosis. Predicting the functional prognosis during acute phase would allow more objective rehabilitation programs and better management of the available resources. The aim of this work is to review the potential role of acute phase neuroimaging and blood biomarkers as functional recovery predictors after ischemic stroke. Review of the literature published between 2005 and 2015, in English, using the terms "ischemic stroke", "neuroimaging" e "blood biomarkers". We included nine studies, based on abstract reading. Computerized tomography, transcranial doppler ultrasound and diffuse magnetic resonance imaging show potential predictive value, based on the blood flow study and the evaluation of stroke's volume and localization, especially when combined with the National Institutes of Health Stroke Scale. Several biomarkers have been studied as diagnostic, risk stratification and prognostic tools, namely the S100 calcium binding protein B, C-reactive protein, matrix metalloproteinases and cerebral natriuretic peptide. Although some biomarkers and neuroimaging techniques have potential predictive value, none of the studies were able to support its use, alone or in association, as a clinically useful functionality predictor model. All the evaluated markers were considered insufficient to predict functional prognosis at three months, when applied in the first hours after stroke. Additional studies are necessary to identify reliable predictive markers for functional

Parsing brain activity with fMRI and mixed designs: what kind of a state is neuroimaging in?

PubMed

Donaldson, David I

2004-08-01

Neuroimaging is often pilloried for providing little more than pretty pictures that simply show where activity occurs in the brain. Strong critics (notably Uttal) have even argued that neuroimaging is nothing more than a modern day version of phrenology: destined to fail, and fundamentally uninformative. Here, I make the opposite case, arguing that neuroimaging is in a vibrant and healthy state of development. As recent investigations of memory illustrate, when used well, neuroimaging goes beyond asking 'where' activity is occurring, to ask questions concerned more with 'what' functional role the activity reflects.

Functional Neuroimaging Studies of Written Sentence Comprehension

ERIC Educational Resources Information Center

Caplan, David

2004-01-01

Sentences convey relationships between the meanings of words, such as who is accomplishing an action or receiving it. Functional neuroimaging based on positron-emission tomography and functional magnetic resonance imaging has been used to identify areas of the brain involved in structuring sentences and determining aspects of meaning associated…

Neuroimaging in ophthalmology

PubMed Central

Kim, James D.; Hashemi, Nafiseh; Gelman, Rachel; Lee, Andrew G.

2012-01-01

In the past three decades, there have been countless advances in imaging modalities that have revolutionized evaluation, management, and treatment of neuro-ophthalmic disorders. Non-invasive approaches for early detection and monitoring of treatments have decreased morbidity and mortality. Understanding of basic methods of imaging techniques and choice of imaging modalities in cases encountered in neuro-ophthalmology clinic is critical for proper evaluation of patients. Two main imaging modalities that are often used are computed tomography (CT) and magnetic resonance imaging (MRI). However, variations of these modalities and appropriate location of imaging must be considered in each clinical scenario. In this article, we review and summarize the best neuroimaging studies for specific neuro-ophthalmic indications and the diagnostic radiographic findings for important clinical entities. PMID:23961025

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.

[Initial diagnosis of Parkinson's disease - neuroradiological diagnosis].

PubMed

Orimo, Satoshi

2013-01-01

Brain MRI is essential for differentiating Parkinson's disease (PD) from other parkinsonian syndromes. The purpose of performing brain MRI is not to make a diagnosis of PD but is to exclude other parkinsonian syndromes. Recently, several new MRI techniques such as voxel based morphometry, relaxometry, magnetization transfer, spectroscopy, tractography, and functional MRI have been introduced in the diagnosis of PD. Neuromelanin imaging is one of the new techniques and can be useful to make an initial diagnosis of PD. MIBG myocardial scintigraphy is a sensitive imaging tool to differentiate PD from other parkinsonian syndromes and is one of the good tools to make an initial diagnosis of PD. Brain perfusion imaging is sometimes useful to make an initial diagnosis of PD, because reduced brain perfusion area can be detected before brain MRI detects morphological changes of the brain. Dopamine transporter imaging, not available in Japan, is a sensitive tool to detect very early parkinsonism and is useful to make an initial diagnosis of PD. However, it is difficult to differentiate PD from other parkinsonian syndromes.

A systemic literature review of neuroimaging studies in women with breast cancer treated with adjuvant chemotherapy

PubMed Central

Wiłkość, Monika; Izdebski, Paweł; Żurawski, Bogdan

2017-01-01

Chemotherapy-induced cognitive deficits in patients with breast cancer, predominantly in attention and verbal memory, have been observed in numerous studies. These neuropsychological findings are corroborated by the results of neuroimaging studies. The aim of this paper was to survey the reports on cerebral structural and functional alterations in women with breast cancer treated with chemotherapy (CTx). First, we discuss the host-related and disease-related mechanisms underlying cognitive impairment after CTx. We point out the direct and indirect neurotoxic effect of cytostatics, which may cause: a damage to neurons or glial cells, changes in neurotransmitter levels, deregulation of the immune system and/or cytokine release. Second, we focus on the results of neuroimaging studies on brain structure and function that revealed decreased: density of grey matter, integrity of white matter and volume of multiple brain regions, as well as their lower activation during cognitive task performance. Finally, we concentrate on compensatory mechanisms, which activate additional brain areas or neural connection to reach the premorbid cognitive efficiency. PMID:28435392

Legal liability and research ethics boards: the case of neuroimaging and incidental findings.

PubMed

Zarzeczny, Amy; Caulfield, Timothy

2012-01-01

Neuroimaging research covers a wide range of intriguing issues from revealing brain structures to investigating what happens in our brain when we lie. The field appears to be thriving, but skepticism and alertness to the various ethical, scientific, policy and philosophical challenges associated with it also appear to be on the rise. One particularly complex issue concerns what to do with incidental findings that emerge during the course of neuroimaging research. Research ethics boards (REBs) play a central role in research oversight. In this paper, we will consider some of the potential issues associated with REB liability in negligence in the context of incidental findings in neuroimaging research. Copyright © 2011 Elsevier Ltd. All rights reserved.

Emerging MRI and metabolic neuroimaging techniques in mild traumatic brain injury.

PubMed

Lu, Liyan; Wei, Xiaoer; Li, Minghua; Li, Yuehua; Li, Wenbin

2014-01-01

Traumatic brain injury (TBI) is one of the leading causes of death worldwide, and mild traumatic brain injury (mTBI) is the most common traumatic injury. It is difficult to detect mTBI using a routine neuroimaging. Advanced techniques with greater sensitivity and specificity for the diagnosis and treatment of mTBI are required. The aim of this review is to offer an overview of various emerging neuroimaging methodologies that can solve the clinical health problems associated with mTBI. Important findings and improvements in neuroimaging that hold value for better detection, characterization and monitoring of objective brain injuries in patients with mTBI are presented. Conventional computed tomography (CT) and magnetic resonance imaging (MRI) are not very efficient for visualizing mTBI. Moreover, techniques such as diffusion tensor imaging, magnetization transfer imaging, susceptibility-weighted imaging, functional MRI, single photon emission computed tomography, positron emission tomography and magnetic resonance spectroscopy imaging were found to be useful for mTBI imaging.

Initial treatment of Parkinson's disease.

PubMed

Tarsy, Daniel

2006-05-01

Initial treatment of early idiopathic Parkinson's disease (PD) begins with diagnosis based on clinical evaluation supplemented by laboratory studies and brain imaging to exclude causes of secondary parkinsonism. In most cases, testing is normal and the diagnosis of PD rests on clinical criteria. In patients with mild symptoms and signs, the diagnosis of PD may not initially be apparent, and follow-up evaluation is needed to arrive at a diagnosis. Once the diagnosis is made, pharmacologic treatment may not be the first step. First, patient education is essential, especially because PD is a high-profile disease for which information and misinformation are readily available to patients and families. Counseling concerning prognosis, future symptoms, future disability, and treatment must be provided. Questions from patients concerning diet, lifestyle, and exercise are especially common at this point. The decision of when to initiate treatment is the next major consideration. Much controversy but relatively little light has been brought to bear on this issue. L-dopa was the first major antiparkinson medication to be introduced and remains the "gold standard" of treatment. Next in efficacy are the dopamine agonists (DAs). A debate has raged concerning whether initial dopaminergic treatment should be with L-dopa or DAs. Physicians have been concerned about forestalling the appearance of dyskinesias and motor fluctuations, whereas patients have incorrectly understood that L-dopa and possibly other antiparkinson drugs have a finite duration of usefulness, making it important to defer treatment for as long as possible. This has created "L-dopa phobia," which may stand in the way of useful treatment. In spite of this controversy, there is uniform agreement that the appropriate time to treat is when the patient is beginning to be disabled. This varies from patient to patient and depends on age, employment status, nature of job, level of physical activity, concern about

International Cognition and Cancer Task Force Recommendations for Neuroimaging Methods in the Study of Cognitive Impairment in Non-CNS Cancer Patients.

PubMed

Deprez, Sabine; Kesler, Shelli R; Saykin, Andrew J; Silverman, Daniel H S; de Ruiter, Michiel B; McDonald, Brenna C

2018-03-01

Cancer- and treatment-related cognitive changes have been a focus of increasing research since the early 1980s, with meta-analyses demonstrating poorer performance in cancer patients in cognitive domains including executive functions, processing speed, and memory. To facilitate collaborative efforts, in 2011 the International Cognition and Cancer Task Force (ICCTF) published consensus recommendations for core neuropsychological tests for studies of cancer populations. Over the past decade, studies have used neuroimaging techniques, including structural and functional magnetic resonance imaging (fMRI) and positron emission tomography, to examine the underlying brain basis for cancer- and treatment-related cognitive declines. As yet, however, there have been no consensus recommendations to guide researchers new to this field or to promote the ability to combine data sets. We first discuss important methodological issues with regard to neuroimaging study design, scanner considerations, and sequence selection, focusing on concerns relevant to cancer populations. We propose a minimum recommended set of sequences, including a high-resolution T1-weighted volume and a resting state fMRI scan. Additional advanced imaging sequences are discussed for consideration when feasible, including task-based fMRI and diffusion tensor imaging. Important image data processing and analytic considerations are also reviewed. These recommendations are offered to facilitate increased use of neuroimaging in studies of cancer- and treatment-related cognitive dysfunction. They are not intended to discourage investigator-initiated efforts to develop cutting-edge techniques, which will be helpful in advancing the state of the knowledge. Use of common imaging protocols will facilitate multicenter and data-pooling initiatives, which are needed to address critical mechanistic research questions.

A New Approach to Investigate the Association between Brain Functional Connectivity and Disease Characteristics of Attention-Deficit/Hyperactivity Disorder: Topological Neuroimaging Data Analysis.

PubMed

Kyeong, Sunghyon; Park, Seonjeong; Cheon, Keun-Ah; Kim, Jae-Jin; Song, Dong-Ho; Kim, Eunjoo

2015-01-01

Attention-deficit/hyperactivity disorder (ADHD) is currently diagnosed by a diagnostic interview, mainly based on subjective reports from parents or teachers. It is necessary to develop methods that rely on objectively measureable neurobiological data to assess brain-behavior relationship in patients with ADHD. We investigated the application of a topological data analysis tool, Mapper, to analyze the brain functional connectivity data from ADHD patients. To quantify the disease severity using the neuroimaging data, the decomposition of individual functional networks into normal and disease components by the healthy state model (HSM) was performed, and the magnitude of the disease component (MDC) was computed. Topological data analysis using Mapper was performed to distinguish children with ADHD (n = 196) from typically developing controls (TDC) (n = 214). In the topological data analysis, the partial clustering results of patients with ADHD and normal subjects were shown in a chain-like graph. In the correlation analysis, the MDC showed a significant increase with lower intelligence scores in TDC. We also found that the rates of comorbidity in ADHD significantly increased when the deviation of the functional connectivity from HSM was large. In addition, a significant correlation between ADHD symptom severity and MDC was found in part of the dataset. The application of HSM and topological data analysis methods in assessing the brain functional connectivity seem to be promising tools to quantify ADHD symptom severity and to reveal the hidden relationship between clinical phenotypic variables and brain connectivity.

Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications

PubMed Central

Goldstein, Rita Z.; Volkow, Nora D.

2012-01-01

The loss of control over drug intake that occurs in addiction was initially believed to result from disruption of subcortical reward circuits. However, imaging studies in addictive behaviours have identified a key involvement of the prefrontal cortex (PFC) both through its regulation of limbic reward regions and its involvement in higher-order executive function (for example, self-control, salience attribution and awareness). This Review focuses on functional neuroimaging studies conducted in the past decade that have expanded our understanding of the involvement of the PFC in drug addiction. Disruption of the PFC in addiction underlies not only compulsive drug taking but also accounts for the disadvantageous behaviours that are associated with addiction and the erosion of free will. PMID:22011681

Multiple Sclerosis in Malaysia: Demographics, Clinical Features, and Neuroimaging Characteristics

PubMed Central

Viswanathan, S.; Rose, N.; Masita, A.; Dhaliwal, J. S.; Puvanarajah, S. D.; Rafia, M. H.; Muda, S.

2013-01-01

Background. Multiple sclerosis (MS) is an uncommon disease in multiracial Malaysia. Diagnosing patients with idiopathic inflammatory demyelinating diseases has been greatly aided by the evolution in diagnostic criterion, the identification of new biomarkers, and improved accessibility to neuroimaging in the country. Objectives. To investigate the spectrum of multiple sclerosis in Malaysia. Methods. Retrospective analysis with longitudinal follow-up of patients referred to a single tertiary medical center with neurology services in Malaysia. Results. Out of 245 patients with idiopathic inflammatory demyelinating disease, 104 patients had multiple sclerosis. Female to male ratio was 5 : 1. Mean age at onset was 28.6 ± 9.9 years. The Malays were the predominant racial group affected followed by the Chinese, Indians, and other indigenous groups. Subgroup analysis revealed more Chinese having neuromyelitis optica and its spectrum disorders rather than multiple sclerosis. Positive family history was reported in 5%. Optic neuritis and myelitis were the commonest presentations at onset of disease, and relapsing remitting course was the commonest disease pattern observed. Oligoclonal band positivity was 57.6%. At disease onset, 61.5% and 66.4% fulfilled the 2005 and 2010 McDonald's criteria for dissemination in space. Mean cord lesion length was 1.86 ± 1.65 vertebral segments in the relapsing remitting group as opposed to 6.25 ± 5.18 vertebral segments in patients with neuromyelitis optica and its spectrum disorders. Conclusion. The spectrum of multiple sclerosis in Malaysia has changed over the years. Further advancement in diagnostic criteria will no doubt continue to contribute to the evolution of this disease here. PMID:24455266

Neuroimaging biomarkers and impaired olfaction in cognitively normal individuals.

PubMed

Vassilaki, Maria; Christianson, Teresa J; Mielke, Michelle M; Geda, Yonas E; Kremers, Walter K; Machulda, Mary M; Knopman, David S; Petersen, Ronald C; Lowe, Val J; Jack, Clifford R; Roberts, Rosebud O

2017-06-01

There is a need for inexpensive noninvasive tests to identify older healthy persons at risk for Alzheimer disease (AD) for enrollment in AD prevention trials. Our objective was to examine whether abnormalities in neuroimaging measures of amyloid and neurodegeneration are correlated with odor identification (OI) in the population-based Mayo Clinic Study of Aging. Cognitively normal (CN) participants had olfactory function assessed using the Brief Smell Identification Test (B-SIT), underwent magnetic resonance imaging (n = 829) to assess a composite AD signature cortical thickness and hippocampal volume (HVa), and underwent 11 C-Pittsburgh compound B (n = 306) and 18 fluorodeoxyglucose (n = 305) positron emission tomography scanning to assess amyloid accumulation and brain hypometabolism, respectively. The association of neuroimaging biomarkers with OI was examined using multinomial logistic regression and simple linear regression models adjusted for potential confounders. Among 829 CN participants (mean age = 79.2 years; 51.5% men), 248 (29.9%) were normosmic and 78 (9.4%) had anosmia (B-SIT score < 6). Abnormal AD signature cortical thickness and reduced HVa were associated with decreased OI as a continuous measure (slope = -0.43, 95% confidence interval [CI] = -0.76 to -0.09, p = 0.01 and slope = -0.72, 95% CI = -1.15 to -0.28, p < 0.01, respectively). Reduced HVa, decreased AD signature cortical thickness, and increased amyloid accumulation were significantly associated with increased odds of anosmia. Our findings suggest that OI may be a noninvasive, inexpensive marker for risk stratification, for identifying participants at the preclinical stage of AD who may be at risk for cognitive impairment and eligible for inclusion in AD prevention clinical trials. These cross-sectional findings remain to be validated prospectively. Ann Neurol 2017;81:871-882. © 2017 American Neurological Association.

Complex biomarker discovery in neuroimaging data: Finding a needle in a haystack☆

PubMed Central

Atluri, Gowtham; Padmanabhan, Kanchana; Fang, Gang; Steinbach, Michael; Petrella, Jeffrey R.; Lim, Kelvin; MacDonald, Angus; Samatova, Nagiza F.; Doraiswamy, P. Murali; Kumar, Vipin

2013-01-01

Neuropsychiatric disorders such as schizophrenia, bipolar disorder and Alzheimer's disease are major public health problems. However, despite decades of research, we currently have no validated prognostic or diagnostic tests that can be applied at an individual patient level. Many neuropsychiatric diseases are due to a combination of alterations that occur in a human brain rather than the result of localized lesions. While there is hope that newer imaging technologies such as functional and anatomic connectivity MRI or molecular imaging may offer breakthroughs, the single biomarkers that are discovered using these datasets are limited by their inability to capture the heterogeneity and complexity of most multifactorial brain disorders. Recently, complex biomarkers have been explored to address this limitation using neuroimaging data. In this manuscript we consider the nature of complex biomarkers being investigated in the recent literature and present techniques to find such biomarkers that have been developed in related areas of data mining, statistics, machine learning and bioinformatics. PMID:24179856

Volumetric neuroimage analysis extensions for the MIPAV software package.

PubMed

Bazin, Pierre-Louis; Cuzzocreo, Jennifer L; Yassa, Michael A; Gandler, William; McAuliffe, Matthew J; Bassett, Susan S; Pham, Dzung L

2007-09-15

We describe a new collection of publicly available software tools for performing quantitative neuroimage analysis. The tools perform semi-automatic brain extraction, tissue classification, Talairach alignment, and atlas-based measurements within a user-friendly graphical environment. They are implemented as plug-ins for MIPAV, a freely available medical image processing software package from the National Institutes of Health. Because the plug-ins and MIPAV are implemented in Java, both can be utilized on nearly any operating system platform. In addition to the software plug-ins, we have also released a digital version of the Talairach atlas that can be used to perform regional volumetric analyses. Several studies are conducted applying the new tools to simulated and real neuroimaging data sets.

A Systematic Review of Intervention Studies Examining Nutritional and Herbal Therapies for Mild Cognitive Impairment and Dementia Using Neuroimaging Methods: Study Characteristics and Intervention Efficacy

PubMed Central

MacMillan, Freya; Camfield, David A.; Seto, Sai W.

2017-01-01

Neuroimaging facilitates the assessment of complementary medicines (CMs) by providing a noninvasive insight into their mechanisms of action in the human brain. This is important for identifying the potential treatment options for target disease cohorts with complex pathophysiologies. The aim of this systematic review was to evaluate study characteristics, intervention efficacy, and the structural and functional neuroimaging methods used in research assessing nutritional and herbal medicines for mild cognitive impairment (MCI) and dementia. Six databases were searched for articles reporting on CMs, dementia, and neuroimaging methods. Data were extracted from 21/2,742 eligible full text articles and risk of bias was assessed. Nine studies examined people with Alzheimer's disease, 7 MCI, 4 vascular dementia, and 1 all-cause dementia. Ten studies tested herbal medicines, 8 vitamins and supplements, and 3 nootropics. Ten studies used electroencephalography (EEG), 5 structural magnetic resonance imaging (MRI), 2 functional MRI (fMRI), 3 cerebral blood flow (CBF), 1 single photon emission tomography (SPECT), and 1 positron emission tomography (PET). Four studies had a low risk of bias, with the majority consistently demonstrating inadequate reporting on randomisation, allocation concealment, blinding, and power calculations. A narrative synthesis approach was assumed due to heterogeneity in study methods, interventions, target cohorts, and quality. Eleven key recommendations are suggested to advance future work in this area. PMID:28303161

Quality Improvement Initiatives in Inflammatory Bowel Disease.

PubMed

Berry, Sameer K; Siegel, Corey A; Melmed, Gil Y

2017-08-01

This article serves as an overview of several quality improvement initiatives in inflammatory bowel disease (IBD). IBD is associated with significant variation in care, suggesting poor quality of care. There have been several efforts to improve the quality of care for patients with IBD. Quality improvement (QI) initiatives in IBD are intended to be patient-centric, improve outcomes for individuals and populations, and reduce costs-all consistent with "the triple aim" put forth by the Institute for Healthcare Improvement (IHI). Current QI initiatives include the development of quality measure sets to standardize processes and outcomes, learning health systems to foster collaborative improvement, and patient-centered medical homes specific to patients with IBD in shared risk models of care. Some of these programs have demonstrated early success in improving patient outcomes, reducing costs, improving patient satisfaction, and facilitating patient engagement. However, further studies are needed to evaluate and compare the effects of these programs over time on clinical outcomes in order to demonstrate long-term value and sustainability.

Diagnosis and Multimodality Management of Cushing's Disease: A Practical Review

PubMed Central

Zada, Gabriel

2013-01-01

Cushing's Disease is caused by oversecretion of ACTH from a pituitary adenoma and results in subsequent elevations of systemic cortisol, ultimately contributing to reduced patient survival. The diagnosis of Cushing's Disease frequently involves a stepwise approach including clinical, laboratory, neuroimaging, and sometimes interventional radiology techniques, often mandating multidisciplinary collaboration from numerous specialty practitioners. Pituitary microadenomas that do not appear on designated pituitary MRI or dynamic contrast protocols may pose a particularly challenging subset of this disease. The treatment of Cushing's Disease typically involves transsphenoidal surgical resection of the pituitary adenoma as a first-line option, yet may require the addition of adjunctive measures such as stereotactic radiosurgery or medical management to achieve normalization of serum cortisol levels. Vigilant long-term serial endocrine monitoring of patients is imperative in order to detect any recurrence that may occur, even years following initial remission. In this paper, a stepwise approach to the diagnosis, and various management strategies and associated outcomes in patients with Cushing's Disease are discussed. PMID:23401686

The neuroimaging of Leigh syndrome: case series and review of the literature.

PubMed

Bonfante, Eliana; Koenig, Mary Kay; Adejumo, Rahmat B; Perinjelil, Vinu; Riascos, Roy F

2016-04-01

Leigh syndrome by definition is (1) a neurodegenerative disease with variable symptoms, (2) caused by mitochondrial dysfunction from a hereditary genetic defect and (3) accompanied by bilateral central nervous system lesions. A genetic etiology is confirmed in approximately 50% of patients, with more than 60 identified mutations in the nuclear and mitochondrial genomes. Here we review the clinical features and imaging studies of Leigh syndrome and describe the neuroimaging findings in a cohort of 17 children with genetically confirmed Leigh syndrome. MR findings include lesions in the brainstem in 9 children (53%), basal ganglia in 13 (76%), thalami in 4 (24%) and dentate nuclei in 2 (12%), and global atrophy in 2 (12%). The brainstem lesions were most frequent in the midbrain and medulla oblongata. With follow-up an increased number of lesions from baseline was observed in 7 of 13 children, evolution of the initial lesion was seen in 6, and complete regression of the lesions was seen in 3. No cerebral white matter lesions were found in any of the 17 children. In concordance with the literature, we found that Leigh syndrome follows a similar pattern of bilateral, symmetrical basal ganglia or brainstem changes. Lesions in Leigh syndrome evolve over time and a lack of visible lesions does not exclude the diagnosis. Reversibility of lesions is seen in some patients, making the continued search for treatment and prevention a priority for clinicians and researchers.

On Statistical Analysis of Neuroimages with Imperfect Registration

PubMed Central

Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas

2016-01-01

A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168

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

Neuroimaging in repetitive brain trauma

PubMed Central

2014-01-01

Sports-related concussions are one of the major causes of mild traumatic brain injury. Although most patients recover completely within days to weeks, those who experience repetitive brain trauma (RBT) may be at risk for developing a condition known as chronic traumatic encephalopathy (CTE). While this condition is most commonly observed in athletes who experience repetitive concussive and/or subconcussive blows to the head, such as boxers, football players, or hockey players, CTE may also affect soldiers on active duty. Currently, the only means by which to diagnose CTE is by the presence of phosphorylated tau aggregations post-mortem. Non-invasive neuroimaging, however, may allow early diagnosis as well as improve our understanding of the underlying pathophysiology of RBT. The purpose of this article is to review advanced neuroimaging methods used to investigate RBT, including diffusion tensor imaging, magnetic resonance spectroscopy, functional magnetic resonance imaging, susceptibility weighted imaging, and positron emission tomography. While there is a considerable literature using these methods in brain injury in general, the focus of this review is on RBT and those subject populations currently known to be susceptible to RBT, namely athletes and soldiers. Further, while direct detection of CTE in vivo has not yet been achieved, all of the methods described in this review provide insight into RBT and will likely lead to a better characterization (diagnosis), in vivo, of CTE than measures of self-report. PMID:25031630

Neurosyphilis: mighty imitator forays with benign presentation and unique neuroimaging findings.

PubMed

Tiwana, Harmanpreet; Ahmed, Aiesha

2018-04-30

Background: Common causes of temporal lobe hyper intensities are central nervous system infections like herpes simplex encephalitis, Lyme disease, limbic encephalitis and vascular pathology like Cerebral Autosomal Dominant Arteriopathy with Subcortical infarcts and Leukoencephalopathy. Methods: Personal assessment, laboratory data analysis and neuroimaging for the patient who was admitted to a central Pennsylvania tertiary care referral centre were conducted. Results: A 52-year-old male presented with a 1-year history of diffuse dysesthesia in upper and lower extremities with associated intermittent headaches and neck stiffness. Evaluation with lumbar puncture revealed increased nucleated cells (50ul) with lymphocytic predominance (96%) and an elevated protein level of 109mg/dl. Magnetic resonance imaging (MRI) of the brain showed T2/FLAIR hyper intensity in bilateral subcortical temporal white matter, left-greater-than-right and associated volume loss in cerebral parenchyma. Additional abnormal work up included reactive serum reactive plasma regain and Treponema pallidum antibody particle agglutination. Diagnosis of neurosyphilis was made and the patient was treated with intramuscular (IM) penicillin for 3 weeks. At the time of discharge, his headache and neck stiffness resolved and dysesthesias were decreased in intensity. Conclusions: The diagnosis of neurosyphilis is intricate, and no reference standard exists. Neuroimaging findings of neurosyphilis commonly are cerebral infarctions, leptomeningeal enhancement or non-specific white matter lesions. Less common features on fluid-attenuated inversion recovery (FLAIR) sequences are cortical atrophy and mesial temporal parenchymal signal changes. It is prudent to keep neurosyphilis in differential of mesial temporal lobe white matter changes, as early diagnosis and treatment results in better prognosis.

Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.

PubMed

Bestmann, Sven; Feredoes, Eva

2013-08-01

Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition. © 2013 New York Academy of Sciences.

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

PubMed Central

Lancaster, Jenessa; Lorenz, Romy; Leech, Rob; Cole, James H.

2018-01-01

Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years). Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm). For predicting chronological age, a mean absolute error (MAE) of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm). This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian

Human Fear Conditioning and Extinction in Neuroimaging: A Systematic Review

PubMed Central

Sehlmeyer, Christina; Schöning, Sonja; Zwitserlood, Pienie; Pfleiderer, Bettina; Kircher, Tilo; Arolt, Volker; Konrad, Carsten

2009-01-01

Fear conditioning and extinction are basic forms of associative learning that have gained considerable clinical relevance in enhancing our understanding of anxiety disorders and facilitating their treatment. Modern neuroimaging techniques have significantly aided the identification of anatomical structures and networks involved in fear conditioning. On closer inspection, there is considerable variation in methodology and results between studies. This systematic review provides an overview of the current neuroimaging literature on fear conditioning and extinction on healthy subjects, taking into account methodological issues such as the conditioning paradigm. A Pubmed search, as of December 2008, was performed and supplemented by manual searches of bibliographies of key articles. Two independent reviewers made the final study selection and data extraction. A total of 46 studies on cued fear conditioning and/or extinction on healthy volunteers using positron emission tomography or functional magnetic resonance imaging were reviewed. The influence of specific experimental factors, such as contingency and timing parameters, assessment of conditioned responses, and characteristics of conditioned and unconditioned stimuli, on cerebral activation patterns was examined. Results were summarized descriptively. A network consisting of fear-related brain areas, such as amygdala, insula, and anterior cingulate cortex, is activated independently of design parameters. However, some neuroimaging studies do not report these findings in the presence of methodological heterogeneities. Furthermore, other brain areas are differentially activated, depending on specific design parameters. These include stronger hippocampal activation in trace conditioning and tactile stimulation. Furthermore, tactile unconditioned stimuli enhance activation of pain related, motor, and somatosensory areas. Differences concerning experimental factors may partly explain the variance between neuroimaging

Translational Immuno- and Neuro-imaging Demonstrate Corneal Neuro-immune Crosstalk

PubMed Central

Hamrah, Pedram; Seyed-Razavi, Yashar; Yamaguchi, Takefumi

2017-01-01

Corneal immuno- and neuro-imaging approaches facilitate in vivo analyses of the cornea, including high-resolution imaging of corneal immune cells and nerves. This approach facilitates the analyses of underlying immune and nerve alterations not detected by clinical slit-lamp examination alone. In this review, we describe recent work performed in our translational ocular immunology center with a focus on ‘bench-to-bedside’ and ‘bedside-to-bench’ research. The ability to visualize dendritiform immune cells (DCs) in patients with laser in vivo confocal microscopy (IVCM), recently discovered in the central murine cornea, has allowed us to demonstrated their utility as a potential surrogate biomarker for inflammatory ocular surface diseases. This biomarker for inflammation allows the measurement of therapeutic efficacy of anti-inflammatory drugs and its utility as an endpoint in clinical trials with high inter-observer agreement. IVCM image analyses from our studies demonstrated a significant increase in DC density and size in ocular disease, a positive correlation between DC density and clinical signs and symptoms of disease and pro-inflammatory tear cytokines, and a strong negative correlation between DC density and subbasal nerve density. In conjunction with pre-clinical research investigating the inflammatory state in a partial or fully denervated cornea, our results indicated that corneal nerves are directly involved in the regulation of homeostasis and immune privilege in the cornea. PMID:27631352

Pain perception and hypnosis: findings from recent functional neuroimaging studies.

PubMed

Del Casale, Antonio; Ferracuti, Stefano; Rapinesi, Chiara; Serata, Daniele; Caltagirone, Saverio Simone; Savoja, Valeria; Piacentino, Daria; Callovini, Gemma; Manfredi, Giovanni; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo

2015-01-01

Hypnosis modulates pain perception and tolerance by affecting cortical and subcortical activity in brain regions involved in these processes. By reviewing functional neuroimaging studies focusing on pain perception under hypnosis, the authors aimed to identify brain activation-deactivation patterns occurring in hypnosis-modulated pain conditions. Different changes in brain functionality occurred throughout all components of the pain network and other brain areas. The anterior cingulate cortex appears to be central in modulating pain circuitry activity under hypnosis. Most studies also showed that the neural functions of the prefrontal, insular, and somatosensory cortices are consistently modified during hypnosis-modulated pain conditions. Functional neuroimaging studies support the clinical use of hypnosis in the management of pain conditions.

Understanding the impact of TV commercials: electrical neuroimaging.

PubMed

Vecchiato, Giovanni; Kong, Wanzeng; Maglione, Anton Giulio; Wei, Daming

2012-01-01

Today, there is a greater interest in the marketing world in using neuroimaging tools to evaluate the efficacy of TV commercials. This field of research is known as neuromarketing. In this article, we illustrate some applications of electrical neuroimaging, a discipline that uses electroencephalography (EEG) and intensive signal processing techniques for the evaluation of marketing stimuli. We also show how the proper usage of these methodologies can provide information related to memorization and attention while people are watching marketing-relevant stimuli. We note that temporal and frequency patterns of EEG signals are able to provide possible descriptors that convey information about the cognitive process in subjects observing commercial advertisements (ads). Such information could be unobtainable through common tools used in standard marketing research. Evidence of this research shows how EEG methodologies could be employed to better design new products that marketers are going to promote and to analyze the global impact of video commercials already broadcast on TV.

Neuroimaging the Effectiveness of Substance Use Disorder Treatments.

PubMed

Cabrera, Elizabeth A; Wiers, Corinde E; Lindgren, Elsa; Miller, Gregg; Volkow, Nora D; Wang, Gene-Jack

2016-09-01

Neuroimaging techniques to measure the function and biochemistry of the human brain such as positron emission tomography (PET), proton magnetic resonance spectroscopy ((1)H MRS), and functional magnetic resonance imaging (fMRI), are powerful tools for assessing neurobiological mechanisms underlying the response to treatments in substance use disorders. Here, we review the neuroimaging literature on pharmacological and behavioral treatment in substance use disorder. We focus on neural effects of medications that reduce craving (e.g., naltrexone, bupropion hydrochloride, baclofen, methadone, varenicline) and that improve cognitive control (e.g., modafinil, N-acetylcysteine), of behavioral treatments for substance use disorders (e.g., cognitive bias modification training, virtual reality, motivational interventions) and neuromodulatory interventions such as neurofeedback and transcranial magnetic stimulation. A consistent finding for the effectiveness of therapeutic interventions identifies the improvement of executive control networks and the dampening of limbic activation, highlighting their values as targets for therapeutic interventions in substance use disorders.

[Neuropsychology of Tourette's disorder: cognition, neuroimaging and creativity].

PubMed

Espert, R; Gadea, M; Alino, M; Oltra-Cucarella, J

2017-02-24

Tourette's disorder is the result of fronto-striatal brain dysfunction affecting people of all ages, with a debut in early childhood and continuing into adolescence and adulthood. This article reviews the main cognitive, functional neuroimaging and creativity-related studies in a disorder characterized by an excess of dopamine in the brain. Given the special cerebral configuration of these patients, neuropsychological alterations, especially in executive functions, should be expected. However, the findings are inconclusive and are conditioned by factors such as comorbidity with attention deficit hyperactivity disorder and obsessive-compulsive disorder, age or methodological variables. On the other hand, the neuroimaging studies carried out over the last decade have been able to explain the clinical symptoms of Tourette's disorder patients, with special relevance for the supplementary motor area and the anterior cingulate gyrus. Finally, although there is no linear relationship between excess of dopamine and creativity, the scientific literature emphasizes an association between Tourette's disorder and musical creativity, which could be translated into intervention programs based on music.

76 FR 28437 - Disease, Disability, and Injury Prevention and Control Special Interest Project (SIP): Initial...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-17

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Disease, Disability, and Injury Prevention and Control Special Interest Project (SIP): Initial Review The meeting... Disease or Treated by Assisted Reproductive Technology, SIP11-048, Panel F,'' initial review In accordance...

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation.

PubMed

Sarwate, Anand D; Plis, Sergey M; Turner, Jessica A; Arbabshirani, Mohammad R; Calhoun, Vince D

2014-01-01

The growth of data sharing initiatives for neuroimaging and genomics represents an exciting opportunity to confront the "small N" problem that plagues contemporary neuroimaging studies while further understanding the role genetic markers play in the function of the brain. When it is possible, open data sharing provides the most benefits. However, some data cannot be shared at all due to privacy concerns and/or risk of re-identification. Sharing other data sets is hampered by the proliferation of complex data use agreements (DUAs) which preclude truly automated data mining. These DUAs arise because of concerns about the privacy and confidentiality for subjects; though many do permit direct access to data, they often require a cumbersome approval process that can take months. An alternative approach is to only share data derivatives such as statistical summaries-the challenges here are to reformulate computational methods to quantify the privacy risks associated with sharing the results of those computations. For example, a derived map of gray matter is often as identifiable as a fingerprint. Thus alternative approaches to accessing data are needed. This paper reviews the relevant literature on differential privacy, a framework for measuring and tracking privacy loss in these settings, and demonstrates the feasibility of using this framework to calculate statistics on data distributed at many sites while still providing privacy.

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation

PubMed Central

Sarwate, Anand D.; Plis, Sergey M.; Turner, Jessica A.; Arbabshirani, Mohammad R.; Calhoun, Vince D.

2014-01-01

The growth of data sharing initiatives for neuroimaging and genomics represents an exciting opportunity to confront the “small N” problem that plagues contemporary neuroimaging studies while further understanding the role genetic markers play in the function of the brain. When it is possible, open data sharing provides the most benefits. However, some data cannot be shared at all due to privacy concerns and/or risk of re-identification. Sharing other data sets is hampered by the proliferation of complex data use agreements (DUAs) which preclude truly automated data mining. These DUAs arise because of concerns about the privacy and confidentiality for subjects; though many do permit direct access to data, they often require a cumbersome approval process that can take months. An alternative approach is to only share data derivatives such as statistical summaries—the challenges here are to reformulate computational methods to quantify the privacy risks associated with sharing the results of those computations. For example, a derived map of gray matter is often as identifiable as a fingerprint. Thus alternative approaches to accessing data are needed. This paper reviews the relevant literature on differential privacy, a framework for measuring and tracking privacy loss in these settings, and demonstrates the feasibility of using this framework to calculate statistics on data distributed at many sites while still providing privacy. PMID:24778614

The iconography of mourning and its neural correlates: a functional neuroimaging study

PubMed Central

Labek, Karin; Berger, Samantha; Buchheim, Anna; Bosch, Julia; Spohrs, Jennifer; Dommes, Lisa; Beschoner, Petra; Stingl, Julia C.

2017-01-01

Abstract The present functional neuroimaging study focuses on the iconography of mourning. A culture-specific pattern of body postures of mourning individuals, mostly suggesting withdrawal, emerged from a survey of visual material. When used in different combinations in stylized drawings in our neuroimaging study, this material activated cortical areas commonly seen in studies of social cognition (temporo-parietal junction, superior temporal gyrus, and inferior temporal lobe), empathy for pain (somatosensory cortex), and loss (precuneus, middle/posterior cingular gyrus). This pattern of activation developed over time. While in the early phases of exposure lower association areas, such as the extrastriate body area, were active, in the late phases activation in parietal and temporal association areas and the prefrontal cortex was more prominent. These findings are consistent with the conventional and contextual character of iconographic material, and further differentiate it from emotionally negatively valenced and high-arousing stimuli. In future studies, this neuroimaging assay may be useful in characterizing interpretive appraisal of material of negative emotional valence. PMID:28449116

Long-term effect of initiating pramipexole vs levodopa in early Parkinson disease.

PubMed

2009-05-01

To compare the long-term outcomes of subjects initially treated with pramipexole dihydrochloride with those of subjects initially treated with levodopa in the Comparison of the Agonist Pramipexole With Levodopa on Motor Complications of Parkinson's Disease (CALM-PD) trial. Up to 2 years of open extended follow-up of the CALM-PD subjects. Academic movement disorders clinics at 22 sites in the United States and Canada. Patients Patients with early Parkinson disease (N = 301) who required dopaminergic therapy to treat emerging disability were enrolled between October 1996 and August 1997, a subset of whom consented to extended follow-up until August 2003 (n = 222). Intervention Subjects were randomized to receive initial treatment with either pramipexole (n = 151) or levodopa (n = 150). Investigators were permitted to add open-label levodopa or other antiparkinsonian medications to treat ongoing or emerging disability. The primary outcome variable was the time-weighted average of self-reported disability scores in the "on" and "off" states as measured by the Schwab and England Activities of Daily Living Scale at the final visit. Secondary outcomes included the Unified Parkinson's Disease Rating Scale score, the presence and severity of dopaminergic motor complications, quality-of-life scale scores, Geriatric Depression Scale score, Epworth Sleepiness Scale score, and adverse events. After a mean (SD) follow-up of 6.0 (0.2) years, mean (SD) self-reported weighted Schwab and England Activities of Daily Living Scale scores were similar in the initial pramipexole (79.9 [16.2]) and initial levodopa (82.5 [14.6]) groups (P = .19). Dopaminergic motor complications (wearing off, on-off effects, or dyskinesias) were more common in the initial levodopa group (68.4%) than in the initial pramipexole group (50.0%) (P = .002), although disabling dyskinesias were uncommon in both groups. The mean (SD) Epworth Sleepiness Scale score was significantly higher in the initial pramipexole

Making an unknown unknown a known unknown: Missing data in longitudinal neuroimaging studies.

PubMed

Matta, Tyler H; Flournoy, John C; Byrne, Michelle L

2017-10-28

The analysis of longitudinal neuroimaging data within the massively univariate framework provides the opportunity to study empirical questions about neurodevelopment. Missing outcome data are an all-to-common feature of any longitudinal study, a feature that, if handled improperly, can reduce statistical power and lead to biased parameter estimates. The goal of this paper is to provide conceptual clarity of the issues and non-issues that arise from analyzing incomplete data in longitudinal studies with particular focus on neuroimaging data. This paper begins with a review of the hierarchy of missing data mechanisms and their relationship to likelihood-based methods, a review that is necessary not just for likelihood-based methods, but also for multiple-imputation methods. Next, the paper provides a series of simulation studies with designs common in longitudinal neuroimaging studies to help illustrate missing data concepts regardless of interpretation. Finally, two applied examples are used to demonstrate the sensitivity of inferences under different missing data assumptions and how this may change the substantive interpretation. The paper concludes with a set of guidelines for analyzing incomplete longitudinal data that can improve the validity of research findings in developmental neuroimaging research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Clinical, pathological, and neuroimaging analyses of two cases of Leigh syndrome in a Chinese family.

PubMed

Jin, Taoran; Shen, Hongrui; Zhao, Zhe; Hu, Jing

2014-11-01

In this study, the authors examined the clinical manifestations, skeletal muscle pathological characteristics, and neuroimaging results of 2 cases of Leigh syndrome in a Chinese family. The 2 patients presented with general weakness, and 1 of them presented with an impairment of vision. Skeletal muscle biopsies showed a deficiency in cytochrome c oxidase levels. Brain magnetic resonance imaging showed increased T1 and T2 signal intensities in the centrum ovale and dentate nucleus. Diffusion-weighted imaging showed a high-intensity signal. Magnetic resonance spectroscopy showed elevated levels of lactic acid in lesions. The examination of 1 patient at disease onset and during disease remission showed that the lesions detected by magnetic resonance imaging and diffusion-weighted imaging, and the peak for lactic acid detected by magnetic resonance spectroscopy, decreased during remission. These data suggest that changes in the imaging results of patients with Leigh syndrome correlate with disease course and pathogenetic condition. © The Author(s) 2014.

Neuroimaging and Neurodevelopmental Outcome in Extremely Preterm Infants

PubMed Central

Barnes, Patrick D.; Bulas, Dorothy; Slovis, Thomas L.; Finer, Neil N.; Wrage, Lisa A.; Das, Abhik; Tyson, Jon E.; Stevenson, David K.; Carlo, Waldemar A.; Walsh, Michele C.; Laptook, Abbot R.; Yoder, Bradley A.; Van Meurs, Krisa P.; Faix, Roger G.; Rich, Wade; Newman, Nancy S.; Cheng, Helen; Heyne, Roy J.; Vohr, Betty R.; Acarregui, Michael J.; Vaucher, Yvonne E.; Pappas, Athina; Peralta-Carcelen, Myriam; Wilson-Costello, Deanne E.; Evans, Patricia W.; Goldstein, Ricki F.; Myers, Gary J.; Poindexter, Brenda B.; McGowan, Elisabeth C.; Adams-Chapman, Ira; Fuller, Janell; Higgins, Rosemary D.

2015-01-01

BACKGROUND: Extremely preterm infants are at risk for neurodevelopmental impairment (NDI). Early cranial ultrasound (CUS) is usual practice, but near-term brain MRI has been reported to better predict outcomes. We prospectively evaluated MRI white matter abnormality (WMA) and cerebellar lesions, and serial CUS adverse findings as predictors of outcomes at 18 to 22 months’ corrected age. METHODS: Early and late CUS, and brain MRI were read by masked central readers, in a large cohort (n = 480) of infants <28 weeks’ gestation surviving to near term in the Neonatal Research Network. Outcomes included NDI or death after neuroimaging, and significant gross motor impairment or death, with NDI defined as cognitive composite score <70, significant gross motor impairment, and severe hearing or visual impairment. Multivariable models evaluated the relative predictive value of neuroimaging while controlling for other factors. RESULTS: Of 480 infants, 15 died and 20 were lost. Increasing severity of WMA and significant cerebellar lesions on MRI were associated with adverse outcomes. Cerebellar lesions were rarely identified by CUS. In full multivariable models, both late CUS and MRI, but not early CUS, remained independently associated with NDI or death (MRI cerebellar lesions: odds ratio, 3.0 [95% confidence interval: 1.3–6.8]; late CUS: odds ratio, 9.8 [95% confidence interval: 2.8–35]), and significant gross motor impairment or death. In models that did not include late CUS, MRI moderate-severe WMA was independently associated with adverse outcomes. CONCLUSIONS: Both late CUS and near-term MRI abnormalities were associated with outcomes, independent of early CUS and other factors, underscoring the relative prognostic value of near-term neuroimaging. PMID:25554820

The Appropriate Use of Neuroimaging in the Diagnostic Work-Up of Dementia

PubMed Central

2014-01-01

Background Diagnosis of dementia is challenging and requires both ruling out potentially treatable underlying causes and ruling in a diagnosis of dementia subtype to manage patients and suitably plan for the future. Objectives This analysis sought to determine the appropriate use of neuroimaging during the diagnostic work-up of dementia, including indications for neuroimaging and comparative accuracy of alternative technologies. Data Sources A literature search was performed using Ovid MEDLINE, Ovid MEDLINE In-Process and Other Non-Indexed Citations, Ovid Embase, the Wiley Cochrane Library, and the Centre for Reviews and Dissemination database, for studies published between 2000 and 2013. Review Methods Data on diagnostic accuracy and impact on clinical decision making were abstracted from included studies. Quality of evidence was assessed using GRADE. Results The search yielded 5,374 citations and 15 studies were included. Approximately 10% of dementia cases are potentially treatable, though less than 1% reverse partially or fully. Neither prediction rules nor clinical indications reliably select the subset of patients who will likely benefit from neuroimaging. Clinical utility is highest in ambiguous cases or where dementia may be mixed, and lowest for clinically diagnosed Alzheimer disease or clinically excluded vascular dementia. There is a lack of evidence that MRI is superior to CT in detecting a vascular component to dementia. Accuracy of structural imaging is moderate to high for discriminating different types of dementia. Limitations There was significant heterogeneity in estimates of diagnostic accuracy, which often prohibited a statistical summary of findings. The quality of data reported by studies prohibited calculation of likelihood ratios in the present analysis. No studies from primary care were found; thus, generalizability beyond tertiary care settings may be limited. Conclusions A diagnosis of reversible dementia is rare. Imaging has the most

Neuroimaging Craving: Urge Intensity Matters

PubMed Central

Wilson, Stephen J.; Sayette, Michael A.

2015-01-01

Functional neuroimaging has become an increasingly common tool for studying drug craving. Furthermore, functional neuroimaging studies, which have addressed an incredibly diverse array of questions regarding the nature and treatment of craving, have had a substantial impact on theoretical models of addiction. Here, we offer three points related to this sizeable and influential body of research. First, we assert that the craving most investigators seek to study represents not just a desire but a strong desire to use drugs, consistent with prominent theoretical and clinical descriptions of craving. Second, we highlight that, despite the clear conceptual and clinical emphasis on craving as an intense desire, brain imaging studies often have been explicitly designed in a way that reduces the ability to generate powerful cravings. We illustrate this point by reviewing the peak urge levels endorsed by participants in functional magnetic resonance imaging (fMRI) studies of cigarette craving in nicotine-deprived versus nondeprived smokers. Third, we suggest that brain responses measured during mild states of desire (such as following satiety) differ in fundamental ways from those measured during states of overpowering desire (i.e., craving) to use drugs. We support this position by way of a meta-analysis revealing that fMRI cue exposure studies using nicotine-deprived smokers have produced different patterns of brain activation than those using nondeprived smokers. Regarding brain imaging studies of craving, intensity of the urges matter, and more explicit attention to urge intensity in future work has the potential to yield valuable information about the nature of craving. PMID:25073979

ABrIL - Advanced Brain Imaging Lab : a cloud based computation environment for cooperative neuroimaging projects.

PubMed

Neves Tafula, Sérgio M; Moreira da Silva, Nádia; Rozanski, Verena E; Silva Cunha, João Paulo

2014-01-01

Neuroscience is an increasingly multidisciplinary and highly cooperative field where neuroimaging plays an important role. Neuroimaging rapid evolution is demanding for a growing number of computing resources and skills that need to be put in place at every lab. Typically each group tries to setup their own servers and workstations to support their neuroimaging needs, having to learn from Operating System management to specific neuroscience software tools details before any results can be obtained from each setup. This setup and learning process is replicated in every lab, even if a strong collaboration among several groups is going on. In this paper we present a new cloud service model - Brain Imaging Application as a Service (BiAaaS) - and one of its implementation - Advanced Brain Imaging Lab (ABrIL) - in the form of an ubiquitous virtual desktop remote infrastructure that offers a set of neuroimaging computational services in an interactive neuroscientist-friendly graphical user interface (GUI). This remote desktop has been used for several multi-institution cooperative projects with different neuroscience objectives that already achieved important results, such as the contribution to a high impact paper published in the January issue of the Neuroimage journal. The ABrIL system has shown its applicability in several neuroscience projects with a relatively low-cost, promoting truly collaborative actions and speeding up project results and their clinical applicability.

[Initial deficits in Alzheimer's disease: 3 practical examples].

PubMed

Jódar-Vicente, M

The aim of the first studies to determine the neuropsychological features of Alzheimer's disease (AD) were based on the concept of the disease as an homogeneous entity. However, clinical observations and the most recent research studies have demonstrated that Alzheimer's disease may present several other neuropsychological deficits on its clinical onset. in the initial process of cognitive function loss, memory deficits are seen as a consequence of hippocampal degeneration; however, a great interindividual variability is observed in the appearance of other cortical deficits. In addiction, new advances in epidemiology, neurochemistry and neuropathology support the idea that AD represents a neuropsychologically heterogeneous disorder. In AD three different subgroups have been established: patients with initial deficits in visuospatial abilities, patients with a major deterioration of linguistic abilities, and a third group with altered visuospatial and linguistic abilities. The most sensitive neuropsychological tests capable of distinguish among these differences were The Boston Naming Test (BNT) and the copy of a drawing. These results have been confirmed with single photon emission computed tomography (SPECT) images, and has been observed that patients with a pattern of a elevated right-hemispheric deterioration presented also a higher right-hipofunctionality. At the same time, patients with an elevated linguistic deficit showed a higher hipofunctionality image in the left hemisphere. In this work we present three patients from a prospective study in course, who have similar background, education, gender and disease evolution, but with an onset of the illness corresponding to each of the patterns previously described All three patients were explored with an extense neuropsychological battery of tests specially chosen for this study.

Functions of the human frontoparietal attention network: Evidence from neuroimaging

PubMed Central

Scolari, Miranda; Seidl-Rathkopf, Katharina N; Kastner, Sabine

2016-01-01

Human frontoparietal cortex has long been implicated as a source of attentional control. However, the mechanistic underpinnings of these control functions have remained elusive due to limitations of neuroimaging techniques that rely on anatomical landmarks to localize patterns of activation. The recent advent of topographic mapping via functional magnetic resonance imaging (fMRI) has allowed the reliable parcellation of the network into 18 independent subregions in individual subjects, thereby offering unprecedented opportunities to address a wide range of empirical questions as to how mechanisms of control operate. Here, we review the human neuroimaging literature that has begun to explore space-based, feature-based, object-based and category-based attentional control within the context of topographically defined frontoparietal cortex. PMID:27398396

The Evolution of Neuroimaging Research and Developmental Language Disorders.

ERIC Educational Resources Information Center

Lane, Angela B.; Foundas, Anne L.; Leonard, Christiana M.

2001-01-01

This article reviews current neuroimaging literature, including computer tomography, positron emission tomography, single photon emission spectroscopy, and magnetic resonance imaging, on individuals with developmental language disorders. The review suggests a complicated relationship between cortical morphometry and language development that is…

Pain as a fact and heuristic: how pain neuroimaging illuminates moral dimensions of law.

PubMed

Pustilnik, Amanda C

2012-05-01

In legal domains ranging from tort to torture, pain and its degree do important definitional work by delimiting boundaries of lawfulness and of entitlements. Yet, for all the work done by pain as a term in legal texts and practice, it has a confounding lack of external verifiability. Now, neuroimaging is rendering pain and myriad other subjective states at least partly ascertainable. This emerging ability to ascertain and quantify subjective states is prompting a "hedonic" or a "subjectivist" turn in legal scholarship, which has sparked a vigorous debate as to whether the quantification of subjective states might affect legal theory and practice. Subjectivists contend that much values-talk in law has been a necessary but poor substitute for quantitative determinations of subjective states--determinations that will be possible in the law's "experiential future." This Article argues the converse: that pain discourse in law frequently is a heuristic for values. Drawing on interviews and laboratory visits with neuroimaging researchers, this Article shows current and in-principle limitations of pain quantification through neuroimaging. It then presents case studies on torture-murder, torture, the death penalty, and abortion to show the largely heuristic role of pain discourse in law. Introducing the theory of "embodied morality," the Article describes how moral conceptions of rights and duties are informed by human physicality and constrained by the limits of empathic identification. Pain neuroimaging helps reveal this dual factual and heuristic nature of pain in the law, and thus itself points to the translational work required for neuroimaging to influence, much less transform, legal practice and doctrine.

A priori collaboration in population imaging: The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium.

PubMed

Adams, Hieab H H; Hilal, Saima; Schwingenschuh, Petra; Wittfeld, Katharina; van der Lee, Sven J; DeCarli, Charles; Vernooij, Meike W; Katschnig-Winter, Petra; Habes, Mohamad; Chen, Christopher; Seshadri, Sudha; van Duijn, Cornelia M; Ikram, M Kamran; Grabe, Hans J; Schmidt, Reinhold; Ikram, M Arfan

2015-12-01

Virchow-Robin spaces (VRS), or perivascular spaces, are compartments of interstitial fluid enclosing cerebral blood vessels and are potential imaging markers of various underlying brain pathologies. Despite a growing interest in the study of enlarged VRS, the heterogeneity in rating and quantification methods combined with small sample sizes have so far hampered advancement in the field. The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement (UNIVRSE) consortium was established with primary aims to harmonize rating and analysis (www.uconsortium.org). The UNIVRSE consortium brings together 13 (sub)cohorts from five countries, totaling 16,000 subjects and over 25,000 scans. Eight different magnetic resonance imaging protocols were used in the consortium. VRS rating was harmonized using a validated protocol that was developed by the two founding members, with high reliability independent of scanner type, rater experience, or concomitant brain pathology. Initial analyses revealed risk factors for enlarged VRS including increased age, sex, high blood pressure, brain infarcts, and white matter lesions, but this varied by brain region. Early collaborative efforts between cohort studies with respect to data harmonization and joint analyses can advance the field of population (neuro)imaging. The UNIVRSE consortium will focus efforts on other potential correlates of enlarged VRS, including genetics, cognition, stroke, and dementia.

A Developmental Neuroimaging Investigation of the Change Paradigm

ERIC Educational Resources Information Center

Thomas, Laura A.; Hall, Julie M.; Skup, Martha; Jenkins, Sarah E.; Pine, Daniel S.; Leibenluft, Ellen

2011-01-01

This neuroimaging study examines the development of cognitive flexibility using the Change task in a sample of youths and adults. The Change task requires subjects to inhibit a prepotent response and substitute an alternative response, and the task incorporates an algorithm that adjusts task difficulty in response to subject performance. Data from…

Cost-effectiveness of cerebrospinal biomarkers for the diagnosis of Alzheimer's disease.

PubMed

Lee, Spencer A W; Sposato, Luciano A; Hachinski, Vladimir; Cipriano, Lauren E

2017-03-16

Accurate and timely diagnosis of Alzheimer's disease (AD) is important for prompt initiation of treatment in patients with AD and to avoid inappropriate treatment of patients with false-positive diagnoses. Using a Markov model, we estimated the lifetime costs and quality-adjusted life-years (QALYs) of cerebrospinal fluid biomarker analysis in a cohort of patients referred to a neurologist or memory clinic with suspected AD who remained without a definitive diagnosis of AD or another condition after neuroimaging. Parametric values were estimated from previous health economic models and the medical literature. Extensive deterministic and probabilistic sensitivity analyses were performed to evaluate the robustness of the results. At a 12.7% pretest probability of AD, biomarker analysis after normal neuroimaging findings has an incremental cost-effectiveness ratio (ICER) of $11,032 per QALY gained. Results were sensitive to the pretest prevalence of AD, and the ICER increased to over $50,000 per QALY when the prevalence of AD fell below 9%. Results were also sensitive to patient age (biomarkers are less cost-effective in older cohorts), treatment uptake and adherence, biomarker test characteristics, and the degree to which patients with suspected AD who do not have AD benefit from AD treatment when they are falsely diagnosed. The cost-effectiveness of biomarker analysis depends critically on the prevalence of AD in the tested population. In general practice, where the prevalence of AD after clinical assessment and normal neuroimaging findings may be low, biomarker analysis is unlikely to be cost-effective at a willingness-to-pay threshold of $50,000 per QALY gained. However, when at least 1 in 11 patients has AD after normal neuroimaging findings, biomarker analysis is likely cost-effective. Specifically, for patients referred to memory clinics with memory impairment who do not present neuroimaging evidence of medial temporal lobe atrophy, pretest prevalence of AD may

Modeling Alzheimer's disease cognitive scores using multi-task sparse group lasso.

PubMed

Liu, Xiaoli; Goncalves, André R; Cao, Peng; Zhao, Dazhe; Banerjee, Arindam

2018-06-01

Alzheimer's disease (AD) is a severe neurodegenerative disorder characterized by loss of memory and reduction in cognitive functions due to progressive degeneration of neurons and their connections, eventually leading to death. In this paper, we consider the problem of simultaneously predicting several different cognitive scores associated with categorizing subjects as normal, mild cognitive impairment (MCI), or Alzheimer's disease (AD) in a multi-task learning framework using features extracted from brain images obtained from ADNI (Alzheimer's Disease Neuroimaging Initiative). To solve the problem, we present a multi-task sparse group lasso (MT-SGL) framework, which estimates sparse features coupled across tasks, and can work with loss functions associated with any Generalized Linear Models. Through comparisons with a variety of baseline models using multiple evaluation metrics, we illustrate the promising predictive performance of MT-SGL on ADNI along with its ability to identify brain regions more likely to help the characterization Alzheimer's disease progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Context is everything: From cardiovascular disease to cerebral microbleeds.

PubMed

Charidimou, Andreas; Blacker, Deborah; Viswanathan, Anand

2018-01-01

Increasingly, our approach to cerebrovascular disease has become blurred by evidence published in literature often without careful consideration of what this evidence implies for specific patients at hand. In this essay, we analyze key contextual issues in cerebrovascular small vessel disease, in an attempt to highlight the symbolic gap that exists between research and clinical practice, a recurring theme in medicine. We highlight the importance of considering context when using data from epidemiologic, neuroimaging, and biomarker studies in determining relevance to the patient at hand. We argue, that while biomarkers and neuroimaging may eventually serve to help to identify individuals with specific cerebrovascular diseases, we must always continue to understand patients in a specific clinical context. These reflections are particularly relevant when considering cerebral microbleeds-a key marker of cerebrovascular small vessel disease whose detection often raises thorny clinical dilemmas.

Cascading network failure across the Alzheimer’s disease spectrum

PubMed Central

Knopman, David S.; Gunter, Jeffrey L.; Graff-Radford, Jonathan; Vemuri, Prashanthi; Boeve, Bradley F.; Petersen, Ronald C.; Weiner, Michael W.; Jack, Clifford R.

2016-01-01

Abstract Complex biological systems are organized across various spatiotemporal scales with particular scientific disciplines dedicated to the study of each scale (e.g. genetics, molecular biology and cognitive neuroscience). When considering disease pathophysiology, one must contemplate the scale at which the disease process is being observed and how these processes impact other levels of organization. Historically Alzheimer’s disease has been viewed as a disease of abnormally aggregated proteins by pathologists and molecular biologists and a disease of clinical symptoms by neurologists and psychologists. Bridging the divide between these scales has been elusive, but the study of brain networks appears to be a pivotal inroad to accomplish this task. In this study, we were guided by an emerging systems-based conceptualization of Alzheimer’s disease and investigated changes in brain networks across the disease spectrum. The default mode network has distinct subsystems with unique functional-anatomic connectivity, cognitive associations, and responses to Alzheimer’s pathophysiology. These distinctions provide a window into the systems-level pathophysiology of Alzheimer’s disease. Using clinical phenotyping, metadata, and multimodal neuroimaging data from the Alzheimer’s Disease Neuroimaging Initiative, we characterized the pattern of default mode network subsystem connectivity changes across the entire disease spectrum (n = 128). The two main findings of this paper are (i) the posterior default mode network fails before measurable amyloid plaques and appears to initiate a connectivity cascade that continues throughout the disease spectrum; and (ii) high connectivity between the posterior default mode network and hubs of high connectivity (many located in the frontal lobe) is associated with amyloid accumulation. These findings support a system model best characterized by a cascading network failure—analogous to cascading failures seen in power grids

The iconography of mourning and its neural correlates: a functional neuroimaging study.

PubMed

Labek, Karin; Berger, Samantha; Buchheim, Anna; Bosch, Julia; Spohrs, Jennifer; Dommes, Lisa; Beschoner, Petra; Stingl, Julia C; Viviani, Roberto

2017-08-01

The present functional neuroimaging study focuses on the iconography of mourning. A culture-specific pattern of body postures of mourning individuals, mostly suggesting withdrawal, emerged from a survey of visual material. When used in different combinations in stylized drawings in our neuroimaging study, this material activated cortical areas commonly seen in studies of social cognition (temporo-parietal junction, superior temporal gyrus, and inferior temporal lobe), empathy for pain (somatosensory cortex), and loss (precuneus, middle/posterior cingular gyrus). This pattern of activation developed over time. While in the early phases of exposure lower association areas, such as the extrastriate body area, were active, in the late phases activation in parietal and temporal association areas and the prefrontal cortex was more prominent. These findings are consistent with the conventional and contextual character of iconographic material, and further differentiate it from emotionally negatively valenced and high-arousing stimuli. In future studies, this neuroimaging assay may be useful in characterizing interpretive appraisal of material of negative emotional valence. © The Author (2017). Published by Oxford University Press.

Effects of BDNF Val66Met polymorphism on brain metabolism in Alzheimer's disease.

PubMed

Xu, Cunlu; Wang, Zhenhua; Fan, Ming; Liu, Bing; Song, Ming; Zhen, Xiantong; Jiang, Tianzi

2010-08-23

Earlier studies showed that the Val66Met polymorphisms of the brain-derived neurotrophic factor differentially affect gray matter volume and brain region activities. This study used resting positron emission tomography to investigate the relationship between the polymorphisms of Val66Met and the regional cerebral metabolic rate in the brain. We analyzed the positron emission tomography images of 215 patients from the Alzheimer's Disease Neuroimaging Initiative and found significant differences in the parahippocampal gyrus, superior temporal gyrus, prefrontal cortex, and inferior parietal lobule when comparing Met carriers with noncarriers among both the normal controls and those with mild cognitive impairment. For those with Alzheimer's disease, we also found additional differences in the bilateral insula between the carriers and noncarriers.

Neural Predictors of Initiating Alcohol Use During Adolescence.

PubMed

Squeglia, Lindsay M; Ball, Tali M; Jacobus, Joanna; Brumback, Ty; McKenna, Benjamin S; Nguyen-Louie, Tam T; Sorg, Scott F; Paulus, Martin P; Tapert, Susan F

2017-02-01

Underage drinking is widely recognized as a leading public health and social problem for adolescents in the United States. Being able to identify at-risk adolescents before they initiate heavy alcohol use could have important clinical and public health implications; however, few investigations have explored individual-level precursors of adolescent substance use. This prospective investigation used machine learning with demographic, neurocognitive, and neuroimaging data in substance-naive adolescents to identify predictors of alcohol use initiation by age 18. Participants (N=137) were healthy substance-naive adolescents (ages 12-14) who underwent neuropsychological testing and structural and functional magnetic resonance imaging (sMRI and fMRI), and then were followed annually. By age 18, 70 youths (51%) initiated moderate to heavy alcohol use, and 67 remained nonusers. Random forest classification models identified the most important predictors of alcohol use from a large set of demographic, neuropsychological, sMRI, and fMRI variables. Random forest models identified 34 predictors contributing to alcohol use by age 18, including several demographic and behavioral factors (being male, higher socioeconomic status, early dating, more externalizing behaviors, positive alcohol expectancies), worse executive functioning, and thinner cortices and less brain activation in diffusely distributed regions of the brain. Incorporating a mix of demographic, behavioral, neuropsychological, and neuroimaging data may be the best strategy for identifying youths at risk for initiating alcohol use during adolescence. The identified risk factors will be useful for alcohol prevention efforts and in research to address brain mechanisms that may contribute to early drinking.

Event time analysis of longitudinal neuroimage data.

PubMed

Sabuncu, Mert R; Bernal-Rusiel, Jorge L; Reuter, Martin; Greve, Douglas N; Fischl, Bruce

2014-08-15

This paper presents a method for the statistical analysis of the associations between longitudinal neuroimaging measurements, e.g., of cortical thickness, and the timing of a clinical event of interest, e.g., disease onset. The proposed approach consists of two steps, the first of which employs a linear mixed effects (LME) model to capture temporal variation in serial imaging data. The second step utilizes the extended Cox regression model to examine the relationship between time-dependent imaging measurements and the timing of the event of interest. We demonstrate the proposed method both for the univariate analysis of image-derived biomarkers, e.g., the volume of a structure of interest, and the exploratory mass-univariate analysis of measurements contained in maps, such as cortical thickness and gray matter density. The mass-univariate method employs a recently developed spatial extension of the LME model. We applied our method to analyze structural measurements computed using FreeSurfer, a widely used brain Magnetic Resonance Image (MRI) analysis software package. We provide a quantitative and objective empirical evaluation of the statistical performance of the proposed method on longitudinal data from subjects suffering from Mild Cognitive Impairment (MCI) at baseline. Copyright © 2014 Elsevier Inc. All rights reserved.

The neuropsychiatry of hyperkinetic movement disorders: insights from neuroimaging into the neural circuit bases of dysfunction.

PubMed

Hayhow, Bradleigh D; Hassan, Islam; Looi, Jeffrey C L; Gaillard, Francesco; Velakoulis, Dennis; Walterfang, Mark

2013-01-01

Movement disorders, particularly those associated with basal ganglia disease, have a high rate of comorbid neuropsychiatric illness. We consider the pathophysiological basis of the comorbidity between movement disorders and neuropsychiatric illness by 1) reviewing the epidemiology of neuropsychiatric illness in a range of hyperkinetic movement disorders, and 2) correlating findings to evidence from studies that have utilized modern neuroimaging techniques to investigate these disorders. In addition to diseases classically associated with basal ganglia pathology, such as Huntington disease, Wilson disease, the neuroacanthocytoses, and diseases of brain iron accumulation, we include diseases associated with pathology of subcortical white matter tracts, brain stem nuclei, and the cerebellum, such as metachromatic leukodystrophy, dentatorubropallidoluysian atrophy, and the spinocerebellar ataxias. Neuropsychiatric symptoms are integral to a thorough phenomenological account of hyperkinetic movement disorders. Drawing on modern theories of cortico-subcortical circuits, we argue that these disorders can be conceptualized as disorders of complex subcortical networks with distinct functional architectures. Damage to any component of these complex information-processing networks can have variable and often profound consequences for the function of more remote neural structures, creating a diverse but nonetheless rational pattern of clinical symptomatology.

Self-development: integrating cognitive, socioemotional, and neuroimaging perspectives.

PubMed

Pfeifer, Jennifer H; Peake, Shannon J

2012-01-01

This review integrates cognitive, socioemotional, and neuroimaging perspectives on self-development. Neural correlates of key processes implicated in personal and social identity are reported from studies of children, adolescents, and adults, including autobiographical memory, direct and reflected self-appraisals, and social exclusion. While cortical midline structures of medial prefrontal cortex and medial posterior parietal cortex are consistently identified in neuroimaging studies considering personal identity from a primarily cognitive perspective ("who am I?"), additional regions are implicated by studies considering personal and social identity from a more socioemotional perspective ("what do others think about me, where do I fit in?"), especially in child or adolescent samples. The involvement of these additional regions (including tempo-parietal junction and posterior superior temporal sulcus, temporal poles, anterior insula, ventral striatum, anterior cingulate cortex, middle cingulate cortex, and ventrolateral prefrontal cortex) suggests mentalizing, emotion, and emotion regulation are central to self-development. In addition, these regions appear to function atypically during personal and social identity tasks in autism and depression, exhibiting a broad pattern of hypoactivation and hyperactivation, respectively. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multiple brain atlas database and atlas-based neuroimaging system.

PubMed

Nowinski, W L; Fang, A; Nguyen, B T; Raphel, J K; Jagannathan, L; Raghavan, R; Bryan, R N; Miller, G A

1997-01-01

For the purpose of developing multiple, complementary, fully labeled electronic brain atlases and an atlas-based neuroimaging system for analysis, quantification, and real-time manipulation of cerebral structures in two and three dimensions, we have digitized, enhanced, segmented, and labeled the following print brain atlases: Co-Planar Stereotaxic Atlas of the Human Brain by Talairach and Tournoux, Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren, Referentially Oriented Cerebral MRI Anatomy by Talairach and Tournoux, and Atlas of the Cerebral Sulci by Ono, Kubik, and Abernathey. Three-dimensional extensions of these atlases have been developed as well. All two- and three-dimensional atlases are mutually preregistered and may be interactively registered with an actual patient's data. An atlas-based neuroimaging system has been developed that provides support for reformatting, registration, visualization, navigation, image processing, and quantification of clinical data. The anatomical index contains about 1,000 structures and over 400 sulcal patterns. Several new applications of the brain atlas database also have been developed, supported by various technologies such as virtual reality, the Internet, and electronic publishing. Fusion of information from multiple atlases assists the user in comprehensively understanding brain structures and identifying and quantifying anatomical regions in clinical data. The multiple brain atlas database and atlas-based neuroimaging system have substantial potential impact in stereotactic neurosurgery and radiotherapy by assisting in visualization and real-time manipulation in three dimensions of anatomical structures, in quantitative neuroradiology by allowing interactive analysis of clinical data, in three-dimensional neuroeducation, and in brain function studies.

Neuroimaging craving: urge intensity matters.

PubMed

Wilson, Stephen J; Sayette, Michael A

2015-02-01

Functional neuroimaging has become an increasingly common tool for studying drug craving. Furthermore, functional neuroimaging studies, which have addressed an incredibly diverse array of questions regarding the nature and treatment of craving, have had a substantial impact on theoretical models of addiction. Here, we offer three points related to this sizeable and influential body of research. First, we assert that the craving most investigators seek to study represents not just a desire but a strong desire to use drugs, consistent with prominent theoretical and clinical descriptions of craving. Secondly, we highlight that, despite the clear conceptual and clinical emphasis on craving as an intense desire, brain imaging studies often have been designed explicitly in a way that reduces the ability to generate powerful cravings. We illustrate this point by reviewing the peak urge levels endorsed by participants in functional magnetic resonance imaging (fMRI) studies of cigarette craving in nicotine-deprived versus non-deprived smokers. Thirdly, we suggest that brain responses measured during mild states of desire (such as following satiety) differ in fundamental ways from those measured during states of overpowering desire (i.e. craving) to use drugs. We support this position by way of a meta-analysis revealing that fMRI cue exposure studies using nicotine-deprived smokers have produced different patterns of brain activation to those using non-deprived smokers. Regarding brain imaging studies of craving, intensity of the urges matter, and more explicit attention to urge intensity in future work has the potential to yield valuable information about the nature of craving. © 2014 Society for the Study of Addiction.

Altered Brain Activity in Unipolar Depression Revisited: Meta-analyses of Neuroimaging Studies.

PubMed

Müller, Veronika I; Cieslik, Edna C; Serbanescu, Ilinca; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B

2017-01-01

During the past 20 years, numerous neuroimaging experiments have investigated aberrant brain activation during cognitive and emotional processing in patients with unipolar depression (UD). The results of those investigations, however, vary considerably; moreover, previous meta-analyses also yielded inconsistent findings. To readdress aberrant brain activation in UD as evidenced by neuroimaging experiments on cognitive and/or emotional processing. Neuroimaging experiments published from January 1, 1997, to October 1, 2015, were identified by a literature search of PubMed, Web of Science, and Google Scholar using different combinations of the terms fMRI (functional magnetic resonance imaging), PET (positron emission tomography), neural, major depression, depression, major depressive disorder, unipolar depression, dysthymia, emotion, emotional, affective, cognitive, task, memory, working memory, inhibition, control, n-back, and Stroop. Neuroimaging experiments (using fMRI or PET) reporting whole-brain results of group comparisons between adults with UD and healthy control individuals as coordinates in a standard anatomic reference space and using an emotional or/and cognitive challenging task were selected. Coordinates reported to show significant activation differences between UD and healthy controls during emotional or cognitive processing were extracted. By using the revised activation likelihood estimation algorithm, different meta-analyses were calculated. Meta-analyses tested for brain regions consistently found to show aberrant brain activation in UD compared with controls. Analyses were calculated across all emotional processing experiments, all cognitive processing experiments, positive emotion processing, negative emotion processing, experiments using emotional face stimuli, experiments with a sex discrimination task, and memory processing. All meta-analyses were calculated across experiments independent of reporting an increase or decrease of activity in

The receiver operational characteristic for binary classification with multiple indices and its application to the neuroimaging study of Alzheimer's disease.

PubMed

Wu, Xia; Li, Juan; Ayutyanont, Napatkamon; Protas, Hillary; Jagust, William; Fleisher, Adam; Reiman, Eric; Yao, Li; Chen, Kewei

2013-01-01

Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple data sources (referred to as multi-indices), such as multimodal neuroimaging data sets, cognitive tests, and clinical ratings and genomic data in Alzheimer’s disease (AD) studies, the single-index-based ROC underutilizes all available information. For a long time, a number of algorithmic/analytic approaches combining multiple indices have been widely used to simultaneously incorporate multiple sources. In this study, we propose an alternative for combining multiple indices using logical operations, such as “AND,” “OR,” and “at least n” (where n is an integer), to construct multivariate ROC (multiV-ROC) and characterize the sensitivity and specificity statistically associated with the use of multiple indices. With and without the “leave-one-out” cross-validation, we used two data sets from AD studies to showcase the potentially increased sensitivity/specificity of the multiV-ROC in comparison to the single-index ROC and linear discriminant analysis (an analytic way of combining multi-indices). We conclude that, for the data sets we investigated, the proposed multiV-ROC approach is capable of providing a natural and practical alternative with improved classification accuracy as compared to univariate ROC and linear discriminant analysis.

Neuroimaging in pediatric traumatic head injury: diagnostic considerations and relationships to neurobehavioral outcome.

PubMed

Bigler, E D

1999-08-01

Contemporary neuorimaging techniques in child traumatic brain injury are reviewed, with an emphasis on computerized tomography (CT) and magnetic resonance (MR) imaging. A brief overview of MR spectroscopy (MRS), functional MR imaging (fMRI), single-photon emission computed tomography (SPECT), and magnetoencephalography (MEG) is also provided because these techniques will likely constitute important neuroimaging techniques of the future. Numerous figures are provided to illustrate the multifaceted manner in which traumatic deficits can be imaged and the role of neuroimaging information as it relates to TBI outcome.

Is the statistic value all we should care about in neuroimaging?

PubMed

Chen, Gang; Taylor, Paul A; Cox, Robert W

2017-02-15

Here we address an important issue that has been embedded within the neuroimaging community for a long time: the absence of effect estimates in results reporting in the literature. The statistic value itself, as a dimensionless measure, does not provide information on the biophysical interpretation of a study, and it certainly does not represent the whole picture of a study. Unfortunately, in contrast to standard practice in most scientific fields, effect (or amplitude) estimates are usually not provided in most results reporting in the current neuroimaging publications and presentations. Possible reasons underlying this general trend include (1) lack of general awareness, (2) software limitations, (3) inaccurate estimation of the BOLD response, and (4) poor modeling due to our relatively limited understanding of FMRI signal components. However, as we discuss here, such reporting damages the reliability and interpretability of the scientific findings themselves, and there is in fact no overwhelming reason for such a practice to persist. In order to promote meaningful interpretation, cross validation, reproducibility, meta and power analyses in neuroimaging, we strongly suggest that, as part of good scientific practice, effect estimates should be reported together with their corresponding statistic values. We provide several easily adaptable recommendations for facilitating this process. Published by Elsevier Inc.

Neuroimaging Research with Children: Ethical Issues and Case Scenarios

ERIC Educational Resources Information Center

Coch, Donna

2007-01-01

There are few available resources for learning and teaching about ethical issues in neuroimaging research with children, who constitute a special and vulnerable population. Here, a brief review of ethical issues in developmental research, situated within the emerging field of neuroethics, highlights the increasingly interdisciplinary nature of…

Coronary heart disease mortality and hormone therapy before and after the Women's Health Initiative.

PubMed

Tuomikoski, Pauliina; Lyytinen, Heli; Korhonen, Pasi; Hoti, Fabian; Vattulainen, Pia; Gissler, Mika; Ylikorkala, Olavi; Mikkola, Tomi S

2014-11-01

To assess whether coronary heart disease mortality in Finnish hormone therapy (HT) users differed before and after 2002 when the Women's Health Initiative study was published. The risks of coronary heart disease death in HT users in relation to the age-matched background population were compared between the pre- (1995-2001) and post- (2002-2009) Women's Health Initiative eras. We used a nationwide register on HT (ie, estradiol with or without progestin) reimbursement and linked them to causes of death in 290,272 women aged 40 years or older. Exposure to HT for 1 year or less was accompanied by a 29% reduction (0.71; 0.63-0.80; three per 10,000 fewer deaths) and an exposure of 1-8 years with a 43% reduction (0.57; 0.48-0.66; three per 10,000 fewer deaths) in the risk of coronary heart disease death in the pre-Women's Health Initiative era. In the post-Women's Health Initiative era, HT use of 1 year or less was associated with an 18% reduction (0.82; 0.76-1.00; one per 10,000 fewer deaths) and an exposure of 1-8 years with a 54% reduction (0.46; 0.32-0.64; two per 10,000 fewer deaths) in coronary heart disease mortality. Discontinuation of HT was associated with an increased risk of cardiac death of 42% (1.42; 1.17-1.71; seven per 10,000 extra deaths) in the pre-Women's Health Initiative era and 31% (1.31; 0.92-1.82; two per 10,000 extra deaths) in the post-Women's Health Initiative era during the first posttreatment year. This risk increase vanished in further follow-up during both eras. Changes in HT use after the Women's Health Initiative failed to affect coronary heart disease mortality of HT users in this nationwide study.

Cognitive and emotional processes during dreaming: a neuroimaging view.

PubMed

Desseilles, Martin; Dang-Vu, Thien Thanh; Sterpenich, Virginie; Schwartz, Sophie

2011-12-01

Dream is a state of consciousness characterized by internally-generated sensory, cognitive and emotional experiences occurring during sleep. Dream reports tend to be particularly abundant, with complex, emotional, and perceptually vivid experiences after awakenings from rapid eye movement (REM) sleep. This is why our current knowledge of the cerebral correlates of dreaming, mainly derives from studies of REM sleep. Neuroimaging results show that REM sleep is characterized by a specific pattern of regional brain activity. We demonstrate that this heterogeneous distribution of brain activity during sleep explains many typical features in dreams. Reciprocally, specific dream characteristics suggest the activation of selective brain regions during sleep. Such an integration of neuroimaging data of human sleep, mental imagery, and the content of dreams is critical for current models of dreaming; it also provides neurobiological support for an implication of sleep and dreaming in some important functions such as emotional regulation. Copyright © 2010 Elsevier Inc. All rights reserved.

Effects of auditory cues on gait initiation and turning in patients with Parkinson's disease.

PubMed

Gómez-González, J; Martín-Casas, P; Cano-de-la-Cuerda, R

2016-12-08

To review the available scientific evidence about the effectiveness of auditory cues during gait initiation and turning in patients with Parkinson's disease. We conducted a literature search in the following databases: Brain, PubMed, Medline, CINAHL, Scopus, Science Direct, Web of Science, Cochrane Database of Systematic Reviews, Cochrane Library Plus, CENTRAL, Trip Database, PEDro, DARE, OTseeker, and Google Scholar. We included all studies published between 2007 and 2016 and evaluating the influence of auditory cues on independent gait initiation and turning in patients with Parkinson's disease. The methodological quality of the studies was assessed with the Jadad scale. We included 13 studies, all of which had a low methodological quality (Jadad scale score≤2). In these studies, high-intensity, high-frequency auditory cues had a positive impact on gait initiation and turning. More specifically, they 1) improved spatiotemporal and kinematic parameters; 2) decreased freezing, turning duration, and falls; and 3) increased gait initiation speed, muscle activation, and gait speed and cadence in patients with Parkinson's disease. We need studies of better methodological quality to establish the Parkinson's disease stage in which auditory cues are most beneficial, as well as to determine the most effective type and frequency of the auditory cue during gait initiation and turning in patients with Parkinson's disease. Copyright © 2016 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Inflaming the Brain: CRPS a model disease to understand Neuroimmune interactions in Chronic Pain

PubMed Central

Linnman, C; Becerra, L; Borsook, D

2012-01-01

We review current concepts in CRPS from a neuroimaging perspective and point out topics and potential mechanisms that are suitable to be investigated in the next step towards understanding the pathophysiology of CRPS. We have outlined functional aspects of the syndrome, from initiating lesion via inflammatory mechanisms to CNS change and associated sickness behavior, with current evidence for up-regulation of immunological factors in CRPS, neuroimaging of systemic inflammation, and neuroimaging findings in CRPS. The initiation, maintenances and CNS targets implicated in CRPS and in the neuro-inflammatory reflex are discussed in terms of CRPS symptoms and recent preclinical studies. Potential avenues for investigating CRPS with PET and fMRI are described, along with roles of inflammation, treatment and behavior in CRPS. It is our hope that this outline will provoke discussion and promote further empirical studies on the interactions between central and peripheral inflammatory pathways manifest in CRPS. PMID:23188523

Inflaming the brain: CRPS a model disease to understand neuroimmune interactions in chronic pain.

PubMed

Linnman, C; Becerra, L; Borsook, D

2013-06-01

We review current concepts in CRPS from a neuroimaging perspective and point out topics and potential mechanisms that are suitable to be investigated in the next step towards understanding the pathophysiology of CRPS. We have outlined functional aspects of the syndrome, from initiating lesion via inflammatory mechanisms to CNS change and associated sickness behavior, with current evidence for up-regulation of immunological factors in CRPS, neuroimaging of systemic inflammation, and neuroimaging findings in CRPS. The initiation, maintenances and CNS targets implicated in CRPS and in the neuro-inflammatory reflex are discussed in terms of CRPS symptoms and recent preclinical studies. Potential avenues for investigating CRPS with PET and fMRI are described, along with roles of inflammation, treatment and behavior in CRPS. It is our hope that this outline will provoke discussion and promote further empirical studies on the interactions between central and peripheral inflammatory pathways manifest in CRPS.

Neuroimaging Findings of Congenital Toxoplasmosis, Cytomegalovirus, and Zika Virus Infections: A Comparison of Three Cases.

PubMed

Werner, Heron; Daltro, Pedro; Fazecas, Tatiana; Zare Mehrjardi, Mohammad; Araujo Júnior, Edward

2017-12-01

Toxoplasmosis, cytomegalovirus (CMV), and Zika virus (ZIKV) are among the common infectious agents that may infect the fetuses vertically. Clinical presentations of these congenital infections overlap significantly, and it is usually impossible to determine the causative agent clinically. The objective was the comparison of neuroimaging findings in three fetuses who underwent intrauterine infection by toxoplasmosis, CMV, and ZIKV. Three confirmed cases of congenital toxoplasmosis, CMV, and ZIKV infections were included in the study over 7 months prospectively. Prenatal ultrasound, fetal brain MRI, and postnatal neuroimaging (CT or MRI) were performed on all of the included cases and interpreted by an expert radiologist. The mean GA at the time of prenatal imaging was 34.5 ± 3.5 weeks. The main neuroimaging findings in congenital toxoplasmosis were randomly distributed brain calcifications and ventricular dilatation on ultrasounds (US), as well as white matter signal change on fetal brain MRI. The main neuroimaging findings of congenital CMV infection included microcephaly, ventriculomegaly, and periventricular calcifications on US, as well as pachygyria revealed by fetal MRI. The case of congenital ZIKV infection showed microcephaly, ventriculomegaly, and periventricular calcifications on ultrasound, as well as brain atrophy and brain surface smoothness on fetal MRI. Although the neuroimaging findings in congenital infections are not pathognomonic, in combination with the patient history may be suggestive of one of the infectious agents, which will guide the management strategy. Copyright © 2017 The Society of Obstetricians and Gynaecologists of Canada/La Société des obstétriciens et gynécologues du Canada. Published by Elsevier Inc. All rights reserved.

CAN NEUROIMAGING HELP US TO UNDERSTAND AND CLASSIFY SOMATOFORM DISORDERS? A SYSTEMATIC AND CRITICAL REVIEW

PubMed Central

Browning, Michael; Fletcher, Paul; Sharpe, Michael

2011-01-01

Objective Debate about the nature of the somatoform disorders and their current diagnostic classification has been stimulated by the anticipation of new editions of the DSM and ICD diagnostic classifications. In the current paper we systematically review the literature on the neuroimaging of somatoform disorders and related conditions with the aim of addressing two specific questions: Is there evidence of altered neural function or structure that is specifically associated with somatoform disorders? What conclusions can we draw from these findings about the etiology of somatoform disorders? Methods Studies reporting neuroimaging findings in patients with a somatoform disorder, or a functional somatic syndrome (such as Fibromyalgia) were found using Pubmed, PsycINFO and EMBASE database searches. Reported structural and functional neuroimaging findings were then extracted to form a narrative review. Results A relatively mature literature on symptoms of pain, and less developed literatures on conversion and fatigue symptoms were identified. The available evidence indicates that, when compared to non-clinical groups, somatoform diagnoses are associated with increased activity of limbic regions in response to painful stimuli and a generalized decrease in grey matter density; however methodological considerations restrict the interpretation of these findings. Conclusions While the neuroimaging literature has provided evidence about the possible mechanisms underlying somatoform disorders this is not yet sufficient to provide a basis for classification. By adopting a wider variety of experimental designs and a more dynamic approach to diagnosis there is every reason to be hopeful that neuroimaging data will play a significant role in future taxonomies. PMID:21217095

Meta-Analysis of Functional Neuroimaging and Cognitive Control Studies in Schizophrenia: Preliminary Elucidation of a Core Dysfunctional Timing Network

PubMed Central

Alústiza, Irene; Radua, Joaquim; Albajes-Eizagirre, Anton; Domínguez, Manuel; Aubá, Enrique; Ortuño, Felipe

2016-01-01

Timing and other cognitive processes demanding cognitive control become interlinked when there is an increase in the level of difficulty or effort required. Both functions are interrelated and share neuroanatomical bases. A previous meta-analysis of neuroimaging studies found that people with schizophrenia had significantly lower activation, relative to normal controls, of most right hemisphere regions of the time circuit. This finding suggests that a pattern of disconnectivity of this circuit, particularly in the supplementary motor area, is a trait of this mental disease. We hypothesize that a dysfunctional temporal/cognitive control network underlies both cognitive and psychiatric symptoms of schizophrenia and that timing dysfunction is at the root of the cognitive deficits observed. The goal of our study was to look, in schizophrenia patients, for brain structures activated both by execution of cognitive tasks requiring increased effort and by performance of time perception tasks. We conducted a signed differential mapping (SDM) meta-analysis of functional neuroimaging studies in schizophrenia patients assessing the brain response to increasing levels of cognitive difficulty. Then, we performed a multimodal meta-analysis to identify common brain regions in the findings of that SDM meta-analysis and our previously-published activation likelihood estimate (ALE) meta-analysis of neuroimaging of time perception in schizophrenia patients. The current study supports the hypothesis that there exists an overlap between neural structures engaged by both timing tasks and non-temporal cognitive tasks of escalating difficulty in schizophrenia. The implication is that a deficit in timing can be considered as a trait marker of the schizophrenia cognitive profile. PMID:26925013

Alzheimer disease-like clinical phenotype in a family with FTDP-17 caused by a MAPT R406W mutation.

PubMed

Lindquist, S G; Holm, I E; Schwartz, M; Law, I; Stokholm, J; Batbayli, M; Waldemar, G; Nielsen, J E

2008-04-01

We report clinical, molecular, neuroimaging and neuropathological features of a Danish family with autosomal dominant inherited dementia, a clinical phenotype resembling Alzheimer's disease and a pathogenic mutation (R406W) in the microtubule associated protein tau (MAPT) gene. Pre-symptomatic and affected family members underwent multidisciplinary (clinical, molecular, neuroimaging and neuropathological) examinations. Treatment with memantine in a family member with early symptoms, based on the clinical phenotype and the lack of specific treatment, appears to stabilize the disease course and increase the glucose metabolism in cortical and subcortical areas, as determined by serial [F(18)]FDG-PET scanning before and after initiation of treatment. Neuropathological examination of a second affected and mutation-positive family member showed moderate atrophy of the temporal lobes including the hippocampi. Microscopy revealed abundant numbers of tau-positive neurofibrillary tangles in all cortical areas and in some brainstem nuclei corresponding to a diagnosis of frontotemporal lobe degeneration on the basis of a MAPT mutation. The clinical and genetic heterogeneity of autosomal dominant inherited dementia must be taken into account in the genetic counselling and genetic testing of families with autosomal dominantly inherited dementia in general.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data.

PubMed

Thompson, Paul M; Stein, Jason L; Medland, Sarah E; Hibar, Derrek P; Vasquez, Alejandro Arias; Renteria, Miguel E; Toro, Roberto; Jahanshad, Neda; Schumann, Gunter; Franke, Barbara; Wright, Margaret J; Martin, Nicholas G; Agartz, Ingrid; Alda, Martin; Alhusaini, Saud; Almasy, Laura; Almeida, Jorge; Alpert, Kathryn; Andreasen, Nancy C; Andreassen, Ole A; Apostolova, Liana G; Appel, Katja; Armstrong, Nicola J; Aribisala, Benjamin; Bastin, Mark E; Bauer, Michael; Bearden, Carrie E; Bergmann, Orjan; Binder, Elisabeth B; Blangero, John; Bockholt, Henry J; Bøen, Erlend; Bois, Catherine; Boomsma, Dorret I; Booth, Tom; Bowman, Ian J; Bralten, Janita; Brouwer, Rachel M; Brunner, Han G; Brohawn, David G; Buckner, Randy L; Buitelaar, Jan; Bulayeva, Kazima; Bustillo, Juan R; Calhoun, Vince D; Cannon, Dara M; Cantor, Rita M; Carless, Melanie A; Caseras, Xavier; Cavalleri, Gianpiero L; Chakravarty, M Mallar; Chang, Kiki D; Ching, Christopher R K; Christoforou, Andrea; Cichon, Sven; Clark, Vincent P; Conrod, Patricia; Coppola, Giovanni; Crespo-Facorro, Benedicto; Curran, Joanne E; Czisch, Michael; Deary, Ian J; de Geus, Eco J C; den Braber, Anouk; Delvecchio, Giuseppe; Depondt, Chantal; de Haan, Lieuwe; de Zubicaray, Greig I; Dima, Danai; Dimitrova, Rali; Djurovic, Srdjan; Dong, Hongwei; Donohoe, Gary; Duggirala, Ravindranath; Dyer, Thomas D; Ehrlich, Stefan; Ekman, Carl Johan; Elvsåshagen, Torbjørn; Emsell, Louise; Erk, Susanne; Espeseth, Thomas; Fagerness, Jesen; Fears, Scott; Fedko, Iryna; Fernández, Guillén; Fisher, Simon E; Foroud, Tatiana; Fox, Peter T; Francks, Clyde; Frangou, Sophia; Frey, Eva Maria; Frodl, Thomas; Frouin, Vincent; Garavan, Hugh; Giddaluru, Sudheer; Glahn, David C; Godlewska, Beata; Goldstein, Rita Z; Gollub, Randy L; Grabe, Hans J; Grimm, Oliver; Gruber, Oliver; Guadalupe, Tulio; Gur, Raquel E; Gur, Ruben C; Göring, Harald H H; Hagenaars, Saskia; Hajek, Tomas; Hall, Geoffrey B; Hall, Jeremy; Hardy, John; Hartman, Catharina A; Hass, Johanna; Hatton, Sean N; Haukvik, Unn K; Hegenscheid, Katrin; Heinz, Andreas; Hickie, Ian B; Ho, Beng-Choon; Hoehn, David; Hoekstra, Pieter J; Hollinshead, Marisa; Holmes, Avram J; Homuth, Georg; Hoogman, Martine; Hong, L Elliot; Hosten, Norbert; Hottenga, Jouke-Jan; Hulshoff Pol, Hilleke E; Hwang, Kristy S; Jack, Clifford R; Jenkinson, Mark; Johnston, Caroline; Jönsson, Erik G; Kahn, René S; Kasperaviciute, Dalia; Kelly, Sinead; Kim, Sungeun; Kochunov, Peter; Koenders, Laura; Krämer, Bernd; Kwok, John B J; Lagopoulos, Jim; Laje, Gonzalo; Landen, Mikael; Landman, Bennett A; Lauriello, John; Lawrie, Stephen M; Lee, Phil H; Le Hellard, Stephanie; Lemaître, Herve; Leonardo, Cassandra D; Li, Chiang-Shan; Liberg, Benny; Liewald, David C; Liu, Xinmin; Lopez, Lorna M; Loth, Eva; Lourdusamy, Anbarasu; Luciano, Michelle; Macciardi, Fabio; Machielsen, Marise W J; Macqueen, Glenda M; Malt, Ulrik F; Mandl, René; Manoach, Dara S; Martinot, Jean-Luc; Matarin, Mar; Mather, Karen A; Mattheisen, Manuel; Mattingsdal, Morten; Meyer-Lindenberg, Andreas; McDonald, Colm; McIntosh, Andrew M; McMahon, Francis J; McMahon, Katie L; Meisenzahl, Eva; Melle, Ingrid; Milaneschi, Yuri; Mohnke, Sebastian; Montgomery, Grant W; Morris, Derek W; Moses, Eric K; Mueller, Bryon A; Muñoz Maniega, Susana; Mühleisen, Thomas W; Müller-Myhsok, Bertram; Mwangi, Benson; Nauck, Matthias; Nho, Kwangsik; Nichols, Thomas E; Nilsson, Lars-Göran; Nugent, Allison C; Nyberg, Lars; Olvera, Rene L; Oosterlaan, Jaap; Ophoff, Roel A; Pandolfo, Massimo; Papalampropoulou-Tsiridou, Melina; Papmeyer, Martina; Paus, Tomas; Pausova, Zdenka; Pearlson, Godfrey D; Penninx, Brenda W; Peterson, Charles P; Pfennig, Andrea; Phillips, Mary; Pike, G Bruce; Poline, Jean-Baptiste; Potkin, Steven G; Pütz, Benno; Ramasamy, Adaikalavan; Rasmussen, Jerod; Rietschel, Marcella; Rijpkema, Mark; Risacher, Shannon L; Roffman, Joshua L; Roiz-Santiañez, Roberto; Romanczuk-Seiferth, Nina; Rose, Emma J; Royle, Natalie A; Rujescu, Dan; Ryten, Mina; Sachdev, Perminder S; Salami, Alireza; Satterthwaite, Theodore D; Savitz, Jonathan; Saykin, Andrew J; Scanlon, Cathy; Schmaal, Lianne; Schnack, Hugo G; Schork, Andrew J; Schulz, S Charles; Schür, Remmelt; Seidman, Larry; Shen, Li; Shoemaker, Jody M; Simmons, Andrew; Sisodiya, Sanjay M; Smith, Colin; Smoller, Jordan W; Soares, Jair C; Sponheim, Scott R; Sprooten, Emma; Starr, John M; Steen, Vidar M; Strakowski, Stephen; Strike, Lachlan; Sussmann, Jessika; Sämann, Philipp G; Teumer, Alexander; Toga, Arthur W; Tordesillas-Gutierrez, Diana; Trabzuni, Daniah; Trost, Sarah; Turner, Jessica; Van den Heuvel, Martijn; van der Wee, Nic J; van Eijk, Kristel; van Erp, Theo G M; van Haren, Neeltje E M; van 't Ent, Dennis; van Tol, Marie-Jose; Valdés Hernández, Maria C; Veltman, Dick J; Versace, Amelia; Völzke, Henry; Walker, Robert; Walter, Henrik; Wang, Lei; Wardlaw, Joanna M; Weale, Michael E; Weiner, Michael W; Wen, Wei; Westlye, Lars T; Whalley, Heather C; Whelan, Christopher D; White, Tonya; Winkler, Anderson M; Wittfeld, Katharina; Woldehawariat, Girma; Wolf, Christiane; Zilles, David; Zwiers, Marcel P; Thalamuthu, Anbupalam; Schofield, Peter R; Freimer, Nelson B; Lawrence, Natalia S; Drevets, Wayne

2014-06-01

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Functional neuroimaging applications for assessment and rehabilitation planning in patients with disorders of consciousness.

PubMed

Giacino, Joseph T; Hirsch, Joy; Schiff, Nicholas; Laureys, Steven

2006-12-01

To describe the theoretic framework, design, and potential clinical applications of functional neuroimaging protocols in patients with disorders of consciousness. Recent published literature and authors' own work. Studies using functional neuroimaging techniques to investigate cognitive processing in patients diagnosed with vegetative and minimally conscious state. Not applicable. Positron-emission tomography activation studies suggest that the vegetative state represents a global disconnection syndrome in which higher order association cortices are functionally disconnected from primary cortical areas. In contrast, patterns of activation in functional magnetic resonance imaging studies of patients in the minimally conscious state show preservation of large-scale cortical networks associated with language and visual processing. Novel applications of functional neuroimaging in patients with disorders of consciousness may aid in differential diagnosis, prognostic assessment and identification of pathophysiologic mechanisms. Improvements in patient characterization may, in turn, provide new opportunities for restoration of function through interventional neuromodulation.

78 FR 17412 - Disease, Disability, and Injury Prevention and Control Special Emphasis Panel (SEP): Initial Review

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-21

... Control of Neglected Tropical Diseases in Africa, FOA GH13-002, initial review. In accordance with Section... Neglected Tropical Diseases in Africa, FOA GH13-002, initial review.'' Contact Person for More Information...

Degree of host susceptibility in the initial disease outbreak influences subsequent epidemic spread

PubMed Central

Severns, Paul M.; Estep, Laura K.; Sackett, Kathryn E.; Mundt, Christopher C.

2014-01-01

Summary Disease epidemics typically begin as an outbreak of a relatively small, spatially explicit population of infected individuals (focus), in which disease prevalence increases and rapidly spreads into the uninfected, at-risk population. Studies of epidemic spread typically address factors influencing disease spread through the at-risk population, but the initial outbreak may strongly influence spread of the subsequent epidemic.We initiated wheat stripe rust Puccinia striiformis f. sp. tritici epidemics to assess the influence of the focus on final disease prevalence when the degree of disease susceptibility differed between the at-risk and focus populations.When the focus/at-risk plantings consisted of partially genetic resistant and susceptible cultivars, final disease prevalence was statistically indistinguishable from epidemics produced by the focus cultivar in monoculture. In these experimental epidemics, disease prevalence was not influenced by the transition into an at-risk population that differed in disease susceptibility. Instead, the focus appeared to exert a dominant influence on the subsequent epidemic.Final disease prevalence was not consistently attributable to either the focus or the at-risk population when focus/at-risk populations were planted in a factorial set-up with a mixture (~28% susceptible and 72% resistant) and susceptible individuals. In these experimental epidemics, spatial heterogeneity in disease susceptibility within the at-risk population appeared to counter the dominant influence of the focus.Cessation of spore production from the focus (through fungicide/glyphosate application) after 1.3 generations of stripe rust spread did not reduce final disease prevalence, indicating that the focus influence on disease spread is established early in the epidemic.Synthesis and applications. Our experiments indicated that outbreak conditions can be highly influential on epidemic spread, even when disease resistance in the at-risk population

A disease state fingerprint for evaluation of Alzheimer's disease.

PubMed

Mattila, Jussi; Koikkalainen, Juha; Virkki, Arho; Simonsen, Anja; van Gils, Mark; Waldemar, Gunhild; Soininen, Hilkka; Lötjönen, Jyrki

2011-01-01

Diagnostic processes of Alzheimer's disease (AD) are evolving. Knowledge about disease-specific biomarkers is constantly increasing and larger volumes of data are being measured from patients. To gain additional benefits from the collected data, a novel statistical modeling and data visualization system is proposed for supporting clinical diagnosis of AD. The proposed system computes an evidence-based estimate of a patient's AD state by comparing his or her heterogeneous neuropsychological, clinical, and biomarker data to previously diagnosed cases. The AD state in this context denotes a patient's degree of similarity to previously diagnosed disease population. A summary of patient data and results of the computation are displayed in a succinct Disease State Fingerprint (DSF) visualization. The visualization clearly discloses how patient data contributes to the AD state, facilitating rapid interpretation of the information. To model the AD state from complex and heterogeneous patient data, a statistical Disease State Index (DSI) method underlying the DSF has been developed. Using baseline data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the ability of the DSI to model disease progression from elderly healthy controls to AD and its ability to predict conversion from mild cognitive impairment (MCI) to AD were assessed. It was found that the DSI provides well-behaving AD state estimates, corresponding well with the actual diagnoses. For predicting conversion from MCI to AD, the DSI attains performance similar to state-of-the-art reference classifiers. The results suggest that the DSF establishes an effective decision support and data visualization framework for improving AD diagnostics, allowing clinicians to rapidly analyze large quantities of diverse patient data.

Alzheimer Disease

PubMed Central

Apostolova, Liana G.

2016-01-01

ABSTRACT Purpose of Review: This article discusses the recent advances in the diagnosis and treatment of Alzheimer disease (AD). Recent Findings: In recent years, significant advances have been made in the fields of genetics, neuroimaging, clinical diagnosis, and staging of AD. One of the most important recent advances in AD is our ability to visualize amyloid pathology in the living human brain. The newly revised criteria for diagnosis of AD dementia embrace the use for biomarkers as supportive evidence for the underlying pathology. Guidelines for the responsible use of amyloid positron emission tomography (PET) have been developed, and the clinical and economic implications of amyloid PET imaging are actively being explored. Summary: Our improved understanding of the clinical onset, progression, neuroimaging, pathologic features, genetics, and other risk factors for AD impacts the approaches to clinical diagnosis and future therapeutic interventions. PMID:27042902

Neuroinformatics Database (NiDB) – A Modular, Portable Database for the Storage, Analysis, and Sharing of Neuroimaging Data

PubMed Central

Anderson, Beth M.; Stevens, Michael C.; Glahn, David C.; Assaf, Michal; Pearlson, Godfrey D.

2013-01-01

We present a modular, high performance, open-source database system that incorporates popular neuroimaging database features with novel peer-to-peer sharing, and a simple installation. An increasing number of imaging centers have created a massive amount of neuroimaging data since fMRI became popular more than 20 years ago, with much of that data unshared. The Neuroinformatics Database (NiDB) provides a stable platform to store and manipulate neuroimaging data and addresses several of the impediments to data sharing presented by the INCF Task Force on Neuroimaging Datasharing, including 1) motivation to share data, 2) technical issues, and 3) standards development. NiDB solves these problems by 1) minimizing PHI use, providing a cost effective simple locally stored platform, 2) storing and associating all data (including genome) with a subject and creating a peer-to-peer sharing model, and 3) defining a sample, normalized definition of a data storage structure that is used in NiDB. NiDB not only simplifies the local storage and analysis of neuroimaging data, but also enables simple sharing of raw data and analysis methods, which may encourage further sharing. PMID:23912507

Annual Research Review: Understudied populations within the autism spectrum – current trends and future directions in neuroimaging research

PubMed Central

Jack, Allison; Pelphrey, Kevin

2017-01-01

Background Autism spectrum disorders (ASDs) are a heterogeneous group of neurodevelopmental conditions that vary in both etiology and phenotypic expression. Expressions of ASD characterized by a more severe phenotype, including autism with intellectual disability (ASD+ID), autism with a history of developmental regression (ASD+R), and minimally verbal autism (ASD+MV) are understudied generally, and especially in the domain of neuroimaging. However, neuroimaging methods are a potentially powerful tool for understanding the etiology of these ASD subtypes. Scope and Methodology This review evaluates existing neuroimaging research on ASD+MV, ASD+ID, and ASD+R, identified by a search of the literature using the PubMed database, and discusses methodological, theoretical, and practical considerations for future research involving neuroimaging assessment of these populations. Findings There is a paucity of neuroimaging research on ASD+ID, ASD+MV, and ASD+R, and what findings do exist are often contradictory, or so sparse as to be ungeneralizable. We suggest that while greater sample sizes and more studies are necessary, more important would be a paradigm shift toward multimodal (e.g., imaging genetics) approaches that allow for the characterization of heterogeneity within etiologically diverse samples. PMID:28102566

Attention to pain! A neurocognitive perspective on attentional modulation of pain in neuroimaging studies.

PubMed

Torta, D M; Legrain, V; Mouraux, A; Valentini, E

2017-04-01

Several studies have used neuroimaging techniques to investigate brain correlates of the attentional modulation of pain. Although these studies have advanced the knowledge in the field, important confounding factors such as imprecise theoretical definitions of attention, incomplete operationalization of the construct under exam, and limitations of techniques relying on measuring regional changes in cerebral blood flow have hampered the potential relevance of the conclusions. Here, we first provide an overview of the major theories of attention and of attention in the study of pain to bridge theory and experimental results. We conclude that load and motivational/affective theories are particularly relevant to study the attentional modulation of pain and should be carefully integrated in functional neuroimaging studies. Then, we summarize previous findings and discuss the possible neural correlates of the attentional modulation of pain. We discuss whether classical functional neuroimaging techniques are suitable to measure the effect of a fluctuating process like attention, and in which circumstances functional neuroimaging can be reliably used to measure the attentional modulation of pain. Finally, we argue that the analysis of brain networks and spontaneous oscillations may be a crucial future development in the study of attentional modulation of pain, and why the interplay between attention and pain, as examined so far, may rely on neural mechanisms shared with other sensory modalities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Molecular neuroimaging in degenerative dementias.

PubMed

Jiménez Bonilla, J F; Carril Carril, J M

2013-01-01

In the context of the limitations of structural imaging, brain perfusion and metabolism using SPECT and PET have provided relevant information for the study of cognitive decline. The introduction of the radiotracers for cerebral amyloid imaging has changed the diagnostic strategy regarding Alzheimer's disease, which is currently considered to be a "continuum." According to this new paradigm, the increasing amyloid load would be associated to the preclinical phase and mild cognitive impairment. It has been possible to observe "in vivo" images using 11C-PIB and PET scans. The characteristics of the 11C-PIB image include specific high brain cortical area retention in the positive cases with typical distribution pattern and no retention in the negative cases. This, in combination with 18F-FDG PET, is the basis of molecular neuroimaging as a biomarker. At present, its prognostic value is being evaluated in longitudinal studies. 11C-PIB-PET has become the reference radiotracer to evaluate the presence of cerebral amyloid. However, its availability is limited due to the need for a nearby cyclotron. Therefore, 18F labeled radiotracers are being introduced. Our experience in the last two years with 11C-PIB, first in the research phase and then as being clinically applied, has shown the utility of the technique in the clinical field, either alone or in combination with FDG. Thus, amyloid image is a useful tool for the differential diagnosis of dementia and it is a potentially useful method for early diagnosis and evaluation of future treatments. Copyright © 2013 Elsevier España, S.L. and SEMNIM. All rights reserved.

Distance-informed metric learning for Alzheimer's disease staging.

PubMed

Shi, Bibo; Wang, Zhewei; Liu, Jundong

2014-01-01

Identifying intermediate biomarkers of Alzheimer's disease (AD) is of great importance for diagnosis and prognosis of the disease. In this study, we develop a new AD staging method to classify patients into Normal Controls (NC), Mild Cognitive Impairment (MCI), and AD groups. Our solution employs a novel metric learning technique that improves classification rates through the guidance of some weak supervisory information in AD progression. More specifically, those information are in the form of pairwise constraints that specify the relative Mini Mental State Examination (MMSE) score disparity of two subjects, depending on whether they are in the same group or not. With the imposed constraints, the common knowledge that MCI generally sits in between of NC and AD can be integrated into the classification distance metric. Subjects from the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; 56 AD, 104 MCI, 161 controls) were used to demonstrate the improvements made comparing with two state-of-the-art metric learning solutions: large margin nearest neighbors (LMNN) and relevant component analysis (RCA).

Right hemispheric dysfunction in a case of pure progressive aphemia: fusion of multimodal neuroimaging.

PubMed

Vitali, Paolo; Nobili, Flavio; Raiteri, Umberto; Canfora, Michela; Rosa, Marco; Calvini, Piero; Girtler, Nicola; Regesta, Giovanni; Rodriguez, Guido

2004-01-15

This article describes the unusual case of a 60-year-old woman suffering from pure progressive aphemia. The fusion of multimodal neuroimaging (MRI, perfusion SPECT) implicated the right frontal lobe, especially the inferior frontal gyrus. This area also showed the greatest functional MRI activation during the performance of a covert phonemic fluency task. Results are discussed in terms of bihemispheric language representation. The fusion of three sets of neuroimages has aided in the interpretation of the patient's cognitive brain dysfunction.

Altered Brain Activity in Unipolar Depression Revisited Meta-analyses of Neuroimaging Studies

PubMed Central

Müller, Veronika I.; Cieslik, Edna C.; Serbanescu, Ilinca; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.

2017-01-01

IMPORTANCE During the past 20 years, numerous neuroimaging experiments have investigated aberrant brain activation during cognitive and emotional processing in patients with unipolar depression (UD). The results of those investigations, however, vary considerably; moreover, previous meta-analyses also yielded inconsistent findings. OBJECTIVE To readdress aberrant brain activation in UD as evidenced by neuroimaging experiments on cognitive and/or emotional processing. DATA SOURCES Neuroimaging experiments published from January 1, 1997, to October 1, 2015, were identified by a literature search of PubMed, Web of Science, and Google Scholar using different combinations of the terms fMRI (functional magnetic resonance imaging), PET (positron emission tomography), neural, major depression, depression, major depressive disorder, unipolar depression, dysthymia, emotion, emotional, affective, cognitive, task, memory, working memory, inhibition, control, n-back, and Stroop. STUDY SELECTION Neuroimaging experiments (using fMRI or PET) reporting whole-brain results of group comparisons between adults with UD and healthy control individuals as coordinates in a standard anatomic reference space and using an emotional or/and cognitive challenging task were selected. DATA EXTRACTION AND SYNTHESIS Coordinates reported to show significant activation differences between UD and healthy controls during emotional or cognitive processing were extracted. By using the revised activation likelihood estimation algorithm, different meta-analyses were calculated. MAIN OUTCOMES AND MEASURES Meta-analyses tested for brain regions consistently found to show aberrant brain activation in UD compared with controls. Analyses were calculated across all emotional processing experiments, all cognitive processing experiments, positive emotion processing, negative emotion processing, experiments using emotional face stimuli, experiments with a sex discrimination task, and memory processing. All meta

ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders.

PubMed

Retico, Alessandra; Arezzini, Silvia; Bosco, Paolo; Calderoni, Sara; Ciampa, Alberto; Coscetti, Simone; Cuomo, Stefano; De Santis, Luca; Fabiani, Dario; Fantacci, Maria Evelina; Giuliano, Alessia; Mazzoni, Enrico; Mercatali, Pietro; Miscali, Giovanni; Pardini, Massimiliano; Prosperi, Margherita; Romano, Francesco; Tamburini, Elena; Tosetti, Michela; Muratori, Filippo

2017-08-01

The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). The main goals of the project are: to analyze neuroimaging data acquired in multiple sites with multivariate approaches based on machine learning; to detect structural and functional brain characteristics that allow the distinguishing of individuals with ASD from control subjects; to identify neuroimaging-based criteria to stratify the population with ASD to support the future development of personalized treatments. Secure data handling and storage are guaranteed within the project, as well as the access to fast grid/cloud-based computational resources. This paper outlines the web-based architecture, the computing infrastructure and the collaborative analysis workflows at the basis of the ARIANNA interdisciplinary working environment. It also demonstrates the full functionality of the research platform. The availability of this innovative working environment for analyzing clinical and neuroimaging information of individuals with ASD is expected to support researchers in disentangling complex data thus facilitating their interpretation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer's disease in veterans, using the Alzheimer's Disease Neuroimaging Initiative.

PubMed

Weiner, Michael W; Veitch, Dallas P; Hayes, Jacqueline; Neylan, Thomas; Grafman, Jordan; Aisen, Paul S; Petersen, Ronald C; Jack, Clifford; Jagust, William; Trojanowski, John Q; Shaw, Leslie M; Saykin, Andrew J; Green, Robert C; Harvey, Danielle; Toga, Arthur W; Friedl, Karl E; Pacifico, Anthony; Sheline, Yvette; Yaffe, Kristine; Mohlenoff, Brian

2014-06-01

Both traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are common problems resulting from military service, and both have been associated with increased risk of cognitive decline and dementia resulting from Alzheimer's disease (AD) or other causes. This study aims to use imaging techniques and biomarker analysis to determine whether traumatic brain injury (TBI) and/or PTSD resulting from combat or other traumas increase the risk for AD and decrease cognitive reserve in Veteran subjects, after accounting for age. Using military and Department of Veterans Affairs records, 65 Vietnam War veterans with a history of moderate or severe TBI with or without PTSD, 65 with ongoing PTSD without TBI, and 65 control subjects are being enrolled in this study at 19 sites. The study aims to select subject groups that are comparable in age, gender, ethnicity, and education. Subjects with mild cognitive impairment (MCI) or dementia are being excluded. However, a new study just beginning, and similar in size, will study subjects with TBI, subjects with PTSD, and control subjects with MCI. Baseline measurements of cognition, function, blood, and cerebrospinal fluid biomarkers; magnetic resonance images (structural, diffusion tensor, and resting state blood-level oxygen dependent (BOLD) functional magnetic resonance imaging); and amyloid positron emission tomographic (PET) images with florbetapir are being obtained. One-year follow-up measurements will be collected for most of the baseline procedures, with the exception of the lumbar puncture, the PET imaging, and apolipoprotein E genotyping. To date, 19 subjects with TBI only, 46 with PTSD only, and 15 with TBI and PTSD have been recruited and referred to 13 clinics to undergo the study protocol. It is expected that cohorts will be fully recruited by October 2014. This study is a first step toward the design and statistical powering of an AD prevention trial using at-risk veterans as subjects, and provides the

“Can It Read My Mind?” – What Do the Public and Experts Think of the Current (Mis)Uses of Neuroimaging?

PubMed Central

Wardlaw, Joanna M.; O'Connell, Garret; Shuler, Kirsten; DeWilde, Janet; Haley, Jane; Escobar, Oliver; Murray, Shaun; Rae, Robert; Jarvie, Donald; Sandercock, Peter; Schafer, Burkhard

2011-01-01

Emerging applications of neuroimaging outside medicine and science have received intense public exposure through the media. Media misrepresentations can create a gulf between public and scientific understanding of the capabilities of neuroimaging and raise false expectations. To determine the extent of this effect and determine public opinions on acceptable uses and the need for regulation, we designed an electronic survey to obtain anonymous opinions from as wide a range of members of the public and neuroimaging experts as possible. The surveys ran from 1st June to 30 September 2010, asked 10 and 21 questions, respectively, about uses of neuroimaging outside traditional medical diagnosis, data storage, science communication and potential methods of regulation. We analysed the responses using descriptive statistics; 660 individuals responded to the public and 303 individuals responded to the expert survey. We found evidence of public skepticism about the use of neuroimaging for applications such as lie detection or to determine consumer preferences and considerable disquiet about use by employers or government and about how their data would be stored and used. While also somewhat skeptical about new applications of neuroimaging, experts grossly underestimated how often neuroimaging had been used as evidence in court. Although both the public and the experts rated highly the importance of a better informed public in limiting the inappropriate uses to which neuroimaging might be put, opinions differed on the need for, and mechanism of, actual regulation. Neuroscientists recognized the risks of inaccurate reporting of neuroimaging capabilities in the media but showed little motivation to engage with the public. The present study also emphasizes the need for better frameworks for scientific engagement with media and public education. PMID:21991367

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond.

PubMed

Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco

2017-01-01

The existence of so-called 'basic emotions' and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond

PubMed Central

Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco

2017-01-01

The existence of so-called ‘basic emotions’ and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In

Neuroimaging in epilepsy.

PubMed

Sidhu, Meneka Kaur; Duncan, John S; Sander, Josemir W

2018-05-17

Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments. The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy. Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.

Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study.

PubMed

Dubois, Bruno; Epelbaum, Stephane; Nyasse, Francis; Bakardjian, Hovagim; Gagliardi, Geoffroy; Uspenskaya, Olga; Houot, Marion; Lista, Simone; Cacciamani, Federica; Potier, Marie-Claude; Bertrand, Anne; Lamari, Foudil; Benali, Habib; Mangin, Jean-François; Colliot, Olivier; Genthon, Remy; Habert, Marie-Odile; Hampel, Harald

2018-04-01

Improved understanding is needed of risk factors and markers of disease progression in preclinical Alzheimer's disease. We assessed associations between brain β-amyloidosis and various cognitive and neuroimaging parameters with progression of cognitive decline in individuals with preclinical Alzheimer's disease. The INSIGHT-preAD is an ongoing single-centre observational study at the Salpêtrière Hospital, Paris, France. Eligible participants were age 70-85 years with subjective memory complaints but unimpaired cognition and memory (Mini-Mental State Examination [MMSE] score ≥27, Clinical Dementia Rating score 0, and Free and Cued Selective Reminding Test [FCSRT] total recall score ≥41). We stratified participants by brain amyloid β deposition on 18 F-florbetapir PET (positive or negative) at baseline. All patients underwent baseline assessments of demographic, cognitive, and psychobehavioural, characteristics, APOE ε4 allele carrier status, brain structure and function on MRI, brain glucose-metabolism on 18 F-fluorodeoxyglucose ( 18 F-FDG) PET, and event-related potentials on electroencephalograms (EEGs). Actigraphy and CSF investigations were optional. Participants were followed up with clinical, cognitive, and psychobehavioural assessments every 6 months, neuropsychological assessments, EEG, and actigraphy every 12 months, and MRI, and 18 F-FDG and 18 F-florbetapir PET every 24 months. We assessed associations of amyloid β deposition status with test outcomes at baseline and 24 months, and with clinical status at 30 months. Progression to prodromal Alzheimer's disease was defined as an amnestic syndrome of the hippocampal type. From May 25, 2013, to Jan 20, 2015, we enrolled 318 participants with a mean age of 76·0 years (SD 3·5). The mean baseline MMSE score was 28·67 (SD 0·96), and the mean level of education was high (score >6 [SD 2] on a scale of 1-8, where 1=infant school and 8=higher education). 88 (28%) of 318 participants showed amyloid �

Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure

PubMed Central

Raschle, Nora M.; Lee, Michelle; Buechler, Roman; Christodoulou, Joanna A.; Chang, Maria; Vakil, Monica; Stering, Patrice L.; Gaab, Nadine

2009-01-01

Within the last decade there has been an increase in the use of structural and functional magnetic resonance imaging (fMRI) to investigate the neural basis of human perception, cognition and behavior 1, 2. Moreover, this non-invasive imaging method has grown into a tool for clinicians and researchers to explore typical and atypical brain development. Although advances in neuroimaging tools and techniques are apparent, (f)MRI in young pediatric populations remains relatively infrequent 2. Practical as well as technical challenges when imaging children present clinicians and research teams with a unique set of problems 3, 2. To name just a few, the child participants are challenged by a need for motivation, alertness and cooperation. Anxiety may be an additional factor to be addressed. Researchers or clinicians need to consider time constraints, movement restriction, scanner background noise and unfamiliarity with the MR scanner environment2,4-10. A progressive use of functional and structural neuroimaging in younger age groups, however, could further add to our understanding of brain development. As an example, several research groups are currently working towards early detection of developmental disorders, potentially even before children present associated behavioral characteristics e.g.11. Various strategies and techniques have been reported as a means to ensure comfort and cooperation of young children during neuroimaging sessions. Play therapy 12, behavioral approaches 13, 14,15, 16-18 and simulation 19, the use of mock scanner areas 20,21, basic relaxation 22 and a combination of these techniques 23 have all been shown to improve the participant's compliance and thus MRI data quality. Even more importantly, these strategies have proven to increase the comfort of families and children involved 12. One of the main advances of such techniques for the clinical practice is the possibility of avoiding sedation or general anesthesia (GA) as a way to manage children

Neuroimaging studies of cognitive remediation in schizophrenia: A systematic and critical review.

PubMed

Penadés, Rafael; González-Rodríguez, Alexandre; Catalán, Rosa; Segura, Bàrbara; Bernardo, Miquel; Junqué, Carme

2017-03-22

To examine the effects of cognitive remediation therapies on brain functioning through neuroimaging procedures in patients with schizophrenia. A systematic, computerised literature search was conducted in the PubMed/Medline and PsychInfo databases. The search was performed through February 2016 without any restrictions on language or publication date. The search was performed using the following search terms: [("cogniti*" and "remediation" or "training" or "enhancement") and ("fMRI" or "MRI" or "PET" or "SPECT") and (schizophrenia or schiz*)]. The search was accompanied by a manual online search and a review of the references from each of the papers selected, and those papers fulfilling our inclusion criteria were also included. A total of 101 studies were found, but only 18 of them fulfilled the inclusion criteria. These studies indicated that cognitive remediation improves brain activation in neuroimaging studies. The most commonly reported changes were those that involved the prefrontal and thalamic regions. Those findings are in agreement with the hypofrontality hypothesis, which proposes that frontal hypoactivation is the underlying mechanism of cognitive impairments in schizophrenia. Nonetheless, great heterogeneity among the studies was found. They presented different hypotheses, different results and different findings. The results of more recent studies interpreted cognitive recovery within broader frameworks, namely, as amelioration of the efficiency of different networks. Furthermore, advances in neuroimaging methodologies, such as the use of whole-brain analysis, tractography, graph analysis, and other sophisticated methodologies of data processing, might be conditioning the interpretation of results and generating new theoretical frameworks. Additionally, structural changes were described in both the grey and white matter, suggesting a neuroprotective effect of cognitive remediation. Cognitive, functional and structural improvements tended to be

Pretibial myxedema without ophthalmopathy: an initial presentation of Graves' disease.

PubMed

Lohiya, Sheela; Lohiya, Vipin; Stahl, Elizabeth J

2013-07-01

To report a rare case of Graves' disease without ophthalmopathy presenting with pretibial myxedema (PM) as an initial presentation. We present the clinical history, physical findings, laboratory studies and biopsy data of a 62-year-old man with a history of uncontrolled type 2 diabetes (DM2) presenting with arm and leg skin lesions in the absence of other physical findings. Histopathology confirmed PM. Graves' disease and its association with PM without Graves' ophthalmopathy and the pertinent literature are reviewed. A 60-year-old man with a history of uncontrolled DM2 presented for glycemic management. He described symptoms of anxiety, insomnia and fatigue for the last 5 to 6 months. He described diffuse chest pain, occasionally associated with palpitations, and a 50-pound weight loss. He also complained of severe itching and burning of his arms and legs for the past several months. Subsequent thyroid studies revealed hyperthyroidism suggestive of Graves' disease. In the interim, he was hospitalized for atrial flutter and was cardioverted. After being started on methimazole, his symptoms abated. His skin lesions were biopsied, and the leg biopsy was consistent with PM. He however had no lid lag or proptosis characteristic of Graves' disease. He subsequently underwent radioiodine ablation. His hyperglycemia was better control led after treatment of his hyperthyroidism. PM is an autoimmune manifestation of Graves' disease. Almost all cases of thyroid dermopathy are associated with relatively severe ophthalmopathy. Usually ophthalmopathy appears first and dermopathy much later. However, this case represents a rare initial presentation of Graves' disease with PM without ophthalmologic symptoms or findings. Hyperthyroidism is typically associated with worsening glycemic control and increased insulin requirements. In patients with diabetes having hyperthyroidism, deterioration in glycemic control should be anticipated and treatment should be adjusted accordingly

The Receiver Operational Characteristic for Binary Classification with Multiple Indices and Its Application to the Neuroimaging Study of Alzheimer’s Disease

PubMed Central

Wu, Xia; Li, Juan; Ayutyanont, Napatkamon; Protas, Hillary; Jagust, William; Fleisher, Adam; Reiman, Eric; Yao, Li; Chen, Kewei

2014-01-01

Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple data sources (referred to as multi-indices), such as multimodal neuroimaging data sets, cognitive tests, and clinical ratings and genomic data in Alzheimer’s disease (AD) studies, the single-index-based ROC underutilizes all available information. For a long time, a number of algorithmic/analytic approaches combining multiple indices have been widely used to simultaneously incorporate multiple sources. In this study, we propose an alternative for combining multiple indices using logical operations, such as “AND,” “OR,” and “at least n” (where n is an integer), to construct multivariate ROC (multiV-ROC) and characterize the sensitivity and specificity statistically associated with the use of multiple indices. With and without the “leave-one-out” cross-validation, we used two data sets from AD studies to showcase the potentially increased sensitivity/specificity of the multiV-ROC in comparison to the single-index ROC and linear discriminant analysis (an analytic way of combining multi-indices). We conclude that, for the data sets we investigated, the proposed multiV-ROC approach is capable of providing a natural and practical alternative with improved classification accuracy as compared to univariate ROC and linear discriminant analysis. PMID:23702553

The role of neuroimaging in the discovery of processing stages. A review.

PubMed

Mulder, G; Wijers, A A; Lange, J J; Buijink, B M; Mulder, L J; Willemsen, A T; Paans, A M

1995-11-01

In this contribution we show how neuroimaging methods can augment behavioural methods to discover processing stages. Event Related Brain Potentials (ERPs), Brain Electrical Source Analysis (BESA) and regional changes in cerebral blood flow (rCBF) do not necessarily require behavioural responses. With the aid of rCBF we are able to discover several cortical and subcortical brain systems (processors) active in selective attention and memory search tasks. BESA describes cortical activity with high temporal resolution in terms of a limited number of neural generators within these brain systems. The combination of behavioural methods and neuroimaging provides a picture of the functional architecture of the brain. The review is organized around three processors: the Visual, Cognitive and Manual Motor Processors.

Is advanced neuroimaging for neuroradiologists? A systematic review of the scientific literature of the last decade.

PubMed

Cocozza, Sirio; Russo, Camilla; Pontillo, Giuseppe; Ugga, Lorenzo; Macera, Antonio; Cervo, Amedeo; De Liso, Maria; Di Paolo, Nilde; Ginocchio, Maria Isabella; Giordano, Flavio; Leone, Giuseppe; Rusconi, Giovanni; Stanzione, Arnaldo; Briganti, Francesco; Quarantelli, Mario; Caranci, Ferdinando; D'Amico, Alessandra; Elefante, Andrea; Tedeschi, Enrico; Brunetti, Arturo

2016-12-01

To evaluate if advanced neuroimaging research is mainly conducted by imaging specialists, we investigated the number of first authorships by radiologists and non-radiologist scientists in articles published in the field of advanced neuroimaging in the past 10 years. Articles in the field of advanced neuroimaging identified in this retrospective bibliometric analysis were divided in four groups, depending on the imaging technique used. For all included studies, educational background of the first authors was recorded (based on available online curriculum vitae) and classified in subgroups, depending on their specialty. Finally, journal impact factors were recorded and comparatively assessed among subgroups as a metric of research quality. A total number of 3831 articles were included in the study. Radiologists accounted as first authors for only 12.8 % of these publications, while 56.9 % of first authors were researchers without a medical degree. Mean impact factor (IF) of journals with non-MD researchers as first authors was significantly higher than the MD subgroup (p < 10 -20 ), while mean IF of journals with radiologists as first authors was significantly lower than articles authored by other MD specialists (p < 10 -11 ). The majority of the studies in the field of advanced neuroimaging in the last decade is conducted by professional figures other than radiologists, who account for less than the 13 % of the publications. Furthermore, the mean IF value of radiologists-authored articles was the lowest among all subgroups. These results, taken together, should question the radiology community about its future role in the development of advanced neuroimaging.

Tobacco-related disease burden and preventive initiatives in China. Global health and the chronic diseases: perspective, policy and practice.

PubMed

Niu, Bolin

2011-06-01

The burden of chronic diseases in global health is a surging area of research. The Global Health Initiative at the National Heart, Lung, and Blood Institute brings together investigators from developing countries with those from the developed world to study these diseases. In China, approximately 83 percent of all deaths in 2000 were attributed to chronic illnesses, which are the research focuses of the Chinese center of the Global Health Initiative. Tobacco use as well as passive smoking are modifiable risk factors in a large number of such chronic conditions. The prevalence of smoking in China is extensive and has inseparable ties to the economy, with tobacco taxes making up a large portion of government revenue in poorer provinces. Methods of smoking prevention have been piloted in some Chinese schools, which have mitigated the increase in smoking rate but have not resulted in a primary preventive effect. Efforts by the Yale Global Health Initiative and the Yale-China Association are bringing researchers together to address chronic disease in China as Yale School of Medicine enters its 200th year.

Identifying Predictors, Moderators, and Mediators of Antidepressant Response in Major Depressive Disorder: Neuroimaging Approaches

PubMed Central

Phillips, Mary L.; Chase, Henry W.; Sheline, Yvette I.; Etkin, Amit; Almeida, Jorge R.C.; Deckersbach, Thilo; Trivedi, Madhukar H.

2015-01-01

Objective Despite significant advances in neuroscience and treatment development, no widely accepted biomarkers are available to inform diagnostics or identify preferred treatments for individuals with major depressive disorder. Method In this critical review, the authors examine the extent to which multimodal neuroimaging techniques can identify biomarkers reflecting key pathophysiologic processes in depression and whether such biomarkers may act as predictors, moderators, and mediators of treatment response that might facilitate development of personalized treatments based on a better understanding of these processes. Results The authors first highlight the most consistent findings from neuroimaging studies using different techniques in depression, including structural and functional abnormalities in two parallel neural circuits: serotonergically modulated implicit emotion regulation circuitry, centered on the amygdala and different regions in the medial prefrontal cortex; and dopaminergically modulated reward neural circuitry, centered on the ventral striatum and medial prefrontal cortex. They then describe key findings from the relatively small number of studies indicating that specific measures of regional function and, to a lesser extent, structure in these neural circuits predict treatment response in depression. Conclusions Limitations of existing studies include small sample sizes, use of only one neuroimaging modality, and a focus on identifying predictors rather than moderators and mediators of differential treatment response. By addressing these limitations and, most importantly, capitalizing on the benefits of multimodal neuroimaging, future studies can yield moderators and mediators of treatment response in depression to facilitate significant improvements in shorter- and longer-term clinical and functional outcomes. PMID:25640931

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging

Metabolic network failures in Alzheimer’s disease: A biochemical road map

PubMed Central

Toledo, Jon B.; Arnold, Matthias; Kastenmüuller, Gabi; Chang, Rui; Baillie, Rebecca A.; Han, Xianlin; Thambisetty, Madhav; Tenenbaum, Jessica D.; Suhre, Karsten; Thompson, J. Will; St. John-Williams, Lisa; MahmoudianDehkordi, Siamak; Rotroff, Daniel M.; Jack, John R.; Motsinger-Reif, Alison; Risacher, Shannon L.; Blach, Colette; Lucas, Joseph E.; Massaro, Tyler; Louie, Gregory; Zhu, Hongjie; Dallmann, Guido; Klavins, Kristaps; Koal, Therese; Kim, Sungeun; Nho, Kwangsik; Shen, Li; Casanova, Ramon; Varma, Sudhir; Legido-Quigley, Cristina; Moseley, M. Arthur; Zhu, Kuixi; Henrion, Marc Y. R.; van der Lee, Sven J.; Harms, Amy C.; Demirkan, Ayse; Hankemeier, Thomas; van Duijn, Cornelia M.; Trojanowski, John Q.; Shaw, Leslie M.; Saykin, Andrew J.; Weiner, Michael W.; Doraiswamy, P. Murali; Kaddurah-Daouk, Rima

2018-01-01

Introduction The Alzheimer’s Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer’s disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance. Methods Fasting serum samples from the Alzheimer’s Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted. Results Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ1–42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease. Discussion Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery. PMID:28341160

Neuroimaging of amblyopia and binocular vision: a review

PubMed Central

Joly, Olivier; Frankó, Edit

2014-01-01

Amblyopia is a cerebral visual impairment considered to derive from abnormal visual experience (e.g., strabismus, anisometropia). Amblyopia, first considered as a monocular disorder, is now often seen as a primarily binocular disorder resulting in more and more studies examining the binocular deficits in the patients. The neural mechanisms of amblyopia are not completely understood even though they have been investigated with electrophysiological recordings in animal models and more recently with neuroimaging techniques in humans. In this review, we summarize the current knowledge about the brain regions that underlie the visual deficits associated with amblyopia with a focus on binocular vision using functional magnetic resonance imaging. The first studies focused on abnormal responses in the primary and secondary visual areas whereas recent evidence shows that there are also deficits at higher levels of the visual pathways within the parieto-occipital and temporal cortices. These higher level areas are part of the cortical network involved in 3D vision from binocular cues. Therefore, reduced responses in these areas could be related to the impaired binocular vision in amblyopic patients. Promising new binocular treatments might at least partially correct the activation in these areas. Future neuroimaging experiments could help to characterize the brain response changes associated with these treatments and help devise them. PMID:25147511

Neuroimaging of amblyopia and binocular vision: a review.

PubMed

Joly, Olivier; Frankó, Edit

2014-01-01

Amblyopia is a cerebral visual impairment considered to derive from abnormal visual experience (e.g., strabismus, anisometropia). Amblyopia, first considered as a monocular disorder, is now often seen as a primarily binocular disorder resulting in more and more studies examining the binocular deficits in the patients. The neural mechanisms of amblyopia are not completely understood even though they have been investigated with electrophysiological recordings in animal models and more recently with neuroimaging techniques in humans. In this review, we summarize the current knowledge about the brain regions that underlie the visual deficits associated with amblyopia with a focus on binocular vision using functional magnetic resonance imaging. The first studies focused on abnormal responses in the primary and secondary visual areas whereas recent evidence shows that there are also deficits at higher levels of the visual pathways within the parieto-occipital and temporal cortices. These higher level areas are part of the cortical network involved in 3D vision from binocular cues. Therefore, reduced responses in these areas could be related to the impaired binocular vision in amblyopic patients. Promising new binocular treatments might at least partially correct the activation in these areas. Future neuroimaging experiments could help to characterize the brain response changes associated with these treatments and help devise them.

Multivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trends.

PubMed

Haller, Sven; Lovblad, Karl-Olof; Giannakopoulos, Panteleimon; Van De Ville, Dimitri

2014-05-01

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

Neuroimaging features in subacute encephalopathy with seizures in alcoholics (SESA syndrome)

PubMed Central

Drake-Pérez, Marta; de Lucas, Enrique Marco; Lyo, John; Fernández-Torre, José L.

2017-01-01

Purpose To describe the neuroimaging findings in subacute encephalopathy with seizures in alcoholics (SESA syndrome). Methods We reviewed all cases reported previously, as well as 4 patients diagnosed in our center. We included a total of 8 patients. All subjects had clinical and EEG findings compatible with SESA syndrome and at least one MRI study that did not show other underlying condition that could be responsible for the clinical presentation. Results Initial MRI studies revealed the following features: cortical-subcortical areas of increased T2/FLAIR signal and restricted diffusion (6 patients), hyperperfusion (3 patients), atrophy (5 patients), chronic microvascular ischemic changes (4 patients). Follow-up MRI was performed in half of the patients, all showing a resolution of the hyperintense lesions, but developing focal atrophic changes in 75%. Conclusions SESA syndrome should be included among the alcohol-related encephalopathies. Its radiological features include transient cortical-subcortical T2-hyperintense areas with restricted diffusion (overlapping the typical findings in status epilepticus) observed in a patient with atrophy and chronic multifocal vascular lesions. PMID:27391464

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury.

PubMed

Amyot, Franck; Arciniegas, David B; Brazaitis, Michael P; Curley, Kenneth C; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R; Manley, Geoffrey T; Pacifico, Anthony; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G; Stocker, Derek

2015-11-15

The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI.

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury

PubMed Central

Amyot, Franck; Arciniegas, David B.; Brazaitis, Michael P.; Curley, Kenneth C.; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R.; Manley, Geoffrey T.; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G.; Stocker, Derek

2015-01-01

Abstract The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI. PMID:26176603

ANOSOGNOSIA FOR MEMORY IMPAIRMENT IN ADDICTION: INSIGHTS FROM NEUROIMAGING AND NEUROPSYCHOLOGICAL ASSESSMENT OF METAMEMORY

PubMed Central

Le Berre, Anne-Pascale; Sullivan, Edith V.

2016-01-01

In addiction, notably, Alcohol Use Disorder (AUD), patients often have a tendency to fail to acknowledge the reality of the disease and to minimize the physical, psychological, and social difficulties attendant to chronic alcohol consumption. This lack of awareness can reduce the chances of initiating and maintaining sobriety. Presented here is a model focusing on compromised awareness in individuals with AUD of mild to moderate cognitive deficits, in particular, for episodic memory impairment—the ability to learn new information, such as recent personal experiences. Early in abstinence, alcoholics can be unaware of their memory deficits and overestimate their mnemonic capacities, which can be investigated with metamemory paradigms. Relevant neuropsychological and neuroimaging results considered suggest that the alcoholics’ impairment of awareness of their attenuated memory function can be a clinical manifestation explained mechanistically by neurobiological factors, including compromise of brain systems that result in a mild form of mnemonic anosognosia. Specifically, unawareness of memory impairment in AUD may result from a lack of personal knowledge updating attributable to damage in brain regions or connections supporting conscious recollection in episodic memory. Likely candidates are posterior parietal and medial frontal regions known to be integral part of the Default Mode Network (DMN) and the insula leading to an impaired switching mechanism between the DMN and the Central-Executive Control (i.e., Lateral Prefronto-Parietal) Network. The cognitive concepts and neural substrates noted for addictive disorders may also be relevant for problems in self-identification of functional impairment resulting from injury following war-related blast, sport-related concussion, and insidiously occurring dementia. PMID:27447979

Effects of Marijuana Use on Brain Structure and Function: Neuroimaging Findings from a Neurodevelopmental Perspective

PubMed Central

Brumback, T.; Castro, N.; Jacobus, J.; Tapert, S.

2016-01-01

Marijuana, behind only tobacco and alcohol, is the most popular recreational drug in America with prevalence rates of use rising over the past decade. A wide range of research has highlighted neurocognitive deficits associated with marijuana use, particularly when initiated during childhood or adolescence. Neuroimaging, describing alterations to brain structure and function, has begun to provide a picture of possible mechanisms associated with the deleterious effects of marijuana use. This chapter provides a neurodevelopmental framework from which recent data on brain structural and functional abnormalities associated with marijuana use is reviewed. Based on the current data, we provide aims for future studies to more clearly delineate the effects of marijuana on the developing brain and to define underlying mechanisms of the potential long-term negative consequences of marijuana use. PMID:27503447

The Road Ahead to Cure Alzheimer’s Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations

PubMed Central

Cavedo, E.; Lista, S.; Khachaturian, Z.; Aisen, P.; Amouyel, P.; Herholz, K.; Jack, C.R.; Sperling, R.; Cummings, J.; Blennow, K.; O’Bryant, S.; Frisoni, G.B.; Khachaturian, A.; Kivipelto, M.; Klunk, W.; Broich, K.; Andrieu, S.; de Schotten, M. Thiebaut; Mangin, J.-F.; Lammertsma, A.A.; Johnson, K.; Teipel, S.; Drzezga, A.; Bokde, A.; Colliot, O.; Bakardjian, H.; Zetterberg, H.; Dubois, B.; Vellas, B.; Schneider, L.S.; Hampel, H.

2015-01-01

Alzheimer’s disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group’s revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard (“core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for “prodromal AD” and “mild cognitive impairment due to AD” include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis

Reproducibility of neuroimaging analyses across operating systems

PubMed Central

Glatard, Tristan; Lewis, Lindsay B.; Ferreira da Silva, Rafael; Adalat, Reza; Beck, Natacha; Lepage, Claude; Rioux, Pierre; Rousseau, Marc-Etienne; Sherif, Tarek; Deelman, Ewa; Khalili-Mahani, Najmeh; Evans, Alan C.

2015-01-01

Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed. PMID:25964757

Reproducibility of neuroimaging analyses across operating systems.

PubMed

Glatard, Tristan; Lewis, Lindsay B; Ferreira da Silva, Rafael; Adalat, Reza; Beck, Natacha; Lepage, Claude; Rioux, Pierre; Rousseau, Marc-Etienne; Sherif, Tarek; Deelman, Ewa; Khalili-Mahani, Najmeh; Evans, Alan C

2015-01-01

Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed.

Neuroimaging in adult penetrating brain injury: a guide for radiographers

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

Temple, Nikki; Donald, Cortny; Skora, Amanda

Penetrating brain injuries (PBI) are a medical emergency, often resulting in complex damage and high mortality rates. Neuroimaging is essential to evaluate the location and extent of injuries, and to manage them accordingly. Currently, a myriad of imaging modalities are included in the diagnostic workup for adult PBI, including skull radiography, computed tomography (CT), magnetic resonance imaging (MRI) and angiography, with each modality providing their own particular benefits. This literature review explores the current modalities available for investigating PBI and aims to assist in decision making for the appropriate use of diagnostic imaging when presented with an adult PBI. Basedmore » on the current literature, the authors have developed an imaging pathway for adult penetrating brain injury that functions as both a learning tool and reference guide for radiographers and other health professionals. Currently, CT is recommended as the imaging modality of choice for the initial assessment of PBI patients, while MRI is important in the sub-acute setting where it aids prognosis prediction and rehabilitation planning, Additional follow-up imaging, such as angiography, should be dependent upon clinical findings.« less

Spatial information is processed even when it is task-irrelevant: implications for neuroimaging task design.

PubMed

Meegan, Daniel V; Honsberger, Michael J M

2005-05-01

Many neuroimaging studies have been designed to differentiate domain-specific processes in the brain. A common design constraint is to use identical stimuli for different domain-specific tasks. For example, an experiment investigating spatial versus identity processing would present compound spatial-identity stimuli in both spatial and identity tasks, and participants would be instructed to attend to, encode, maintain, or retrieve spatial information in the spatial task, and identity information in the identity task. An assumption in such studies is that spatial information will not be processed in the identity task, as it is irrelevant for that task. We report three experiments demonstrating violations of this assumption. Our results suggest that comparisons of spatial and identity tasks in existing neuroimaging studies have underestimated the amount of brain activation that is spatial-specific. For future neuroimaging studies, we recommend unique stimulus displays for each domain-specific task, and event-related measurement of post-stimulus processing.

The Power of Neuroimaging Biomarkers for Screening Frontotemporal Dementia

PubMed Central

McMillan, Corey T.; Avants, Brian B.; Cook, Philip; Ungar, Lyle; Trojanowski, John Q.; Grossman, Murray

2014-01-01

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative disease that can result from either frontotemporal lobar degeneration (FTLD) or Alzheimer’s disease (AD) pathology. It is critical to establish statistically powerful biomarkers that can achieve substantial cost-savings and increase feasibility of clinical trials. We assessed three broad categories of neuroimaging methods to screen underlying FTLD and AD pathology in a clinical FTD series: global measures (e.g., ventricular volume), anatomical volumes of interest (VOIs) (e.g., hippocampus) using a standard atlas, and data-driven VOIs using Eigenanatomy. We evaluated clinical FTD patients (N=93) with cerebrospinal fluid, gray matter (GM) MRI, and diffusion tensor imaging (DTI) to assess whether they had underlying FTLD or AD pathology. Linear regression was performed to identify the optimal VOIs for each method in a training dataset and then we evaluated classification sensitivity and specificity in an independent test cohort. Power was evaluated by calculating minimum sample sizes (mSS) required in the test classification analyses for each model. The data-driven VOI analysis using a multimodal combination of GM MRI and DTI achieved the greatest classification accuracy (89% SENSITIVE; 89% SPECIFIC) and required a lower minimum sample size (N=26) relative to anatomical VOI and global measures. We conclude that a data-driven VOI approach employing Eigenanatomy provides more accurate classification, benefits from increased statistical power in unseen datasets, and therefore provides a robust method for screening underlying pathology in FTD patients for entry into clinical trials. PMID:24687814

Chronic disorders of consciousness: role of neuroimaging

NASA Astrophysics Data System (ADS)

Kremneva, E.; Sergeev, D.; Zmeykina, E.; Legostaeva, L.; Piradov, M.

2017-08-01

Chronic disorders of consciousness are clinically challenging conditions, and advanced methods of imaging for better understanding of diagnosis and prognosis are needed. Recent functional neuroradiological studies utilizing PET and fMRI demonstrated that besides widespread neuronal loss disruption of interconnection between certain cortical networks after the injury may also play the leading role in the development of behaviourally assessed unresponsiveness. Functional and structural connectivity, evaluated by neuroimaging approaches, may correlate with clinical status and may also play prognostic role. Integration of data from various diagnostic modalities is needed for further progress in this area.

Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci.

PubMed

Scelsi, Marzia A; Khan, Raiyan R; Lorenzi, Marco; Christopher, Leigh; Greicius, Michael D; Schott, Jonathan M; Ourselin, Sebastien; Altmann, Andre

2018-05-30

Identifying genetic risk factors underpinning different aspects of Alzheimer's disease has the potential to provide important insights into pathogenesis. Moving away from simple case-control definitions, there is considerable interest in using quantitative endophenotypes, such as those derived from imaging as outcome measures. Previous genome-wide association studies of imaging-derived biomarkers in sporadic late-onset Alzheimer's disease focused only on phenotypes derived from single imaging modalities. In contrast, we computed a novel multi-modal neuroimaging phenotype comprising cortical amyloid burden and bilateral hippocampal volume. Both imaging biomarkers were used as input to a disease progression modelling algorithm, which estimates the biomarkers' long-term evolution curves from population-based longitudinal data. Among other parameters, the algorithm computes the shift in time required to optimally align a subjects' biomarker trajectories with these population curves. This time shift serves as a disease progression score and it was used as a quantitative trait in a discovery genome-wide association study with n = 944 subjects from the Alzheimer's Disease Neuroimaging Initiative database diagnosed as Alzheimer's disease, mild cognitive impairment or healthy at the time of imaging. We identified a genome-wide significant locus implicating LCORL (rs6850306, chromosome 4; P = 1.03 × 10-8). The top variant rs6850306 was found to act as an expression quantitative trait locus for LCORL in brain tissue. The clinical role of rs6850306 in conversion from healthy ageing to mild cognitive impairment or Alzheimer's disease was further validated in an independent cohort comprising healthy, older subjects from the National Alzheimer's Coordinating Center database. Specifically, possession of a minor allele at rs6850306 was protective against conversion from mild cognitive impairment to Alzheimer's disease in the National Alzheimer's Coordinating Center cohort (hazard

Quantifying cognition and behavior in normal aging, mild cognitive impairment, and Alzheimer's disease

NASA Astrophysics Data System (ADS)

Giraldo, Diana L.; Sijbers, Jan; Romero, Eduardo

2017-11-01

The diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) is based on neuropsychological evaluation of the patient. Different cognitive and memory functions are assessed by a battery of tests that are composed of items devised to specifically evaluate such upper functions. This work aims to identify and quantify the factors that determine the performance in neuropsychological evaluation by conducting an Exploratory Factor Analysis (EFA). For this purpose, using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), EFA was applied to 67 item scores taken from the baseline neuropsychological battery of the three phases of ADNI study. The found factors are directly related to specific brain functions such as memory, behavior, orientation, or verbal fluency. The identification of factors is followed by the calculation of factor scores given by weighted linear combinations of the items scores.

Legal and ethical issues in neuroimaging research: human subjects protection, medical privacy, and the public communication of research results.

PubMed

Kulynych, Jennifer

2002-12-01

Humans subjects research entails significant legal and ethical obligations. Neuroimaging researchers must be familiar with the requirements of human subjects protection, including evolving standards for the protection of privacy and the disclosure of risk in "non-therapeutic" research. Techniques for creating veridical surface renderings from volumetric anatomical imaging data raise new privacy concerns, particularly under the federal medical privacy regulation. Additionally, neuroimaging researchers must consider their obligation to communicate research results responsibly. The emerging field of neuroethics should strive to raise awareness of these issues and to involve neuroimaging researchers in the legal, ethical, and policy debates that currently surround human subjects research.

Musical hallucinations: a brief review of functional neuroimaging findings.

PubMed

Bernardini, Francesco; Attademo, Luigi; Blackmon, Karen; Devinsky, Orrin

2017-10-01

Musical hallucinations are uncommon phenomena characterized by intrusive and frequently distressful auditory musical percepts without an external source, often associated with hypoacusis, psychiatric illness, focal brain lesion, epilepsy, and intoxication/pharmacology. Their physiological basis is thought to involve diverse mechanisms, including "release" from normal sensory or inhibitory inputs as well as stimulation during seizures, or they can be produced by functional or structural disorders in diverse cortical and subcortical areas. The aim of this review is to further explore their pathophysiology, describing the functional neuroimaging findings regarding musical hallucinations. A literature search of the PubMed electronic database was conducted through to 29 December 2015. Search terms included "musical hallucinations" combined with the names of specific functional neuroimaging techniques. A total of 18 articles, all clinical case reports, providing data on 23 patients, comprised the set we reviewed. Diverse pathological processes and patient populations with musical hallucinations were included in the studies. Converging data from multiple studies suggest that the superior temporal sulcus is the most common site and that activation is the most common mechanism. Further neurobiological research is needed to clarify the pathophysiology of musical hallucinations.

76 FR 28437 - Disease, Disability, and Injury Prevention and Control Special Interest Project (SIP): Initial...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-17

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Disease, Disability, and Injury Prevention and Control Special Interest Project (SIP): Initial Review The meeting...), the Centers for Disease Control and Prevention (CDC) announces the aforementioned meeting: Time and...

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease.

PubMed

Cheng, Bo; Liu, Mingxia; Shen, Dinggang; Li, Zuoyong; Zhang, Daoqiang

2017-04-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multi-domain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods.

Neuroimaging studies of cognitive remediation in schizophrenia: A systematic and critical review

PubMed Central

Penadés, Rafael; González-Rodríguez, Alexandre; Catalán, Rosa; Segura, Bàrbara; Bernardo, Miquel; Junqué, Carme

2017-01-01

AIM To examine the effects of cognitive remediation therapies on brain functioning through neuroimaging procedures in patients with schizophrenia. METHODS A systematic, computerised literature search was conducted in the PubMed/Medline and PsychInfo databases. The search was performed through February 2016 without any restrictions on language or publication date. The search was performed using the following search terms: [(“cogniti*” and “remediation” or “training” or “enhancement”) and (“fMRI” or “MRI” or “PET” or “SPECT”) and (schizophrenia or schiz*)]. The search was accompanied by a manual online search and a review of the references from each of the papers selected, and those papers fulfilling our inclusion criteria were also included. RESULTS A total of 101 studies were found, but only 18 of them fulfilled the inclusion criteria. These studies indicated that cognitive remediation improves brain activation in neuroimaging studies. The most commonly reported changes were those that involved the prefrontal and thalamic regions. Those findings are in agreement with the hypofrontality hypothesis, which proposes that frontal hypoactivation is the underlying mechanism of cognitive impairments in schizophrenia. Nonetheless, great heterogeneity among the studies was found. They presented different hypotheses, different results and different findings. The results of more recent studies interpreted cognitive recovery within broader frameworks, namely, as amelioration of the efficiency of different networks. Furthermore, advances in neuroimaging methodologies, such as the use of whole-brain analysis, tractography, graph analysis, and other sophisticated methodologies of data processing, might be conditioning the interpretation of results and generating new theoretical frameworks. Additionally, structural changes were described in both the grey and white matter, suggesting a neuroprotective effect of cognitive remediation. Cognitive

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly

Subependymal giant cell astrocytoma: clinical and neuroimaging features of four cases.

PubMed

Nishio, S; Morioka, T; Suzuki, S; Kira, R; Mihara, F; Fukui, M

2001-01-01

The clinical history, neuroimaging features, treatments, and outcome of 4 patients with histologically verified subependymal giant cell astrocytomas (SEGA) were retrospectively reviewed. The average age at the time of surgery was 13.3 years. Headache related to raised intracranial pressure was the first and only sign in 2 patients, with the remaining 2 being admitted because of sequential neuroimaging studies over several years revealing the growth of 'subependymal nodules' into intraventricular tumours. In each case the tumour was in the region of Monro's foramen and was associated with ventricular dilatation. On computed tomography (CT), multiple subependymal nodules were found in 3 patients, and these well circumscribed isodense SEGAs were markedly enhanced by contrast medium. On magnetic resonance imaging (MRI), which was obtained in 3 patients, 2 SEGAs were isointense with the cerebral cortex and one with the white matter on T1-weighted images, and on T2-weighted images, 2 were isointense with the cortex and one with the white matter. At surgery the tumours appeared to originate from the inferolateral wall of the lateral ventricle in the region of the head of the caudate nuclei. Total macroscopic removal was achieved in 3 patients, and subtotal removal in one patient. Follow up ranged from 4.6 to 13.2 years, and all patients have exhibited similar physical and mental conditions to preoperative. So far there has been no evidence of any recurrences. The diagnosis and the surgical indications for SEGA are discussed, with periodic monitoring with neuroimaging studies being recommended even for asymptomatic patients with 'subependymal nodules'.

Application of positron emission tomography to neuroimaging in sports sciences.

PubMed

Tashiro, Manabu; Itoh, Masatoshi; Fujimoto, Toshihiko; Masud, Md Mehedi; Watanuki, Shoichi; Yanai, Kazuhiko

2008-08-01

To investigate exercise-induced regional metabolic and perfusion changes in the human brain, various methods are available, such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), near-infrared spectroscopy (NIRS) and electroencephalography (EEG). In this paper, details of methods of metabolic measurement using PET, [(18)F]fluorodeoxyglucose ([(18)F]FDG) and [(15)O]radio-labelled water ([(15)O]H(2)O) will be explained. Functional neuroimaging in the field of neuroscience was started in the 1970s using an autoradiography technique on experimental animals. The first human functional neuroimaging exercise study was conducted in 1987 using a rough measurement system known as (133)Xe inhalation. Although the data was useful, more detailed and exact functional neuroimaging, especially with respect to spatial resolution, was achieved by positron emission tomography. Early studies measured the cerebral blood flow changes during exercise. Recently, PET was made more applicable to exercise physiology and psychology by the use of the tracer [(18)F]FDG. This technique allowed subjects to be scanned after an exercise task is completed but still obtain data from the exercise itself, which is similar to autoradiography studies. In this report, methodological information is provided with respect to the recommended protocol design, the selection of the scanning mode, how to evaluate the cerebral glucose metabolism and how to interpret the regional brain activity using voxel-by-voxel analysis and regions of interest techniques (ROI). Considering the important role of exercise in health promotion, further efforts in this line of research should be encouraged in order to better understand health behavior. Although the number of research papers is still limited, recent work has indicated that the [(18)F]FDG-PET technique is a useful tool to understand brain activity during exercise.

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance.

PubMed

Schlund, Michael W; Cataldo, Michael F; Siegle, Greg J; Ladouceur, Cecile D; Silk, Jennifer S; Forbes, Erika E; McFarland, Ashley; Iyengar, Satish; Dahl, Ronald E; Ryan, Neal D

2011-05-06

Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N=120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks. The proposed approach contributes to the pediatric neuroimaging literature by

77 FR 30292 - Disease, Disability, and Injury Prevention and Control Special Interest Project (SIP): Initial...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-22

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Disease, Disability, and Injury Prevention and Control Special Interest Project (SIP): Initial Review The meeting...)(2) of the Federal Advisory Committee Act (Pub. L. 92-463), the Centers for Disease Control and...

Neuroimaging in attention-deficit hyperactivity disorder: beyond the frontostriatal circuitry.

PubMed

Cherkasova, Mariya V; Hechtman, Lily

2009-10-01

To review the findings of structural and functional neuroimaging studies in attention-deficit hyperactivity disorder (ADHD), with a focus on abnormalities reported in brain regions that lie outside the frontostriatal circuitry, which is currently believed to play a central role in the pathophysiology of ADHD. Relevant publications were found primarily by searching the MEDLINE and PubMed databases using the keywords ADHD and the abbreviations of magnetic resonance imaging (MRI), functional MRI, positron emission tomography, and single photon emission computed tomography. The reference lists of the articles found through the databases were then reviewed for the purpose of finding additional articles. There is now substantial evidence of structural and functional alterations in regions outside the frontostriatal circuitry in ADHD, most notably in the cerebellum and the parietal lobes. Although there is compelling evidence suggesting that frontostriatal dysfunction may be central to the pathophysiology of ADHD, the neuroimaging findings point to distributed neural substrates rather than a single one. More research is needed to elucidate the nature of contributions of nonfrontostriatal regions to the pathophysiology of ADHD.

Magnetic Resonance Techniques Applied to the Diagnosis and Treatment of Parkinson’s Disease

PubMed Central

de Celis Alonso, Benito; Hidalgo-Tobón, Silvia S.; Menéndez-González, Manuel; Salas-Pacheco, José; Arias-Carrión, Oscar

2015-01-01

Parkinson’s disease (PD) affects at least 10 million people worldwide. It is a neurodegenerative disease, which is currently diagnosed by neurological examination. No neuroimaging investigation or blood biomarker is available to aid diagnosis and prognosis. Most effort toward diagnosis using magnetic resonance (MR) has been focused on the use of structural/anatomical neuroimaging and diffusion tensor imaging (DTI). However, deep brain stimulation, a current strategy for treating PD, is guided by MR imaging (MRI). For clinical prognosis, diagnosis, and follow-up investigations, blood oxygen level-dependent MRI, DTI, spectroscopy, and transcranial magnetic stimulation have been used. These techniques represent the state of the art in the last 5 years. Here, we focus on MR techniques for the diagnosis and treatment of Parkinson’s disease. PMID:26191037

The central extended amygdala in fear and anxiety: Closing the gap between mechanistic and neuroimaging research.

PubMed

Fox, Andrew S; Shackman, Alexander J

2017-11-30

Anxiety disorders impose a staggering burden on public health, underscoring the need to develop a deeper understanding of the distributed neural circuits underlying extreme fear and anxiety. Recent work highlights the importance of the central extended amygdala, including the central nucleus of the amygdala (Ce) and neighboring bed nucleus of the stria terminalis (BST). Anatomical data indicate that the Ce and BST form a tightly interconnected unit, where different kinds of threat-relevant information can be integrated to assemble states of fear and anxiety. Neuroimaging studies show that the Ce and BST are engaged by a broad spectrum of potentially threat-relevant cues. Mechanistic work demonstrates that the Ce and BST are critically involved in organizing defensive responses to a wide range of threats. Studies in rodents have begun to reveal the specific molecules, cells, and microcircuits within the central extended amygdala that underlie signs of fear and anxiety, but the relevance of these tantalizing discoveries to human experience and disease remains unclear. Using a combination of focal perturbations and whole-brain imaging, a new generation of nonhuman primate studies is beginning to close this gap. This work opens the door to discovering the mechanisms underlying neuroimaging measures linked to pathological fear and anxiety, to understanding how the Ce and BST interact with one another and with distal brain regions to govern defensive responses to threat, and to developing improved intervention strategies. Copyright © 2017. Published by Elsevier B.V.

Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study.

PubMed

Gordon, Brian A; Blazey, Tyler M; Su, Yi; Hari-Raj, Amrita; Dincer, Aylin; Flores, Shaney; Christensen, Jon; McDade, Eric; Wang, Guoqiao; Xiong, Chengjie; Cairns, Nigel J; Hassenstab, Jason; Marcus, Daniel S; Fagan, Anne M; Jack, Clifford R; Hornbeck, Russ C; Paumier, Katrina L; Ances, Beau M; Berman, Sarah B; Brickman, Adam M; Cash, David M; Chhatwal, Jasmeer P; Correia, Stephen; Förster, Stefan; Fox, Nick C; Graff-Radford, Neill R; la Fougère, Christian; Levin, Johannes; Masters, Colin L; Rossor, Martin N; Salloway, Stephen; Saykin, Andrew J; Schofield, Peter R; Thompson, Paul M; Weiner, Michael M; Holtzman, David M; Raichle, Marcus E; Morris, John C; Bateman, Randall J; Benzinger, Tammie L S

2018-03-01

Models of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal. Between Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11 C-Pittsburgh Compound B ( 11 C-PiB) PET, 18 F-Fluorodeoxyglucose ( 18 F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) FINDINGS: 11 C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18 F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the

Applications of Optical Neuroimaging in Usability Research

PubMed Central

Hill, Audrey P.; Bohil, Corey J.

2016-01-01

FEATURE AT A GLANCE In this article we review recent and potential applications of optical neuroimaging to human factors and usability research. We focus specifically on functional near-infrared spectroscopy (fNIRS) because of its cost-effectiveness and ease of implementation. Researchers have used fNIRS to assess a range of psychological phenomena relevant to human factors, such as cognitive workload, attention, motor activity, and more. It offers the opportunity to measure hemodynamic correlates of mental activity during task completion in human factors and usability studies. We also consider some limitations and future research directions. PMID:28286404

[Conversion disorder : functional neuroimaging and neurobiological mechanisms].

PubMed

Lejeune, J; Piette, C; Salmon, E; Scantamburlo, G

2017-04-01

Conversion disorder is a psychiatric disorder often encountered in neurology services. This condition without organic lesions was and still is sometimes referred as an imaginary illness or feigning. However, the absence of organic lesions does not exclude the possibility of cerebral dysfunction. The etiologic mechanisms underlying this disorder remain uncertain even today.The advent of cognitive and functional imaging opens up a field of exploration for psychiatry in understanding the neurobiological mechanisms underlying mental disorders and especially the conversion disorder. This article reports several neuroimaging studies of conversion disorder and attempts to generate hypotheses about neurobiological mechanisms.

Whole-Brain Microscopy Meets In Vivo Neuroimaging: Techniques, Benefits, and Limitations.

PubMed

Aswendt, Markus; Schwarz, Martin; Abdelmoula, Walid M; Dijkstra, Jouke; Dedeurwaerdere, Stefanie

2017-02-01

Magnetic resonance imaging, positron emission tomography, and optical imaging have emerged as key tools to understand brain function and neurological disorders in preclinical mouse models. They offer the unique advantage of monitoring individual structural and functional changes over time. What remained unsolved until recently was to generate whole-brain microscopy data which can be correlated to the 3D in vivo neuroimaging data. Conventional histological sections are inappropriate especially for neuronal tracing or the unbiased screening for molecular targets through the whole brain. As part of the European Society for Molecular Imaging (ESMI) meeting 2016 in Utrecht, the Netherlands, we addressed this issue in the Molecular Neuroimaging study group meeting. Presentations covered new brain clearing methods, light sheet microscopes for large samples, and automatic registration of microscopy to in vivo imaging data. In this article, we summarize the discussion; give an overview of the novel techniques; and discuss the practical needs, benefits, and limitations.

Data-Driven Sequence of Changes to Anatomical Brain Connectivity in Sporadic Alzheimer's Disease.

PubMed

Oxtoby, Neil P; Garbarino, Sara; Firth, Nicholas C; Warren, Jason D; Schott, Jonathan M; Alexander, Daniel C

2017-01-01

Model-based investigations of transneuronal spreading mechanisms in neurodegenerative diseases relate the pattern of pathology severity to the brain's connectivity matrix, which reveals information about how pathology propagates through the connectivity network. Such network models typically use networks based on functional or structural connectivity in young and healthy individuals, and only end-stage patterns of pathology, thereby ignoring/excluding the effects of normal aging and disease progression. Here, we examine the sequence of changes in the elderly brain's anatomical connectivity over the course of a neurodegenerative disease. We do this in a data-driven manner that is not dependent upon clinical disease stage, by using event-based disease progression modeling. Using data from the Alzheimer's Disease Neuroimaging Initiative dataset, we sequence the progressive decline of anatomical connectivity, as quantified by graph-theory metrics, in the Alzheimer's disease brain. Ours is the first single model to contribute to understanding all three of the nature, the location, and the sequence of changes to anatomical connectivity in the human brain due to Alzheimer's disease. Our experimental results reveal new insights into Alzheimer's disease: that degeneration of anatomical connectivity in the brain may be a viable, even early, biomarker and should be considered when studying such neurodegenerative diseases.

Echocardiography Criteria for Structural Heart Disease in Patients With End-Stage Renal Disease Initiating Hemodialysis.

PubMed

Hickson, LaTonya J; Negrotto, Sara M; Onuigbo, Macaulay; Scott, Christopher G; Rule, Andrew D; Norby, Suzanne M; Albright, Robert C; Casey, Edward T; Dillon, John J; Pellikka, Patricia A; Pislaru, Sorin V; Best, Patricia J M; Villarraga, Hector R; Lin, Grace; Williams, Amy W; Nkomo, Vuyisile T

2016-03-15

Cardiovascular disease among hemodialysis (HD) patients is linked to poor outcomes. The Acute Dialysis Quality Initiative Workgroup proposed echocardiographic (ECHO) criteria for structural heart disease (SHD) in dialysis patients. The association of SHD with important patient outcomes is not well defined. This study sought to determine prevalence of ECHO-determined SHD and its association with survival among incident HD patients. We analyzed patients who began chronic HD from 2001 to 2013 who underwent ECHO ≤1 month prior to or ≤3 months following initiation of HD (n = 654). Mean patient age was 66 ± 16 years, and 60% of patients were male. ECHO findings that met 1 or more and ≥3 of the new criteria were discovered in 87% and 54% of patients, respectively. Over a median of 2.4 years, 415 patients died: 108 (26%) died within 6 months. Five-year mortality was 62%. Age- and sex-adjusted structural heart disease variables associated with death were left ventricular ejection fraction (LVEF) ≤45% (hazard ratio [HR]: 1.48; confidence interval [CI]: 1.20 to 1.83) and right ventricular (RV) systolic dysfunction (HR: 1.68; CI: 1.35 to 2.07). An additive of higher death risk included LVEF ≤45% and RV systolic dysfunction rather than neither (HR: 2.04; CI: 1.57 to 2.67; p = 0.53 for test for interaction). Following adjustment for age, sex, race, diabetic kidney disease, and dialysis access, RV dysfunction was independently associated with death (HR: 1.66; CI 1.34 to 2.06; p < 0.001). SHD was common in our HD study population, and RV systolic dysfunction independently predicted mortality. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Offering to Share: How to Put Heads Together in Autism Neuroimaging

ERIC Educational Resources Information Center

Belmonte, Matthew K.; Mazziotta, John C.; Minshew, Nancy J.; Evans, Alan C.; Courchesne, Eric; Dager, Stephen R.; Bookheimer, Susan Y.; Aylward, Elizabeth H.; Amaral, David G.; Cantor, Rita M.; Chugani, Diane C.; Dale, Anders M.; Davatzikos, Christos; Gerig, Guido; Herbert, Martha R.; Lainhart, Janet E.; Murphy, Declan G.; Piven, Joseph; Reiss, Allan L.; Schultz, Robert T.; Zeffiro, Thomas A.; Levi-Pearl, Susan; Lajonchere, Clara; Colamarino, Sophia A.

2008-01-01

Data sharing in autism neuroimaging presents scientific, technical, and social obstacles. We outline the desiderata for a data-sharing scheme that combines imaging with other measures of phenotype and with genetics, defines requirements for comparability of derived data and recommendations for raw data, outlines a core protocol including…

Emotional state affects gait initiation in individuals with Parkinson’s disease

PubMed Central

Hass, Chris J.; Bowers, Dawn; Janelle, Christopher M.

2013-01-01

The purpose of the present study was to determine the impact of manipulating emotional state on gait initiation in persons with Parkinson’s disease (PD) and healthy older adults. Following the presentation of pictures that are known to elicit specific emotional responses, participants initiated gait and continued to walk for several steps at their normal pace. Reaction time, the displacement and velocity of the center of pressure (COP) trajectory during the preparatory postural adjustments, and length and velocity of the first two steps were measured. Analysis of the gait initiation measures revealed that exposure to (1) threatening pictures, relative to all other pictures, speeded the initiation of gait for PD patients and healthy older adults; (2) approach-oriented emotional pictures (erotic and happy people), relative to withdrawal-oriented pictures, facilitated the anticipatory postural adjustments of gait initiation for PD patients and healthy older adults, as evidenced by greater displacement and velocity of the COP movement; and (3) emotional pictures modulated gait initiation parameters in PD patients to the same degree as in healthy older adults. Collectively, these findings hold significant implications for understanding the circuitry underlying the manner by which emotions modulate movement and for the development of emotion-based interventions designed to maximize improvements in gait initiation for individuals with PD. PMID:22194236

Feasibility of functional neuroimaging to understand adolescent women's sexual decision making.

PubMed

Hensel, Devon J; Hummer, Tom A; Acrurio, Lindsay R; James, Thomas W; Fortenberry, J Dennis

2015-04-01

For young women, new sexual experiences normatively increase after puberty and coincide with extensive changes to brain regions governing self-regulation of risk behavior. These neurodevelopmental changes could leave some young women vulnerable for negative sexual outcomes, including sexually transmitted infection and unintended pregnancy. We evaluated the feasibility of using functional neuroimaging to understand the sexual decision making of adolescent women. Adolescent women (N = 14; 14-15 years) completed enrollment interviews, a neuroimaging task gauging neural activation to appetitive stimuli, and 30 days of prospective diaries following the scan characterizing daily affect and sexual behaviors. Descriptive and inferential statistics assessed the association between imaging and behavioral data. Young women were highly compliant with neuroimaging and diary protocol. Neural activity in a cognitive-affective network, including prefrontal and anterior cingulate regions, was significantly greater during low-risk decisions. Compared with other decisions, high-risk sexual decisions elicited greater activity in the anterior cingulate, and low-risk sexual decision elicited greater activity in regions of the visual cortex. Young women's sexual decision ratings were linked to their sexual history characteristics and daily self-reports of sexual emotions and behaviors. It is feasible to recruit and retain a cohort of female participants to perform a functional magnetic resonance imaging task focused on making decisions about sex, on the basis of varying levels of hypothetical sexual risk, and to complete longitudinal prospective diaries following this task. Preliminary evidence suggests that risk level differentially impacts brain activity related to sexual decision making in these women, which may be related to past and future sexual behaviors. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Investigating the pathogenesis of posttraumatic stress disorder with neuroimaging.

PubMed

Pitman, R K; Shin, L M; Rauch, S L

2001-01-01

Rapidly evolving brain neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) are proving fruitful in exploring the pathogenesis and pathophysiology of posttraumatic stress disorder (PTSD). Structural abnormalities in PTSD found with MRI include nonspecific white matter lesions and decreased hippocampal volume. These abnormalities may reflect pretrauma vulnerability to develop PTSD, or they may be a consequence of traumatic exposure, PTSD, and/or PTSD sequelae. Functional neuroimaging symptom provocation and cognitive activation paradigms using PET measurement of regional cerebral blood flow have revealed greater activation of the amygdala and anterior paralimbic structures (which are known to be involved in processing negative emotions such as fear), greater deactivation of Broca's region (motor speech) and other nonlimbic cortical regions, and failure of activation of the cingulate cortex (which possibly plays an inhibitory role) in response to trauma-related stimuli in individuals with PTSD. Functional MRI research has shown the amygdala to be hyperresponsive to fear-related stimuli in this disorder. Research with PET suggests that cortical, notably hippocampal, metabolism is suppressed to a greater extent by pharmacologic stimulation of the noradrenergic system in persons with PTSD. The growth of knowledge concerning the anatomical and neurochemical basis of this important mental disorder will hopefully eventually lead to rational psychological and pharmacologic treatments.

Initiating an undiagnosed diseases program in the Western Australian public health system.

PubMed

Baynam, Gareth; Broley, Stephanie; Bauskis, Alicia; Pachter, Nicholas; McKenzie, Fiona; Townshend, Sharron; Slee, Jennie; Kiraly-Borri, Cathy; Vasudevan, Anand; Hawkins, Anne; Schofield, Lyn; Helmholz, Petra; Palmer, Richard; Kung, Stefanie; Walker, Caroline E; Molster, Caron; Lewis, Barry; Mina, Kym; Beilby, John; Pathak, Gargi; Poulton, Cathryn; Groza, Tudor; Zankl, Andreas; Roscioli, Tony; Dinger, Marcel E; Mattick, John S; Gahl, William; Groft, Stephen; Tifft, Cynthia; Taruscio, Domenica; Lasko, Paul; Kosaki, Kenjiro; Wilhelm, Helene; Melegh, Bela; Carapetis, Jonathan; Jana, Sayanta; Chaney, Gervase; Johns, Allison; Owen, Peter Wynn; Daly, Frank; Weeramanthri, Tarun; Dawkins, Hugh; Goldblatt, Jack

2017-05-03

New approaches are required to address the needs of complex undiagnosed diseases patients. These approaches include clinical genomic diagnostic pipelines, utilizing intra- and multi-disciplinary platforms, as well as specialty-specific genomic clinics. Both are advancing diagnostic rates. However, complementary cross-disciplinary approaches are also critical to address those patients with multisystem disorders who traverse the bounds of multiple specialties and remain undiagnosed despite existing intra-specialty and genomic-focused approaches. The diagnostic possibilities of undiagnosed diseases include genetic and non-genetic conditions. The focus on genetic diseases addresses some of these disorders, however a cross-disciplinary approach is needed that also simultaneously addresses other disorder types. Herein, we describe the initiation and summary outcomes of a public health system approach for complex undiagnosed patients - the Undiagnosed Diseases Program-Western Australia (UDP-WA). Briefly the UDP-WA is: i) one of a complementary suite of approaches that is being delivered within health service, and with community engagement, to address the needs of those with severe undiagnosed diseases; ii) delivered within a public health system to support equitable access to health care, including for those from remote and regional areas; iii) providing diagnoses and improved patient care; iv) delivering a platform for in-service and real time genomic and phenomic education for clinicians that traverses a diverse range of specialties; v) retaining and recapturing clinical expertise; vi) supporting the education of junior and more senior medical staff; vii) designed to integrate with clinical translational research; and viii) is supporting greater connectedness for patients, families and medical staff. The UDP-WA has been initiated in the public health system to complement existing clinical genomic approaches; it has been targeted to those with a specific diagnostic need

Analysis of the relationships between type 2 diabetes status, glycemic control, and neuroimaging measures in the Diabetes Heart Study Mind.

PubMed

Raffield, Laura M; Cox, Amanda J; Freedman, Barry I; Hugenschmidt, Christina E; Hsu, Fang-Chi; Wagner, Benjamin C; Xu, Jianzhao; Maldjian, Joseph A; Bowden, Donald W

2016-06-01

To examine the relationships between type 2 diabetes (T2D) status, glycemic control, and T2D duration with magnetic resonance imaging (MRI)-derived neuroimaging measures in European Americans from the Diabetes Heart Study (DHS) Mind cohort. Relationships were examined using marginal models with generalized estimating equations in 784 participants from 514 DHS Mind families. Fasting plasma glucose, glycated hemoglobin, and diabetes duration were analyzed in 682 participants with T2D. Models were adjusted for potential confounders, including age, sex, history of cardiovascular disease, smoking, educational attainment, and use of statins or blood pressure medications. Association was tested with gray and white matter volume, white matter lesion volume, gray matter cerebral blood flow, and white and gray matter fractional anisotropy and mean diffusivity. Adjusting for multiple comparisons, T2D status was associated with reduced white matter volume (p = 2.48 × 10(-6)) and reduced gray and white matter fractional anisotropy (p ≤ 0.001) in fully adjusted models, with a trend toward increased white matter lesion volume (p = 0.008) and increased gray and white matter mean diffusivity (p ≤ 0.031). Among T2D-affected participants, neither fasting glucose, glycated hemoglobin, nor diabetes duration were associated with the neuroimaging measures assessed (p > 0.05). While T2D was significantly associated with MRI-derived neuroimaging measures, differences in glycemic control in T2D-affected individuals in the DHS Mind study do not appear to significantly contribute to variation in these measures. This supports the idea that the presence or absence of T2D, not fine gradations of glycemic control, may be more significantly associated with age-related changes in the brain.

78 FR 60878 - Disease, Disability, and Injury Prevention and Control Special Emphasis Panel (SEP): Initial Review

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-02

... announced below concerns Health Promotion and Disease Prevention Research Centers, Funding Opportunity... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Disease... Be Discussed: The meeting will include the initial review, discussion, and evaluation of ``Health...

Polio Eradication Initiative: Contribution to improved communicable diseases surveillance in WHO African region.

PubMed

Mwengee, William; Okeibunor, Joseph; Poy, Alain; Shaba, Keith; Mbulu Kinuani, Leon; Minkoulou, Etienne; Yahaya, Ali; Gaturuku, Peter; Landoh, Dadja Essoya; Nsubuga, Peter; Salla, Mbaye; Mihigo, Richard; Mkanda, Pascal

2016-10-10

Since the launch of the Global Polio Eradication Initiative (GPEI) in 1988, there has been a tremendous progress in the reduction of cases of poliomyelitis. The world is on the verge of achieving global polio eradication and in May 2013, the 66th World Health Assembly endorsed the Polio Eradication and Endgame Strategic Plan (PEESP) 2013-2018. The plan provides a timeline for the completion of the GPEI by eliminating all paralytic polio due to both wild and vaccine-related polioviruses. We reviewed how GPEI supported communicable disease surveillance in seven of the eight countries that were documented as part of World Health Organization African Region best practices documentation. Data from WHO African region was also reviewed to analyze the performance of measles cases based surveillance. All 7 countries (100%) which responded had integrated communicable diseases surveillance core functions with AFP surveillance. The difference is on the number of diseases included based on epidemiology of diseases in a particular country. The results showed that the polio eradication infrastructure has supported and improved the implementation of surveillance of other priority communicable diseases under integrated diseases surveillance and response strategy. As we approach polio eradication, polio-eradication initiative staff, financial resources, and infrastructure can be used as one strategy to build IDSR in Africa. As we are now focusing on measles and rubella elimination by the year 2020, other disease-specific programs having similar goals of eradicating and eliminating diseases like malaria, might consider investing in general infectious disease surveillance following the polio example. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

HCV Treatment Initiation in Patients with Chronic Kidney Disease: Results from ERCHIVES

PubMed Central

Butt, Adeel; Ren, Yanjie; Puenpatom, Amy; Arduino, Jean Marie; Kumar, Ritesh; Abou-Samra, Abdul-Badi

2017-01-01

Abstract Background Newer directing antiviral agents against HCV (DAAs) are safe and efficacious in persons with chronic kidney disease (CKD). Whether availability of these newer DAAs has resulted in more persons with CKD initiating HCV treatment remains unknown. Methods We identified HCV+ persons in ERCHIVES. We excluded HIV+ and HBsAg+ and those with missing HCV RNA and eGFR data. We determined the CKD stage according to National Kidney Foundation criteria. We determined the number of persons initiated on any of the approved DAA-regimen (defined as >14 days of DAA prescription). Logistic regression analyses was used to determine factors associated with treatment initiation. Results Among 76,513 evaluable persons, 21.1% initiated DAA treatment. Initiation rates differed significantly by CKD stage: 21.1% (15,136/68,469) for eGFR>90mL/minute/1.73m2 and CKD stage-2; 14.0% 9853/6,086) for CKD stage 3; and 7.6% (148/1,958) for CKD stage-4/5. Those with CKD stage-3 were 35% less likely and those with CKD stage-4/5 were 65% less likely to initiate treatment with a DAA compared with those with baseline eGFR>90mL/minute/1.73m2. Those with Body Mass Index (BMI)>30 were more likely to initiate treatment (OR 1.24, 95% CI 1.19,1.29). Treatment initiation was less likely in HCV genotype 2 or 3 and those with diabetes (OR 0.82, 95% CI 0.78,0.86), cardiovascular disease (OR 0.73, 95% CI 0.68,0.78), alcohol abuse or dependence (OR 0.75, 95% CI 0.72,0.78) or cirrhosis (OR 0.85, 95% CI 0.80,0.89) at baseline. Conclusion Persons with more advanced CKD are less likely to receive treatment for HCV. Strategies are needed to improve treatment rates in the HCV/CKD population. Disclosures A. Butt, Merck: Investigator, Grant recipient. A. Puenpatom, Merck: Employee, Salary. J. M. Arduino, Merck: Employee, Salary. R. Kumar, Merck: Employee, Salary

Can Neuroimaging Markers of Vascular Pathology Explain Cognitive Performance in Adults with Sickle Cell Anemia? A Review of the Literature

PubMed Central

Jorgensen, Dana R.; Rosano, Caterina; Novelli, Enrico M.

2017-01-01

Adults with homozygous sickle cell anemia have, on average, lower cognitive function than unaffected controls. The mechanisms underlying cognitive deterioration in this population are poorly understood, but cerebral small vessel disease (CSVD) is likely to be implicated. We conducted a systematic review using the Prisma Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of articles that included both measures of cognitive function and magnetic resonance imaging (MRI) neuroimaging markers of small vessel disease. While all five studies identified small vessel disease by MRI, only two of them found a significant relationship between structural changes and cognitive performance. Differences in methodologies and small sample sizes likely accounted for the discrepancies between the studies. We conclude that while MRI is a valuable tool to identify markers of CSVD in this population, larger studies are needed to definitely establish a link between MRI-detectable abnormalities and cognitive function in sickle cell anemia. PMID:27689914

Similar clinical and neuroimaging features in monozygotic twin pair with mutation in progranulin

PubMed Central

McDade, E.; Burrus, T.M.; Boot, B.P.; Kantarci, K.; Fields, J.; Lowe, V.J.; Peller, P.; Knopman, D.; Baker, M.; Finch, N.; Rademakers, R.; Petersen, R.

2012-01-01

Objective: To report the phenotypic characterization of monozygotic twins with mutations encoding progranulin (PGRN). Methods: We studied a twin pair with an exon 4 gene deletion in the PGRN gene. Both twins had clinical and neuropsychological examinations as well as structural MRI and fluorodeoxyglucose PET (FDG-PET) scans. PGRN gene sequencing was performed followed by progranulin ELISA in plasma. Results: Both twins manifested symptoms within 3 years of each other, with early behavioral, language, dysexecutive, and memory problems. MRI and FDG-PET imaging demonstrated a strikingly similar topography of findings with clear left hemisphere predominance. Serum progranulin levels in both were well below those from a normal population sample. Conclusions: Compared with the heterogeneity seen in many families with PGRN mutations, these monozygotic twins demonstrated strong clinical, neuroimaging, and serum progranulin level similarities, demonstrating the importance of shared genetic profiles beyond environmental influences in the symptomatic expression of the disease. PMID:22491866

Loss of executive function after dialysis initiation in adults with chronic kidney disease.

PubMed

Kurella Tamura, Manjula; Vittinghoff, Eric; Hsu, Chi-Yuan; Tam, Karman; Seliger, Stephen L; Sozio, Stephen; Fischer, Michael; Chen, Jing; Lustigova, Eva; Strauss, Louise; Deo, Rajat; Go, Alan S; Yaffe, Kristine

2017-04-01

The association of dialysis initiation with changes in cognitive function among patients with advanced chronic kidney disease is poorly described. To better define this, we enrolled participants with advanced chronic kidney disease from the Chronic Renal Insufficiency Cohort in a prospective study of cognitive function. Eligible participants had a glomerular filtration rate of 20 ml/min/1.73m 2 or less, or dialysis initiation within the past two years. We evaluated cognitive function by a validated telephone battery at regular intervals over two years and analyzed test scores as z scores. Of 212 participants, 123 did not transition to dialysis during follow-up, 37 transitioned to dialysis after baseline, and 52 transitioned to dialysis prior to baseline. In adjusted analyses, the transition to dialysis was associated with a significant loss of executive function, but no significant changes in global cognition or memory. The estimated net difference in cognitive z scores at two years for participants who transitioned to dialysis during follow-up compared to participants who did not transition to dialysis was -0.01 (95% confidence interval -0.13, 0.11) for global cognition, -0.24 (-0.51, 0.03) for memory, and -0.33 (-0.60, -0.07) for executive function. Thus, among adults with advanced chronic kidney disease, dialysis initiation was associated with loss of executive function with no change in other aspects of cognition. Larger studies are needed to evaluate cognition during dialysis initiation. Published by Elsevier Inc.

Chronic granulomatous otitis externa as an initial presentation of cutaneous Crohn disease.

PubMed

Raynor, Eileen M

2014-08-01

In the limited number of Crohn disease cases involving the head and neck, there is a predilection for mucosal surfaces and rare reports of involvement in the postauricular region. To our knowledge, in all previously reported cases involving the head and neck, the patients had a known diagnosis of Crohn disease. This case describes a 10-year-old boy with a history of psoriasis and psoriasiform dermatitis who presented with bilateral chronic granulomatous otitis externa, obliteration of the external auditory canal, and fissuring, resulting in separation of the lobule from the preauricular skin. Pathologic examination results were consistent with granulomatous dermatitis concerning for cutaneous Crohn disease, and a subsequent gastroenterologic workup confirmed the diagnosis of Crohn disease. This is a report of chronic granulomatous otitis as the initial presentation of cutaneous Crohn disease in a child.

Age-specific MRI templates for pediatric neuroimaging

PubMed Central

Sanchez, Carmen E.; Richards, John E.; Almli, C. Robert

2012-01-01

This study created a database of pediatric age-specific MRI brain templates for normalization and segmentation. Participants included children from 4.5 through 19.5 years, totaling 823 scans from 494 subjects. Open-source processing programs (FSL, SPM, ANTS) constructed head, brain and segmentation templates in 6 month intervals. The tissue classification (WM, GM, CSF) showed changes over age similar to previous reports. A volumetric analysis of age-related changes in WM and GM based on these templates showed expected increase/decrease pattern in GM and an increase in WM over the sampled ages. This database is available for use for neuroimaging studies (blindedforreview). PMID:22799759

Neuroimaging of Narcolepsy and Kleine-Levin Syndrome.

PubMed

Hong, Seung Bong

2017-09-01

Narcolepsy is a chronic neurologic disorder with the abnormal regulation of the sleep-wake cycle, resulting in excessive daytime sleepiness, disturbed nocturnal sleep, and manifestations related to rapid eye movement sleep, such as cataplexy, sleep paralysis, and hypnagogic hallucination. Over the past decade, numerous neuroimaging studies have been performed to characterize the pathophysiology and various clinical features of narcolepsy. This article reviews structural and functional brain imaging findings in narcolepsy and Kleine-Levin syndrome. Based on the current state of research, brain imaging is a useful tool to investigate and understand the neuroanatomic correlates and brain abnormalities of narcolepsy and other hypersomnia. Copyright © 2017 Elsevier Inc. All rights reserved.

78 FR 9926 - Disease, Disability, and Injury Prevention and Control Special Emphasis Panel (SEP): Initial Review

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-12

... announced below concerns Prevalence and Incidence of Inflammatory Bowel Disease, FOA DP 13-001, initial... evaluation of applications received in response to ``Prevalence and Incidence of Inflammatory Bowel Disease...

Mood and neural correlates of excessive daytime sleepiness in Parkinson's disease.

PubMed

Wen, M-C; Chan, L L; Tan, L C S; Tan, E K

2017-08-01

For patients with Parkinson's disease (PD), excessive daytime sleepiness (PD-EDS) is a debilitating non-motor symptom and may be affected by mood symptoms, especially depression and anxiety. Few neuroimaging works have attempted to identify the neural features of PD-EDS, but various findings were reported. The purpose of this study was to systematically review the literature on mood and neuroimaging correlates of PD-EDS. A MEDLINE, PubMed, EMBASE, and PsycInfo search for peer-reviewed original research articles on depression, anxiety, and neuroimaging in PD-EDS identified 26 studies on depression, nine on anxiety, and eight on neuroimaging. Half of the studies reported greater depression in PD-EDS-positive patients compared with PD-EDS-negative patients. There was a significantly positive correlation between depression and PD-EDS. Limited studies on anxiety in PD-EDS suggested a weak correlation between anxiety and EDS. For depression and anxiety, the effect sizes were medium when EDS was subjectively measured, but became small when EDS was objective measured. Current neuroimaging studies generally suggested diminished neural structural and functional features (eg, brain volume, white matter integrity as indicated by fractional anisotropy, and cerebral metabolism) in patients with PD-EDS. Future studies should apply objective and subjective measures of mood symptoms and EDS and improve the neuroimaging methodology via using multimodal techniques and whole-brain analysis to provide new clues on the mood and neural correlates of PD-EDS. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies.

PubMed

Guillaume, Bryan; Wang, Changqing; Poh, Joann; Shen, Mo Jun; Ong, Mei Lyn; Tan, Pei Fang; Karnani, Neerja; Meaney, Michael; Qiu, Anqi

2018-06-01

Statistical inference on neuroimaging data is often conducted using a mass-univariate model, equivalent to fitting a linear model at every voxel with a known set of covariates. Due to the large number of linear models, it is challenging to check if the selection of covariates is appropriate and to modify this selection adequately. The use of standard diagnostics, such as residual plotting, is clearly not practical for neuroimaging data. However, the selection of covariates is crucial for linear regression to ensure valid statistical inference. In particular, the mean model of regression needs to be reasonably well specified. Unfortunately, this issue is often overlooked in the field of neuroimaging. This study aims to adopt the existing Confounder Adjusted Testing and Estimation (CATE) approach and to extend it for use with neuroimaging data. We propose a modification of CATE that can yield valid statistical inferences using Principal Component Analysis (PCA) estimators instead of Maximum Likelihood (ML) estimators. We then propose a non-parametric hypothesis testing procedure that can improve upon parametric testing. Monte Carlo simulations show that the modification of CATE allows for more accurate modelling of neuroimaging data and can in turn yield a better control of False Positive Rate (FPR) and Family-Wise Error Rate (FWER). We demonstrate its application to an Epigenome-Wide Association Study (EWAS) on neonatal brain imaging and umbilical cord DNA methylation data obtained as part of a longitudinal cohort study. Software for this CATE study is freely available at http://www.bioeng.nus.edu.sg/cfa/Imaging_Genetics2.html. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Drugs for Neglected Diseases initiative model of drug development for neglected diseases: current status and future challenges.

PubMed

Ioset, Jean-Robert; Chang, Shing

2011-09-01

The Drugs for Neglected Diseases initiative (DNDi) is a patients' needs-driven organization committed to the development of new treatments for neglected diseases. Created in 2003, DNDi has delivered four improved treatments for malaria, sleeping sickness and visceral leishmaniasis. A main DNDi challenge is to build a solid R&D portfolio for neglected diseases and to deliver preclinical candidates in a timely manner using an original model based on partnership. To address this challenge DNDi has remodeled its discovery activities from a project-based academic-bound network to a fully integrated process-oriented platform in close collaboration with pharmaceutical companies. This discovery platform relies on dedicated screening capacity and lead-optimization consortia supported by a pragmatic, structured and pharmaceutical-focused compound sourcing strategy.

Hypnosis and pain perception: An Activation Likelihood Estimation (ALE) meta-analysis of functional neuroimaging studies.

PubMed

Del Casale, Antonio; Ferracuti, Stefano; Rapinesi, Chiara; De Rossi, Pietro; Angeletti, Gloria; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo

2015-12-01

Several studies reported that hypnosis can modulate pain perception and tolerance by affecting cortical and subcortical activity in brain regions involved in these processes. We conducted an Activation Likelihood Estimation (ALE) meta-analysis on functional neuroimaging studies of pain perception under hypnosis to identify brain activation-deactivation patterns occurring during hypnotic suggestions aiming at pain reduction, including hypnotic analgesic, pleasant, or depersonalization suggestions (HASs). We searched the PubMed, Embase and PsycInfo databases; we included papers published in peer-reviewed journals dealing with functional neuroimaging and hypnosis-modulated pain perception. The ALE meta-analysis encompassed data from 75 healthy volunteers reported in 8 functional neuroimaging studies. HASs during experimentally-induced pain compared to control conditions correlated with significant activations of the right anterior cingulate cortex (Brodmann's Area [BA] 32), left superior frontal gyrus (BA 6), and right insula, and deactivation of right midline nuclei of the thalamus. HASs during experimental pain impact both cortical and subcortical brain activity. The anterior cingulate, left superior frontal, and right insular cortices activation increases could induce a thalamic deactivation (top-down inhibition), which may correlate with reductions in pain intensity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging.

PubMed

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging

PubMed Central

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research. PMID:29033866

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease

PubMed Central

Schmitter, Daniel; Roche, Alexis; Maréchal, Bénédicte; Ribes, Delphine; Abdulkadir, Ahmed; Bach-Cuadra, Meritxell; Daducci, Alessandro; Granziera, Cristina; Klöppel, Stefan; Maeder, Philippe; Meuli, Reto; Krueger, Gunnar

2014-01-01

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease. PMID:25429357

Exploration of Prostate Cancer Treatment Induced Neurotoxicity with Neuroimaging

DTIC Science & Technology

2008-05-01

report are those of the author( s ) and should not be construed as an official Department of the Army position, policy or decision unless so designated...Prostate Cancer Treatment Induced Neurotoxicity with Neuroimaging 5b. GRANT NUMBER W81XWH-06-1-0033 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) Jeri...Janowsky, Ph.D. 5d. PROJECT NUMBER 5e. TASK NUMBER E-Mail: janowskj@ohsu.edu 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance

PubMed Central

2011-01-01

Background Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. Method In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N = 120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Results Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. Discussion We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks Conclusion The proposed approach

The Spanish biology/disease initiative within the human proteome project: Application to rheumatic diseases.

PubMed

Ruiz-Romero, Cristina; Calamia, Valentina; Albar, Juan Pablo; Casal, José Ignacio; Corrales, Fernando J; Fernández-Puente, Patricia; Gil, Concha; Mateos, Jesús; Vivanco, Fernando; Blanco, Francisco J

2015-09-08

The Spanish Chromosome 16 consortium is integrated in the global initiative Human Proteome Project, which aims to develop an entire map of the proteins encoded following a gene-centric strategy (C-HPP) in order to make progress in the understanding of human biology in health and disease (B/D-HPP). Chromosome 16 contains many genes encoding proteins involved in the development of a broad range of diseases, which have a significant impact on the health care system. The Spanish HPP consortium has developed a B/D platform with five programs focused on selected medical areas: cancer, obesity, cardiovascular, infectious and rheumatic diseases. Each of these areas has a clinical leader associated to a proteomic investigator with the responsibility to get a comprehensive understanding of the proteins encoded by Chromosome 16 genes. Proteomics strategies have enabled great advances in the area of rheumatic diseases, particularly in osteoarthritis, with studies performed on joint cells, tissues and fluids. In this manuscript we describe how the Spanish HPP-16 consortium has developed a B/D platform with five programs focused on selected medical areas: cancer, obesity, cardiovascular, infectious and rheumatic diseases. Each of these areas has a clinical leader associated to a proteomic investigator with the responsibility to get a comprehensive understanding of the proteins encoded by Chromosome 16 genes. We show how the Proteomic strategy has enabled great advances in the area of rheumatic diseases, particularly in osteoarthritis, with studies performed on joint cells, tissues and fluids. This article is part of a Special Issue entitled: HUPO 2014. Copyright © 2015 Elsevier B.V. All rights reserved.

What Is Self-Specific? Theoretical Investigation and Critical Review of Neuroimaging Results

ERIC Educational Resources Information Center

Legrand, Dorothee; Ruby, Perrine

2009-01-01

The authors propose a paradigm shift in the investigation of the self. Synthesizing neuroimaging results from studies investigating the self, the authors first demonstrate that self-relatedness evaluation involves a wide cerebral network, labeled E-network, comprising the medial prefrontal cortex, precuneus, temporoparietal junction, and temporal…

Integrating Functional Brain Neuroimaging and Developmental Cognitive Neuroscience in Child Psychiatry Research

ERIC Educational Resources Information Center

Pavuluri, Mani N.; Sweeney, John A.

2008-01-01

The use of cognitive neuroscience and functional brain neuroimaging to understand brain dysfunction in pediatric psychiatric disorders is discussed. Results show that bipolar youths demonstrate impairment in affective and cognitive neural systems and in these two circuits' interface. Implications for the diagnosis and treatment of psychiatric…

Adolescent Schizophrenia: A Methodologic Review of the Current Neuroimaging and Neuropsychologic Literature.

ERIC Educational Resources Information Center

Findling, Robert L.; And Others

1995-01-01

This paper reviews the methodology in articles that have reported structural neuroimaging or neuropsychological data in adolescent patients with schizophrenia. Identification of methodological issues led to the finding that, at present, no conclusions can be made regarding the presence or absence of neuropsychologic dysfunction or structural…

Neuroimaging of classic neuralgic amyotrophy.

PubMed

Lieba-Samal, Doris; Jengojan, Suren; Kasprian, Gregor; Wöber, Christian; Bodner, Gerd

2016-12-01

Neuralgic amyotrophy (NA) often imposes diagnostic problems. Recently, MRI and high-resolution ultrasound (HRUS) have proven useful in diagnosing peripheral nerve disorders. We performed a chart and imaging review of patients who were examined using neuroimaging and who were referred because of clinically diagnosed NA between March 1, 2014 and May 1, 2015. Six patients were included. All underwent HRUS, and 5 underwent MRI. Time from onset to evaluation ranged from 2 weeks to 6 months. HRUS showed segmental swelling of all clinically affected nerves/trunks. Atrophy of muscles was detected in those assessed >1 month after onset. MRI showed T2-weighted hyperintensity in all clinically affected nerves, except for the long thoracic nerve, and denervation edema of muscles. HRUS and MRI are valuable diagnostic tools in NA. This could change the diagnostic approach from one now focused on excluding other disorders to confirming NA through imaging markers. Muscle Nerve 54: 1079-1085, 2016. © 2016 Wiley Periodicals, Inc.

Building chronic disease management capacity in General Practice: The South Australian GP Plus Practice Nurse Initiative.

PubMed

Fuller, Jeffrey; Koehne, Kristy; Verrall, Claire C; Szabo, Natalie; Bollen, Chris; Parker, Sharon

2015-01-01

This paper draws on the implementation experience of the South Australian GP Plus Practice Nurse Initiative in order to establish what is needed to support the development of the chronic disease management role of practice nurses. The Initiative was delivered between 2007 and 2010 to recruit, train and place 157 nurses across 147 General Practices in Adelaide. The purpose was to improve chronic disease management in General Practice, by equipping nurses to work as practice nurses who would coordinate care and establish chronic disease management systems. Secondary analysis of qualitative data contained in the Initiative evaluation report, specifically drawing on quarterly project records and four focus groups conducted with practice nurses, practice nurse coordinators and practice nurse mentors. As evidenced by the need to increase the amount of support provided during the implementation of the Initiative, nurses new to General Practice faced challenges in their new role. Nurses described a big learning curve as they dealt with role transition to a new work environment and learning a range of new skills while developing chronic disease management systems. Informants valued the skills development and support offered by the Initiative, however the ongoing difficulties in implementing the role suggested that change is also needed at the level of the Practice. While just over a half of the placement positions were retained, practice nurses expressed concern with having to negotiate the conditions of their employment. In order to advance the role of practice nurses as managers of chronic disease support is needed at two levels. At one level support is needed to assist practice nurses to build their own skills. At the level of the Practice, and in the wider health workforce system, support is also needed to ensure that Practices are organisationally ready to include the practice nurse within the practice team.

Automatic morphometry in Alzheimer's disease and mild cognitive impairment☆☆☆

PubMed Central

Heckemann, Rolf A.; Keihaninejad, Shiva; Aljabar, Paul; Gray, Katherine R.; Nielsen, Casper; Rueckert, Daniel; Hajnal, Joseph V.; Hammers, Alexander

2011-01-01

This paper presents a novel, publicly available repository of anatomically segmented brain images of healthy subjects as well as patients with mild cognitive impairment and Alzheimer's disease. The underlying magnetic resonance images have been obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. T1-weighted screening and baseline images (1.5 T and 3 T) have been processed with the multi-atlas based MAPER procedure, resulting in labels for 83 regions covering the whole brain in 816 subjects. Selected segmentations were subjected to visual assessment. The segmentations are self-consistent, as evidenced by strong agreement between segmentations of paired images acquired at different field strengths (Jaccard coefficient: 0.802 ± 0.0146). Morphometric comparisons between diagnostic groups (normal; stable mild cognitive impairment; mild cognitive impairment with progression to Alzheimer's disease; Alzheimer's disease) showed highly significant group differences for individual regions, the majority of which were located in the temporal lobe. Additionally, significant effects were seen in the parietal lobe. Increased left/right asymmetry was found in posterior cortical regions. An automatically derived white-matter hypointensities index was found to be a suitable means of quantifying white-matter disease. This repository of segmentations is a potentially valuable resource to researchers working with ADNI data. PMID:21397703

Using Base Rate of Low Scores to Identify Progression from Amnestic Mild Cognitive Impairment to Alzheimer's Disease.

PubMed

Oltra-Cucarella, Javier; Sánchez-SanSegundo, Miriam; Lipnicki, Darren M; Sachdev, Perminder S; Crawford, John D; Pérez-Vicente, José A; Cabello-Rodríguez, Luis; Ferrer-Cascales, Rosario

2018-05-10

To investigate the implications of obtaining one or more low scores on a battery of cognitive tests on diagnosing mild cognitive impairment (MCI). Observational longitudinal study. Alzheimer's Disease Neuroimaging Initiative. Normal controls (NC, n = 280) and participants with MCI (n = 415) according to Petersen criteria were reclassified using the Jak/Bondi criteria and number of impaired tests (NIT) criteria. Diagnostic statistics and hazard ratios of progression to Alzheimer's disease (AD) were compared according to diagnostic criteria. The NIT criteria were a better predictor of progression to AD than the Petersen or Jak/Bondi criteria, with optimal sensitivity, specificity, and positive and negative predictive value. Considering normal variability in cognitive test performance when diagnosing MCI may help identify individuals at greatest risk of progression to AD with greater certainty. © 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.

Neuroimaging in aphasia treatment research: Consensus and practical guidelines for data analysis

PubMed Central

Meinzer, Marcus; Beeson, Pélagie M.; Cappa, Stefano; Crinion, Jenny; Kiran, Swathi; Saur, Dorothee; Parrish, Todd; Crosson, Bruce; Thompson, Cynthia K.

2012-01-01

Functional magnetic resonance imaging is the most widely used imaging technique to study treatment-induced recovery in post-stroke aphasia. The longitudinal design of such studies adds to the challenges researchers face when studying patient populations with brain damage in cross-sectional settings. The present review focuses on issues specifically relevant to neuroimaging data analysis in aphasia treatment research identified in discussions among international researchers at the Neuroimaging in Aphasia Treatment Research Workshop held at Northwestern University (Evanston, Illinois, USA). In particular, we aim to provide the reader with a critical review of unique problems related to the pre-processing, statistical modeling and interpretation of such data sets. Despite the fact that data analysis procedures critically depend on specific design features of a given study, we aim to discuss and communicate a basic set of practical guidelines that should be applicable to a wide range of studies and useful as a reference for researchers pursuing this line of research. PMID:22387474

Functional neuroimaging studies in addiction: multisensory drug stimuli and neural cue reactivity.

PubMed

Yalachkov, Yavor; Kaiser, Jochen; Naumer, Marcus J

2012-02-01

Neuroimaging studies on cue reactivity have substantially contributed to the understanding of addiction. In the majority of studies drug cues were presented in the visual modality. However, exposure to conditioned cues in real life occurs often simultaneously in more than one sensory modality. Therefore, multisensory cues should elicit cue reactivity more consistently than unisensory stimuli and increase the ecological validity and the reliability of brain activation measurements. This review includes the data from 44 whole-brain functional neuroimaging studies with a total of 1168 subjects (812 patients and 356 controls). Correlations between neural cue reactivity and clinical covariates such as craving have been reported significantly more often for multisensory than unisensory cues in the motor cortex, insula and posterior cingulate cortex. Thus, multisensory drug cues are particularly effective in revealing brain-behavior relationships in neurocircuits of addiction responsible for motivation, craving awareness and self-related processing. Copyright © 2011 Elsevier Ltd. All rights reserved.

Correlated patterns of neuropsychological and behavioral symptoms in frontal variant of Alzheimer disease and behavioral variant frontotemporal dementia: a comparative case study.

PubMed

Li, Pan; Zhou, Yu-Ying; Lu, Da; Wang, Yan; Zhang, Hui-Hong

2016-05-01

Although the neuropathologic changes and diagnostic criteria for the neurodegenerative disorder Alzheimer's disease (AD) are well-established, the clinical symptoms vary largely. Symptomatically, frontal variant of AD (fv-AD) presents very similarly to behavioral variant frontotemporal dementia (bvFTD), which creates major challenges for differential diagnosis. Here, we report two patients who present with progressive cognitive impairment, early and prominent behavioral features, and significant frontotemporal lobe atrophy on magnetic resonance imaging, consistent with an initial diagnosis of probable bvFTD. However, multimodal functional neuroimaging revealed neuropathological data consistent with a diagnosis of probable AD for one patient (pathology distributed in the frontal lobes) and a diagnosis of probable bvFTD for the other patient (hypometabolism in the bilateral frontal lobes). In addition, the fv-AD patient presented with greater executive impairment and milder behavioral symptoms relative to the bvFTD patient. These cases highlight that recognition of these atypical syndromes using detailed neuropsychological tests, biomarkers, and multimodal neuroimaging will lead to greater accuracy in diagnosis and patient management.

Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer’s disease in veterans, using the Alzheimer’s Disease Neuroimaging Initiative

PubMed Central

Weiner, Michael W.; Veitch, Dallas P.; Hayes, Jacqueline; Neylan, Thomas; Grafman, Jordan; Aisen, Paul S.; Petersen, Ronald C.; Jack, Clifford; Jagust, William; Trojanowski, John Q.; Shaw, Leslie M.; Saykin, Andrew J.; Green, Robert C.; Harvey, Danielle; Toga, Arthur W.; Friedl, Karl E.; Pacifico, Anthony; Sheline, Yvette; Yaffe, Kristine; Mohlenoff, Brian

2015-01-01

Both traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are common problems resulting from military service, and both have been associated with increased risk of cognitive decline and dementia resulting from Alzheimer’s disease (AD) or other causes. This study aims to use imaging techniques and biomarker analysis to determine whether traumatic brain injury (TBI) and/or PTSD resulting from combat or other traumas increase the risk for AD and decrease cognitive reserve in Veteran subjects, after accounting for age. Using military and Department of Veterans Affairs records, 65 Vietnam War veterans with a history of moderate or severe TBI with or without PTSD, 65 with ongoing PTSD without TBI, and 65 control subjects are being enrolled in this study at 19 sites. The study aims to select subject groups that are comparable in age, gender, ethnicity, and education. Subjects with mild cognitive impairment (MCI) or dementia are being excluded. However, a new study just beginning, and similar in size, will study subjects with TBI, subjects with PTSD, and control subjects with MCI. Baseline measurements of cognition, function, blood, and cerebrospinal fluid bio-markers; magnetic resonance images (structural, diffusion tensor, and resting state blood-level oxygen dependent (BOLD) functional magnetic resonance imaging); and amyloid positron emission tomographic (PET) images with florbetapir are being obtained. One-year follow-up measurements will be collected for most of the baseline procedures, with the exception of the lumbar puncture, the PET imaging, and apolipoprotein E genotyping. To date, 19 subjects with TBI only, 46 with PTSD only, and 15 with TBI and PTSD have been recruited and referred to 13 clinics to undergo the study protocol. It is expected that cohorts will be fully recruited by October 2014. This study is a first step toward the design and statistical powering of an AD prevention trial using at-risk veterans as subjects, and provides the

Hemorrhage recurrence risk factors in cerebral amyloid angiopathy: Comparative analysis of the overall small vessel disease severity score versus individual neuroimaging markers.

PubMed

Boulouis, Gregoire; Charidimou, Andreas; Pasi, Marco; Roongpiboonsopit, Duangnapa; Xiong, Li; Auriel, Eitan; van Etten, Ellis S; Martinez-Ramirez, Sergi; Ayres, Alison; Vashkevich, Anastasia; Schwab, Kristin M; Rosand, Jonathan; Goldstein, Joshua N; Gurol, M Edip; Greenberg, Steven M; Viswanathan, Anand

2017-09-15

An MRI-based score of total small vessel disease burden (CAA-SVD-Score) in cerebral amyloid angiopathy (CAA) has been demonstrated to correlate with severity of pathologic changes. Evidence suggests that CAA-related intracerebral hemorrhage (ICH) recurrence risk is associated with specific disease imaging manifestations rather than overall severity. We compared the correlation between the CAA-SVD-Score with the risk of recurrent CAA-related lobar ICH versus the predictive role of each of its components. Consecutive patients with CAA-related ICH from a single-center prospective cohort were analyzed. Radiological markers of CAA related SVD damage were quantified and categorized according to the CAA-SVD-Score (0-6 points). Subjects were followed prospectively for recurrent symptomatic ICH. Adjusted Cox proportional hazards models were used to investigate associations between the CAA-SVD-Score as well as each of the individual MRI signatures of CAA and the risk of recurrent ICH. In 229 CAA patients with ICH, a total of 56 recurrent ICH events occurred during a median follow-up of 2.8years [IQR 0.9-5.4years, 781 person-years). Higher CAA-SVD-Score (HR=1.26 per additional point, 95%CI [1.04-1.52], p=0.015) and older age were independently associated with higher ICH recurrence risk. Analysis of individual markers of CAA showed that CAA-SVD-Score findings were due to the independent effect of disseminated superficial siderosis (HR for disseminated cSS vs none: 2.89, 95%CI [1.47-5.5], p=0.002) and high degree of perivascular spaces enlargement (RR=3.50-95%CI [1.04-21], p=0.042). In lobar CAA-ICH patients, higher CAA-SVD-Score does predict recurrent ICH. Amongst individual elements of the score, superficial siderosis and dilated perivascular spaces are the only markers independently associated with ICH recurrence, contributing to the evidence for distinct CAA phenotypes singled out by neuro-imaging manifestations. Copyright © 2017 Elsevier B.V. All rights reserved.

Replication Validity of Initial Association Studies: A Comparison between Psychiatry, Neurology and Four Somatic Diseases.

PubMed

Dumas-Mallet, Estelle; Button, Katherine; Boraud, Thomas; Munafo, Marcus; Gonon, François

2016-01-01

There are growing concerns about effect size inflation and replication validity of association studies, but few observational investigations have explored the extent of these problems. Using meta-analyses to measure the reliability of initial studies and explore whether this varies across biomedical domains and study types (cognitive/behavioral, brain imaging, genetic and "others"). We analyzed 663 meta-analyses describing associations between markers or risk factors and 12 pathologies within three biomedical domains (psychiatry, neurology and four somatic diseases). We collected the effect size, sample size, publication year and Impact Factor of initial studies, largest studies (i.e., with the largest sample size) and the corresponding meta-analyses. Initial studies were considered as replicated if they were in nominal agreement with meta-analyses and if their effect size inflation was below 100%. Nominal agreement between initial studies and meta-analyses regarding the presence of a significant effect was not better than chance in psychiatry, whereas it was somewhat better in neurology and somatic diseases. Whereas effect sizes reported by largest studies and meta-analyses were similar, most of those reported by initial studies were inflated. Among the 256 initial studies reporting a significant effect (p<0.05) and paired with significant meta-analyses, 97 effect sizes were inflated by more than 100%. Nominal agreement and effect size inflation varied with the biomedical domain and study type. Indeed, the replication rate of initial studies reporting a significant effect ranged from 6.3% for genetic studies in psychiatry to 86.4% for cognitive/behavioral studies. Comparison between eight subgroups shows that replication rate decreases with sample size and "true" effect size. We observed no evidence of association between replication rate and publication year or Impact Factor. The differences in reliability between biological psychiatry, neurology and somatic

Alterations in cholesterol metabolism-related genes in sporadic Alzheimer's disease.

PubMed

Picard, Cynthia; Julien, Cédric; Frappier, Josée; Miron, Justin; Théroux, Louise; Dea, Doris; Breitner, John C S; Poirier, Judes

2018-06-01

Genome-wide association studies have identified several cholesterol metabolism-related genes as top risk factors for late-onset Alzheimer's disease (LOAD). We hypothesized that specific genetic variants could act as disease-modifying factors by altering the expression of those genes. Targeted association studies were conducted with available genomic, transcriptomic, proteomic, and histopathological data from 3 independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Quebec Founder Population (QFP), and the United Kingdom Brain Expression Consortium (UKBEC). First, a total of 273 polymorphisms located in 17 cholesterol metabolism-related loci were screened for associations with cerebrospinal fluid LOAD biomarkers beta amyloid, phosphorylated tau, and tau (from the ADNI) and with amyloid plaque and tangle densities (from the QFP). Top polymorphisms were then contrasted with gene expression levels measured in 134 autopsied healthy brains (from the UKBEC). In the end, only SREBF2 polymorphism rs2269657 showed significant dual associations with LOAD pathological biomarkers and gene expression levels. Furthermore, SREBF2 expression levels measured in LOAD frontal cortices inversely correlated with age at death; suggesting a possible influence on survival rate. Copyright © 2018 Elsevier Inc. All rights reserved.

Oxytocin and Social Adaptation: Insights from Neuroimaging Studies of Healthy and Clinical Populations.

PubMed

Ma, Yina; Shamay-Tsoory, Simone; Han, Shihui; Zink, Caroline F

2016-02-01

Adaptation to the social environment is critical for human survival. The neuropeptide oxytocin (OT), implicated in social cognition and emotions pivotal to sociality and well-being, is a promising pharmacological target for social and emotional dysfunction. We suggest here that the multifaceted role of OT in socio-affective processes improves the capability for social adaptation. We review OT effects on socio-affective processes, with a focus on OT-neuroimaging studies, to elucidate neuropsychological mechanisms through which OT promotes social adaptation. We also review OT-neuroimaging studies of individuals with social deficits and suggest that OT ameliorates impaired social adaptation by normalizing hyper- or hypo-brain activity. The social adaption model (SAM) provides an integrative understanding of discrepant OT effects and the modulations of OT action by personal milieu and context. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neuroimaging studies of aggressive and violent behavior: current findings and implications for criminology and criminal justice.

PubMed

Bufkin, Jana L; Luttrell, Vickie R

2005-04-01

With the availability of new functional and structural neuroimaging techniques, researchers have begun to localize brain areas that may be dysfunctional in offenders who are aggressive and violent. Our review of 17 neuroimaging studies reveals that the areas associated with aggressive and/or violent behavioral histories, particularly impulsive acts, are located in the prefrontal cortex and the medial temporal regions. These findings are explained in the context of negative emotion regulation, and suggestions are provided concerning how such findings may affect future theoretical frameworks in criminology, crime prevention efforts, and the functioning of the criminal justice system.

Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging☆