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.

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.

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.

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

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'.

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

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

[Seeking the aetiology of autistic spectrum disorder. Part 2: Functional neuroimaging].

PubMed

Bryńska, Anita

2012-01-01

Multiple functional imaging techniques help to a better understanding of the neurobiological basis of autism-spectrum disorders (ASD). The early functional imaging studies on ASD focused on task-specific methods related to core symptom domains and explored patterns of activation in response to face processing, theory of mind tasks, language processing and executive function tasks. On the other hand, fMRI research in ASD focused on the development of functional connectivity methods and has provided evidence of alterations in cortical connectivity in ASD and establish autism as a disorder of under-connectivity among the brain regions participating in cortical networks. This atypical functional connectivity in ASD results in inefficiency and poor integration of processing in network connections to achieve task performance. The goal of this review is to summarise the actual neuroimaging functional data and examine their implication for understanding of the neurobiology of ASD.

Towards Tunable Consensus Clustering for Studying Functional Brain Connectivity During Affective Processing.

PubMed

Liu, Chao; Abu-Jamous, Basel; Brattico, Elvira; Nandi, Asoke K

2017-03-01

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package "UNCLES" available on http://cran.r-project.org/web/packages/UNCLES/index.html .

Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.

PubMed

Franco, Alexandre R; Ling, Josef; Caprihan, Arvind; Calhoun, Vince D; Jung, Rex E; Heileman, Gregory L; Mayer, Andrew R

2008-12-01

The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the methods.

Shining a Light on Awareness: A Review of Functional Near-Infrared Spectroscopy for Prolonged Disorders of Consciousness

PubMed Central

Rupawala, Mohammed; Dehghani, Hamid; Lucas, Samuel J. E.; Tino, Peter; Cruse, Damian

2018-01-01

Qualitative clinical assessments of the recovery of awareness after severe brain injury require an assessor to differentiate purposeful behavior from spontaneous behavior. As many such behaviors are minimal and inconsistent, behavioral assessments are susceptible to diagnostic errors. Advanced neuroimaging tools can bypass behavioral responsiveness and reveal evidence of covert awareness and cognition within the brains of some patients, thus providing a means for more accurate diagnoses, more accurate prognoses, and, in some instances, facilitated communication. The majority of reports to date have employed the neuroimaging methods of functional magnetic resonance imaging, positron emission tomography, and electroencephalography (EEG). However, each neuroimaging method has its own advantages and disadvantages (e.g., signal resolution, accessibility, etc.). Here, we describe a burgeoning technique of non-invasive optical neuroimaging—functional near-infrared spectroscopy (fNIRS)—and review its potential to address the clinical challenges of prolonged disorders of consciousness. We also outline the potential for simultaneous EEG to complement the fNIRS signal and suggest the future directions of research that are required in order to realize its clinical potential. PMID:29872420

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.

Structural and functional neural correlates of music perception.

PubMed

Limb, Charles J

2006-04-01

This review article highlights state-of-the-art functional neuroimaging studies and demonstrates the novel use of music as a tool for the study of human auditory brain structure and function. Music is a unique auditory stimulus with properties that make it a compelling tool with which to study both human behavior and, more specifically, the neural elements involved in the processing of sound. Functional neuroimaging techniques represent a modern and powerful method of investigation into neural structure and functional correlates in the living organism. These methods have demonstrated a close relationship between the neural processing of music and language, both syntactically and semantically. Greater neural activity and increased volume of gray matter in Heschl's gyrus has been associated with musical aptitude. Activation of Broca's area, a region traditionally considered to subserve language, is important in interpreting whether a note is on or off key. The planum temporale shows asymmetries that are associated with the phenomenon of perfect pitch. Functional imaging studies have also demonstrated activation of primitive emotional centers such as ventral striatum, midbrain, amygdala, orbitofrontal cortex, and ventral medial prefrontal cortex in listeners of moving musical passages. In addition, studies of melody and rhythm perception have elucidated mechanisms of hemispheric specialization. These studies show the power of music and functional neuroimaging to provide singularly useful tools for the study of brain structure and function.

The use of functional neuroimaging to evaluate psychological and other non-pharmacological treatments for clinical pain

PubMed Central

Jensen, Karin B.; Berna, Chantal; Loggia, Marco L.; Wasan, Ajay; Edwards, Robert R.; Gollub, Randy L.

2013-01-01

A large number of studies have provided evidence for the efficacy of psychological and other non-pharmacological interventions in the treatment of chronic pain. While these methods are increasingly used to treat pain, remarkably few studies focused on the exploration of their neural correlates. The aim of this article was to review the findings from neuroimaging studies that evaluated the neural response to distraction-based techniques, cognitive behavioral therapy (CBT), clinical hypnosis, mental imagery, physical therapy/exercise, biofeedback, and mirror therapy. To date, the results from studies that used neuroimaging to evaluate these methods have not been conclusive and the experimental methods have been suboptimal for assessing clinical pain. Still, several different psychological and non-pharmacological treatment modalities were associated with increased painrelated activations of executive cognitive brain regions, such as the ventral- and dorsolateral prefrontal cortex. There was also evidence for decreased pain-related activations in afferent pain regions and limbic structures. If future studies will address the technical and methodological challenges of today’s experiments, neuroimaging might have the potential of segregating the neural mechanisms of different treatment interventions and elucidate predictive and mediating factors for successful treatment outcomes. Evaluations of treatment-related brain changes (functional and structural) might also allow for sub-grouping of patients and help to develop individualized treatments. PMID:22445888

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.

iELVis: An open source MATLAB toolbox for localizing and visualizing human intracranial electrode data.

PubMed

Groppe, David M; Bickel, Stephan; Dykstra, Andrew R; Wang, Xiuyuan; Mégevand, Pierre; Mercier, Manuel R; Lado, Fred A; Mehta, Ashesh D; Honey, Christopher J

2017-04-01

Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive. iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg. Copyright © 2017 Elsevier B.V. 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

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

Brain Morphometry using MRI in Schizophrenia Patients

NASA Astrophysics Data System (ADS)

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

2010-01-01

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

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

Mapping brain function in freely moving subjects

PubMed Central

Holschneider, Daniel P.; Maarek, Jean-Michel I.

2014-01-01

Expression of many fundamental mammalian behaviors such as, for example, aggression, mating, foraging or social behaviors, depend on locomotor activity. A central dilemma in the functional neuroimaging of these behaviors has been the fact that conventional neuroimaging techniques generally rely on immobilization of the subject, which extinguishes all but the simplest activity. Ideally, imaging could occur in freely moving subjects, while presenting minimal interference with the subject’s natural behavior. Here we provide an overview of several approaches that have been undertaken in the past to achieve this aim in both tethered and freely moving animals, as well as in nonrestrained human subjects. Applications of specific radiotracers to single photon emission computed tomography and positron emission tomography are discussed in which brain activation is imaged after completion of the behavioral task and capture of the tracer. Potential applications to clinical neuropsychiatry are discussed, as well as challenges inherent to constraint-free functional neuroimaging. Future applications of these methods promise to increase our understanding of the neural circuits underlying mammalian behavior in health and disease. PMID:15465134

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

Individual differences in cognition, affect, and performance: Behavioral, neuroimaging, and molecular genetic approaches

PubMed Central

Parasuraman, Raja; Jiang, Yang

2012-01-01

We describe the use of behavioral, neuroimaging, and genetic methods to examine individual differences in cognition and affect, guided by three criteria: (1) relevance to human performance in work and everyday settings; (2) interactions between working memory, decision-making, and affective processing; and (3) examination of individual differences. The results of behavioral, functional MRI (fMRI), event-related potential (ERP), and molecular genetic studies show that analyses at the group level often mask important findings associated with sub-groups of individuals. Dopaminergic/noradrenergic genes influencing prefrontal cortex activity contribute to inter-individual variation in working memory and decision behavior, including performance in complex simulations of military decision-making. The interactive influences of individual differences in anxiety, sensation seeking, and boredom susceptibility on evaluative decision-making can be systematically described using ERP and fMRI methods. We conclude that a multi-modal neuroergonomic approach to examining brain function (using both neuroimaging and molecular genetics) can be usefully applied to understanding individual differences in cognition and affect and has implications for human performance at work. PMID:21569853

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.

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 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

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.

The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software.

PubMed

Lucas, Blake C; Bogovic, John A; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L; Pham, Dzung L; Landman, Bennett A

2010-03-01

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).

The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

PubMed Central

Lucas, Blake C.; Bogovic, John A.; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L.; Pham, Dzung

2010-01-01

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). PMID:20077162

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

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.

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.

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

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging.

PubMed

Bilenko, Natalia Y; Gallant, Jack L

2016-01-01

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging

PubMed Central

Bilenko, Natalia Y.; Gallant, Jack L.

2016-01-01

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model. PMID:27920675

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…

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…

Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.

PubMed

Tulay, Emine Elif; Metin, Barış; Tarhan, Nevzat; Arıkan, Mehmet Kemal

2018-06-01

Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion. This literature review aimed to provide a brief summary and basic information about MN techniques (data fusion approaches in particular) and classification approaches. Data fusion approaches are generally categorized as asymmetric and symmetric. The present review focused exclusively on studies based on symmetric data fusion methods (data-driven methods), such as independent component analysis and principal component analysis. Machine learning techniques have recently been introduced for use in identifying diseases and biomarkers of disease. The machine learning technique most widely used by neuroscientists is classification-especially support vector machine classification. Several studies differentiated patients with psychiatric diseases and healthy controls with using combined datasets. The common conclusion among these studies is that the prediction of diseases increases when combining data via MN techniques; however, there remain a few challenges associated with MN, such as sample size. Perhaps in the future N-way fusion can be used to combine multiple neuroimaging techniques or nonimaging predictors (eg, cognitive ability) to overcome the limitations of MN.

Are Imaging and Lesioning Convergent Methods for Assessing Functional Specialisation? Investigations Using an Artificial Neural Network

ERIC Educational Resources Information Center

Thomas, Michael S. C.; Purser, Harry R. M.; Tomlinson, Simon; Mareschal, Denis

2012-01-01

This article presents an investigation of the relationship between lesioning and neuroimaging methods of assessing functional specialisation, using synthetic brain imaging (SBI) and lesioning of a connectionist network of past-tense formation. The model comprised two processing "routes": one was a direct route between layers of input and output…

Data warehousing methods and processing infrastructure for brain recovery research.

PubMed

Gee, T; Kenny, S; Price, C J; Seghier, M L; Small, S L; Leff, A P; Pacurar, A; Strother, S C

2010-09-01

In order to accelerate translational neuroscience with the goal of improving clinical care it has become important to support rapid accumulation and analysis of large, heterogeneous neuroimaging samples and their metadata from both normal control and patient groups. We propose a multi-centre, multinational approach to accelerate the data mining of large samples and facilitate data-led clinical translation of neuroimaging results in stroke. Such data-driven approaches are likely to have an early impact on clinically relevant brain recovery while we simultaneously pursue the much more challenging model-based approaches that depend on a deep understanding of the complex neural circuitry and physiological processes that support brain function and recovery. We present a brief overview of three (potentially converging) approaches to neuroimaging data warehousing and processing that aim to support these diverse methods for facilitating prediction of cognitive and behavioral recovery after stroke, or other types of brain injury or disease.

Scientific and Pragmatic Challenges for Bridging Education and Neuroscience

ERIC Educational Resources Information Center

Varma, Sashank; McCandliss, Bruce D.; Schwartz, Daniel L.

2008-01-01

Educational neuroscience is an emerging effort to integrate neuroscience methods, particularly functional neuroimaging, with behavioral methods to address issues of learning and instruction. This article consolidates common concerns about connecting education and neuroscience. One set of concerns is scientific: in-principle differences in methods,…

Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers

PubMed Central

Crosson, Bruce; Ford, Anastasia; McGregor, Keith M.; Meinzer, Marcus; Cheshkov, Sergey; Li, Xiufeng; Walker-Batson, Delaina; Briggs, Richard W.

2010-01-01

Functional neuroimaging and related neuroimaging techniques are becoming important tools for rehabilitation research. Functional neuroimaging techniques can be used to determine the effects of brain injury or disease on brain systems related to cognition and behavior and to determine how rehabilitation changes brain systems. These techniques include: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), and transcranial magnetic stimulation (TMS). Related diffusion weighted magnetic resonance imaging techniques (DWI), including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), can quantify white matter integrity. With the proliferation of these imaging techniques in rehabilitation research, it is critical that rehabilitation researchers, as well as consumers of rehabilitation research, become familiar with neuroimaging techniques, what they can offer, and their strengths and weaknesses The purpose to this review is to provide such an introduction to these neuroimaging techniques. PMID:20593321

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.

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

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

Defining functioning levels in patients with schizophrenia: A combination of a novel clustering method and brain SPECT analysis.

PubMed

Catherine, Faget-Agius; Aurélie, Vincenti; Eric, Guedj; Pierre, Michel; Raphaëlle, Richieri; Marine, Alessandrini; Pascal, Auquier; Christophe, Lançon; Laurent, Boyer

2017-12-30

This study aims to define functioning levels of patients with schizophrenia by using a method of interpretable clustering based on a specific functioning scale, the Functional Remission Of General Schizophrenia (FROGS) scale, and to test their validity regarding clinical and neuroimaging characterization. In this observational study, patients with schizophrenia have been classified using a hierarchical top-down method called clustering using unsupervised binary trees (CUBT). Socio-demographic, clinical, and neuroimaging SPECT perfusion data were compared between the different clusters to ensure their clinical relevance. A total of 242 patients were analyzed. A four-group functioning level structure has been identified: 54 are classified as "minimal", 81 as "low", 64 as "moderate", and 43 as "high". The clustering shows satisfactory statistical properties, including reproducibility and discriminancy. The 4 clusters consistently differentiate patients. "High" functioning level patients reported significantly the lowest scores on the PANSS and the CDSS, and the highest scores on the GAF, the MARS and S-QoL 18. Functioning levels were significantly associated with cerebral perfusion of two relevant areas: the left inferior parietal cortex and the anterior cingulate. Our study provides relevant functioning levels in schizophrenia, and may enhance the use of functioning scale. Copyright © 2017 Elsevier B.V. All rights reserved.

Structural, Metabolic, and Functional Brain Abnormalities as a Result of Prenatal Exposure to Drugs of Abuse: Evidence from Neuroimaging

PubMed Central

Roussotte, Florence; Soderberg, Lindsay

2010-01-01

Prenatal exposure to alcohol and stimulants negatively affects the developing trajectory of the central nervous system in many ways. Recent advances in neuroimaging methods have allowed researchers to study the structural, metabolic, and functional abnormalities resulting from prenatal exposure to drugs of abuse in living human subjects. Here we review the neuroimaging literature of prenatal exposure to alcohol, cocaine, and methamphetamine. Neuroimaging studies of prenatal alcohol exposure have reported differences in the structure and metabolism of many brain systems, including in frontal, parietal, and temporal regions, in the cerebellum and basal ganglia, as well as in the white matter tracts that connect these brain regions. Functional imaging studies have identified significant differences in brain activation related to various cognitive domains as a result of prenatal alcohol exposure. The published literature of prenatal exposure to cocaine and methamphetamine is much smaller, but evidence is beginning to emerge suggesting that exposure to stimulant drugs in utero may be particularly toxic to dopamine-rich basal ganglia regions. Although the interpretation of such findings is somewhat limited by the problem of polysubstance abuse and by the difficulty of obtaining precise exposure histories in retrospective studies, such investigations provide important insights into the effects of drugs of abuse on the structure, function, and metabolism of the developing human brain. These insights may ultimately help clinicians develop better diagnostic tools and devise appropriate therapeutic interventions to improve the condition of children with prenatal exposure to drugs of abuse. PMID:20978945

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:24108708

Somatosensory attention identifies both overt and covert awareness in disorders of consciousness.

PubMed

Gibson, Raechelle M; Chennu, Srivas; Fernández-Espejo, Davinia; Naci, Lorina; Owen, Adrian M; Cruse, Damian

2016-09-01

Some patients diagnosed with disorders of consciousness retain sensory and cognitive abilities beyond those apparent from their overt behavior. Characterizing these covert abilities is crucial for diagnosis, prognosis, and medical ethics. This multimodal study investigates the relationship between electroencephalographic evidence for perceptual/cognitive preservation and both overt and covert markers of awareness. Fourteen patients with severe brain injuries were evaluated with an electroencephalographic vibrotactile attention task designed to identify a hierarchy of residual somatosensory and cognitive abilities: (1) somatosensory steady-state evoked responses, (2) bottom-up attention orienting (P3a event-related potential), and (3) top-down attention (P3b event-related potential). Each patient was also assessed with a clinical behavioral scale and 2 functional magnetic resonance imaging assessments of covert command following. Six patients produced only sensory responses, with no evidence of cognitive event-related potentials. A further 8 patients demonstrated reliable bottom-up attention-orienting responses (P3a). No patient showed evidence of top-down attention (P3b). Only those patients who followed commands, whether overtly with behavior or covertly with functional neuroimaging, also demonstrated event-related potential evidence of attentional orienting. Somatosensory attention-orienting event-related potentials differentiated patients who could follow commands from those who could not. Crucially, this differentiation was irrespective of whether command following was evident through overt external behavior, or through covert functional neuroimaging methods. Bedside electroencephalographic methods may corroborate more expensive and challenging methods such as functional neuroimaging, and thereby assist in the accurate diagnosis of awareness. Ann Neurol 2016;80:412-423. © 2016 American Neurological Association.

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.

Structural and Functional Imaging Studies in Chronic Cannabis Users: A Systematic Review of Adolescent and Adult Findings

PubMed Central

Batalla, Albert; Bhattacharyya, Sagnik; Yücel, Murat; Fusar-Poli, Paolo; Crippa, Jose Alexandre; Nogué, Santiago; Torrens, Marta; Pujol, Jesús; Farré, Magí; Martin-Santos, Rocio

2013-01-01

Background The growing concern about cannabis use, the most commonly used illicit drug worldwide, has led to a significant increase in the number of human studies using neuroimaging techniques to determine the effect of cannabis on brain structure and function. We conducted a systematic review to assess the evidence of the impact of chronic cannabis use on brain structure and function in adults and adolescents. Methods Papers published until August 2012 were included from EMBASE, Medline, PubMed and LILACS databases following a comprehensive search strategy and pre-determined set of criteria for article selection. Only neuroimaging studies involving chronic cannabis users with a matched control group were considered. Results One hundred and forty-two studies were identified, of which 43 met the established criteria. Eight studies were in adolescent population. Neuroimaging studies provide evidence of morphological brain alterations in both population groups, particularly in the medial temporal and frontal cortices, as well as the cerebellum. These effects may be related to the amount of cannabis exposure. Functional neuroimaging studies suggest different patterns of resting global and brain activity during the performance of several cognitive tasks both in adolescents and adults, which may indicate compensatory effects in response to chronic cannabis exposure. Limitations However, the results pointed out methodological limitations of the work conducted to date and considerable heterogeneity in the findings. Conclusion Chronic cannabis use may alter brain structure and function in adult and adolescent population. Further studies should consider the use of convergent methodology, prospective large samples involving adolescent to adulthood subjects, and data-sharing initiatives. PMID:23390554

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 Neuro Imaging data archive. Notable leading researchers in the field of Alzheimer’s Disease and epilepsy have used the interface to access and process the data and visualize the results. Tabulated results with unique visualization mechanisms help guide more informed diagnosis and expert rating, providing a truly unique multimodal imaging platform that combines magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and resting state functional magnetic resonance imaging. A quality control component was reinforced through expert visual rating involving at least 2 experts. Conclusions To our knowledge, there is no validated Web-based system offering all the services that Neuroimaging Web Services Interface offers. The intent of Neuroimaging Web Services Interface is to create a tool for clinicians and researchers with keen interest on multimodal neuroimaging. More importantly, Neuroimaging Web Services Interface significantly augments the Alzheimer’s Disease Neuroimaging Initiative data, especially since our data contain a large cohort of Hispanic normal controls and Alzheimer’s Disease patients. The obtained results could be scrutinized visually or through the tabulated forms, informing researchers on subtle changes that characterize the different stages of the disease. PMID:29699962

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.

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 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.

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 perspective could represent a significant advancement for the field. PMID:27555810

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

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.

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

The Dopamine Imbalance Hypothesis of Fatigue in Multiple Sclerosis and Other Neurological Disorders

PubMed Central

Dobryakova, Ekaterina; Genova, Helen M.; DeLuca, John; Wylie, Glenn R.

2015-01-01

Fatigue is one of the most pervasive symptoms of multiple sclerosis (MS), and has engendered hundreds of investigations on the topic. While there is a growing literature using various methods to study fatigue, a unified theory of fatigue in MS is yet to emerge. In the current review, we synthesize findings from neuroimaging, pharmacological, neuropsychological, and immunological studies of fatigue in MS, which point to a specific hypothesis of fatigue in MS: the dopamine imbalance hypothesis. The communication between the striatum and prefrontal cortex is reliant on dopamine, a modulatory neurotransmitter. Neuroimaging findings suggest that fatigue results from the disruption of communication between these regions. Supporting the dopamine imbalance hypothesis, structural and functional neuroimaging studies show abnormalities in the frontal and striatal regions that are heavily innervated by dopamine neurons. Further, dopaminergic psychostimulant medication has been shown to alleviate fatigue in individuals with traumatic brain injury, chronic fatigue syndrome, and in cancer patients, also indicating that dopamine might play an important role in fatigue perception. This paper reviews the structural and functional neuroimaging evidence as well as pharmacological studies that suggest that dopamine plays a critical role in the phenomenon of fatigue. We conclude with how specific aspects of the dopamine imbalance hypothesis can be tested in future research. PMID:25814977

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.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

Automated annotation of functional imaging experiments via multi-label classification

PubMed Central

Turner, Matthew D.; Chakrabarti, Chayan; Jones, Thomas B.; Xu, Jiawei F.; Fox, Peter T.; Luger, George F.; Laird, Angela R.; Turner, Jessica A.

2013-01-01

Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text. PMID:24409112

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, functional and structural improvements tended to be positively correlated. CONCLUSION Neuroimaging studies of cognitive remediation in patients with schizophrenia suggest a positive effect on brain functioning in terms of the functional reorganisation of neural networks. PMID:28401047

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.

Cognitive functions of the posterior parietal cortex: top-down and bottom-up attentional control

PubMed Central

Shomstein, Sarah

2012-01-01

Although much less is known about human parietal cortex than that of homologous monkey cortex, recent studies, employing neuroimaging, and neuropsychological methods, have begun to elucidate increasingly fine-grained functional and structural distinctions. This review is focused on recent neuroimaging and neuropsychological studies elucidating the cognitive roles of dorsal and ventral regions of parietal cortex in top-down and bottom-up attentional orienting, and on the interaction between the two attentional allocation mechanisms. Evidence is reviewed arguing that regions along the dorsal areas of the parietal cortex, including the superior parietal lobule (SPL) are involved in top-down attentional orienting, while ventral regions including the temporo-parietal junction (TPJ) are involved in bottom-up attentional orienting. PMID:22783174

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

The secret lives of experiments: methods reporting in the fMRI literature.

PubMed

Carp, Joshua

2012-10-15

Replication of research findings is critical to the progress of scientific understanding. Accordingly, most scientific journals require authors to report experimental procedures in sufficient detail for independent researchers to replicate their work. To what extent do research reports in the functional neuroimaging literature live up to this standard? The present study evaluated methods reporting and methodological choices across 241 recent fMRI articles. Many studies did not report critical methodological details with regard to experimental design, data acquisition, and analysis. Further, many studies were underpowered to detect any but the largest statistical effects. Finally, data collection and analysis methods were highly flexible across studies, with nearly as many unique analysis pipelines as there were studies in the sample. Because the rate of false positive results is thought to increase with the flexibility of experimental designs, the field of functional neuroimaging may be particularly vulnerable to false positives. In sum, the present study documented significant gaps in methods reporting among fMRI studies. Improved methodological descriptions in research reports would yield significant benefits for the field. Copyright © 2012 Elsevier Inc. All rights reserved.

Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models.

PubMed Central

Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P

1999-01-01

Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

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…

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.

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

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.

PubMed

Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P; Frank, Lawrence R

2018-04-13

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Shedding Light on Words and Sentences: Near-Infrared Spectroscopy in Language Research

ERIC Educational Resources Information Center

Rossi, Sonja; Telkemeyer, Silke; Wartenburger, Isabell; Obrig, Hellmuth

2012-01-01

Investigating the neuronal network underlying language processing may contribute to a better understanding of how the brain masters this complex cognitive function with surprising ease and how language is acquired at a fast pace in infancy. Modern neuroimaging methods permit to visualize the evolvement and the function of the language network. The…

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.

Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment.

PubMed

Torgerson, Carinna M; Quinn, Catherine; Dinov, Ivo; Liu, Zhizhong; Petrosyan, Petros; Pelphrey, Kevin; Haselgrove, Christian; Kennedy, David N; Toga, Arthur W; Van Horn, John Darrell

2015-03-01

Under the umbrella of the National Database for Clinical Trials (NDCT) related to mental illnesses, the National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline workflow design and execution environment to enable large-scale analyses of cortical architecture and function via local, cluster, or "cloud"-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources. We discuss the utility of such database and workflow processing interactivity as a motivation for the sharing of additional primary data in ASD research and elsewhere.

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, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment.

Developmental Sex Differences in the Relation of Neuroanatomical Connectivity to Intelligence

ERIC Educational Resources Information Center

Schmithorst, Vincent J.

2009-01-01

Recent neuroimaging research has shown sex-related differences in the relationship between brain structure and cognitive function. Anatomical studies have shown a greater reliance for cognitive function on white matter structure in adult females, and a greater reliance on gray matter structure in adult males. Functional neuroimaging studies have…

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…

Multilingual Processing in the Brain

ERIC Educational Resources Information Center

van den Noort, Maurits; Struys, Esli; Kim, Kayoung; Bosch, Peggy; Mondt, Katrien; van Kralingen, Rosalinde; Lee, Mikyoung; van de Craen, Piet

2014-01-01

In this paper, in contrast to previous neuroimaging literature reviews on first language (L1) and second language (L2), the focus was only on neuroimaging studies that were directly conducted on multilingual participants. In total, 14 neuroimaging studies were included in our study such as 10 functional magnetic resonance imaging, 1 positron…

Use of functional near-infrared spectroscopy to monitor cortical plasticity induced by transcranial direct current stimulation

NASA Astrophysics Data System (ADS)

Khan, Bilal; Hervey, Nathan; Stowe, Ann; Hodics, Timea; Alexandrakis, George

2013-03-01

Electrical stimulation of the human cortex in conjunction with physical rehabilitation has been a valuable approach in facilitating the plasticity of the injured brain. One such method is transcranial direct current stimulation (tDCS) which is a non-invasive method to elicit neural stimulation by delivering current through electrodes placed on the scalp. In order to better understand the effects tDCS has on cortical plasticity, neuroimaging techniques have been used pre and post tDCS stimulation. Recently, neuroimaging methods have discovered changes in resting state cortical hemodynamics after the application of tDCS on human subjects. However, analysis of the cortical hemodynamic activity for a physical task during and post tDCS stimulation has not been studied to our knowledge. A viable and sensitive neuroimaging method to map changes in cortical hemodynamics during activation is functional near-infrared spectroscopy (fNIRS). In this study, the cortical activity during an event-related, left wrist curl task was mapped with fNIRS before, during, and after tDCS stimulation on eight healthy adults. Along with the fNIRS optodes, two electrodes were placed over the sensorimotor hand areas of both brain hemispheres to apply tDCS. Changes were found in both resting state cortical connectivity and cortical activation patterns that occurred during and after tDCS. Additionally, changes to surface electromyography (sEMG) measurements of the wrist flexor and extensor of both arms during the wrist curl movement, acquired concurrently with fNIRS, were analyzed and related to the transient cortical plastic changes induced by tDCS.

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).

Aging, training, and the brain: A review and future directions

PubMed Central

Lustig, Cindy; Shah, Priti; Seidler, Rachael; Reuter-Lorenz, Patricia A.

2010-01-01

As the population ages, the need for effective methods to maintain or even improve older adults’ cognitive performance becomes increasingly pressing. Here we provide a brief review of the major intervention approaches that have been the focus of past research with healthy older adults (strategy training, multi-modal interventions, cardiovascular exercise, and process-based training), and new approaches that incorporate neuroimaging. As outcome measures, neuroimaging data on intervention-related changes in volume, structural integrity, and functional activation can provide important insights into the nature and duration of an intervention's effects. Perhaps even more intriguingly, several recent studies have used neuroimaging data as a guide to identify core cognitive processes that can be trained in one task with effective transfer to other tasks that share the same underlying processes. Although many open questions remain, this research has greatly increased our understanding of how to promote successful aging of cognition and the brain. PMID:19876740

A novel GLM-based method for the Automatic IDentification of functional Events (AIDE) in fNIRS data recorded in naturalistic environments.

PubMed

Pinti, Paola; Merla, Arcangelo; Aichelburg, Clarisse; Lind, Frida; Power, Sarah; Swingler, Elizabeth; Hamilton, Antonia; Gilbert, Sam; Burgess, Paul W; Tachtsidis, Ilias

2017-07-15

Recent technological advances have allowed the development of portable functional Near-Infrared Spectroscopy (fNIRS) devices that can be used to perform neuroimaging in the real-world. However, as real-world experiments are designed to mimic everyday life situations, the identification of event onsets can be extremely challenging and time-consuming. Here, we present a novel analysis method based on the general linear model (GLM) least square fit analysis for the Automatic IDentification of functional Events (or AIDE) directly from real-world fNIRS neuroimaging data. In order to investigate the accuracy and feasibility of this method, as a proof-of-principle we applied the algorithm to (i) synthetic fNIRS data simulating both block-, event-related and mixed-design experiments and (ii) experimental fNIRS data recorded during a conventional lab-based task (involving maths). AIDE was able to recover functional events from simulated fNIRS data with an accuracy of 89%, 97% and 91% for the simulated block-, event-related and mixed-design experiments respectively. For the lab-based experiment, AIDE recovered more than the 66.7% of the functional events from the fNIRS experimental measured data. To illustrate the strength of this method, we then applied AIDE to fNIRS data recorded by a wearable system on one participant during a complex real-world prospective memory experiment conducted outside the lab. As part of the experiment, there were four and six events (actions where participants had to interact with a target) for the two different conditions respectively (condition 1: social-interact with a person; condition 2: non-social-interact with an object). AIDE managed to recover 3/4 events and 3/6 events for conditions 1 and 2 respectively. The identified functional events were then corresponded to behavioural data from the video recordings of the movements and actions of the participant. Our results suggest that "brain-first" rather than "behaviour-first" analysis is possible and that the present method can provide a novel solution to analyse real-world fNIRS data, filling the gap between real-life testing and functional neuroimaging. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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.

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.

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 clinical practice is limited. PMID:25068111

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.

On testing for spatial correspondence between maps of human brain structure and function.

PubMed

Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D; Glahn, David C; Shinohara, Russell T; Vandekar, Simon N; Raznahan, Armin

2018-06-01

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data. Copyright © 2018 Elsevier Inc. All rights reserved.

Neurophysiology and Neuroanatomy of Reflexive and Volitional Saccades: Evidence from Studies of Humans

PubMed Central

McDowell, Jennifer E.; Dyckman, Kara A.; Austin, Benjamin; Clementz, Brett A.

2008-01-01

This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually-guided saccades (redirections of gaze to a visual stimulus or prosaccades) and more complex volitional saccades require similar basic neural circuitry with additional neural regions supporting requisite higher level processes. The saccadic system has been studied extensively in non-human primates (e.g. single unit recordings) and humans (e.g. lesions and neuroimaging). Considerable knowledge of this system’s functional neuroanatomy makes it useful for investigating models of cognitive control. The network involved in prosaccade generation (by definition exogenously-driven) includes subcortical (striatum, thalamus, superior colliculus, and cerebellar vermis) and cortical structures (primary visual, extrastriate, and parietal cortices, and frontal and supplementary eye fields). Activation in these regions is also observed during endogenously-driven voluntary saccades (e.g. antisaccades, ocular motor delayed response or memory saccades, predictive tracking tasks and anticipatory saccades, and saccade sequencing), all of which require complex cognitive processes like inhibition and working memory. These additional requirements are supported by changes in neural activity in basic saccade circuitry and by recruitment of additional neural regions (such as prefrontal and anterior cingulate cortices). Activity in visual cortex is modulated as a function of task demands and may predict the type of saccade to be generated, perhaps via top-down control mechanisms. Neuroimaging studies suggest two foci of activation within FEF - medial and lateral - which may correspond to volitional and reflexive demands, respectively. Future research on saccade control could usefully (i) delineate important anatomical subdivisions that underlie functional differences, (ii) evaluate functional connectivity of anatomical regions supporting saccade generation using methods such as ICA and structural equation modeling, (iii) investigate how context affects behavior and brain activity, and (iv) use multi-modal neuroimaging to maximize spatial and temporal resolution. PMID:18835656

Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging

NASA Astrophysics Data System (ADS)

Reisman, Matthew David

As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.

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.

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.

Dynamic GSCA (Generalized Structured Component Analysis) with Applications to the Analysis of Effective Connectivity in Functional Neuroimaging Data

ERIC Educational Resources Information Center

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S.

2012-01-01

We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also…

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…

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

[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 prognosis after ischemic stroke.

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

Neural correlates of cognitive intervention in persons at risk of developing Alzheimer’s disease

PubMed Central

Hosseini, S. M. Hadi; Kramer, Joel H.; Kesler, Shelli R.

2014-01-01

Cognitive training is an emergent approach that has begun to receive increased attention in recent years as a non-pharmacological, cost-effective intervention for Alzheimer’s disease (AD). There has been increasing behavioral evidence regarding training-related improvement in cognitive performance in early stages of AD. Although these studies provide important insight about the efficacy of cognitive training, neuroimaging studies are crucial to pinpoint changes in brain structure and function associated with training and to examine their overlap with pathology in AD. In this study, we reviewed the existing neuroimaging studies on cognitive training in persons at risk of developing AD to provide an overview of the overlap between neural networks rehabilitated by the current training methods and those affected in AD. The data suggest a consistent training-related increase in brain activity in medial temporal, prefrontal, and posterior default mode networks, as well as increase in gray matter structure in frontoparietal and entorhinal regions. This pattern differs from the observed pattern in healthy older adults that shows a combination of increased and decreased activity in response to training. Detailed investigation of the data suggests that training in persons at risk of developing AD mainly improves compensatory mechanisms and partly restores the affected functions. While current neuroimaging studies are quite helpful in identifying the mechanisms underlying cognitive training, the data calls for future multi-modal neuroimaging studies with focus on multi-domain cognitive training, network level connectivity, and individual differences in response to training. PMID:25206335

The Cerefy Neuroradiology Atlas: a Talairach-Tournoux atlas-based tool for analysis of neuroimages available over the internet.

PubMed

Nowinski, Wieslaw L; Belov, Dmitry

2003-09-01

The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.

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

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

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

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data

PubMed Central

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-01-01

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716

77 FR 62244 - National Institute of Mental Health; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-12

... investigators, to include the Unit on Learning and Decision Making, the Section on Integrative Neuroimaging, the Section on Neurocircuitry, the Section on Cognitive Neuropsychology, the Section on Functional Imaging Methods, the Unit on Learning and Plasticity, and the Section on Neuroadaptation and Protein Metabolism...

Phenotypic regional fMRI activation patterns during memory encoding in MCI and AD

PubMed Central

Browndyke, Jeffrey N.; Giovanello, Kelly; Petrella, Jeffrey; Hayden, Kathleen; Chiba-Falek, Ornit; Tucker, Karen A.; Burke, James R.; Welsh-Bohmer, Kathleen A.

2014-01-01

Background Reliable blood-oxygen-level-dependent (BOLD) fMRI phenotypic biomarkers of Alzheimer's disease (AD) or mild cognitive impairment (MCI) are likely to emerge only from a systematic, quantitative, and aggregate examination of the functional neuroimaging research literature. Methods A series of random-effects, activation likelihood estimation (ALE) meta-analyses were conducted on studies of episodic memory encoding operations in AD and MCI samples relative to normal controls. ALE analyses were based upon a thorough literature search for all task-based functional neuroimaging studies in AD and MCI published up to January 2010. Analyses covered 16 fMRI studies, which yielded 144 distinct foci for ALE meta-analysis. Results ALE results indicated several regional task-based BOLD consistencies in MCI and AD patients relative to normal controls across the aggregate BOLD functional neuroimaging research literature. Patients with AD and those at significant risk (MCI) showed statistically significant consistent activation differences during episodic memory encoding in the medial temporal lobe (MTL), specifically parahippocampal gyrus, as well superior frontal gyrus, precuneus, and cuneus, relative to normal controls. Conclusions ALE consistencies broadly support the presence of frontal compensatory activity, MTL activity alteration, and posterior midline “default mode” hyperactivation during episodic memory encoding attempts in the diseased or prospective pre-disease condition. Taken together these robust commonalities may form the foundation for a task-based fMRI phenotype of memory encoding in AD. PMID:22841497

The functional neuroanatomy of bipolar disorder: a consensus model

PubMed Central

Strakowski, Stephen M; Adler, Caleb M; Almeida, Jorge; Altshuler, Lori L; Blumberg, Hilary P; Chang, Kiki D; DelBello, Melissa P; Frangou, Sophia; McIntosh, Andrew; Phillips, Mary L; Sussman, Jessika E; Townsend, Jennifer D

2013-01-01

Objectives Functional neuroimaging methods have proliferated in recent years, such that functional magnetic resonance imaging, in particular, is now widely used to study bipolar disorder. However, discrepant findings are common. A workgroup was organized by the Department of Psychiatry, University of Cincinnati (Cincinnati, OH, USA) to develop a consensus functional neuroanatomic model of bipolar I disorder based upon the participants’ work as well as that of others. Methods Representatives from several leading bipolar disorder neuroimaging groups were organized to present an overview of their areas of expertise as well as focused reviews of existing data. The workgroup then developed a consensus model of the functional neuroanatomy of bipolar disorder based upon these data. Results Among the participants, a general consensus emerged that bipolar I disorder arises from abnormalities in the structure and function of key emotional control networks in the human brain. Namely, disruption in early development (e.g., white matter connectivity, prefrontal pruning) within brain networks that modulate emotional behavior leads to decreased connectivity among ventral prefrontal networks and limbic brain regions, especially amygdala. This developmental failure to establish healthy ventral prefrontal–limbic modulation underlies the onset of mania and ultimately, with progressive changes throughout these networks over time and with affective episodes, a bipolar course of illness. Conclusions This model provides a potential substrate to guide future investigations and areas needing additional focus are identified. PMID:22631617

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

Applications of Functional Near-Infrared Spectroscopy (fNIRS) in Studying Cognitive Development: The Case of Mathematics and Language.

PubMed

Soltanlou, Mojtaba; Sitnikova, Maria A; Nuerk, Hans-Christoph; Dresler, Thomas

2018-01-01

In this review, we aim to highlight the application of functional near-infrared spectroscopy (fNIRS) as a useful neuroimaging technique for the investigation of cognitive development. We focus on brain activation changes during the development of mathematics and language skills in schoolchildren. We discuss how technical limitations of common neuroimaging techniques such as functional magnetic resonance imaging (fMRI) have resulted in our limited understanding of neural changes during development, while fNIRS would be a suitable and child-friendly method to examine cognitive development. Moreover, this technique enables us to go to schools to collect large samples of data from children in ecologically valid settings. Furthermore, we report findings of fNIRS studies in the fields of mathematics and language, followed by a discussion of the outlook of fNIRS in these fields. We suggest fNIRS as an additional technique to track brain activation changes in the field of educational neuroscience.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) in Studying Cognitive Development: The Case of Mathematics and Language

PubMed Central

Soltanlou, Mojtaba; Sitnikova, Maria A.; Nuerk, Hans-Christoph; Dresler, Thomas

2018-01-01

In this review, we aim to highlight the application of functional near-infrared spectroscopy (fNIRS) as a useful neuroimaging technique for the investigation of cognitive development. We focus on brain activation changes during the development of mathematics and language skills in schoolchildren. We discuss how technical limitations of common neuroimaging techniques such as functional magnetic resonance imaging (fMRI) have resulted in our limited understanding of neural changes during development, while fNIRS would be a suitable and child-friendly method to examine cognitive development. Moreover, this technique enables us to go to schools to collect large samples of data from children in ecologically valid settings. Furthermore, we report findings of fNIRS studies in the fields of mathematics and language, followed by a discussion of the outlook of fNIRS in these fields. We suggest fNIRS as an additional technique to track brain activation changes in the field of educational neuroscience. PMID:29666589

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 particular, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment. PMID:28883803

A problem-solving task specialized for functional neuroimaging: validation of the Scarborough adaptation of the Tower of London (S-TOL) using near-infrared spectroscopy

PubMed Central

Ruocco, Anthony C.; Rodrigo, Achala H.; Lam, Jaeger; Di Domenico, Stefano I.; Graves, Bryanna; Ayaz, Hasan

2014-01-01

Problem-solving is an executive function subserved by a network of neural structures of which the dorsolateral prefrontal cortex (DLPFC) is central. Whereas several studies have evaluated the role of the DLPFC in problem-solving, few standardized tasks have been developed specifically for use with functional neuroimaging. The current study adapted a measure with established validity for the assessment of problem-solving abilities to design a test more suitable for functional neuroimaging protocols. The Scarborough adaptation of the Tower of London (S-TOL) was administered to 38 healthy adults while hemodynamic oxygenation of the PFC was measured using 16-channel continuous-wave functional near-infrared spectroscopy (fNIRS). Compared to a baseline condition, problems that required two or three steps to achieve a goal configuration were associated with higher activation in the left DLPFC and deactivation in the medial PFC. Individuals scoring higher in trait deliberation showed consistently higher activation in the left DLPFC regardless of task difficulty, whereas individuals lower in this trait displayed less activation when solving simple problems. Based on these results, the S-TOL may serve as a standardized task to evaluate problem-solving abilities in functional neuroimaging studies. PMID:24734017

[Neuroimaging and the neurobiology of obsessive-compulsive disorder].

PubMed

Schiepek, Günter; Tominschek, Igor; Karch, Susanne; Mulert, Christoph; Pogarell, Oliver

2007-01-01

The following review is focusing on results of functional neuroimaging. After some introductory remarks on the phenomenology, epidemiology, and psychotherapy approaches of obsessive-compulsive disorders (OCD) the most important OCD-related brain regions are presented. Obviously, not only the prominent cortico-striato-thalamo-cortical feedback loops are involved, as functional brain imaging studies tell us, but also other regions as the inferior parietal lobe, the anterior and posterior cingulate gyrus, insula, amygdala, cerebellum, and others. Subclassifications using factor-analysis methods support the hypothesis, that most important subtypes ("washing/contamination fear", "obsessions/checking", "symmetry/ordering", "hoarding") involve different, but partially overlapping brain areas. Stimulation paradigms in fMRI-research are commonly based on symptom provocation by visual or tactile stimuli, or on action-monitoring and error-monitoring tasks. Deficits in action-monitoring and planning are discussed to be one of the basic dysfunctions of OCD. Finally, results of psychotherapeutic induced variations of brain activations in OCD are presented.

Assessment of Diverse Biological Indicators in Gulf War Illness: Are They Replicable Are They Related

DTIC Science & Technology

2016-04-01

compared to 50 healthy veteran controls in a protocol that includes physical and neuropsychological evaluations, neuroimaging (MRI, fMRI, DTI), adrenal...SUBJECT TERMS Gulf War illness, neuroimaging, neuropsychological testing, immune function, hypothalamic-pituitary-adrenal testing 16. SECURITY... neuropsychological evaluations, assessment of hypothalamic-pituitary-adrenal function, standard clinical diagnostic laboratory tests, and research

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

Functional imaging and the cerebellum: recent developments and challenges. Editorial.

PubMed

Habas, Christophe

2012-06-01

Recent neuroimaging developments allow a better in vivo characterization of the structural and functional connectivity of the human cerebellum. Ultrahigh fields, which considerably increase spatial resolution, enable to visualize deep cerebellar nuclei and cerebello-cortical sublayers. Tractography reconstructs afferent and efferent pathway of the cerebellum. Resting-state functional connectivity individualizes the prewired, parallel close-looped sensorimotor, cognitive, and affective networks passing through the cerebellum. These results are un agreement with activation maps obtained during stimulation functional neuroimaging or inferred from neurological deficits due to cerebellar lesions. Therefore, neuroimaging supports the hypothesis that cerebellum constitutes a general modulator involved in optimizing mental performance and computing internal models. However, the great challenges will remain to unravel: (1) the functional role of red and bulbar olivary nuclei, (2) the information processing in the cerebellar microcircuitry, and (3) the abstract computation performed by the cerebellum and shared by sensorimotor, cognitive, and affective domains.

Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling

ERIC Educational Resources Information Center

Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.

2009-01-01

The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…

Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review.

PubMed

Orrù, Graziella; Pettersson-Yeo, William; Marquand, Andre F; Sartori, Giuseppe; Mechelli, Andrea

2012-04-01

Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical and functional differences between healthy individuals and patients suffering a wide range of neurological and psychiatric disorders. Significant only at group level however these findings have had limited clinical translation, and recent attention has turned toward alternative forms of analysis, including Support-Vector-Machine (SVM). A type of machine learning, SVM allows categorisation of an individual's previously unseen data into a predefined group using a classification algorithm, developed on a training data set. In recent years, SVM has been successfully applied in the context of disease diagnosis, transition prediction and treatment prognosis, using both structural and functional neuroimaging data. Here we provide a brief overview of the method and review those studies that applied it to the investigation of Alzheimer's disease, schizophrenia, major depression, bipolar disorder, presymptomatic Huntington's disease, Parkinson's disease and autistic spectrum disorder. We conclude by discussing the main theoretical and practical challenges associated with the implementation of this method into the clinic and possible future directions. Copyright © 2012 Elsevier Ltd. All rights reserved.

On consciousness, resting state fMRI, and neurodynamics

PubMed Central

2010-01-01

Background During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively. Results The present work deals with a pluralistic approach to "consciousness'', where we connect theory and tools from three quite different disciplines: (1) philosophy of mind (emergentism and global workspace theory), (2) functional neuroimaging acquisitions, and (3) theory of deterministic and statistical neurodynamics – in particular the Wilson-Cowan model and stochastic resonance. Conclusions Based on recent experimental and theoretical work, we believe that the study of large-scale neuronal processes (activity fluctuations, state transitions) that goes on in the living human brain while examined with functional MRI during "resting state", can deepen our understanding of graded consciousness in a clinical setting, and clarify the concept of "consiousness" in neurocognitive and neurophilosophy research. PMID:20522270

A critical appraisal of neuroimaging studies of bipolar disorder: toward a new conceptualization of underlying neural circuitry and roadmap for future research

PubMed Central

Phillips, Mary L; Swartz, Holly A.

2014-01-01

Objective This critical review appraises neuroimaging findings in bipolar disorder in emotion processing, emotion regulation, and reward processing neural circuitry, to synthesize current knowledge of the neural underpinnings of bipolar disorder, and provide a neuroimaging research “roadmap” for future studies. Method We examined findings from all major studies in bipolar disorder that used fMRI, volumetric analyses, diffusion imaging, and resting state techniques, to inform current conceptual models of larger-scale neural circuitry abnormalities in bipolar disorder Results Bipolar disorder can be conceptualized in neural circuitry terms as parallel dysfunction in bilateral prefrontal cortical (especially ventrolateral prefrontal cortical)-hippocampal-amygdala emotion processing and emotion regulation neural circuitries, together with an “overactive” left-sided ventral striatal-ventrolateral and orbitofrontal cortical reward processing circuitry, that result in characteristic behavioral abnormalities associated with bipolar disorder: emotional lability, emotional dysregulation and heightened reward sensitivity. A potential structural basis for these functional abnormalities are gray matter decreases in prefrontal and temporal cortices, amygdala and hippocampus, and fractional anisotropy decreases in white matter tracts connecting prefrontal and subcortical regions. Conclusion Neuroimaging studies of bipolar disorder clearly demonstrate abnormalities in neural circuitries supporting emotion processing, emotion regulation and reward processing, although there are several limitations to these studies. Future neuroimaging research in bipolar disorder should include studies adopting dimensional approaches; larger studies examining neurodevelopmental trajectories in bipolar disorder and at-risk youth; multimodal neuroimaging studies using integrated systems approaches; and studies using pattern recognition approaches to provide clinically useful, individual-level data. Such studies will help identify clinically-relevant biomarkers to guide diagnosis and treatment decision-making for individuals with bipolar disorder. PMID:24626773

Subjective memory complaint only relates to verbal episodic memory performance in mild cognitive impairment

PubMed Central

Gifford, Katherine A.; Liu, Dandan; Damon, Stephen M.; Chapman, William G.; Romano, Raymond R.; Samuels, Lauren R.; Lu, Zengqi; Jefferson, Angela L.

2015-01-01

Background A cognitive concern from the patient, informant, or clinician is required for the diagnosis of mild cognitive impairment (MCI); however, the cognitive and neuroanatomical correlates of complaint are poorly understood. Objective We assessed how self-complaint relates to cognitive and neuroimaging measures in older adults with MCI. Method MCI participants were drawn from the Alzheimer’s Disease Neuroimaging Initiative and dichotomized into two groups based on the presence of self-reported memory complaint (no complaint n=191, 77±7 years; complaint n=206, 73±8 years). Cognitive outcomes included episodic memory, executive functioning, information processing speed, and language. Imaging outcomes included regional lobar volumes (frontal, parietal, temporal, cingulate) and specific medial temporal lobe structures (hippocampal volume, entorhinal cortex thickness, parahippocampal gyrus thickness). Results Linear regressions, adjusting for age, gender, race, education, Mini-Mental State Examination score, mood, and apolipoprotein E-4 status, found that cognitive complaint related to immediate (β=−1.07, p<0.001) and delayed episodic memory performances assessed on a serial list learning task (β=−1.06, p=0.001) but no other cognitive measures or neuroimaging markers. Conclusions Self-reported memory concern was unrelated to structural neuroimaging markers of atrophy and measures of information processing speed, executive functioning, or language. In contrast, subjective memory complaint related to objective verbal episodic learning performance. Future research is warranted to better understand the relation between cognitive complaint and surrogate markers of abnormal brain aging, including Alzheimer’s disease, across the cognitive aging spectrum. PMID:25281602

Understanding Youth Antisocial Behavior Using Neuroscience through a Developmental Psychopathology Lens: Review, Integration, and Directions for Research

PubMed Central

Hyde, Luke W.; Shaw, Daniel S.; Hariri, Ahmad R.

2013-01-01

Youth antisocial behavior (AB) is an important public health concern impacting perpetrators, victims, and society. Functional neuroimaging is becoming a more common and useful modality for understanding neural correlates of youth AB. Although there has been a recent increase in neuroimaging studies of youth AB and corresponding theoretical articles on the neurobiology of AB, there has been little work critically examining the strengths and weaknesses of individual studies and using this knowledge to inform the design of future studies. Additionally, research on neuroimaging and youth AB has not been integrated within the broader framework of developmental psychopathology. Thus, this paper provides an in-depth review of the youth AB functional neuroimaging literature with the following goals: 1. to evaluate how this literature has informed our understanding of youth AB, 2. to evaluate current neuroimaging studies of youth AB from a developmental psychopathology perspective with a focus on integrating research from neuroscience and developmental psychopathology, as well as placing this research in the context of other related areas (e.g., psychopathy, molecular genetics), and 3. to examine strengths and weaknesses of neuroimaging and behavioral studies of youth AB to suggest how future studies can develop a more informed and integrated understanding of youth AB. PMID:24273368

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

PubMed

Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F

2017-11-01

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

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.

Research Review: Emanuel Miller Memorial Lecture 2012 – Neuroscientific studies of intervention for language impairment in children: interpretive and methodological problems

PubMed Central

Bishop, D V M

2013-01-01

Background Our ability to look at structure and function of a living brain has increased exponentially since the early 1970s. Many studies of developmental disorders now routinely include a brain imaging or electrophysiological component. Amid current enthusiasm for applications of neuroscience to educational interventions, we need to pause to consider what neuroimaging data can tell us. Images of brain activity are seductive, and have been used to give credibility to commercial interventions, yet we have only a limited idea of what the brain bases of language disorders are, let alone how to alter them. Scope and findings A review of six studies of neuroimaging correlates of language intervention found recurring methodological problems: lack of an adequate control group, inadequate power, incomplete reporting of data, no correction for multiple comparisons, data dredging and failure to analyse treatment effects appropriately. In addition, there is a tendency to regard neuroimaging data as more meaningful than behavioural data, even though it is behaviour that interventions aim to alter. Conclusion In our current state of knowledge, it would be better to spend research funds doing well-designed trials of behavioural treatment to establish which methods are effective, rather than rushing headlong into functional imaging studies of unproven treatments. PMID:23278309

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.

Improving the clinical assessment of consciousness with advances in electrophysiological and neuroimaging techniques

PubMed Central

2010-01-01

In clinical neurology, a comprehensive understanding of consciousness has been regarded as an abstract concept - best left to philosophers. However, times are changing and the need to clinically assess consciousness is increasingly becoming a real-world, practical challenge. Current methods for evaluating altered levels of consciousness are highly reliant on either behavioural measures or anatomical imaging. While these methods have some utility, estimates of misdiagnosis are worrisome (as high as 43%) - clearly this is a major clinical problem. The solution must involve objective, physiologically based measures that do not rely on behaviour. This paper reviews recent advances in physiologically based measures that enable better evaluation of consciousness states (coma, vegetative state, minimally conscious state, and locked in syndrome). Based on the evidence to-date, electroencephalographic and neuroimaging based assessments of consciousness provide valuable information for evaluation of residual function, formation of differential diagnoses, and estimation of prognosis. PMID:20113490

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

PubMed Central

Williams, David A; Gracely, Richard H

2006-01-01

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data.

PubMed

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-05-15

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2.

PubMed

Jack, Clifford R; Barnes, Josephine; Bernstein, Matt A; Borowski, Bret J; Brewer, James; Clegg, Shona; Dale, Anders M; Carmichael, Owen; Ching, Christopher; DeCarli, Charles; Desikan, Rahul S; Fennema-Notestine, Christine; Fjell, Anders M; Fletcher, Evan; Fox, Nick C; Gunter, Jeff; Gutman, Boris A; Holland, Dominic; Hua, Xue; Insel, Philip; Kantarci, Kejal; Killiany, Ron J; Krueger, Gunnar; Leung, Kelvin K; Mackin, Scott; Maillard, Pauline; Malone, Ian B; Mattsson, Niklas; McEvoy, Linda; Modat, Marc; Mueller, Susanne; Nosheny, Rachel; Ourselin, Sebastien; Schuff, Norbert; Senjem, Matthew L; Simonson, Alix; Thompson, Paul M; Rettmann, Dan; Vemuri, Prashanthi; Walhovd, Kristine; Zhao, Yansong; Zuk, Samantha; Weiner, Michael

2015-07-01

Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A Review of Transcranial Magnetic Stimulation and Multimodal Neuroimaging to Characterize Post-Stroke Neuroplasticity

PubMed Central

Auriat, Angela M.; Neva, Jason L.; Peters, Sue; Ferris, Jennifer K.; Boyd, Lara A.

2015-01-01

Following stroke, the brain undergoes various stages of recovery where the central nervous system can reorganize neural circuitry (neuroplasticity) both spontaneously and with the aid of behavioral rehabilitation and non-invasive brain stimulation. Multiple neuroimaging techniques can characterize common structural and functional stroke-related deficits, and importantly, help predict recovery of function. Diffusion tensor imaging (DTI) typically reveals increased overall diffusivity throughout the brain following stroke, and is capable of indexing the extent of white matter damage. Magnetic resonance spectroscopy (MRS) provides an index of metabolic changes in surviving neural tissue after stroke, serving as a marker of brain function. The neural correlates of altered brain activity after stroke have been demonstrated by abnormal activation of sensorimotor cortices during task performance, and at rest, using functional magnetic resonance imaging (fMRI). Electroencephalography (EEG) has been used to characterize motor dysfunction in terms of increased cortical amplitude in the sensorimotor regions when performing upper limb movement, indicating abnormally increased cognitive effort and planning in individuals with stroke. Transcranial magnetic stimulation (TMS) work reveals changes in ipsilesional and contralesional cortical excitability in the sensorimotor cortices. The severity of motor deficits indexed using TMS has been linked to the magnitude of activity imbalance between the sensorimotor cortices. In this paper, we will provide a narrative review of data from studies utilizing DTI, MRS, fMRI, EEG, and brain stimulation techniques focusing on TMS and its combination with uni- and multimodal neuroimaging methods to assess recovery after stroke. Approaches that delineate the best measures with which to predict or positively alter outcomes will be highlighted. PMID:26579069

Learning to See Words

PubMed Central

2011-01-01

Skilled reading requires recognizing written words rapidly; functional neuroimaging research has clarified how the written word initiates a series of responses in visual cortex. These responses are communicated to circuits in ventral occipitotemporal (VOT) cortex that learn to identify words rapidly. Structural neuroimaging has further clarified aspects of the white matter pathways that communicate reading signals between VOT and language systems. We review this circuitry, its development, and its deficiencies in poor readers. This review emphasizes data that measure the cortical responses and white matter pathways in individual subjects rather than group differences. Such methods have the potential to clarify why a child has difficulty learning to read and to offer guidance about the interventions that may be useful for that child. PMID:21801018

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

Dissociations between behavioural and functional magnetic resonance imaging-based evaluations of cognitive function after brain injury

PubMed Central

Bardin, Jonathan C.; Fins, Joseph J.; Katz, Douglas I.; Hersh, Jennifer; Heier, Linda A.; Tabelow, Karsten; Dyke, Jonathan P.; Ballon, Douglas J.; Schiff, Nicholas D.

2011-01-01

Functional neuroimaging methods hold promise for the identification of cognitive function and communication capacity in some severely brain-injured patients who may not retain sufficient motor function to demonstrate their abilities. We studied seven severely brain-injured patients and a control group of 14 subjects using a novel hierarchical functional magnetic resonance imaging assessment utilizing mental imagery responses. Whereas the control group showed consistent and accurate (for communication) blood-oxygen-level-dependent responses without exception, the brain-injured subjects showed a wide variation in the correlation of blood-oxygen-level-dependent responses and overt behavioural responses. Specifically, the brain-injured subjects dissociated bedside and functional magnetic resonance imaging-based command following and communication capabilities. These observations reveal significant challenges in developing validated functional magnetic resonance imaging-based methods for clinical use and raise interesting questions about underlying brain function assayed using these methods in brain-injured subjects. PMID:21354974

Neurobiological Circuits Regulating Attention, Cognitive Control, Motivation, and Emotion: Disruptions in Neurodevelopmental Psychiatric Disorders

ERIC Educational Resources Information Center

Arnsten, Amy F. T.; Rubia, Katya

2012-01-01

Objective: This article aims to review basic and clinical studies outlining the roles of prefrontal cortical (PFC) networks in the behavior and cognitive functions that are compromised in childhood neurodevelopmental disorders and how these map into the neuroimaging evidence of circuit abnormalities in these disorders. Method: Studies of animals,…

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.

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Q.; Culver, Joseph P.; Wang, Lihong V.

2014-03-01

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer's, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging.

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.

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 contributes to the pediatric neuroimaging literature by providing a useful way to conceptualize and measure task noncompliance and by providing simple cost effective tactics for improving the effectiveness of common reward-based protocols. PMID:21548928

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.

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.

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

Case studies continue to illuminate the cognitive neuroscience of memory.

PubMed

Rosenbaum, R Shayna; Gilboa, Asaf; Moscovitch, Morris

2014-05-01

The current ubiquity of functional neuroimaging studies, and the importance they have had in elucidating brain function, obscures the fact that much of what we know about brain-behavior relationships derives largely from the study of single- and multiple-patient cases. A major goal of the present review is to describe how single cases continue to uniquely and critically contribute to cognitive neuroscience theory. With several recent examples from the literature, we demonstrate that single cases can both challenge accepted dogma and generate hypotheses and theories that steer the field in new directions. We discuss recent findings from case studies that specify critical functions of the hippocampus in episodic memory and recollection, and clarify its role in nonmnemonic abilities. Although we focus on the hippocampus, we discuss other regions and the occurrence of new associative learning, as well as the involvement of the ventromedial prefrontal and parietal cortices in memory encoding and retrieval. We also describe ways of dealing with the shortcomings of case studies, and emphasize the partnership of patient and neuroimaging methods in constraining neurocognitive models of memory. © 2014 New York Academy of Sciences.

[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.

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.

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 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

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.

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

Portable Functional Neuroimaging as an Environmental Epidemiology Tool: A How-To Guide for the Use of fNIRS in Field Studies.

PubMed

Baker, Joseph M; Rojas-Valverde, Daniel; Gutiérrez, Randall; Winkler, Mirko; Fuhrimann, Samuel; Eskenazi, Brenda; Reiss, Allan L; Mora, Ana M

2017-09-21

The widespread application of functional neuroimaging within the field of environmental epidemiology has the potential to greatly enhance our understanding of how environmental toxicants affect brain function. Because many epidemiological studies take place in remote and frequently changing environments, it is necessary that the primary neuroimaging approach adopted by the epidemiology community be robust to many environments, easy to use, and, preferably, mobile. Here, we outline our use of functional near-infrared spectroscopy (fNIRS) to collect functional brain imaging data from Costa Rican farm workers enrolled in an epidemiological study on the health effects of chronic pesticide exposure. While couched in this perspective, we focus on the methodological considerations that are necessary to conduct a mobile fNIRS study in a diverse range of environments. Thus, this guide is intended to be generalizable to all research scenarios and projects in which fNIRS may be used to collect functional brain imaging data in epidemiological field surveys. https://doi.org/10.1289/EHP2049.

Portable Functional Neuroimaging as an Environmental Epidemiology Tool: A How-To Guide for the Use of fNIRS in Field Studies

PubMed Central

Rojas-Valverde, Daniel; Gutiérrez, Randall; Winkler, Mirko; Fuhrimann, Samuel; Eskenazi, Brenda; Reiss, Allan L.; Mora, Ana M.

2017-01-01

Summary: The widespread application of functional neuroimaging within the field of environmental epidemiology has the potential to greatly enhance our understanding of how environmental toxicants affect brain function. Because many epidemiological studies take place in remote and frequently changing environments, it is necessary that the primary neuroimaging approach adopted by the epidemiology community be robust to many environments, easy to use, and, preferably, mobile. Here, we outline our use of functional near-infrared spectroscopy (fNIRS) to collect functional brain imaging data from Costa Rican farm workers enrolled in an epidemiological study on the health effects of chronic pesticide exposure. While couched in this perspective, we focus on the methodological considerations that are necessary to conduct a mobile fNIRS study in a diverse range of environments. Thus, this guide is intended to be generalizable to all research scenarios and projects in which fNIRS may be used to collect functional brain imaging data in epidemiological field surveys. https://doi.org/10.1289/EHP2049 PMID:28937962

Neuroanatomy of episodic and semantic memory in humans: a brief review of neuroimaging studies.

PubMed

García-Lázaro, Haydée G; Ramirez-Carmona, Rocio; Lara-Romero, Ruben; Roldan-Valadez, Ernesto

2012-01-01

One of the most basic functions in every individual and species is memory. Memory is the process by which information is saved as knowledge and retained for further use as needed. Learning is a neurobiological phenomenon by which we acquire certain information from the outside world and is a precursor to memory. Memory consists of the capacity to encode, store, consolidate, and retrieve information. Recently, memory has been defined as a network of connections whose function is primarily to facilitate the long-lasting persistence of learned environmental cues. In this review, we present a brief description of the current classifications of memory networks with a focus on episodic memory and its anatomical substrate. We also present a brief review of the anatomical basis of memory systems and the most commonly used neuroimaging methods to assess memory, illustrated with magnetic resonance imaging images depicting the hippocampus, temporal lobe, and hippocampal formation, which are the main brain structures participating in memory networks.

Evaluation of cerebral function after carotid endarterectomy.

PubMed

Uclés, P; Almárcegui, C; Lorente, S; Romero, F; Marco, M

1997-05-01

Neuroimaging methods have failed to disclose correlation between degree of cerebral atrophy and blood flow in carotid artery stenosis patients. Moreover, intellectual improvement after carotid endarterectomy does not correlate fully with neuroimaging data in such patients. We performed brain electrical activity mapping and psychological testing before and 4 weeks after operation in 28 patients with symptomatic, high-grade, carotid stenosis. Postoperatively, electroencephalographic (EEG) mean frequency and absolute theta power improved significantly (p < 0.01). Mean frequency increased >1 Hz in most areas while power decreased dramatically, mainly because of resolution of high-voltage foci in 8 patients. Differences were conspicuous in both frontal lobes irrespective of the operated side, which suggests changes in perfusion affecting the whole brain. This is a positive effect of endarterectomy. Mini-Mental test and Set Test for verbal fluency had a positive correlation with the qEEG changes. Quantitative EEG as a measure of cerebral function has disclosed discriminative improvement in the early postoperative period. Our results support the thesis of improvement subsequent to endarterectomy.

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.

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

What do patients with epilepsy tell us about language dynamics? A review of fMRI studies.

PubMed

Baciu, Monica; Perrone-Bertolotti, Marcela

2015-01-01

The objective of this review is to resume major neuroimaging findings on language organization and plasticity in patients with focal and refractory epilepsy, to discuss the effect of modulatory variables that should be considered alongside patterns of reorganization, and to propose possible models of language reorganization. The focal and refractory epilepsy provides a real opportunity to investigate various types of language reorganization in different conditions. The 'chronic' condition (induced by the epileptogenic zone or EZ) is associated with either recruitment of homologous regions of the opposite hemisphere or recruitment of intrahemispheric, nonlinguistic regions. In the 'acute' condition (neurosurgery and EZ resection), the initial interhemispheric shift (induced by the chronic EZ) could follow a reverse direction, back to the initial hemisphere. These different patterns depend on several modulatory factors and are associated with various levels of language performance. As a neuroimaging tool, functional magnetic resonance imaging enables the detailed investigation of both hemispheres simultaneously and allows for comparison with healthy controls, potentially creating a more comprehensive and more realistic picture of brain-language relations. Importantly, functional neuroimaging approaches demonstrate a good degree of concordance on a theoretical level, but also a considerable degree of individual variability, attesting to the clinical importance with these methods to establish, empirically, language localization in individual patients. Overall, the unique features of epilepsy, combined with ongoing advances in technology, promise further improvement in understanding of language substrate.

Neurobiological Risk Factors for Suicide Insights from Brain Imaging

PubMed Central

Cox Lippard, Elizabeth T.; Johnston, Jennifer A.Y.; Blumberg, Hilary P.

2014-01-01

Context This article reviews neuroimaging studies on neural circuitry associated with suicide-related thoughts and behaviors to identify areas of convergence in findings. Gaps in the literature for which additional research is needed are identified. Evidence acquisition A PubMed search was conducted and articles published prior to March 2014 were reviewed that compared individuals who made suicide attempts to those with similar diagnoses who had not made attempts or to healthy comparison subjects. Articles on adults with suicidal ideation and adolescents who had made attempts, or with suicidal ideation, were also included. Reviewed imaging modalities included structural magnetic resonance imaging, diffusion tensor imaging, single photon emission computerized tomography, positron emission tomography, and functional magnetic resonance imaging. Evidence synthesis Although many studies include small samples, and subject characteristics and imaging methods vary across studies, there were convergent findings involving the structure and function of frontal neural systems and the serotonergic system. Conclusions These initial neuroimaging studies of suicide behavior have provided promising results. Future neuroimaging efforts could be strengthened by more strategic use of common data elements, and a focus on suicide risk trajectories. At-risk subgroups defined by biopsychosocial risk factors and multidimensional assessment of suicidal thoughts and behaviors may provide a clearer picture of the neural circuitry associated with risk status—both current and lifetime. Also needed are studies investigating neural changes associated with interventions that are effective in risk reduction. PMID:25145733

Cognitive-behavioral therapy for obsessive–compulsive disorder: access to treatment, prediction of long-term outcome with neuroimaging

PubMed Central

O’Neill, Joseph; Feusner, Jamie D

2015-01-01

This article reviews issues related to a major challenge to the field for obsessive–compulsive disorder (OCD): improving access to cognitive-behavioral therapy (CBT). Patient-related barriers to access include the stigma of OCD and reluctance to take on the demands of CBT. Patient-external factors include the shortage of trained CBT therapists and the high costs of CBT. The second half of the review focuses on one partial, yet plausible aid to improve access – prediction of long-term response to CBT, particularly using neuroimaging methods. Recent pilot data are presented revealing a potential for pretreatment resting-state functional magnetic resonance imaging and magnetic resonance spectroscopy of the brain to forecast OCD symptom severity up to 1 year after completing CBT. PMID:26229514

Changes of Visual Pathway and Brain Connectivity in Glaucoma: A Systematic Review

PubMed Central

Nuzzi, Raffaele; Dallorto, Laura; Rolle, Teresa

2018-01-01

Background: Glaucoma is a leading cause of irreversible blindness worldwide. The increasing interest in the involvement of the cortical visual pathway in glaucomatous patients is due to the implications in recent therapies, such as neuroprotection and neuroregeneration. Objective: In this review, we outline the current understanding of brain structural, functional, and metabolic changes detected with the modern techniques of neuroimaging in glaucomatous subjects. Methods: We screened MEDLINE, EMBASE, CINAHL, CENTRAL, LILACS, Trip Database, and NICE for original contributions published until 31 October 2017. Studies with at least six patients affected by any type of glaucoma were considered. We included studies using the following neuroimaging techniques: functional Magnetic Resonance Imaging (fMRI), resting-state fMRI (rs-fMRI), magnetic resonance spectroscopy (MRS), voxel- based Morphometry (VBM), surface-based Morphometry (SBM), diffusion tensor MRI (DTI). Results: Over a total of 1,901 studies, 56 case series with a total of 2,381 patients were included. Evidence of neurodegenerative process in glaucomatous patients was found both within and beyond the visual system. Structural alterations in visual cortex (mainly reduced cortex thickness and volume) have been demonstrated with SBM and VBM; these changes were not limited to primary visual cortex but also involved association visual areas. Other brain regions, associated with visual function, demonstrated a certain grade of increased or decreased gray matter volume. Functional and metabolic abnormalities resulted within primary visual cortex in all studies with fMRI and MRS. Studies with rs-fMRI found disrupted connectivity between the primary and higher visual cortex and between visual cortex and associative visual areas in the task-free state of glaucomatous patients. Conclusions: This review contributes to the better understanding of brain abnormalities in glaucoma. It may stimulate further speculation about brain plasticity at a later age and therapeutic strategies, such as the prevention of cortical degeneration in patients with glaucoma. Structural, functional, and metabolic neuroimaging methods provided evidence of changes throughout the visual pathway in glaucomatous patients. Other brain areas, not directly involved in the processing of visual information, also showed alterations. PMID:29896087

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.

Neurobiological model of obsessive-compulsive disorder: evidence from recent neuropsychological and neuroimaging findings.

PubMed

Nakao, Tomohiro; Okada, Kayo; Kanba, Shigenobu

2014-08-01

Obsessive-compulsive disorder (OCD) was previously considered refractory to most types of therapeutic intervention. There is now, however, ample evidence that selective serotonin reuptake inhibitors and behavior therapy are highly effective methods for treatment of OCD. Furthermore, recent neurobiological studies of OCD have found a close correlation between clinical symptoms, cognitive function, and brain function. A large number of previous neuroimaging studies using positron emission tomography, single-photon emission computed tomography or functional magnetic resonance imaging (fMRI) have identified abnormally high activities throughout the frontal cortex and subcortical structures in patients with OCD. Most studies reported excessive activation of these areas during symptom provocation. Furthermore, these hyperactivities were decreased after successful treatment using either selective serotonin reuptake inhibitors or behavioral therapy. Based on these findings, an orbitofronto-striatal model has been postulated as an abnormal neural circuit that mediates symptomatic expression of OCD. On the other hand, previous neuropsychological studies of OCD have reported cognitive dysfunction in executive function, attention, nonverbal memory, and visuospatial skills. Moreover, recent fMRI studies have revealed a correlation between neuropsychological dysfunction and clinical symptoms in OCD by using neuropsychological tasks during fMRI. The evidence from fMRI studies suggests that broader regions, including dorsolateral prefrontal and posterior regions, might be involved in the pathophysiology of OCD. Further, we should consider that OCD is heterogeneous and might have several different neural systems related to clinical factors, such as symptom dimensions. This review outlines recent neuropsychological and neuroimaging studies of OCD. We will also describe several neurobiological models that have been developed recently. Advanced findings in these fields will update the conventional biological model of OCD. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.

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.

Dissociation and Alterations in Brain Function and Structure: Implications for Borderline Personality Disorder.

PubMed

Krause-Utz, Annegret; Frost, Rachel; Winter, Dorina; Elzinga, Bernet M

2017-01-01

Dissociation involves disruptions of usually integrated functions of consciousness, perception, memory, identity, and affect (e.g., depersonalization, derealization, numbing, amnesia, and analgesia). While the precise neurobiological underpinnings of dissociation remain elusive, neuroimaging studies in disorders, characterized by high dissociation (e.g., depersonalization/derealization disorder (DDD), dissociative identity disorder (DID), dissociative subtype of posttraumatic stress disorder (D-PTSD)), have provided valuable insight into brain alterations possibly underlying dissociation. Neuroimaging studies in borderline personality disorder (BPD), investigating links between altered brain function/structure and dissociation, are still relatively rare. In this article, we provide an overview of neurobiological models of dissociation, primarily based on research in DDD, DID, and D-PTSD. Based on this background, we review recent neuroimaging studies on associations between dissociation and altered brain function and structure in BPD. These studies are discussed in the context of earlier findings regarding methodological differences and limitations and concerning possible implications for future research and the clinical setting.

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

Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.

PubMed

Dennis, Emily L; Babikian, Talin; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-02-01

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

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 leading researchers in the field of Alzheimer’s Disease and epilepsy have used the interface to access and process the data and visualize the results. Tabulated results with unique visualization mechanisms help guide more informed diagnosis and expert rating, providing a truly unique multimodal imaging platform that combines magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and resting state functional magnetic resonance imaging. A quality control component was reinforced through expert visual rating involving at least 2 experts. To our knowledge, there is no validated Web-based system offering all the services that Neuroimaging Web Services Interface offers. The intent of Neuroimaging Web Services Interface is to create a tool for clinicians and researchers with keen interest on multimodal neuroimaging. More importantly, Neuroimaging Web Services Interface significantly augments the Alzheimer’s Disease Neuroimaging Initiative data, especially since our data contain a large cohort of Hispanic normal controls and Alzheimer’s Disease patients. The obtained results could be scrutinized visually or through the tabulated forms, informing researchers on subtle changes that characterize the different stages of the disease. ©Gabriel Lizarraga, Chunfei Li, Mercedes Cabrerizo, Warren Barker, David A Loewenstein, Ranjan Duara, Malek Adjouadi. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 26.04.2018.

Language Switching in the Bilingual Brain: What's Next?

ERIC Educational Resources Information Center

Hernandez, Arturo E.

2009-01-01

Recent work using functional neuroimaging with early bilinguals has found little evidence for separate neural systems for each language during picture naming (Hernandez, A. E., Dapretto, M., Mazziotta, J., & Bookheimer, S. (2001). "Language switching and language representation in Spanish-English bilinguals: An fMRI study." "Neuroimage, 14,"…

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, 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. PMID:23964224

Abnormal Brain Dynamics Underlie Speech Production in Children with Autism Spectrum Disorder.

PubMed

Pang, Elizabeth W; Valica, Tatiana; MacDonald, Matt J; Taylor, Margot J; Brian, Jessica; Lerch, Jason P; Anagnostou, Evdokia

2016-02-01

A large proportion of children with autism spectrum disorder (ASD) have speech and/or language difficulties. While a number of structural and functional neuroimaging methods have been used to explore the brain differences in ASD with regards to speech and language comprehension and production, the neurobiology of basic speech function in ASD has not been examined. Magnetoencephalography (MEG) is a neuroimaging modality with high spatial and temporal resolution that can be applied to the examination of brain dynamics underlying speech as it can capture the fast responses fundamental to this function. We acquired MEG from 21 children with high-functioning autism (mean age: 11.43 years) and 21 age- and sex-matched controls as they performed a simple oromotor task, a phoneme production task and a phonemic sequencing task. Results showed significant differences in activation magnitude and peak latencies in primary motor cortex (Brodmann Area 4), motor planning areas (BA 6), temporal sequencing and sensorimotor integration areas (BA 22/13) and executive control areas (BA 9). Our findings of significant functional brain differences between these two groups on these simple oromotor and phonemic tasks suggest that these deficits may be foundational and could underlie the language deficits seen in ASD. © 2015 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research.

[The neurobiology of obsessive-compulsive disorder: new findings from functional magnetic resonance imaging (II)].

PubMed

Pena-Garijo, Josep; Ruipérez-Rodríguez, M Angeles; Barros-Loscertales, Alfonso

2010-05-01

In recent years, neuroscience has shown a growing interest in applying its methods to furthering the knowledge of psychiatric disorders, and one of the fundamental tools used to do so are neuroimaging techniques. Yet, in general, few studies have been conducted in which functional magnetic resonance has been applied in this field and findings are sometimes contradictory. In this study we review the specialised bibliography and present a critical discussion on the scientific literature published to date on the application of functional magnetic resonance and diffusion tensor imaging to one of the most widely studied disorders, from a neurobiological point of view, namely, obsessive-compulsive disorder. The study reviews the articles on the use of functional magnetic resonance imaging, as well as those dealing with neural connectivity, that have been indexed in the most commonly used medical databases on the topic since 1996. Most studies suggest that the prefrontal cortex (orbitofrontal and cingulate), the basal ganglia and the thalamus are involved in the pathogenesis of obsessive-compulsive disorder. Likewise, alterations in the white matter that affect neural connectivity have also been found. The contributions made by neuroimaging and, more specifically, by functional magnetic resonance imaging are and will undoubtedly continue to be a particularly interesting tool for explaining the aetiology of this disorder.

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine

PubMed Central

Pettersson-Yeo, William; Benetti, Stefania; Marquand, Andre F.; Joules, Richard; Catani, Marco; Williams, Steve C. R.; Allen, Paul; McGuire, Philip; Mechelli, Andrea

2014-01-01

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a single decision function based on an integrated kernel matrix, or, by creating an ensemble of multiple single modality classifiers and integrating their predictions. Here, we describe four integrative approaches: (1) an un-weighted sum of kernels, (2) multi-kernel learning, (3) prediction averaging, and (4) majority voting, and compare their ability to enhance classification accuracy relative to the best single-modality classification accuracy. We achieve this by integrating structural, functional, and diffusion tensor magnetic resonance imaging data, in order to compare ultra-high risk (n = 19), first episode psychosis (n = 19) and healthy control subjects (n = 23). Our results show that (i) whilst integration can enhance classification accuracy by up to 13%, the frequency of such instances may be limited, (ii) where classification can be enhanced, simple methods may yield greater increases relative to more computationally complex alternatives, and, (iii) the potential for classification enhancement is highly influenced by the specific diagnostic comparison under consideration. In conclusion, our findings suggest that for moderately sized clinical neuroimaging datasets, combining different imaging modalities in a data-driven manner is no “magic bullet” for increasing classification accuracy. However, it remains possible that this conclusion is dependent on the use of neuroimaging modalities that had little, or no, complementary information to offer one another, and that the integration of more diverse types of data would have produced greater classification enhancement. We suggest that future studies ideally examine a greater variety of data types (e.g., genetic, cognitive, and neuroimaging) in order to identify the data types and combinations optimally suited to the classification of early stage psychosis. PMID:25076868

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine.

PubMed

Pettersson-Yeo, William; Benetti, Stefania; Marquand, Andre F; Joules, Richard; Catani, Marco; Williams, Steve C R; Allen, Paul; McGuire, Philip; Mechelli, Andrea

2014-01-01

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a single decision function based on an integrated kernel matrix, or, by creating an ensemble of multiple single modality classifiers and integrating their predictions. Here, we describe four integrative approaches: (1) an un-weighted sum of kernels, (2) multi-kernel learning, (3) prediction averaging, and (4) majority voting, and compare their ability to enhance classification accuracy relative to the best single-modality classification accuracy. We achieve this by integrating structural, functional, and diffusion tensor magnetic resonance imaging data, in order to compare ultra-high risk (n = 19), first episode psychosis (n = 19) and healthy control subjects (n = 23). Our results show that (i) whilst integration can enhance classification accuracy by up to 13%, the frequency of such instances may be limited, (ii) where classification can be enhanced, simple methods may yield greater increases relative to more computationally complex alternatives, and, (iii) the potential for classification enhancement is highly influenced by the specific diagnostic comparison under consideration. In conclusion, our findings suggest that for moderately sized clinical neuroimaging datasets, combining different imaging modalities in a data-driven manner is no "magic bullet" for increasing classification accuracy. However, it remains possible that this conclusion is dependent on the use of neuroimaging modalities that had little, or no, complementary information to offer one another, and that the integration of more diverse types of data would have produced greater classification enhancement. We suggest that future studies ideally examine a greater variety of data types (e.g., genetic, cognitive, and neuroimaging) in order to identify the data types and combinations optimally suited to the classification of early stage psychosis.

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's compliance during MR imaging sessions 19,20. In the current video report, we present a pediatric neuroimaging protocol with guidelines and procedures that have proven to be successful to date in young children. PMID:19684560

Quantitative magnetic resonance imaging in traumatic brain injury.

PubMed

Bigler, E D

2001-04-01

Quantitative neuroimaging has now become a well-established method for analyzing magnetic resonance imaging in traumatic brain injury (TBI). A general review of studies that have examined quantitative changes following TBI is presented. The consensus of quantitative neuroimaging studies is that most brain structures demonstrate changes in volume or surface area after injury. The patterns of atrophy are consistent with the generalized nature of brain injury and diffuse axonal injury. Various clinical caveats are provided including how quantitative neuroimaging findings can be used clinically and in predicting rehabilitation outcome. The future of quantitative neuroimaging also is discussed.

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.

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.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

The Role of Neuroimaging Techniques in Establishing Diagnosis, Prognosis and Therapy in Disorders of Consciousness

PubMed Central

Gosseries, Olivia; Pistoia, Francesca; Charland-Verville, Vanessa; Carolei, Antonio; Sacco, Simona; Laureys, Steven

2016-01-01

Non-communicative brain damaged patients raise important clinical and scientific issues. Here, we review three major pathological disorders of consciousness: coma, the unresponsive wakefulness syndrome and the minimally conscious state. A number of clinical studies highlight the difficulty in making a correct diagnosis in patients with disorders of consciousness based only on behavioral examinations. The increasing use of neuroimaging techniques allows improving clinical characterization of these patients. Recent neuroimaging studies using positron emission tomography, functional magnetic resonance imaging, electroencephalography and transcranial magnetic stimulation can help assess diagnosis, prognosis, and therapeutic treatment. These techniques, using resting state, passive and active paradigms, also highlight possible dissociations between consciousness and responsiveness, and are facilitating a more accurate understanding of brain function in this challenging population. PMID:27347265

Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure☆

PubMed Central

Frick, Andreas; Gingnell, Malin; Marquand, Andre F.; Howner, Katarina; Fischer, Håkan; Kristiansson, Marianne; Williams, Steven C.R.; Fredrikson, Mats; Furmark, Tomas

2014-01-01

Functional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n = 14) from healthy controls (n = 12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD. PMID:24239689

ICA model order selection of task co-activation networks.

PubMed

Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

ICA model order selection of task co-activation networks

PubMed Central

Ray, Kimberly L.; McKay, D. Reese; Fox, Peter M.; Riedel, Michael C.; Uecker, Angela M.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.; Laird, Angela R.

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders. PMID:24339802

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 Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

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.

Contribution of Neuroimaging Studies to Understanding Development of Human Cognitive Brain Functions

PubMed Central

Morita, Tomoyo; Asada, Minoru; Naito, Eiichi

2016-01-01

Humans experience significant physical and mental changes from birth to adulthood, and a variety of perceptual, cognitive and motor functions mature over the course of approximately 20 years following birth. To deeply understand such developmental processes, merely studying behavioral changes is not sufficient; simultaneous investigation of the development of the brain may lead us to a more comprehensive understanding. Recent advances in noninvasive neuroimaging technologies largely contribute to this understanding. Here, it is very important to consider the development of the brain from the perspectives of “structure” and “function” because both structure and function of the human brain mature slowly. In this review, we first discuss the process of structural brain development, i.e., how the structure of the brain, which is crucial when discussing functional brain development, changes with age. Second, we introduce some representative studies and the latest studies related to the functional development of the brain, particularly for visual, facial recognition, and social cognition functions, all of which are important for humans. Finally, we summarize how brain science can contribute to developmental study and discuss the challenges that neuroimaging should address in the future. PMID:27695409

Infant Brain Structures, Executive Function, and Attention Deficit/Hyperactivity Problems at Preschool Age. A Prospective Study

ERIC Educational Resources Information Center

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

2013-01-01

Background: Neuroimaging findings have provided evidence for a relation between variations in brain structures and Attention Deficit/Hyperactivity Disorder (ADHD). However, longitudinal neuroimaging studies are typically confined to children who have already been diagnosed with ADHD. In a population-based study, we aimed to characterize the…

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

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.

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.

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 neurocognitive impairment, fatigue and depressive symptoms in some studies. Patients with chronic hepatitis C exhibit cerebral metabolite alterations and structural or functional neuroimaging abnormalities, which sustain the hypothesis of hepatitis C virus involvement in brain disturbances. © 2018 John Wiley & Sons Ltd.

Labeling and tracking exosomes within the brain using gold nanoparticles

NASA Astrophysics Data System (ADS)

Betzer, Oshra; Perets, Nisim; Barnoy, Eran; Offen, Daniel; Popovtzer, Rachela

2018-02-01

Cell-to-cell communication system involves Exosomes, small, membrane-enveloped nanovesicles. Exosomes are evolving as effective therapeutic tools for different pathologies. These extracellular vesicles can bypass biological barriers such as the blood-brain barrier, and can function as powerful nanocarriers for drugs, proteins and gene therapeutics. However, to promote exosomes' therapy development, especially for brain pathologies, a better understanding of their mechanism of action, trafficking, pharmacokinetics and bio-distribution is needed. In this research, we established a new method for non-invasive in-vivo neuroimaging of mesenchymal stem cell (MSC)-derived exosomes, based on computed tomography (CT) imaging with glucose-coated gold nanoparticle (GNP) labeling. We demonstrated that the exosomes were efficiently and directly labeled with GNPs, via an energy-dependent mechanism. Additionally, we found the optimal parameters for exosome labeling and neuroimaging, wherein 5 nm GNPs enhanced labeling, and intranasal administration produced superior brain accumulation. We applied our technique in a mouse model of focal ischemia. Imaging and tracking of intranasally-administered GNP-labeled exosomes revealed specific accumulation and prolonged presence at the lesion area, up to 24 hrs. We propose that this novel exosome labeling and in-vivo neuroimaging technique can serve as a general platform for brain theranostics.

Neuroimaging to Investigate Multisystem Involvement and Provide Biomarkers in Amyotrophic Lateral Sclerosis

PubMed Central

Pradat, Pierre-François; El Mendili, Mohamed-Mounir

2014-01-01

Neuroimaging allows investigating the extent of neurological systems degeneration in amyotrophic lateral sclerosis (ALS). Advanced MRI methods can detect changes related to the degeneration of upper motor neurons but have also demonstrated the participation of other systems such as the sensory system or basal ganglia, demonstrating in vivo that ALS is a multisystem disorder. Structural and functional imaging also allows studying dysfunction of brain areas associated with cognitive signs. From a biomarker perspective, numerous studies using diffusion tensor imaging showed a decrease of fractional anisotropy in the intracranial portion of the corticospinal tract but its diagnostic value at the individual level remains limited. A multiparametric approach will be required to use MRI in the diagnostic workup of ALS. A promising avenue is the new methodological developments of spinal cord imaging that has the advantage to investigate the two motor system components that are involved in ALS, that is, the lower and upper motor neuron. For all neuroimaging modalities, due to the intrinsic heterogeneity of ALS, larger pooled banks of images with standardized image acquisition and analysis procedures are needed. In this paper, we will review the main findings obtained with MRI, PET, SPECT, and nuclear magnetic resonance spectroscopy in ALS. PMID:24949452

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.

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

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.

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

[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.

Brain alterations in paedophilia: a critical review.

PubMed

Mohnke, Sebastian; Müller, Sabine; Amelung, Till; Krüger, Tillmann H C; Ponseti, Jorge; Schiffer, Boris; Walter, Martin; Beier, Klaus M; Walter, Henrik

2014-11-01

Psychosocial and biological factors have been implicated in paedophilia, such as alterations in brain structure and function. The purpose of this paper is to review the expanding body of literature on this topic including brain abnormality case reports, as well as structural and functional neuroimaging studies. Case studies of men who have committed sexual offences against children implicate frontal and temporal abnormalities that may be associated with impaired impulse inhibition. Structural neuroimaging investigations show volume reductions in paedophilic men. Although the findings have been heterogeneous, smaller amygdala volume has been replicated repeatedly. Functional neuroimaging investigations demonstrate an overlap between paedophiles and teleiophiles during sexual arousal processing. While it is controversial among studies regarding group differences, reliable discrimination between paedophilic and teleiophilic men may be achieved using functional activation patterns. Nevertheless, the heterogeneous findings published so far suggest further research is necessary to disentangle the neurobiological mechanisms of paedophilic preference. A number of methodological confounds have been identified, which may account for the inconsistent results that could prove to be beneficial for future investigations. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

[Methodological aspects of functional neuroimaging at high field strength: a critical review].

PubMed

Scheef, L; Landsberg, M W; Boecker, H

2007-09-01

The last few years have proven that high field magnetic resonance imaging (MRI) is superior in nearly every way to conventional equipment up to 1.5 tesla (T). Following the global success of 3T-scanners in research institutes and medical practices, a new generation of MRI devices with field strengths of 7T and higher is now on the horizon. The introduction of ultra high fields has brought MRI technology closer to the physical limitations and increasingly greater costs are required to achieve this goal. This article provides a critical overview of the advantages and problems of functional neuroimaging using ultra high field strengths. This review is principally limited to T2*-based functional imaging techniques not dependent on contrast agents. The main issues include the significance of high field technology with respect to SNR, CNR, resolution, and sequences, as well as artifacts, noise exposure, and SAR. Of great relevance is the discussion of parallel imaging, which will presumably determine the further development of high and ultra high field strengths. Finally, the importance of high field strengths for functional neuroimaging is explained by selected publications.

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.

Genome-wide linkage analysis of human auditory cortical activation suggests distinct loci on chromosomes 2, 3, and 8.

PubMed

Renvall, Hanna; Salmela, Elina; Vihla, Minna; Illman, Mia; Leinonen, Eira; Kere, Juha; Salmelin, Riitta

2012-10-17

Neural processes are explored through macroscopic neuroimaging and microscopic molecular measures, but the two levels remain primarily detached. The identification of direct links between the levels would facilitate use of imaging signals as probes of genetic function and, vice versa, access to molecular correlates of imaging measures. Neuroimaging patterns have been mapped for a few isolated genes, chosen based on their connection with a clinical disorder. Here we propose an approach that allows an unrestricted discovery of the genetic basis of a neuroimaging phenotype in the normal human brain. The essential components are a subject population that is composed of relatives and selection of a neuroimaging phenotype that is reproducible within an individual and similar between relatives but markedly variable across a population. Our present combined magnetoencephalography and genome-wide linkage study in 212 healthy siblings demonstrates that auditory cortical activation strength is highly heritable and, specifically in the right hemisphere, regulated oligogenically with linkages to chromosomes 2q37, 3p12, and 8q24. The identified regions delimit as candidate genes TRAPPC9, operating in neuronal differentiation, and ROBO1, regulating projections of thalamocortical axons. Identification of normal genetic variation underlying neurophysiological phenotypes offers a non-invasive platform for an in-depth, concerted capitalization of molecular and neuroimaging levels in exploring neural function.

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

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

Structural and functional imaging studies in chronic cannabis users: a systematic review of adolescent and adult findings.

PubMed

Batalla, Albert; Bhattacharyya, Sagnik; Yücel, Murat; Fusar-Poli, Paolo; Crippa, Jose Alexandre; Nogué, Santiago; Torrens, Marta; Pujol, Jesús; Farré, Magí; Martin-Santos, Rocio

2013-01-01

The growing concern about cannabis use, the most commonly used illicit drug worldwide, has led to a significant increase in the number of human studies using neuroimaging techniques to determine the effect of cannabis on brain structure and function. We conducted a systematic review to assess the evidence of the impact of chronic cannabis use on brain structure and function in adults and adolescents. Papers published until August 2012 were included from EMBASE, Medline, PubMed and LILACS databases following a comprehensive search strategy and pre-determined set of criteria for article selection. Only neuroimaging studies involving chronic cannabis users with a matched control group were considered. One hundred and forty-two studies were identified, of which 43 met the established criteria. Eight studies were in adolescent population. Neuroimaging studies provide evidence of morphological brain alterations in both population groups, particularly in the medial temporal and frontal cortices, as well as the cerebellum. These effects may be related to the amount of cannabis exposure. Functional neuroimaging studies suggest different patterns of resting global and brain activity during the performance of several cognitive tasks both in adolescents and adults, which may indicate compensatory effects in response to chronic cannabis exposure. However, the results pointed out methodological limitations of the work conducted to date and considerable heterogeneity in the findings. Chronic cannabis use may alter brain structure and function in adult and adolescent population. Further studies should consider the use of convergent methodology, prospective large samples involving adolescent to adulthood subjects, and data-sharing initiatives.

The cerebellum and cognition: evidence from functional imaging studies.

PubMed

Stoodley, Catherine J

2012-06-01

Evidence for a role of the human cerebellum in cognitive functions comes from anatomical, clinical and neuroimaging data. Functional neuroimaging reveals cerebellar activation during a variety of cognitive tasks, including language, visual-spatial, executive, and working memory processes. It is important to note that overt movement is not a prerequisite for cerebellar activation: the cerebellum is engaged during conditions which either control for motor output or do not involve motor responses. Resting-state functional connectivity data reveal that, in addition to networks underlying motor control, the cerebellum is part of "cognitive" networks with prefrontal and parietal association cortices. Consistent with these findings, regional differences in activation patterns within the cerebellum are evident depending on the task demands, suggesting that the cerebellum can be broadly divided into functional regions based on the patterns of anatomical connectivity between different regions of the cerebellum and sensorimotor and association areas of the cerebral cortex. However, the distinct contribution of the cerebellum to cognitive tasks is not clear. Here, the functional neuroimaging evidence for cerebellar involvement in cognitive functions is reviewed and related to hypotheses as to why the cerebellum is active during such tasks. Identifying the precise role of the cerebellum in cognition-as well as the mechanism by which the cerebellum modulates performance during a wide range of tasks-remains a challenge for future investigations.

Assessment of Diverse Biological Indicators in Gulf War Illness: Are They Replicable Are They Related

DTIC Science & Technology

2015-10-01

that includes physical and neuropsychological evaluations, neuroimaging (MRI, fMRI , DTI), adrenal function tests, and diverse immune, inflammatory...characterized by a profile of concurrent symptoms that typically includes persistent headaches, memory and cognitive difficulties, widespread pain, unexplained...includes physical examinations, neuroimaging (MRI volumetric assessments, fMRI , diffusion tensor imaging), neuropsychological evaluations, assessment

Neuroimaging in Pediatric Traumatic Brain Injury: Current and Future Predictors of Functional Outcome

ERIC Educational Resources Information Center

Suskauer, Stacy J.; Huisman, Thierry A. G. M.

2009-01-01

Although neuroimaging has long played a role in the acute management of pediatric traumatic brain injury (TBI), until recently, its use as a tool for understanding and predicting long-term brain-behavior relationships after TBI has been limited by the relatively poor sensitivity of routine clinical imaging for detecting diffuse axonal injury…

BrainMap VBM: An environment for structural meta-analysis.

PubMed

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

2018-05-02

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

The search for the number form area: A functional neuroimaging meta-analysis.

PubMed

Yeo, Darren J; Wilkey, Eric D; Price, Gavin R

2017-07-01

Recent studies report a putative "number form area" (NFA) in the inferior temporal gyrus (ITG) suggested to be specialized for Arabic numeral processing. However, a number of earlier studies report no such NFA. The reasons for such discrepancies across studies are unclear. To examine evidence for a convergent NFA across studies, we conducted two activation likelihood estimation meta-analyses on 31 and a subset of 20 neuroimaging studies that have contrasted digits with other meaningful symbols. Results suggest the potential existence of an NFA in the right ITG, in addition to a 'symbolic number processing network' comprising bilateral parietal regions, and right-lateralized superior and inferior frontal regions. Critically, convergent localization for the NFA was only evident when contrasts were appropriately controlled for task demands, and does not appear to depend on employing methods designed to overcome fMRI signal dropout in the ITG. Importantly, only five studies had foci within the identified ITG NFA cluster boundary, indicating that more empirical evidence is necessary to determine the true functional specialization and regional specificity of the putative NFA. Copyright © 2017 Elsevier Ltd. All rights reserved.

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 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.

Modeling functional Magnetic Resonance Imaging (fMRI) experimental variables in the Ontology of Experimental Variables and Values (OoEVV)

PubMed Central

Burns, Gully A.P.C.; Turner, Jessica A.

2015-01-01

Neuroimaging data is raw material for cognitive neuroscience experiments, leading to scientific knowledge about human neurological and psychological disease, language, perception, attention and ultimately, cognition. The structure of the variables used in the experimental design defines the structure of the data gathered in the experiments; this in turn structures the interpretative assertions that may be presented as experimental conclusions. Representing these assertions and the experimental data which support them in a computable way means that they could be used in logical reasoning environments, i.e. for automated meta-analyses, or linking hypotheses and results across different levels of neuroscientific experiments. Therefore, a crucial first step in being able to represent neuroimaging results in a clear, computable way is to develop representations for the scientific variables involved in neuroimaging experiments. These representations should be expressive, computable, valid, extensible, and easy-to-use. They should also leverage existing semantic standards to interoperate easily with other systems. We present an ontology design pattern called the Ontology of Experimental Variables and Values (OoEVV). This is designed to provide a lightweight framework to capture mathematical properties of data, with appropriate ‘hooks’ to permit linkage to other ontology-driven projects (such as the Ontology of Biomedical Investigations, OBI). We instantiate the OoEVV system with a small number of functional Magnetic Resonance Imaging datasets, to demonstrate the system’s ability to describe the variables of a neuroimaging experiment. OoEVV is designed to be compatible with the XCEDE neuroimaging data standard for data collection terminology, and with the Cognitive Paradigm Ontology (CogPO) for specific reasoning elements of neuroimaging experimental designs. PMID:23684873

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 positively correlated. Neuroimaging studies of cognitive remediation in patients with schizophrenia suggest a positive effect on brain functioning in terms of the functional reorganisation of neural networks.

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.

Neuroimaging and sexual behavior: identification of regional and functional differences.

PubMed

Cheng, Joseph C; Secondary, Joseph; Burke, William H; Fedoroff, J Paul; Dwyer, R Gregg

2015-07-01

The neuroanatomical correlates of human sexual desire, arousal, and behavior have been characterized in recent years with functional brain imaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Here, we briefly review the results of functional neuroimaging studies in humans, whether healthy or suffering from sexual disorders, and the current models of regional and network activation in sexual arousal. Attention is paid, in particular, to findings from both regional and network studies in the past 3 years. We also identify yet unanswered and pressing questions of interest to areas of ongoing investigations for psychiatric, scientific, and forensic disciplines.

Recent advances in Tourette syndrome research.

PubMed

Albin, Roger L; Mink, Jonathan W

2006-03-01

Tourette syndrome (TS) is a developmentally regulated neurobehavioral disorder characterized by involuntary, stereotyped, repetitive movements. Recent anatomical and neuroimaging studies have provided evidence for abnormal basal ganglia and dopaminergic function in TS. Basic research on striatal inhibitory mechanisms and dopaminergic function complements the recent neuroimaging and anatomical data. Parallel studies of basal ganglia participation in the normal performance and learning of stereotyped repetitive behaviors or habits has provided additional insight. These lines of research have provided new pieces to the TS puzzle, and their increasing convergence is showing how those pieces can be put together.

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.

Structural, functional and spectroscopic MRI studies of methamphetamine addiction.

PubMed

Salo, Ruth; Fassbender, Catherine

2012-01-01

This chapter reviews selected neuroimaging findings related to long-term amphetamine and methamphetamine (MA) use. An overview of structural and functional (fMRI) MR studies, Diffusion Tensor Imaging (DTI), Magnetic Resonance Spectroscopy (MRS) and Positron Emission Tomography (PET) studies conducted in long-term MA abusers is presented. The focus of this chapter is to present the relevant studies as tools to understand brain changes following drug abstinence and recovery from addiction. The behavioral relevance of these neuroimaging studies is discussed as they relate to clinical symptoms and treatment. Within each imaging section this chapter includes a discussion of the relevant imaging studies as they relate to patterns of drug use (i.e., duration of MA use, cumulative lifetime dose and time MA abstinent) as well as an overview of studies that link the imaging findings to cognitive measures. In our conclusion we discuss some of the future directions of neuroimaging as it relates to the pathophysiology of addiction.

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.

Technology-Aided Assessment of Sensorimotor Function in Early Infancy

PubMed Central

Allievi, Alessandro G.; Arichi, Tomoki; Gordon, Anne L.; Burdet, Etienne

2014-01-01

There is a pressing need for new techniques capable of providing accurate information about sensorimotor function during the first 2 years of childhood. Here, we review current clinical methods and challenges for assessing motor function in early infancy, and discuss the potential benefits of applying technology-assisted methods. We also describe how the use of these tools with neuroimaging, and in particular functional magnetic resonance imaging (fMRI), can shed new light on the intra-cerebral processes underlying neurodevelopmental impairment. This knowledge is of particular relevance in the early infant brain, which has an increased capacity for compensatory neural plasticity. Such tools could bring a wealth of knowledge about the underlying pathophysiological processes of diseases such as cerebral palsy; act as biomarkers to monitor the effects of possible therapeutic interventions; and provide clinicians with much needed early diagnostic information. PMID:25324827

Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

PubMed

Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

2011-05-15

There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

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.

Delineating potential epileptogenic areas utilizing resting functional magnetic resonance imaging (fMRI) in epilepsy patients.

PubMed

Pizarro, Ricardo; Nair, Veena; Meier, Timothy; Holdsworth, Ryan; Tunnell, Evelyn; Rutecki, Paul; Sillay, Karl; Meyerand, Mary E; Prabhakaran, Vivek

2016-08-01

Seizure localization includes neuroimaging like electroencephalogram, and magnetic resonance imaging (MRI) with limited ability to characterize the epileptogenic network. Temporal clustering analysis (TCA) characterizes epileptogenic network congruent with interictal epileptiform discharges by clustering together voxels with transient signals. We generated epileptogenic areas for 12 of 13 epilepsy patients with TCA, congruent with different areas of seizure onset. Resting functional MRI (fMRI) scans are noninvasive, and can be acquired quickly, in patients with different levels of severity and function. Analyzing resting fMRI data using TCA is quick and can complement clinical methods to characterize the epileptogenic network.

Pharmacological MRI in animal models: a useful tool for 5-HT research?

PubMed

Martin, Chris; Sibson, Nicola R

2008-11-01

Pharmacological magnetic resonance imaging (phMRI) offers the potential to provide novel insights into the functioning of neurotransmitter systems and drug action in the central nervous system. To date, much of the neuropharmacological research that has applied phMRI techniques has focused on the dopaminergic system with relatively few studies into serotonergic function. In this article, we discuss the current capabilities of, and future potential for phMRI to address fundamental questions in serotonergic research using animal models. Firstly we review existing literature on the application of phMRI to the serotonergic system by exploring 3 broad research themes: (i) the functional anatomy of the serotonergic system; (ii) drug-receptor targeting and distribution; and (iii) disease models and drug development. Subsequently, we discuss the interpretation of phMRI data in terms of neuropharmacological action with a focus on issues specific to neuroimaging studies of the serotonergic system. Unlike other neuroimaging approaches such as positron emission tomography, phMRI methods do not currently offer sensitivity to markers of specific pharmacological action. However, they can provide in vivo markers of the neuropharmacological modulation of neuronal activity across the whole brain with unparalleled spatial and temporal resolution. Furthermore, due to the non-invasive nature of MRI, these markers are readily translatable to human studies. Whilst there are a number of constraints and limitations to phMRI methods that necessitate careful data interpretation, we argue that phMRI could become a valuable research tool in neuropharmacological studies of the serotonergic system.

Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data.

PubMed

Abram, Samantha V; Helwig, Nathaniel E; Moodie, Craig A; DeYoung, Colin G; MacDonald, Angus W; Waller, Niels G

2016-01-01

Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks.

Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data

PubMed Central

Abram, Samantha V.; Helwig, Nathaniel E.; Moodie, Craig A.; DeYoung, Colin G.; MacDonald, Angus W.; Waller, Niels G.

2016-01-01

Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks. PMID:27516732

Neuroimaging and psychophysiological measurement in organizational research: an agenda for research in organizational cognitive neuroscience.

PubMed

Lee, Nick; Chamberlain, Laura

2007-11-01

Although organizational research has made tremendous strides in the last century, recent advances in neuroscience and the imaging of functional brain activity remain underused. In fact, even the use of well-established psychophysiological measurement tools is comparatively rare. Following the lead of social cognitive neuroscience, in this review, we conceptualize organizational cognitive neuroscience as a field dedicated to exploring the processes within the brain that underlie or influence human decisions, behaviors, and interactions either (a) within organizations or (b) in response to organizational manifestations or institutions. We discuss organizational cognitive neuroscience, bringing together work that may previously have been characterized rather atomistically, and provide a brief overview of individual methods that may be of use. Subsequently, we discuss the possible convergence and integration of the different neuroimaging and psychophysiological measurement modalities. A brief review of prior work in the field shows a significant need for a more coherent and theory-driven approach to organizational cognitive neuroscience. In response, we discuss a recent example of such work, along with three hypothetical case studies that exemplify the link between organizational and psychological theory and neuroscientific methods.

“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

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

The "handwriting brain": a meta-analysis of neuroimaging studies of motor versus orthographic processes.

PubMed

Planton, Samuel; Jucla, Mélanie; Roux, Franck-Emmanuel; Démonet, Jean-François

2013-01-01

Handwriting is a modality of language production whose cerebral substrates remain poorly known although the existence of specific regions is postulated. The description of brain damaged patients with agraphia and, more recently, several neuroimaging studies suggest the involvement of different brain regions. However, results vary with the methodological choices made and may not always discriminate between "writing-specific" and motor or linguistic processes shared with other abilities. We used the "Activation Likelihood Estimate" (ALE) meta-analytical method to identify the cerebral network of areas commonly activated during handwriting in 18 neuroimaging studies published in the literature. Included contrasts were also classified according to the control tasks used, whether non-specific motor/output-control or linguistic/input-control. These data were included in two secondary meta-analyses in order to reveal the functional role of the different areas of this network. An extensive, mainly left-hemisphere network of 12 cortical and sub-cortical areas was obtained; three of which were considered as primarily writing-specific (left superior frontal sulcus/middle frontal gyrus area, left intraparietal sulcus/superior parietal area, right cerebellum) while others related rather to non-specific motor (primary motor and sensorimotor cortex, supplementary motor area, thalamus and putamen) or linguistic processes (ventral premotor cortex, posterior/inferior temporal cortex). This meta-analysis provides a description of the cerebral network of handwriting as revealed by various types of neuroimaging experiments and confirms the crucial involvement of the left frontal and superior parietal regions. These findings provide new insights into cognitive processes involved in handwriting and their cerebral substrates. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Emotion and Theory of Mind in Schizophrenia-Investigating the Role of the Cerebellum.

PubMed

Mothersill, Omar; Knee-Zaska, Charlotte; Donohoe, Gary

2016-06-01

Social cognitive dysfunction, including deficits in facial emotion recognition and theory of mind, is a core feature of schizophrenia and more strongly predicts functional outcome than neurocognition alone. Although traditionally considered to play an important role in motor coordination, the cerebellum has been suggested to play a role in emotion processing and theory of mind, and also shows structural and functional abnormalities in schizophrenia. The aim of this systematic review was to investigate the specific role of the cerebellum in emotion and theory of mind deficits in schizophrenia using previously published functional neuroimaging studies. PubMed and PsycINFO were used to search for all functional neuroimaging studies reporting altered cerebellum activity in schizophrenia patients during emotion processing or theory of mind tasks, published until December 2014. Overall, 14 functional neuroimaging studies were retrieved. Most emotion studies reported lower cerebellum activity in schizophrenia patients relative to healthy controls. In contrast, the theory of mind studies reported mixed findings. Altered activity was observed across several posterior cerebellar regions involved in emotion and cognition. Weaker cerebellum activity in schizophrenia patients relative to healthy controls during emotion processing may contribute to blunted affect and reduced ability to recognise emotion in others. This research could be expanded by examining the relationship between cerebellum function, symptomatology and behaviour, and examining cerebellum functional connectivity in patients during emotion and theory of mind tasks.

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.

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.

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.

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 findings in the at-risk mental state: a review of recent literature.

PubMed

Wood, Stephen J; Reniers, Renate L E P; Heinze, Kareen

2013-01-01

The at-risk mental state (ARMS) has been the subject of much interest during the past 15 years. A great deal of effort has been expended to identify neuroimaging markers that can inform our understanding of the risk state and to help predict who will transition to frank psychotic illness. Recently, there has been an explosion of neuroimaging literature from people with an ARMS, which has meant that reviews and meta-analyses lack currency. Here we review papers published in the past 2 years, and contrast their findings with previous reports. While it is clear that people in the ARMS do show brain alterations when compared with healthy control subjects, there is an overall lack of consistency as to which of these alterations predict the development of psychosis. This problem arises because of variations in methodology (in patient recruitment, region of interest, method of analysis, and functional task employed), but there has also been too little effort put into replicating previous research. Nonetheless, there are areas of promise, notably that activation of the stress system and increased striatal dopamine synthesis seem to mark out patients in the ARMS most at risk for later transition. Future studies should focus on these areas, and on network-level analysis, incorporating graph theoretical approaches and intrinsic connectivity networks.

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

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.

Loss anticipation and outcome during the Monetary Incentive Delay Task: a neuroimaging systematic review and meta-analysis

PubMed Central

Dugré, Jules R.; Dumais, Alexandre; Bitar, Nathalie

2018-01-01

Background Reward seeking and avoidance of punishment are key motivational processes. Brain-imaging studies often use the Monetary Incentive Delay Task (MIDT) to evaluate motivational processes involved in maladaptive behavior. Although the bulk of research has been done on the MIDT reward events, little is known about the neural basis of avoidance of punishment. Therefore, we conducted a meta-analysis of brain activations during anticipation and receipt of monetary losses in healthy controls. Methods All functional neuro-imaging studies using the MIDT in healthy controls were retrieved using PubMed, Google Scholar & EMBASE databases. Functional neuro-imaging data was analyzed using the Seed-based d Mapping Software. Results Thirty-five studies met the inclusion criteria, comprising 699 healthy adults. In both anticipation and loss outcome phases, participants showed large and robust activations in the bilateral striatum, (anterior) insula, and anterior cingulate gyrus relatively to Loss > Neutral contrast. Although relatively similar activation patterns were observed during the two event types, they differed in the pattern of prefrontal activations: ventro-lateral prefrontal activations were observed during loss anticipation, while medial prefrontal activations were observed during loss receipt. Discussion Considering that previous meta-analyses highlighted activations in the medial prefrontal cortex/anterior cingulate cortex, the anterior insula and the ventral striatum, the current meta-analysis highlighted the potential specificity of the ventro-lateral prefrontal regions, the median cingulate cortex and the amygdala in the loss events. Future studies can rely on these latter results to examine the neural correlates of loss processing in psychiatric populations characterized by harm avoidance or insensitivity to punishment. PMID:29761060

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

Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS.

PubMed

Kuttikat, Anoop; Noreika, Valdas; Shenker, Nicholas; Chennu, Srivas; Bekinschtein, Tristan; Brown, Christopher Andrew

2016-01-01

Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits.

Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS

PubMed Central

Kuttikat, Anoop; Noreika, Valdas; Shenker, Nicholas; Chennu, Srivas; Bekinschtein, Tristan; Brown, Christopher Andrew

2016-01-01

Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits. PMID:26858626

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

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

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

Northwestern University Schizophrenia Data and Software Tool (NUSDAST)

PubMed Central

Wang, Lei; Kogan, Alex; Cobia, Derin; Alpert, Kathryn; Kolasny, Anthony; Miller, Michael I.; Marcus, Daniel

2013-01-01

The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data), cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function), clinical (demographic, sibling relationship, SAPS and SANS psychopathology), and genetic (20 polymorphisms) data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions. PMID:24223551

Northwestern University Schizophrenia Data and Software Tool (NUSDAST).

PubMed

Wang, Lei; Kogan, Alex; Cobia, Derin; Alpert, Kathryn; Kolasny, Anthony; Miller, Michael I; Marcus, Daniel

2013-01-01

The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data), cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function), clinical (demographic, sibling relationship, SAPS and SANS psychopathology), and genetic (20 polymorphisms) data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions.

[Language Functions in the Frontal Association Area: Brain Mechanisms That Create Language].

PubMed

Yamamoto, Kayako; Sakai, Kuniyoshi L

2016-11-01

Broca's area is known to be critically involved in language processing for more than 150 years. Recent neuroimaging techniques, including functional magnetic resonance imaging (fMRI) and diffusion MRI, enabled the subdivision of Broca's area based on both functional and anatomical aspects. Networks among the frontal association areas, especially the left inferior frontal gyrus (IFG), and other cortical regions in the temporal/parietal association areas, are also important for language-related information processing. Here, we review how neuroimaging studies, combined with research paradigms based on theoretical linguistics, have contributed to clarifying the critical roles of the left IFG in syntactic processing and those of language-related networks, including cortical and cerebellar regions.

The Body of Evidence: What Can Neuroscience Tell Us about Embodied Semantics?

PubMed Central

Hauk, Olaf; Tschentscher, Nadja

2013-01-01

Semantic knowledge is based on the way we perceive and interact with the world. However, the jury is still out on the question: to what degree are neuronal systems that subserve acquisition of semantic knowledge, such as sensory-motor networks, involved in its representation and processing? We will begin with a critical evaluation of the main behavioral and neuroimaging methods with respect to their capability to define the functional roles of specific brain areas. Any behavioral or neuroscientific measure is a conflation of representations and processes. Hence, a combination of behavioral and neurophysiological interactions as well as time-course information is required to define the functional roles of brain areas. This will guide our review of the empirical literature. Most research in this area has been done on semantics of concrete words, where clear theoretical frameworks for an involvement of sensory-motor systems in semantics exist. Most of this evidence still stems from correlational studies that are ambiguous with respect to the behavioral relevance of effects. Evidence for causal effects of sensory-motor systems on semantic processes is still scarce but evolving. Relatively few neuroscientific studies so far have investigated the embodiment of abstract semantics for words, numbers, and arithmetic facts. Here, some correlational evidence exists, but data on causality are mostly absent. We conclude that neuroimaging data, just as behavioral data, have so far not disentangled the fundamental link between process and representation. Future studies should therefore put more emphasis on the effects of task and context on semantic processing. Strong conclusions can only be drawn from a combination of methods that provide time-course information, determine the connectivity among poly- or amodal and sensory-motor areas, link behavioral with neuroimaging measures, and allow causal inferences. We will conclude with suggestions on how this could be accomplished in future research. PMID:23407791

[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.

Combining Feature Extraction Methods to Assist the Diagnosis of Alzheimer's Disease.

PubMed

Segovia, F; Górriz, J M; Ramírez, J; Phillips, C

2016-01-01

Neuroimaging data as (18)F-FDG PET is widely used to assist the diagnosis of Alzheimer's disease (AD). Looking for regions with hypoperfusion/ hypometabolism, clinicians may predict or corroborate the diagnosis of the patients. Modern computer aided diagnosis (CAD) systems based on the statistical analysis of whole neuroimages are more accurate than classical systems based on quantifying the uptake of some predefined regions of interests (ROIs). In addition, these new systems allow determining new ROIs and take advantage of the huge amount of information comprised in neuroimaging data. A major branch of modern CAD systems for AD is based on multivariate techniques, which analyse a neuroimage as a whole, considering not only the voxel intensities but also the relations among them. In order to deal with the vast dimensionality of the data, a number of feature extraction methods have been successfully applied. In this work, we propose a CAD system based on the combination of several feature extraction techniques. First, some commonly used feature extraction methods based on the analysis of the variance (as principal component analysis), on the factorization of the data (as non-negative matrix factorization) and on classical magnitudes (as Haralick features) were simultaneously applied to the original data. These feature sets were then combined by means of two different combination approaches: i) using a single classifier and a multiple kernel learning approach and ii) using an ensemble of classifier and selecting the final decision by majority voting. The proposed approach was evaluated using a labelled neuroimaging database along with a cross validation scheme. As conclusion, the proposed CAD system performed better than approaches using only one feature extraction technique. We also provide a fair comparison (using the same database) of the selected feature extraction methods.

Brain age predicts mortality

PubMed Central

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

2018-01-01

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

Neonatal brain resting-state functional connectivity imaging modalities.

PubMed

Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza

2018-06-01

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations.

PubMed

Kim, Junghi; Pan, Wei

2017-04-01

There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting-state functional MRI (rs-fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n. © 2017 WILEY PERIODICALS, INC.

[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.

Cognitive Contributions to Gait and Falls: Evidence and Implications

PubMed Central

Amboni, Marianna; Barone, Paolo; Hausdorff, Jeffrey M.

2014-01-01

Dementia and gait impairments often coexist in older adults and patients with neurodegenerative disease. Both conditions represent independent risk factors for falls. The relationship between cognitive function and gait has recently received increasing attention. Gait is no longer considered merely automated motor activity but rather an activity that requires executive function and attention as well as judgment of external and internal cues. In this review, we intend to: (1) summarize and synthesize the experimental, neuropsychological, and neuroimaging evidence that supports the role played by cognition in the control of gait; and (2) briefly discuss the implications deriving from the interplay between cognition and gait. In recent years, the dual task paradigm has been widely used as an experimental method to explore the interplay between gait and cognition. Several neuropsychological investigations have also demonstrated that walking relies on the use of several cognitive domains, including executive-attentional function, visuospatial abilities, and even memory resources. A number of morphological and functional neuroimaging studies have offered additional evidence supporting the relationship between gait and cognitive resources. Based on the findings from 3 lines of studies, it appears that a growing body of evidence indicates a pivotal role of cognition in gait control and fall prevention. The interplay between higher-order neural function and gait has a number of clinical implications, ranging from integrated assessment tools to possible innovative lines of interventions, including cognitive therapy for falls prevention on one hand and walking program for reducing dementia risk on the other. PMID:24132840

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

Neural Bases Of Food Perception: Coordinate-Based Meta-Analyses Of Neuroimaging Studies In Multiple Modalities

PubMed Central

Huerta, Claudia I; Sarkar, Pooja R; Duong, Timothy Q.; Laird, Angela R; Fox, Peter T

2013-01-01

Objective The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm; and, ii) the relative robustness and reliability of responses to each paradigm. Design and Methods functional magnetic resonance imaging (fMRI) studies using standardized stereotactic coordinates to report brain responses to food cues were identified using on-line databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation (ALE) was used to identify statistically reliable regional responses within each stimulation paradigm. Results Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. Conclusions These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions. PMID:24174404

Neuroimaging correlates of parent ratings of working memory in typically developing children

PubMed Central

Mahone, E. Mark; Martin, Rebecca; Kates, Wendy R.; Hay, Trisha; Horská, Alena

2009-01-01

The purpose of the present study was to investigate construct validity of parent ratings of working memory in children, using a multi-trait/multi-method design including neuroimaging, rating scales, and performance-based measures. Thirty-five typically developing children completed performance-based tests of working memory and nonexecutive function (EF) skills, received volumetric MRI, and were rated by parents on both EF-specific and broad behavior rating scales. After controlling for total cerebral volume and age, parent ratings of working memory were significantly correlated with frontal gray, but not temporal, parietal, or occipital gray, or any lobar white matter volumes. Performance-based measures of working memory were also moderately correlated with frontal lobe gray matter volume; however, non-EF parent ratings and non-EF performance-based measures were not correlated with frontal lobe volumes. Results provide preliminary support for the convergent and discriminant validity of parent ratings of working memory, and emphasize their utility in exploring brain–behavior relationships in children. Rating scales that directly examine EF skills may potentially have ecological validity, not only for “everyday” function, but also as correlates of brain volume. PMID:19128526

Neuroimaging Findings from Childhood Onset Schizophrenia Patients and their Non-Psychotic Siblings

PubMed Central

Ordóñez, Anna E.; Luscher, Zoe; Gogtay, Nitin

2015-01-01

Childhood onset schizophrenia (COS), with onset of psychosis before age 13, is a rare form of schizophrenia that represents a more severe and chronic form of the adult onset illness. In this review we examine structural and functional magnetic resonance imaging (MRI) studies of COS and non-psychotic siblings of COS patients in the context of studies of schizophrenia as a whole. Studies of COS to date reveal progressive loss of gray matter volume and cortical thinning, ventricular enlargement, progressive decline in cerebellar volume and a significant but fixed deficit in hippocampal volume. COS is also associated with a slower rate of white matter growth and disrupted local connectivity strength. Sibling studies indicate that non-psychotic siblings of COS patients share many of these brain abnormalities, including decreased cortical thickness and disrupted white matter growth, yet these abnormalities normalize with age. Cross-sectional and longitudinal neuroimaging studies remain some of the few methods for assessing human brain function and play a pivotal role in the quest for understanding the neurobiology of schizophrenia as well as other psychiatric disorders. Parallel studies in non-psychotic siblings provide a unique opportunity to understand both risk and resilience in schizophrenia. PMID:25819937

Neuroimaging findings from childhood onset schizophrenia patients and their non-psychotic siblings.

PubMed

Ordóñez, Anna E; Luscher, Zoe I; Gogtay, Nitin

2016-06-01

Childhood onset schizophrenia (COS), with onset of psychosis before age 13, is a rare form of schizophrenia that represents a more severe and chronic form of the adult onset illness. In this review we examine structural and functional magnetic resonance imaging (MRI) studies of COS and non-psychotic siblings of COS patients in the context of studies of schizophrenia as a whole. Studies of COS to date reveal progressive loss of gray matter volume and cortical thinning, ventricular enlargement, progressive decline in cerebellar volume and a significant but fixed deficit in hippocampal volume. COS is also associated with a slower rate of white matter growth and disrupted local connectivity strength. Sibling studies indicate that non-psychotic siblings of COS patients share many of these brain abnormalities, including decreased cortical thickness and disrupted white matter growth, yet these abnormalities normalize with age. Cross-sectional and longitudinal neuroimaging studies remain some of the few methods for assessing human brain function and play a pivotal role in the quest for understanding the neurobiology of schizophrenia as well as other psychiatric disorders. Parallel studies in non-psychotic siblings provide a unique opportunity to understand both risk and resilience in schizophrenia. Published by Elsevier B.V.

Simultaneous acquisition of corrugator electromyography and functional magnetic resonance imaging: A new method for objectively measuring affect and neural activity concurrently

PubMed Central

Heller, Aaron S.; Greischar, Lawrence L; Honor, Ann; Anderle, Michael J; Davidson, Richard J.

2011-01-01

The development of functional neuroimaging of emotion holds the promise to enhance our understanding of the biological bases of affect and improve our knowledge of psychiatric diseases. However, up to this point, researchers have been unable to objectively, continuously and unobtrusively measure the intensity and dynamics of affect concurrently with functional magnetic resonance imaging (fMRI). This has hindered the development and generalizability of our field. Facial electromyography (EMG) is an objective, reliable, valid, sensitive, and unobtrusive measure of emotion. Here, we report the successful development of a method for simultaneously acquiring fMRI and facial EMG. The ability to simultaneously acquire brain activity and facial physiology will allow affective neuroscientists to address theoretical, psychiatric, and individual difference questions in a more rigorous and generalizable way. PMID:21742043

A Window into the Brain: Advances in Psychiatric fMRI

PubMed Central

Zhan, Xiaoyan

2015-01-01

Functional magnetic resonance imaging (fMRI) plays a key role in modern psychiatric research. It provides a means to assay differences in brain systems that underlie psychiatric illness, treatment response, and properties of brain structure and function that convey risk factor for mental diseases. Here we review recent advances in fMRI methods in general use and progress made in understanding the neural basis of mental illness. Drawing on concepts and findings from psychiatric fMRI, we propose that mental illness may not be associated with abnormalities in specific local regions but rather corresponds to variation in the overall organization of functional communication throughout the brain network. Future research may need to integrate neuroimaging information drawn from different analysis methods and delineate spatial and temporal patterns of brain responses that are specific to certain types of psychiatric disorders. PMID:26413531

Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition Study.

PubMed

Schmaal, Lianne; Marquand, Andre F; Rhebergen, Didi; van Tol, Marie-José; Ruhé, Henricus G; van der Wee, Nic J A; Veltman, Dick J; Penninx, Brenda W J H

2015-08-15

A chronic course of major depressive disorder (MDD) is associated with profound alterations in brain volumes and emotional and cognitive processing. However, no neurobiological markers have been identified that prospectively predict MDD course trajectories. This study evaluated the prognostic value of different neuroimaging modalities, clinical characteristics, and their combination to classify MDD course trajectories. One hundred eighteen MDD patients underwent structural and functional magnetic resonance imaging (MRI) (emotional facial expressions and executive functioning) and were clinically followed-up at 2 years. Three MDD trajectories (chronic n = 23, gradual improving n = 36, and fast remission n = 59) were identified based on Life Chart Interview measuring the presence of symptoms each month. Gaussian process classifiers were employed to evaluate prognostic value of neuroimaging data and clinical characteristics (including baseline severity, duration, and comorbidity). Chronic patients could be discriminated from patients with more favorable trajectories from neural responses to various emotional faces (up to 73% accuracy) but not from structural MRI and functional MRI related to executive functioning. Chronic patients could also be discriminated from remitted patients based on clinical characteristics (accuracy 69%) but not when age differences between the groups were taken into account. Combining different task contrasts or data sources increased prediction accuracies in some but not all cases. Our findings provide evidence that the prediction of naturalistic course of depression over 2 years is improved by considering neuroimaging data especially derived from neural responses to emotional facial expressions. Neural responses to emotional salient faces more accurately predicted outcome than clinical data. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Neural systems and time course of proactive interference in working memory.

PubMed

Du, Yingchun; Zhang, John X; Xiao, Zhuangwei; Wu, Renhua

2007-01-01

The storage of information in working memory suffers as a function of proactive interference. Many works using neuroimaging technique have been done to reveal the brain mechanism of interference resolution. However, less is yet known about the time course of this process. Event-related potential method(ERP) and standardized Low Resolution Brain Electromagnetic Tomography method (sLORETA) were used in this study to discover the time course of interference resolution in working memory. The anterior P2 was thought to reflect interference resolution and if so, this process occurred earlier in working memory than in long-term memory.

"This is Why you've Been Suffering": Reflections of Providers on Neuroimaging in Mental Health Care.

PubMed

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

2011-03-01

Mental health care providers increasingly confront challenges posed by the introduction of new neurotechnology into the clinic, but little is known about the impact of such capabilities on practice patterns and relationships with patients. To address this important gap, we sought providers' perspectives on the potential clinical translation of functional neuroimaging for prediction and diagnosis of mental illness. We conducted 32 semi-structured telephone interviews with mental health care providers representing psychiatry, psychology, family medicine, and allied mental health. Our results suggest that mental health providers have begun to re-conceptualize mental illness with a neuroscience gaze. They report an epistemic commitment to the value of a brain scan to provide a meaningful explanation of mental illness for their clients. If functional neuroimaging continues along its projected trajectory to translation, providers will ultimately have to negotiate its role in mental health. Their perspectives, therefore, enrich bioethical discourse surrounding neurotechnology and inform the translational pathway.

“This is Why you've Been Suffering”: Reflections of Providers on Neuroimaging in Mental Health Care

PubMed Central

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

2011-01-01

Mental health care providers increasingly confront challenges posed by the introduction of new neurotechnology into the clinic, but little is known about the impact of such capabilities on practice patterns and relationships with patients. To address this important gap, we sought providers' perspectives on the potential clinical translation of functional neuroimaging for prediction and diagnosis of mental illness. We conducted 32 semi-structured telephone interviews with mental health care providers representing psychiatry, psychology, family medicine, and allied mental health. Our results suggest that mental health providers have begun to re-conceptualize mental illness with a neuroscience gaze. They report an epistemic commitment to the value of a brain scan to provide a meaningful explanation of mental illness for their clients. If functional neuroimaging continues along its projected trajectory to translation, providers will ultimately have to negotiate its role in mental health. Their perspectives, therefore, enrich bioethical discourse surrounding neurotechnology and inform the translational pathway. PMID:21572566

A studyforrest extension, retinotopic mapping and localization of higher visual areas

PubMed Central

Sengupta, Ayan; Kaule, Falko R.; Guntupalli, J. Swaroop; Hoffmann, Michael B.; Häusler, Christian; Stadler, Jörg; Hanke, Michael

2016-01-01

The studyforrest (http://studyforrest.org) dataset is likely the largest neuroimaging dataset on natural language and story processing publicly available today. In this article, along with a companion publication, we present an update of this dataset that extends its scope to vision and multi-sensory research. 15 participants of the original cohort volunteered for a series of additional studies: a clinical examination of visual function, a standard retinotopic mapping procedure, and a localization of higher visual areas—such as the fusiform face area. The combination of this update, the previous data releases for the dataset, and the companion publication, which includes neuroimaging and eye tracking data from natural stimulation with a motion picture, form an extremely versatile and comprehensive resource for brain imaging research—with almost six hours of functional neuroimaging data across five different stimulation paradigms for each participant. Furthermore, we describe employed paradigms and present results that document the quality of the data for the purpose of characterising major properties of participants’ visual processing stream. PMID:27779618

[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.

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 cerebellum, sensory-motor and fronto-limbic areas. The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

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 with headaches to the emergency department. The presence of red flag findings is associated with emergency department neuroimaging, although the risk of emergent intracranial abnormalities is low. Many children with headaches may be receiving unnecessary neuroimaging due to the high prevalence of non-specific red flag findings.

Predicting individual brain functional connectivity using a Bayesian hierarchical model.

PubMed

Dai, Tian; Guo, Ying

2017-02-15

Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual functional connectivity. We show there exists a nice connection between our proposed estimator and a recently developed shrinkage estimator of connectivity measures in the neuroimaging community. We develop an expectation-maximization (EM) algorithm for estimation of the proposed Bayesian hierarchical model. Simulations studies are performed to evaluate the accuracy of our proposed prediction methods. We illustrate the application of the methods with two data examples: the longitudinal resting-state fMRI from ADNI2 study and the test-retest fMRI data from Kirby21 study. In both the simulation studies and the fMRI data applications, we demonstrate that the proposed methods provide more accurate prediction and more reliable estimation of individual functional connectivity as compared with alternative methods. Copyright © 2017 Elsevier Inc. All rights reserved.

The nature of individual differences in inhibited temperament and risk for psychiatric disease: a review and meta-analysis

PubMed Central

Clauss, J. A.; Avery, S. N.; Blackford, J. U.

2015-01-01

What makes us different from one another? Why does one person jump out of airplanes for fun while another prefers to stay home and read? Why are some babies born with a predisposition to become anxious? Questions about individual differences in temperament have engaged the minds of scientists, psychologists, and philosophers for centuries. Recent technological advances in neuroimaging and genetics provide an unprecedented opportunity to answer these questions. Here we review the literature on the neurobiology of one of the most basic individual differences—the tendency to approach or avoid novelty. This trait, called inhibited temperament, is innate, heritable, and observed across species. Importantly, inhibited temperament also confers risk for psychiatric disease. Here, we provide a comprehensive review of inhibited temperament including neuroimaging and genetic studies in human and non-human primates. We conducted a meta-analysis of neuroimaging findings in inhibited humans that points to alterations in a fronto-limbic-basal ganglia circuit; these findings provide the basis of a model of inhibited temperament neurocircuitry. Lesion and neuroimaging studies in non-human primate models of inhibited temperament highlight roles for the amygdala, hippocampus, orbitofrontal cortex, and dorsal prefrontal cortex. Genetic studies highlight a role for genes that regulate neurotransmitter function, such as the serotonin transporter polymorphisms (5-HTTLPR), as well as genes that regulate stress response, such as corticotropin-releasing hormone (CRH). Together these studies provide a foundation of knowledge about the genetic and neural substrates of this most basic of temperament traits. Future studies using novel imaging methods and genetic approaches promise to expand upon these biological bases of inhibited temperament and inform our understanding of risk for psychiatric disease. PMID:25784645

The nature of individual differences in inhibited temperament and risk for psychiatric disease: A review and meta-analysis.

PubMed

Clauss, J A; Avery, S N; Blackford, J U

2015-04-01

What makes us different from one another? Why does one person jump out of airplanes for fun while another prefers to stay home and read? Why are some babies born with a predisposition to become anxious? Questions about individual differences in temperament have engaged the minds of scientists, psychologists, and philosophers for centuries. Recent technological advances in neuroimaging and genetics provide an unprecedented opportunity to answer these questions. Here we review the literature on the neurobiology of one of the most basic individual differences-the tendency to approach or avoid novelty. This trait, called inhibited temperament, is innate, heritable, and observed across species. Importantly, inhibited temperament also confers risk for psychiatric disease. Here, we provide a comprehensive review of inhibited temperament, including neuroimaging and genetic studies in human and non-human primates. We conducted a meta-analysis of neuroimaging findings in inhibited humans that points to alterations in a fronto-limbic-basal ganglia circuit; these findings provide the basis of a model of inhibited temperament neurocircuitry. Lesion and neuroimaging studies in non-human primate models of inhibited temperament highlight roles for the amygdala, hippocampus, orbitofrontal cortex, and dorsal prefrontal cortex. Genetic studies highlight a role for genes that regulate neurotransmitter function, such as the serotonin transporter polymorphisms (5-HTTLPR), as well as genes that regulate stress response, such as corticotropin-releasing hormone (CRH). Together these studies provide a foundation of knowledge about the genetic and neural substrates of this most basic of temperament traits. Future studies using novel imaging methods and genetic approaches promise to expand upon these biological bases of inhibited temperament and inform our understanding of risk for psychiatric disease. Copyright © 2015 Elsevier Ltd. All rights reserved.

Insights from neuroenergetics into the interpretation of functional neuroimaging: an alternative empirical model for studying the brain's support of behavior

PubMed Central

Shulman, Robert G; Hyder, Fahmeed; Rothman, Douglas L

2014-01-01

Functional neuroimaging measures quantitative changes in neurophysiological parameters coupled to neuronal activity during observable behavior. These results have usually been interpreted by assuming that mental causation of behavior arises from the simultaneous actions of distinct psychological mechanisms or modules. However, reproducible localization of these modules in the brain using functional magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging has been elusive other than for sensory systems. In this paper, we show that neuroenergetic studies using PET, calibrated functional magnetic resonance imaging (fMRI), 13C magnetic resonance spectroscopy, and electrical recordings do not support the standard approach, which identifies the location of mental modules from changes in brain activity. Of importance in reaching this conclusion is that changes in neuronal activities underlying the fMRI signal are many times smaller than the high ubiquitous, baseline neuronal activity, or energy in resting, awake humans. Furthermore, the incremental signal depends on the baseline activity contradicting theoretical assumptions about linearity and insertion of mental modules. To avoid these problems, while making use of these valuable results, we propose that neuroimaging should be used to identify observable brain activities that are necessary for a person's observable behavior rather than being used to seek hypothesized mental processes. PMID:25160670

Overlapping neurobehavioral circuits in ADHD, obesity, and binge eating: Evidence from Neuroimaging Research

PubMed Central

Seymour, Karen E.; Reinblatt, Shauna P.; Benson, Leora; Carnell, Susan

2015-01-01

Attention-deficit/hyperactivity disorder (ADHD) and conditions involving excessive eating (e.g. obesity, binge / loss of control eating) are increasingly prevalent within pediatric populations, and correlational and some longitudinal studies have suggested inter-relationships between these disorders. In addition, a number of common neural correlates are emerging across conditions, e.g. functional abnormalities within circuits subserving reward processing and executive functioning. To explore this potential cross-condition overlap in neurobehavioral underpinnings, we selectively review relevant functional neuroimaging literature, specifically focusing on studies probing i) reward processing, ii) response inhibition, and iii) emotional processing and regulation, and outline three specific shared neurobehavioral circuits. Based on our review, we also identify gaps within the literature that would benefit from further research. PMID:26098969

The “Task B problem” and other considerations in developmental functional neuroimaging

PubMed Central

Church, Jessica A.; Petersen, Steven E.; Schlaggar, Bradley L.

2012-01-01

Functional neuroimaging provides a remarkable tool to allow us to study cognition across the lifespan and in special populations in a safe way. However, experimenters face a number of methodological issues, and these issues are particularly pertinent when imaging children. This brief article discusses assessing task performance, strategies for dealing with group performance differences, controlling for movement, statistical power, proper atlas registration, and data analysis strategies. In addition, there will be discussion of two other topics that have important implications for interpreting fMRI data: the question of whether functional neuroanatomical differences between adults and children are the consequence of putative developmental neurovascular differences, and the issue of interpreting negative blood oxygenation-level dependent (BOLD) signal change. PMID:20496376

Morning Glory Syndrome with Carotid and Middle Cerebral Artery Vasculopathy.

PubMed

Nezzar, Hachemi; Mbekeani, Joyce N; Dalens, Helen

2015-12-01

To report a case of incidental asymptomatic atypical morning glory syndrome (MGS) with concomitant ipsilateral carotid and middle cerebral dysgenesis. A 6-year-old child was discovered to have incidental findings of MGS, with atypia. All visual functions were normal including vision and stereopsis. Neuroimaging revealed ipsilateral carotid and middle cerebral vascular narrowing without associated collateral vessels or cerebral ischemia commonly seen in Moyamoya disease. Subsequent annual examinations have been stable, without signs of progression. This case demonstrates disparity between structural aberrations and final visual and neurological function and reinforces the association between MGS and intracranial vascular disruption. Full ancillary ophthalmic and neuroimaging studies should be performed in all patients with MGS with interval reassessments, even when the patient is asymptomatic and functionally intact.

AuthorSynth: a collaboration network and behaviorally-based visualization tool of activation reports from the neuroscience literature.

PubMed

Sochat, Vanessa V

2015-01-01

Targeted collaboration is becoming more challenging with the ever-increasing number of publications, conferences, and academic responsibilities that the modern-day researcher must synthesize. Specifically, the field of neuroimaging had roughly 10,000 new papers in PubMed for the year 2013, presenting tens of thousands of international authors, each a potential collaborator working on some sub-domain in the field. To remove the burden of synthesizing an entire corpus of publications, talks, and conference interactions to find and assess collaborations, we combine meta-analytical neuroimaging informatics methods with machine learning and network analysis toward this goal. We present "AuthorSynth," a novel application prototype that includes (1) a collaboration network to identify researchers with similar results reported in the literature; and (2) a 2D plot-"brain lattice"-to visually summarize a single author's contribution to the field, and allow for searching of authors based on behavioral terms. This method capitalizes on intelligent synthesis of the neuroimaging literature, and demonstrates that data-driven approaches can be used to confirm existing collaborations, reveal potential ones, and identify gaps in published knowledge. We believe this tool exemplifies how methods from neuroimaging informatics can better inform researchers about progress and knowledge in the field, and enhance the modern workflow of finding collaborations.

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.

Cholinergic modulation of cognition: Insights from human pharmacological functional neuroimaging

PubMed Central

Bentley, Paul; Driver, Jon; Dolan, Raymond J.

2011-01-01

Evidence from lesion and cortical-slice studies implicate the neocortical cholinergic system in the modulation of sensory, attentional and memory processing. In this review we consider findings from sixty-three healthy human cholinergic functional neuroimaging studies that probe interactions of cholinergic drugs with brain activation profiles, and relate these to contemporary neurobiological models. Consistent patterns that emerge are: (1) the direction of cholinergic modulation of sensory cortex activations depends upon top-down influences; (2) cholinergic hyperstimulation reduces top-down selective modulation of sensory cortices; (3) cholinergic hyperstimulation interacts with task-specific frontoparietal activations according to one of several patterns, including: suppression of parietal-mediated reorienting; decreasing ‘effort’-associated activations in prefrontal regions; and deactivation of a ‘resting-state network’ in medial cortex, with reciprocal recruitment of dorsolateral frontoparietal regions during performance-challenging conditions; (4) encoding-related activations in both neocortical and hippocampal regions are disrupted by cholinergic blockade, or enhanced with cholinergic stimulation, while the opposite profile is observed during retrieval; (5) many examples exist of an ‘inverted-U shaped’ pattern of cholinergic influences by which the direction of functional neural activation (and performance) depends upon both task (e.g. relative difficulty) and subject (e.g. age) factors. Overall, human cholinergic functional neuroimaging studies both corroborate and extend physiological accounts of cholinergic function arising from other experimental contexts, while providing mechanistic insights into cholinergic-acting drugs and their potential clinical applications. PMID:21708219

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.

Leigh Syndrome in Childhood: Neurologic Progression and Functional Outcome.

PubMed

Lee, Jin Sook; Kim, Hunmin; Lim, Byung Chan; Hwang, Hee; Choi, Jieun; Kim, Ki Joong; Hwang, Yong Seung; Chae, Jong Hee

2016-04-01

Few studies have analyzed the clinical course and functional outcome in Leigh syndrome (LS). The aim of this study was to determine the clinical, radiological, biochemical, and genetic features of patients with LS, and identify prognostic indicators of the disease progression and neurological outcome. Thirty-nine patients who had been diagnosed with LS at the Seoul National University Children's Hospital were included. Their medical records, neuroimaging findings, and histological/biochemical findings of skeletal muscle specimens were reviewed. Targeted sequencing of mitochondrial DNA was performed based on mitochondrial respiratory chain (MRC) enzyme defects. Isolated complex I deficiency was the most frequently observed MRC defect (in 42% of 38 investigated patients). Mitochondrial DNA mutations were identified in 11 patients, of which 81.8% were MT-ND genes. The clinical outcome varied widely, from independent daily activity to severe disability. Poor functional outcomes and neurological deterioration were significantly associated with early onset (before an age of 1 year) and the presence of other lesions additional to basal ganglia involvement in the initial neuroimaging. The neurological severity and outcome of LS may vary widely and be better than those predicted based on previous studies. We suggest that age at onset and initial neuroimaging findings are prognostic indicators in LS.

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

PubMed

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

Single photon emission computed tomography (SPECT) in epilepsy

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

Leroy, R.F.

1991-12-31

Epilepsy is a common neurologic disorder which has just begun to be studied with single photon emission computerized tomography (SPECT). Epilepsy usually is studied with electroencephalographic (EEG) techniques that demonstrate the physiologic changes that occur during seizures, and with neuroimaging techniques that show the brain structures where seizures originate. Neither method alone has been adequate to describe the pathophysiology of the patient with epilepsy. EEG techniques lack anatomic sensitivity, and there are no structural abnormalities shown by neuroimaging which are specific for epilepsy. Functional imaging (FI) has developed as a physiologic tool with anatomic sensitivity, and SPECT has been promotedmore » as a FI technique because of its potentially wide availability. However, SPECT is early in its development and its clinical utility for epilepsy still has to be demonstrated. To understand this role of SPECT, consideration must be given to the pathophysiology of epilepsy, brain physiology, types of seizure, epileptic syndromes, and the SPECT technique itself. 44 refs., 2 tabs.« less

How acute and chronic alcohol consumption affects brain networks: insights from multimodal neuroimaging.

PubMed

Schulte, Tilman; Oberlin, Brandon G; Kareken, David A; Marinkovic, Ksenija; Müller-Oehring, Eva M; Meyerhoff, Dieter J; Tapert, Susan

2012-12-01

Multimodal imaging combining 2 or more techniques is becoming increasingly important because no single imaging approach has the capacity to elucidate all clinically relevant characteristics of a network. This review highlights recent advances in multimodal neuroimaging (i.e., combined use and interpretation of data collected through magnetic resonance imaging [MRI], functional MRI, diffusion tensor imaging, positron emission tomography, magnetoencephalography, MR perfusion, and MR spectroscopy methods) that leads to a more comprehensive understanding of how acute and chronic alcohol consumption affect neural networks underlying cognition, emotion, reward processing, and drinking behavior. Several innovative investigators have started utilizing multiple imaging approaches within the same individual to better understand how alcohol influences brain systems, both during intoxication and after years of chronic heavy use. Their findings can help identify mechanism-based therapeutic and pharmacological treatment options, and they may increase the efficacy and cost effectiveness of such treatments by predicting those at greatest risk for relapse. Copyright © 2012 by the Research Society on Alcoholism.

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

The cerebellum: its role in language and related cognitive and affective functions.

PubMed

De Smet, Hyo Jung; Paquier, Philippe; Verhoeven, Jo; Mariën, Peter

2013-12-01

The traditional view on the cerebellum as the sole coordinator of motor function has been substantially redefined during the past decades. Neuroanatomical, neuroimaging and clinical studies have extended the role of the cerebellum to the modulation of cognitive and affective processing. Neuroanatomical studies have demonstrated cerebellar connectivity with the supratentorial association areas involved in higher cognitive and affective functioning, while functional neuroimaging and clinical studies have provided evidence of cerebellar involvement in a variety of cognitive and affective tasks. This paper reviews the recently acknowledged role of the cerebellum in linguistic and related cognitive and behavioral-affective functions. In addition, typical cerebellar syndromes such as the cerebellar cognitive affective syndrome (CCAS) and the posterior fossa syndrome (PFS) will be briefly discussed and the current hypotheses dealing with the presumed neurobiological mechanisms underlying the linguistic, cognitive and affective modulatory role of the cerebellum will be reviewed. Copyright © 2012 Elsevier Inc. All rights reserved.

Successful Object Encoding Induces Increased Directed Connectivity in Presymptomatic Early-Onset Alzheimer’s Disease

PubMed Central

Ochoa, John Fredy; Alonso, Joan Francesc; Duque, Jon Edinson; Tobón, Carlos Andrés; Mañanas, Miguel Angel; Lopera, Francisco; Hernández, Alher Mauricio

2016-01-01

Background: Recent studies report increases in neural activity in brain regions critical to episodic memory at preclinical stages of Alzheimer’s disease (AD). Although electroencephalography (EEG) is widely used in AD studies, given its non-invasiveness and low cost, there is a need to translate the findings in other neuroimaging methods to EEG. Objective: To examine how the previous findings using functional magnetic resonance imaging (fMRI) at preclinical stage in presenilin-1 E280A mutation carriers could be assessed and extended, using EEG and a connectivity approach. Methods: EEG signals were acquired during resting and encoding in 30 normal cognitive young subjects, from an autosomal dominant early-onset AD kindred from Antioquia, Colombia. Regions of the brain previously reported as hyperactive were used for connectivity analysis. Results: Mutation carriers exhibited increasing connectivity at analyzed regions. Among them, the right precuneus exhibited the highest changes in connectivity. Conclusion: Increased connectivity in hyperactive cerebral regions is seen in individuals, genetically-determined to develop AD, at preclinical stage. The use of a connectivity approach and a widely available neuroimaging technique opens the possibility to increase the use of EEG in early detection of preclinical AD. PMID:27792014

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

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.

Noninvasive PK11195-PET Image Analysis Techniques Can Detect Abnormal Cerebral Microglial Activation in Parkinson's Disease.

PubMed

Kang, Yeona; Mozley, P David; Verma, Ajay; Schlyer, David; Henchcliffe, Claire; Gauthier, Susan A; Chiao, Ping C; He, Bin; Nikolopoulou, Anastasia; Logan, Jean; Sullivan, Jenna M; Pryor, Kane O; Hesterman, Jacob; Kothari, Paresh J; Vallabhajosula, Shankar

2018-05-04

Neuroinflammation has been implicated in the pathophysiology of Parkinson's disease (PD), which might be influenced by successful neuroprotective drugs. The uptake of [ 11 C](R)-PK11195 (PK) is often considered to be a proxy for neuroinflammation, and can be quantified using the Logan graphical method with an image-derived blood input function, or the Logan reference tissue model using automated reference region extraction. The purposes of this study were (1) to assess whether these noninvasive image analysis methods can discriminate between patients with PD and healthy volunteers (HVs), and (2) to establish the effect size that would be required to distinguish true drug-induced changes from system variance in longitudinal trials. The sample consisted of 20 participants with PD and 19 HVs. Two independent teams analyzed the data to compare the volume of distribution calculated using image-derived input functions (IDIFs), and binding potentials calculated using the Logan reference region model. With all methods, the higher signal-to-background in patients resulted in lower variability and better repeatability than in controls. We were able to use noninvasive techniques showing significantly increased uptake of PK in multiple brain regions of participants with PD compared to HVs. Although not necessarily reflecting absolute values, these noninvasive image analysis methods can discriminate between PD patients and HVs. We see a difference of 24% in the substantia nigra between PD and HV with a repeatability coefficient of 13%, showing that it will be possible to estimate responses in longitudinal, within subject trials of novel neuroprotective drugs. © 2018 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.

The role of magnetic resonance imaging in the diagnosis of Parkinson's disease: a review.

PubMed

Al-Radaideh, Ali M; Rababah, Eman M

2016-01-01

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's in elderly people. Different structural and functional neuroimaging methods play a great role in the early diagnosis of neurodegenerative diseases. This review discusses the role of magnetic resonance imaging (MRI) in the diagnosis of PD. MRI provides clinicians with structural and functional information of human brain noninvasively. Advanced quantitative MRI techniques have shown promise for detecting pathological changes related to different stages of PD. Collectively, advanced MRI techniques at high and ultrahigh magnetic fields aid in better understanding of the nature and progression of PD. Copyright © 2016 Elsevier Inc. All rights reserved.

Neuroimaging and neuromodulation approaches to study eating behavior and prevent and treat eating disorders and obesity.

PubMed

Val-Laillet, D; Aarts, E; Weber, B; Ferrari, M; Quaresima, V; Stoeckel, L E; Alonso-Alonso, M; Audette, M; Malbert, C H; Stice, E

2015-01-01

Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at risk by exploring different neurobehavioral dimensions of the food choices and motivation processes. In the first part of this review, advantages and limitations of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), pharmacogenetic fMRI and functional near-infrared spectroscopy (fNIRS) will be discussed in the context of recent work dealing with eating behavior, with a particular focus on obesity. In the second part of the review, non-invasive strategies to modulate food-related brain processes and functions will be presented. At the leading edge of non-invasive brain-based technologies is real-time fMRI (rtfMRI) neurofeedback, which is a powerful tool to better understand the complexity of human brain-behavior relationships. rtfMRI, alone or when combined with other techniques and tools such as EEG and cognitive therapy, could be used to alter neural plasticity and learned behavior to optimize and/or restore healthy cognition and eating behavior. Other promising non-invasive neuromodulation approaches being explored are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct-current stimulation (tDCS). Converging evidence points at the value of these non-invasive neuromodulation strategies to study basic mechanisms underlying eating behavior and to treat its disorders. Both of these approaches will be compared in light of recent work in this field, while addressing technical and practical questions. The third part of this review will be dedicated to invasive neuromodulation strategies, such as vagus nerve stimulation (VNS) and deep brain stimulation (DBS). In combination with neuroimaging approaches, these techniques are promising experimental tools to unravel the intricate relationships between homeostatic and hedonic brain circuits. Their potential as additional therapeutic tools to combat pharmacorefractory morbid obesity or acute eating disorders will be discussed, in terms of technical challenges, applicability and ethics. In a general discussion, we will put the brain at the core of fundamental research, prevention and therapy in the context of obesity and eating disorders. First, we will discuss the possibility to identify new biological markers of brain functions. Second, we will highlight the potential of neuroimaging and neuromodulation in individualized medicine. Third, we will introduce the ethical questions that are concomitant to the emergence of new neuromodulation therapies.

Neuroimaging and neuromodulation approaches to study eating behavior and prevent and treat eating disorders and obesity

PubMed Central

Val-Laillet, D.; Aarts, E.; Weber, B.; Ferrari, M.; Quaresima, V.; Stoeckel, L.E.; Alonso-Alonso, M.; Audette, M.; Malbert, C.H.; Stice, E.

2015-01-01

Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at risk by exploring different neurobehavioral dimensions of the food choices and motivation processes. In the first part of this review, advantages and limitations of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), pharmacogenetic fMRI and functional near-infrared spectroscopy (fNIRS) will be discussed in the context of recent work dealing with eating behavior, with a particular focus on obesity. In the second part of the review, non-invasive strategies to modulate food-related brain processes and functions will be presented. At the leading edge of non-invasive brain-based technologies is real-time fMRI (rtfMRI) neurofeedback, which is a powerful tool to better understand the complexity of human brain–behavior relationships. rtfMRI, alone or when combined with other techniques and tools such as EEG and cognitive therapy, could be used to alter neural plasticity and learned behavior to optimize and/or restore healthy cognition and eating behavior. Other promising non-invasive neuromodulation approaches being explored are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct-current stimulation (tDCS). Converging evidence points at the value of these non-invasive neuromodulation strategies to study basic mechanisms underlying eating behavior and to treat its disorders. Both of these approaches will be compared in light of recent work in this field, while addressing technical and practical questions. The third part of this review will be dedicated to invasive neuromodulation strategies, such as vagus nerve stimulation (VNS) and deep brain stimulation (DBS). In combination with neuroimaging approaches, these techniques are promising experimental tools to unravel the intricate relationships between homeostatic and hedonic brain circuits. Their potential as additional therapeutic tools to combat pharmacorefractory morbid obesity or acute eating disorders will be discussed, in terms of technical challenges, applicability and ethics. In a general discussion, we will put the brain at the core of fundamental research, prevention and therapy in the context of obesity and eating disorders. First, we will discuss the possibility to identify new biological markers of brain functions. Second, we will highlight the potential of neuroimaging and neuromodulation in individualized medicine. Third, we will introduce the ethical questions that are concomitant to the emergence of new neuromodulation therapies. PMID:26110109

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 with entorhinal cortex thickness (FDR-corrected p-value < 0.05). In further analysis, the functional exonic rare variants in FANCC were also significantly associated with hippocampal volume and cerebrospinal fluid (CSF) Aβ 1-42 (p-value < 0.05). Our novel binning approach identified rare variants in FANCC as well as 7 evolutionary conserved regions significantly associated with a LOAD-related neuroimaging endophenotype. FANCC (fanconi anemia complementation group C) has been shown to modulate TLR and p38 MAPK-dependent expression of IL-1β in macrophages. Our results warrant further investigation in a larger independent cohort and demonstrate that the biological knowledge-driven binning approach is a powerful strategy to identify rare variants associated with AD and other complex disease.

Neuroimaging supports behavioral personality assessment: Overlapping activations during reflective and impulsive risk taking.

PubMed

Pletzer, Belinda; M Ortner, Tuulia

2016-09-01

Personality assessment has been challenged by the fact that different assessment methods (implicit measures, behavioral measures and explicit rating scales) show little or no convergence in behavioral studies. In this neuroimaging study we address for the first time, whether different assessment methods rely on separate or overlapping neuronal systems. Fifty nine healthy adult participants completed two objective personality tests of risk propensity: the more implicit Balloon Analogue Risk Task (BART) and the more explicit Game of Dice Task (GDT). Significant differences in activation, as well as connectivity patterns between both tasks were observed. In both tasks, risky decisions yielded significantly stronger activations than safe decisions in the bilateral caudate, as well as the bilateral Insula. The finding of overlapping brain areas validates different assessment methods, despite their behavioral non-convergence. This suggests that neuroimaging can be an important tool of validation in the field of personality assessment. Copyright © 2016 Elsevier B.V. All rights reserved.

Abnormal cerebellar morphometry in abstinent adolescent marijuana users

PubMed Central

Medina, Krista Lisdahl; Nagel, Bonnie J.; Tapert, Susan F.

2010-01-01

Background Functional neuroimaging data from adults have, in general, found frontocerebellar dysfunction associated with acute and chronic marijuana (MJ) use (Loeber & Yurgelun-Todd, 1999). One structural neuroimaging study found reduced cerebellar vermis volume in young adult MJ users with a history of heavy polysubstance use (Aasly et al., 1993). The goal of this study was to characterize cerebellar volume in adolescent chronic MJ users following one month of monitored abstinence. Method Participants were MJ users (n=16) and controls (n=16) aged 16-18 years. Extensive exclusionary criteria included history of psychiatric or neurologic disorders. Drug use history, neuropsychological data, and structural brain scans were collected after 28 days of monitored abstinence. Trained research staff defined cerebellar volumes (including three cerebellar vermis lobes and both cerebellar hemispheres) on high-resolution T1-weighted magnetic resonance images. Results Adolescent MJ users demonstrated significantly larger inferior posterior (lobules VIII-X) vermis volume (p<.009) than controls, above and beyond effects of lifetime alcohol and other drug use, gender, and intracranial volume. Larger vermis volumes were associated with poorer executive functioning (p’s<.05). Conclusions Following one month of abstinence, adolescent MJ users had significantly larger posterior cerebellar vermis volumes than non-using controls. These greater volumes are suggested to be pathological based on linkage to poorer executive functioning. Longitudinal studies are needed to examine typical cerebellar development during adolescence and the influence of marijuana use. PMID:20413277

A Meta-analysis of Cerebellar Contributions to Higher Cognition from PET and fMRI studies

PubMed Central

Keren-Happuch, E; Chen, Shen-Hsing Annabel; Ho, Moon-Ho Ringo; Desmond, John E.

2013-01-01

A growing interest in cerebellar function and its involvement in higher cognition have prompted much research in recent years. Cerebellar presence in a wide range of cognitive functions examined within an increasing body of neuroimaging literature has been observed. We applied a meta-analytic approach, which employed the activation likelihood estimate method, to consolidate results of cerebellar involvement accumulated in different cognitive tasks of interest and systematically identified similarities among the studies. The current analysis included 88 neuroimaging studies demonstrating cerebellar activations in higher cognitive domains involving emotion, executive function, language, music, timing and working memory. While largely consistent with a prior meta-analysis by Stoodley and Schmahmann (2009), our results extended their findings to include music and timing domains to provide further insights into cerebellar involvement and elucidate its role in higher cognition. In addition, we conducted inter- and intra-domain comparisons for the cognitive domains of emotion, language and working memory. We also considered task differences within the domain of verbal working memory by conducting a comparison of the Sternberg with the n-back task, as well as an analysis of the differential components within the Sternberg task. Results showed a consistent cerebellar presence in the timing domain, providing evidence for a role in time keeping. Unique clusters identified within the domain further refine the topographic organization of the cerebellum. PMID:23125108

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.

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.

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 reproducible research.

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 reproducible research. PMID:21897815

Brain PET scan

MedlinePlus

... tissues are working. Other imaging tests, such as magnetic resonance imaging ( MRI ) and computed tomography ( CT ) scans only reveal ... M, Hellwig S, Kloppel S, Weiller C. Functional neuroimaging: functional magnetic resonance imaging, positron emission tomography, and single-photon emission computed ...

Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches.

PubMed

Wang, Jiaojian; Yang, Yong; Fan, Lingzhong; Xu, Jinping; Li, Changhai; Liu, Yong; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2015-01-01

The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions. © 2014 Wiley Periodicals, Inc.

Imaging Evidence for Disturbances in Multiple Learning and Memory Systems in Persons with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Goh, Suzanne; Peterson, Bradley S.

2012-01-01

Aim: The aim of this article is to review neuroimaging studies of autism spectrum disorders (ASD) that examine declarative, socio-emotional, and procedural learning and memory systems. Method: We conducted a search of PubMed from 1996 to 2010 using the terms "autism,""learning,""memory," and "neuroimaging." We limited our review to studies…

Defective functional connectivity between posterior hypothalamus and regions of the diencephalic-mesencephalic junction in chronic cluster headache.

PubMed

Ferraro, Stefania; Nigri, Anna; Bruzzone, Maria Grazia; Brivio, Luca; Proietti Cecchini, Alberto; Verri, Mattia; Chiapparini, Luisa; Leone, Massimo

2018-01-01

Objective We tested the hypothesis of a defective functional connectivity between the posterior hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache based on: a) clinical and neuro-endocrinological findings in cluster headache patients; b) neuroimaging findings during cluster headache attacks; c) neuroimaging findings in drug-refractory chronic cluster headache patients improved after successful deep brain stimulation. Methods Resting state functional magnetic resonance imaging, associated with a seed-based approach, was employed to investigate the functional connectivity of the posterior hypothalamus in chronic cluster headache patients (n = 17) compared to age and sex-matched healthy subjects (n = 16). Random-effect analyses were performed to study differences between patients and controls in ipsilateral and contralateral-to-the-pain posterior hypothalamus functional connectivity. Results Cluster headache patients showed an increased functional connectivity between the ipsilateral posterior hypothalamus and a number of diencephalic-mesencephalic structures, comprising ventral tegmental area, dorsal nuclei of raphe, and bilateral substantia nigra, sub-thalamic nucleus, and red nucleus ( p < 0.005 FDR-corrected vs . control group). No difference between patients and controls was found comparing the contralateral hypothalami. Conclusions The observed deranged functional connectivity between the posterior ipsilateral hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache patients mainly involves structures that are part of (i.e. ventral tegmental area, substantia nigra) or modulate (dorsal nuclei of raphe, sub-thalamic nucleus) the midbrain dopaminergic systems. The midbrain dopaminergic systems could play a role in cluster headache pathophysiology and in particular in the chronicization process. Future studies are needed to better clarify if this finding is specific to cluster headache or if it represents an unspecific response to chronic pain.

Pain and functional imaging.

PubMed Central

Ingvar, M

1999-01-01

Functional neuroimaging has fundamentally changed our knowledge about the cerebral representation of pain. For the first time it has been possible to delineate the functional anatomy of different aspects of pain in the medial and lateral pain systems in the brain. The rapid developments in imaging methods over the past years have led to a consensus in the description of the central pain responses between different studies and also to a definition of a central pain matrix with specialized subfunctions in man. In the near future we will see studies where a systems perspective allows for a better understanding of the regulatory mechanisms in the higher-order frontal and parietal cortices. Also, pending the development of experimental paradigms, the functional anatomy of the emotional aspects of pain will become better known. PMID:10466155

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

When encoding yields remembering: insights from event-related neuroimaging.

PubMed Central

Wagner, A D; Koutstaal, W; Schacter, D L

1999-01-01

To understand human memory, it is important to determine why some experiences are remembered whereas others are forgotten. Until recently, insights into the neural bases of human memory encoding, the processes by which information is transformed into an enduring memory trace, have primarily been derived from neuropsychological studies of humans with select brain lesions. The advent of functional neuroimaging methods, such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), has provided a new opportunity to gain additional understanding of how the brain supports memory formation. Importantly, the recent development of event-related fMRI methods now allows for examination of trial-by-trial differences in neural activity during encoding and of the consequences of these differences for later remembering. In this review, we consider the contributions of PET and fMRI studies to the understanding of memory encoding, placing a particular emphasis on recent event-related fMRI studies of the Dm effect: that is, differences in neural activity during encoding that are related to differences in subsequent memory. We then turn our attention to the rich literature on the Dm effect that has emerged from studies using event-related potentials (ERPs). It is hoped that the integration of findings from ERP studies, which offer higher temporal resolution, with those from event-related fMRI studies, which offer higher spatial resolution, will shed new light on when and why encoding yields subsequent remembering. PMID:10466153

Network measures predict neuropsychological outcome after brain injury

PubMed Central

Warren, David E.; Power, Jonathan D.; Bruss, Joel; Denburg, Natalie L.; Waldron, Eric J.; Sun, Haoxin; Petersen, Steven E.; Tranel, Daniel

2014-01-01

Hubs are network components that hold positions of high importance for network function. Previous research has identified hubs in human brain networks derived from neuroimaging data; however, there is little consensus on the localization of such hubs. Moreover, direct evidence regarding the role of various proposed hubs in network function (e.g., cognition) is scarce. Regions of the default mode network (DMN) have been frequently identified as “cortical hubs” of brain networks. On theoretical grounds, we have argued against some of the methods used to identify these hubs and have advocated alternative approaches that identify different regions of cortex as hubs. Our framework predicts that our proposed hub locations may play influential roles in multiple aspects of cognition, and, in contrast, that hubs identified via other methods (including salient regions in the DMN) might not exert such broad influence. Here we used a neuropsychological approach to directly test these predictions by studying long-term cognitive and behavioral outcomes in 30 patients, 19 with focal lesions to six “target” hubs identified by our approaches (high system density and participation coefficient) and 11 with focal lesions to two “control” hubs (high degree centrality). In support of our predictions, we found that damage to target locations produced severe and widespread cognitive deficits, whereas damage to control locations produced more circumscribed deficits. These findings support our interpretation of how neuroimaging-derived network measures relate to cognition and augment classic neuroanatomically based predictions about cognitive and behavioral outcomes after focal brain injury. PMID:25225403

A permutation testing framework to compare groups of brain networks.

PubMed

Simpson, Sean L; Lyday, Robert G; Hayasaka, Satoru; Marsh, Anthony P; Laurienti, Paul J

2013-01-01

Brain network analyses have moved to the forefront of neuroimaging research over the last decade. However, methods for statistically comparing groups of networks have lagged behind. These comparisons have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Current comparison approaches generally either rely on a summary metric or on mass-univariate nodal or edge-based comparisons that ignore the inherent topological properties of the network, yielding little power and failing to make network level comparisons. Gleaning deeper insights into normal and abnormal changes in complex brain function demands methods that take advantage of the wealth of data present in an entire brain network. Here we propose a permutation testing framework that allows comparing groups of networks while incorporating topological features inherent in each individual network. We validate our approach using simulated data with known group differences. We then apply the method to functional brain networks derived from fMRI data.

Abnormal Functional Lateralization and Activity of Language Brain Areas in Typical Specific Language Impairment (Developmental Dysphasia)

ERIC Educational Resources Information Center

de Guibert, Clement; Maumet, Camille; Jannin, Pierre; Ferre, Jean-Christophe; Treguier, Catherine; Barillot, Christian; Le Rumeur, Elisabeth; Allaire, Catherine; Biraben, Arnaud

2011-01-01

Atypical functional lateralization and specialization for language have been proposed to account for developmental language disorders, yet results from functional neuroimaging studies are sparse and inconsistent. This functional magnetic resonance imaging study compared children with a specific subtype of specific language impairment affecting…

Cortical surface-based threshold-free cluster enhancement and cortexwise mediation.

PubMed

Lett, Tristram A; Waller, Lea; Tost, Heike; Veer, Ilya M; Nazeri, Arash; Erk, Susanne; Brandl, Eva J; Charlet, Katrin; Beck, Anne; Vollstädt-Klein, Sabine; Jorde, Anne; Kiefer, Falk; Heinz, Andreas; Meyer-Lindenberg, Andreas; Chakravarty, M Mallar; Walter, Henrik

2017-06-01

Threshold-free cluster enhancement (TFCE) is a sensitive means to incorporate spatial neighborhood information in neuroimaging studies without using arbitrary thresholds. The majority of methods have applied TFCE to voxelwise data. The need to understand the relationship among multiple variables and imaging modalities has become critical. We propose a new method of applying TFCE to vertexwise statistical images as well as cortexwise (either voxel- or vertexwise) mediation analysis. Here we present TFCE_mediation, a toolbox that can be used for cortexwise multiple regression analysis with TFCE, and additionally cortexwise mediation using TFCE. The toolbox is open source and publicly available (https://github.com/trislett/TFCE_mediation). We validated TFCE_mediation in healthy controls from two independent multimodal neuroimaging samples (N = 199 and N = 183). We found a consistent structure-function relationship between surface area and the first independent component (IC1) of the N-back task, that white matter fractional anisotropy is strongly associated with IC1 N-back, and that our voxel-based results are essentially identical to FSL randomise using TFCE (all P FWE <0.05). Using cortexwise mediation, we showed that the relationship between white matter FA and IC1 N-back is mediated by surface area in the right superior frontal cortex (P FWE  < 0.05). We also demonstrated that the same mediation model is present using vertexwise mediation (P FWE  < 0.05). In conclusion, cortexwise analysis with TFCE provides an effective analysis of multimodal neuroimaging data. Furthermore, cortexwise mediation analysis may identify or explain a mechanism that underlies an observed relationship among a predictor, intermediary, and dependent variables in which one of these variables is assessed at a whole-brain scale. Hum Brain Mapp 38:2795-2807, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Concepts of Connectivity and Human Epileptic Activity

PubMed Central

Lemieux, Louis; Daunizeau, Jean; Walker, Matthew C.

2011-01-01

This review attempts to place the concept of connectivity from increasingly sophisticated neuroimaging data analysis methodologies within the field of epilepsy research. We introduce the more principled connectivity terminology developed recently in neuroimaging and review some of the key concepts related to the characterization of propagation of epileptic activity using what may be called traditional correlation-based studies based on EEG. We then show how essentially similar methodologies, and more recently models addressing causality, have been used to characterize whole-brain and regional networks using functional MRI data. Following a discussion of our current understanding of the neuronal system aspects of the onset and propagation of epileptic discharges and seizures, we discuss the most advanced and ambitious framework to attempt to fully characterize epileptic networks based on neuroimaging data. PMID:21472027

The same analysis approach: Practical protection against the pitfalls of novel neuroimaging analysis methods.

PubMed

Görgen, Kai; Hebart, Martin N; Allefeld, Carsten; Haynes, John-Dylan

2017-12-27

Standard neuroimaging data analysis based on traditional principles of experimental design, modelling, and statistical inference is increasingly complemented by novel analysis methods, driven e.g. by machine learning methods. While these novel approaches provide new insights into neuroimaging data, they often have unexpected properties, generating a growing literature on possible pitfalls. We propose to meet this challenge by adopting a habit of systematic testing of experimental design, analysis procedures, and statistical inference. Specifically, we suggest to apply the analysis method used for experimental data also to aspects of the experimental design, simulated confounds, simulated null data, and control data. We stress the importance of keeping the analysis method the same in main and test analyses, because only this way possible confounds and unexpected properties can be reliably detected and avoided. We describe and discuss this Same Analysis Approach in detail, and demonstrate it in two worked examples using multivariate decoding. With these examples, we reveal two sources of error: A mismatch between counterbalancing (crossover designs) and cross-validation which leads to systematic below-chance accuracies, and linear decoding of a nonlinear effect, a difference in variance. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional specificity for high-level linguistic processing in the human brain.

PubMed

Fedorenko, Evelina; Behr, Michael K; Kanwisher, Nancy

2011-09-27

Neuroscientists have debated for centuries whether some regions of the human brain are selectively engaged in specific high-level mental functions or whether, instead, cognition is implemented in multifunctional brain regions. For the critical case of language, conflicting answers arise from the neuropsychological literature, which features striking dissociations between deficits in linguistic and nonlinguistic abilities, vs. the neuroimaging literature, which has argued for overlap between activations for linguistic and nonlinguistic processes, including arithmetic, domain general abilities like cognitive control, and music. Here, we use functional MRI to define classic language regions functionally in each subject individually and then examine the response of these regions to the nonlinguistic functions most commonly argued to engage these regions: arithmetic, working memory, cognitive control, and music. We find little or no response in language regions to these nonlinguistic functions. These data support a clear distinction between language and other cognitive processes, resolving the prior conflict between the neuropsychological and neuroimaging literatures.

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

Neurocircuitry models of posttraumatic stress disorder and extinction: human neuroimaging research--past, present, and future.

PubMed

Rauch, Scott L; Shin, Lisa M; Phelps, Elizabeth A

2006-08-15

The prevailing neurocircuitry models of anxiety disorders have been amygdalocentric in form. The bases for such models have progressed from theoretical considerations, extrapolated from research in animals, to in vivo human imaging data. For example, one current model of posttraumatic stress disorder (PTSD) has been highly influenced by knowledge from rodent fear conditioning research. Given the phenomenological parallels between fear conditioning and the pathogenesis of PTSD, we have proposed that PTSD is characterized by exaggerated amygdala responses (subserving exaggerated acquisition of fear associations and expression of fear responses) and deficient frontal cortical function (mediating deficits in extinction and the capacity to suppress attention/response to trauma-related stimuli), as well as deficient hippocampal function (mediating deficits in appreciation of safe contexts and explicit learning/memory). Neuroimaging studies have yielded convergent findings in support of this model. However, to date, neuroimaging investigations of PTSD have not principally employed conditioning and extinction paradigms per se. The recent development of such imaging probes now sets the stage for directly testing hypotheses regarding the neural substrates of fear conditioning and extinction abnormalities in PTSD.

Is Listening in Noise Worth It? The Neurobiology of Speech Recognition in Challenging Listening Conditions.

PubMed

Eckert, Mark A; Teubner-Rhodes, Susan; Vaden, Kenneth I

2016-01-01

This review examines findings from functional neuroimaging studies of speech recognition in noise to provide a neural systems level explanation for the effort and fatigue that can be experienced during speech recognition in challenging listening conditions. Neuroimaging studies of speech recognition consistently demonstrate that challenging listening conditions engage neural systems that are used to monitor and optimize performance across a wide range of tasks. These systems appear to improve speech recognition in younger and older adults, but sustained engagement of these systems also appears to produce an experience of effort and fatigue that may affect the value of communication. When considered in the broader context of the neuroimaging and decision making literature, the speech recognition findings from functional imaging studies indicate that the expected value, or expected level of speech recognition given the difficulty of listening conditions, should be considered when measuring effort and fatigue. The authors propose that the behavioral economics or neuroeconomics of listening can provide a conceptual and experimental framework for understanding effort and fatigue that may have clinical significance.

Is Listening in Noise Worth It? The Neurobiology of Speech Recognition in Challenging Listening Conditions

PubMed Central

Eckert, Mark A.; Teubner-Rhodes, Susan; Vaden, Kenneth I.

2016-01-01

This review examines findings from functional neuroimaging studies of speech recognition in noise to provide a neural systems level explanation for the effort and fatigue that can be experienced during speech recognition in challenging listening conditions. Neuroimaging studies of speech recognition consistently demonstrate that challenging listening conditions engage neural systems that are used to monitor and optimize performance across a wide range of tasks. These systems appear to improve speech recognition in younger and older adults, but sustained engagement of these systems also appears to produce an experience of effort and fatigue that may affect the value of communication. When considered in the broader context of the neuroimaging and decision making literature, the speech recognition findings from functional imaging studies indicate that the expected value, or expected level of speech recognition given the difficulty of listening conditions, should be considered when measuring effort and fatigue. We propose that the behavioral economics and/or neuroeconomics of listening can provide a conceptual and experimental framework for understanding effort and fatigue that may have clinical significance. PMID:27355759

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Substrates of neuropsychological functioning in stimulant dependence: a review of functional neuroimaging research

PubMed Central

Crunelle, Cleo L; Veltman, Dick J; Booij, Jan; Emmerik – van Oortmerssen, Katelijne; den Brink, Wim

2012-01-01

Stimulant dependence is associated with neuropsychological impairments. Here, we summarize and integrate the existing neuroimaging literature on the neural substrates of neuropsychological (dys)function in stimulant dependence, including cocaine, (meth-)amphetamine, ecstasy and nicotine dependence, and excessive caffeine use, comparing stimulant abusers (SAs) to nondrug using healthy controls (HCs). Despite some inconsistencies, most studies indicated altered brain activation in prefrontal cortex (PFC) and insula in response to reward and punishment, and higher limbic and anterior cingulate cortex (ACC)/PFC activation during craving and attentional bias paradigms in SAs compared with HCs. Impulsivity in SAs was associated with lower ACC and presupplementary motor area activity compared with HCs, and related to both ventral (amygdala, ventrolateral PFC, insula) and dorsal (dorsolateral PFC, dorsal ACC, posterior parietal cortex) systems. Decision making in SAs was associated with low dorsolateral PFC activity and high orbitofrontal activity. Finally, executive function in SAs was associated with lower activation in frontotemporal regions and higher activation in premotor cortex compared with HCs. It is concluded that the lower activations compared with HCs are likely to reflect the neural substrate of impaired neurocognitive functions, whereas higher activations in SAs compared with HCs are likely to reflect compensatory cognitive control mechanisms to keep behavioral task performance to a similar level as in HCs. However, before final conclusions can be drawn, additional research is needed using neuroimaging in SAs and HCs using larger and more homogeneous samples as well as more comparable task paradigms, study designs, and statistical analyses. PMID:22950052

Neural Systems Approaches to Understanding Major Depressive Disorder: An Intrinsic Functional Organization Perspective

PubMed Central

Hamilton, J. Paul; Chen, Michael C.; Gotlib, Ian H.

2012-01-01

Recent research detailing the intrinsic functional organization of the brain provides a unique and useful framework to gain a better understanding of the neural bases of Major Depressive Disorder (MDD). In this review, we first present a brief history of neuroimaging research that has increased our understanding of the functional macro-architecture of the brain. From this macro-architectural perspective, we examine the extant body of functional neuroimaging research assessing MDD with a specific emphasis on the contributions of default-mode, executive, and salience networks in this debilitating disorder. Next, we describe recent investigations conducted in our laboratory in which we explicitly adopt a neural-systems perspective in examining the relations among these networks in MDD. Finally, we offer directions for future research that we believe will facilitate the development of more detailed and integrative models of neural dysfunction in depression. PMID:23477309

Aging and Visual Attention

PubMed Central

Madden, David J.

2007-01-01

Older adults are often slower and less accurate than are younger adults in performing visual-search tasks, suggesting an age-related decline in attentional functioning. Age-related decline in attention, however, is not entirely pervasive. Visual search that is based on the observer’s expectations (i.e., top-down attention) is relatively preserved as a function of adult age. Neuroimaging research suggests that age-related decline occurs in the structure and function of brain regions mediating the visual sensory input, whereas activation of regions in the frontal and parietal lobes is often greater for older adults than for younger adults. This increased activation may represent an age-related increase in the role of top-down attention during visual tasks. To obtain a more complete account of age-related decline and preservation of visual attention, current research is beginning to explore the relation of neuroimaging measures of brain structure and function to behavioral measures of visual attention. PMID:18080001

Functional atlas of the awake rat brain: A neuroimaging study of rat brain specialization and integration.

PubMed

Ma, Zhiwei; Perez, Pablo; Ma, Zilu; Liu, Yikang; Hamilton, Christina; Liang, Zhifeng; Zhang, Nanyin

2018-04-15

Connectivity-based parcellation approaches present an innovative method to segregate the brain into functionally specialized regions. These approaches have significantly advanced our understanding of the human brain organization. However, parallel progress in animal research is sparse. Using resting-state fMRI data and a novel, data-driven parcellation method, we have obtained robust functional parcellations of the rat brain. These functional parcellations reveal the regional specialization of the rat brain, which exhibited high within-parcel homogeneity and high reproducibility across animals. Graph analysis of the whole-brain network constructed based on these functional parcels indicates that the rat brain has a topological organization similar to humans, characterized by both segregation and integration. Our study also provides compelling evidence that the cingulate cortex is a functional hub region conserved from rodents to humans. Together, this study has characterized the rat brain specialization and integration, and has significantly advanced our understanding of the rat brain organization. In addition, it is valuable for studies of comparative functional neuroanatomy in mammalian brains. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Centrality of prefrontal and motor preparation cortices to Tourette Syndrome revealed by meta-analysis of task-based neuroimaging studies.

PubMed

Polyanska, Liliana; Critchley, Hugo D; Rae, Charlotte L

2017-01-01

Tourette Syndrome (TS) is a neurodevelopmental condition characterized by chronic multiple tics, which are experienced as compulsive and 'unwilled'. Patients with TS can differ markedly in the frequency, severity, and bodily distribution of tics. Moreover, there are high comorbidity rates with attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), anxiety disorders, and depression. This complex clinical profile may account for apparent variability of findings across neuroimaging studies that connect neural function to cognitive and motor behavior in TS. Here we crystalized information from neuroimaging regarding the functional circuitry of TS, and furthermore, tested specifically for neural determinants of tic severity, by applying activation likelihood estimation (ALE) meta-analyses to neuroimaging (activation) studies of TS. Fourteen task-based studies (13 fMRI and one H2O-PET) met rigorous inclusion criteria. These studies, encompassing 25 experiments and 651 participants, tested for differences between TS participants and healthy controls across cognitive, motor, perceptual and somatosensory domains. Relative to controls, TS participants showed distributed differences in the activation of prefrontal (inferior, middle, and superior frontal gyri), anterior cingulate, and motor preparation cortices (lateral premotor cortex and supplementary motor area; SMA). Differences also extended into sensory (somatosensory cortex and the lingual gyrus; V4); and temporo-parietal association cortices (posterior superior temporal sulcus, supramarginal gyrus, and retrosplenial cortex). Within TS participants, tic severity (reported using the Yale Global Tic Severity Scale; YGTSS) selectively correlated with engagement of SMA, precentral gyrus, and middle frontal gyrus across tasks. The dispersed involvement of multiple cortical regions with differences in functional reactivity may account for heterogeneity in the symptomatic expression of TS and its comorbidities. More specifically for tics and tic severity, the findings reinforce previously proposed contributions of premotor and lateral prefrontal cortices to tic expression.

The Effects of Tai Chi Intervention on Healthy Elderly by Means of Neuroimaging and EEG: A Systematic Review.

PubMed

Pan, Zhujun; Su, Xiwen; Fang, Qun; Hou, Lijuan; Lee, Younghan; Chen, Chih C; Lamberth, John; Kim, Mi-Lyang

2018-01-01

Aging is a process associated with a decline in cognitive and motor functions, which can be attributed to neurological changes in the brain. Tai Chi, a multimodal mind-body exercise, can be practiced by people across all ages. Previous research identified effects of Tai Chi practice on delaying cognitive and motor degeneration. Benefits in behavioral performance included improved fine and gross motor skills, postural control, muscle strength, and so forth. Neural plasticity remained in the aging brain implies that Tai Chi-associated benefits may not be limited to the behavioral level. Instead, neurological changes in the human brain play a significant role in corresponding to the behavioral improvement. However, previous studies mainly focused on the effects of behavioral performance, leaving neurological changes largely unknown. This systematic review summarized extant studies that used brain imaging techniques and EEG to examine the effects of Tai Chi on older adults. Eleven articles were eligible for the final review. Three neuroimaging techniques including fMRI ( N = 6), EEG ( N = 4), and MRI ( N = 1), were employed for different study interests. Significant changes were reported on subjects' cortical thickness, functional connectivity and homogeneity of the brain, and executive network neural function after Tai Chi intervention. The findings suggested that Tai Chi intervention give rise to beneficial neurological changes in the human brain. Future research should develop valid and convincing study design by applying neuroimaging techniques to detect effects of Tai Chi intervention on the central nervous system of older adults. By integrating neuroimaging techniques into randomized controlled trials involved with Tai Chi intervention, researchers can extend the current research focus from behavioral domain to neurological level.

On the interpretation of weight vectors of linear models in multivariate neuroimaging.

PubMed

Haufe, Stefan; Meinecke, Frank; Görgen, Kai; Dähne, Sven; Haynes, John-Dylan; Blankertz, Benjamin; Bießmann, Felix

2014-02-15

The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

PubMed

Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

2018-04-20

Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.

A longitudinal model for functional connectivity networks using resting-state fMRI.

PubMed

Hart, Brian; Cribben, Ivor; Fiecas, Mark

2018-06-04

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Speech problems affect more than one in two children with cerebral palsy: Swedish population-based study.

PubMed

Nordberg, A; Miniscalco, C; Lohmander, A; Himmelmann, K

2013-02-01

To describe speech ability in a population-based study of children with cerebral palsy (CP), in relation to CP subtype, motor function, cognitive level and neuroimaging findings. A retrospective chart review of 129 children (66 girls, 63 boys) with CP, born in 1999-2002, was carried out. Speech ability and background information, such as type of CP, motor function, cognitive level and neuroimaging data, were collected and analysed. Speech disorders were found in 21% of the children and were present in all types of CP. Forty-one per cent of the children with speech disorders also had mental retardation, and 42% were able to walk independently. A further 32% of the children were nonverbal, and maldevelopment and basal ganglia lesions were most common in this group. The remaining 47% had no speech disorders, and this group was most likely to display white matter lesions of immaturity. More than half of the children in this CP cohort had a speech disorder (21%) or were nonverbal (32%). Speech ability was related to the type of CP, gross motor function, the presence of mental retardation and the localization of brain maldevelopment and lesions. Neuroimaging results differed between the three speech ability groups. ©2012 The Author(s)/Acta Paediatrica ©2012 Foundation Acta Paediatrica.

Use of near-infrared spectroscopy in the investigation of brain activation during cognitive aging: A systematic review of an emerging area of research.

PubMed

Agbangla, Nounagnon F; Audiffren, Michel; Albinet, Cédric T

2017-09-01

The cognitive neuroscience of aging is a growing and stimulating research area. The development of neuroimaging techniques in the past two decades has considerably increased our understanding of the brain mechanisms that might underlie cognitive performance and resulting changes due to normal aging. Beside traditional metabolic neuroimaging techniques, such as Positron Emission Tomography and functional Magnetic Resonance Imaging, near infrared spectroscopy (NIRS), an optical imaging technique allowing to monitor real-time cerebral blood oxygenation, has gained recent interest in this field. The aim of the present review paper, after briefly presenting the NIRS technique, is to review and to summarize the recent results of neuroimaging studies using this technique in the field of cognitive aging. The reviewed literature shows that, despite low spatial resolution and cerebral depth penetration, this technique provides consistent findings on the reduced hemodynamic activity as a function of chronological age, mainly in the prefrontal cortex. Important moderators of brain hemodynamics, such as cognitive load, subjects' characteristics and experimental conditions, for which the NIRS technique is sensitive, are discussed. Strengths and weaknesses of functional NIRS in the field of cognitive aging are presented and finally, novel perspectives of research are proposed. Copyright © 2017 Elsevier B.V. All rights reserved.

Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing.

PubMed

Yanes, Julio A; Riedel, Michael C; Ray, Kimberly L; Kirkland, Anna E; Bird, Ryan T; Boeving, Emily R; Reid, Meredith A; Gonzalez, Raul; Robinson, Jennifer L; Laird, Angela R; Sutherland, Matthew T

2018-03-01

Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain.

Functional lateralization of temporoparietal junction - imitation inhibition, visual perspective-taking and theory of mind.

PubMed

Santiesteban, Idalmis; Banissy, Michael J; Catmur, Caroline; Bird, Geoffrey

2015-10-01

Although neuroimaging studies have consistently identified the temporoparietal junction (TPJ) as a key brain region involved in social cognition, the literature is far from consistent with respect to lateralization of function. For example, during theory-of-mind tasks bilateral TPJ activation is found in some studies but only right hemisphere activation in others. Visual perspective-taking and imitation inhibition, which have been argued to recruit the same socio-cognitive processes as theory of mind, are associated with unilateral activation of either left TPJ (perspective taking) or right TPJ (imitation inhibition). The present study investigated the functional lateralization of TPJ involvement in the above three socio-cognitive abilities using transcranial direct current stimulation. Three groups of healthy adults received anodal stimulation over right TPJ, left TPJ or the occipital cortex prior to performing three tasks (imitation inhibition, visual perspective-taking and theory of mind). In contrast to the extant neuroimaging literature, our results suggest bilateral TPJ involvement in imitation inhibition and visual perspective-taking, while no effect of anodal stimulation was observed on theory of mind. The discrepancy between these findings and those obtained using neuroimaging highlight the efficacy of neurostimulation as a complementary methodological tool in cognitive neuroscience. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

PubMed Central

Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.

2010-01-01

The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

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).

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

Neuroimaging studies of the striatum in cognition Part I: healthy individuals

PubMed Central

Provost, Jean-Sebastien; Hanganu, Alexandru; Monchi, Oury

2015-01-01

The striatum has traditionally mainly been associated with playing a key role in the modulation of motor functions. Indeed, lesion studies in animals and studies of some neurological conditions in humans have brought further evidence to this idea. However, better methods of investigation have raised concerns about this notion, and it was proposed that the striatum could also be involved in different types of functions including cognitive ones. Although the notion was originally a matter of debate, it is now well-accepted that the caudate nucleus contributes to cognition, while the putamen could be involved in motor functions, and to some extent in cognitive functions as well. With the arrival of modern neuroimaging techniques in the early 1990, knowledge supporting the cognitive aspect of the striatum has greatly increased, and a substantial number of scientific papers were published studying the role of the striatum in healthy individuals. For the first time, it was possible to assess the contribution of specific areas of the brain during the execution of a cognitive task. Neuroanatomical studies have described functional loops involving the striatum and the prefrontal cortex suggesting a specific interaction between these two structures. This review examines the data up to date and provides strong evidence for a specific contribution of the fronto-striatal regions in different cognitive processes, such as set-shifting, self-initiated responses, rule learning, action-contingency, and planning. Finally, a new two-level functional model involving the prefrontal cortex and the dorsal striatum is proposed suggesting an essential role of the dorsal striatum in selecting between competing potential responses or actions, and in resolving a high level of ambiguity. PMID:26500513

Neuroimaging studies of the striatum in cognition Part I: healthy individuals.

PubMed

Provost, Jean-Sebastien; Hanganu, Alexandru; Monchi, Oury

2015-01-01

The striatum has traditionally mainly been associated with playing a key role in the modulation of motor functions. Indeed, lesion studies in animals and studies of some neurological conditions in humans have brought further evidence to this idea. However, better methods of investigation have raised concerns about this notion, and it was proposed that the striatum could also be involved in different types of functions including cognitive ones. Although the notion was originally a matter of debate, it is now well-accepted that the caudate nucleus contributes to cognition, while the putamen could be involved in motor functions, and to some extent in cognitive functions as well. With the arrival of modern neuroimaging techniques in the early 1990, knowledge supporting the cognitive aspect of the striatum has greatly increased, and a substantial number of scientific papers were published studying the role of the striatum in healthy individuals. For the first time, it was possible to assess the contribution of specific areas of the brain during the execution of a cognitive task. Neuroanatomical studies have described functional loops involving the striatum and the prefrontal cortex suggesting a specific interaction between these two structures. This review examines the data up to date and provides strong evidence for a specific contribution of the fronto-striatal regions in different cognitive processes, such as set-shifting, self-initiated responses, rule learning, action-contingency, and planning. Finally, a new two-level functional model involving the prefrontal cortex and the dorsal striatum is proposed suggesting an essential role of the dorsal striatum in selecting between competing potential responses or actions, and in resolving a high level of ambiguity.

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.

Experimental Design and Interpretation of Functional Neuroimaging Studies of Cognitive Processes

PubMed Central

Caplan, David

2008-01-01

This article discusses how the relation between experimental and baseline conditions in functional neuroimaging studies affects the conclusions that can be drawn from a study about the neural correlates of components of the cognitive system and about the nature and organization of those components. I argue that certain designs in common use—in particular the contrast of qualitatively different representations that are processed at parallel stages of a functional architecture—can never identify the neural basis of a cognitive operation and have limited use in providing information about the nature of cognitive systems. Other types of designs—such as ones that contrast representations that are computed in immediately sequential processing steps and ones that contrast qualitatively similar representations that are parametrically related within a single processing stage—are more easily interpreted. PMID:17979122

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

Distinguishing between Unipolar Depression and Bipolar Depression: Current and Future Clinical and Neuroimaging Perspectives

PubMed Central

de Almeida, Jorge Renner Cardoso; Phillips, Mary Louise

2012-01-01

Differentiating bipolar disorder (BD) from recurrent unipolar depression (UD) is a major clinical challenge. Main reasons for this include the higher prevalence of depressive relative to hypo/manic symptoms during the course of BD illness and the high prevalence of subthreshold manic symptoms in both BD and UD depression. Identifying objective markers of BD might help improve accuracy in differentiating between BD and UD depression, to ultimately optimize clinical and functional outcome for all depressed individuals. Yet, only eight neuroimaging studies to date directly compared UD and BD depressed individuals. Findings from these studies suggest more widespread abnormalities in white matter connectivity and white matter hyperintensities in BD than UD depression, habenula volume reductions in BD but not UD depression, and differential patterns of functional abnormalities in emotion regulation and attentional control neural circuitry in the two depression types. These findings suggest different pathophysiologic processes, especially in emotion regulation, reward and attentional control neural circuitry in BD versus UD depression. This review thereby serves as a “call to action” to highlight the pressing need for more neuroimaging studies, using larger samples sizes, comparing BD and UD depressed individuals. These future studies should also include dimensional approaches, studies of at risk individuals, and more novel neuroimaging approaches, such as, connectivity analysis and machine learning. Ultimately, these approaches might provide biomarkers to identify individuals at future risk for BD versus UD, and biological targets for more personalized treatment and new treatment developments for BD and UD depression. PMID:22784485

Subjective memory complaint only relates to verbal episodic memory performance in mild cognitive impairment.

PubMed

Gifford, Katherine A; Liu, Dandan; Damon, Stephen M; Chapman, William G; Romano Iii, Raymond R; Samuels, Lauren R; Lu, Zengqi; Jefferson, Angela L

2015-01-01

A cognitive concern from the patient, informant, or clinician is required for the diagnosis of mild cognitive impairment (MCI); however, the cognitive and neuroanatomical correlates of complaint are poorly understood. We assessed how self-complaint relates to cognitive and neuroimaging measures in older adults with MCI. MCI participants were drawn from the Alzheimer's Disease Neuroimaging Initiative and dichotomized into two groups based on the presence of self-reported memory complaint (no complaint n = 191, 77 ± 7 years; complaint n = 206, 73 ± 8 years). Cognitive outcomes included episodic memory, executive functioning, information processing speed, and language. Imaging outcomes included regional lobar volumes (frontal, parietal, temporal, cingulate) and specific medial temporal lobe structures (hippocampal volume, entorhinal cortex thickness, parahippocampal gyrus thickness). Linear regressions, adjusting for age, gender, race, education, Mini-Mental State Examination score, mood, and apolipoprotein E4 status, found that cognitive complaint related to immediate (β = -1.07, p < 0.001) and delayed episodic memory performances assessed on a serial list learning task (β = -1.06, p = 0.001) but no other cognitive measures or neuroimaging markers. Self-reported memory concern was unrelated to structural neuroimaging markers of atrophy and measures of information processing speed, executive functioning, or language. In contrast, subjective memory complaint related to objective verbal episodic learning performance. Future research is warranted to better understand the relation between cognitive complaint and surrogate markers of abnormal brain aging, including Alzheimer's disease, across the cognitive aging spectrum.

Haptic fMRI: combining functional neuroimaging with haptics for studying the brain's motor control representation.

PubMed

Menon, Samir; Brantner, Gerald; Aholt, Chris; Kay, Kendrick; Khatib, Oussama

2013-01-01

A challenging problem in motor control neuroimaging studies is the inability to perform complex human motor tasks given the Magnetic Resonance Imaging (MRI) scanner's disruptive magnetic fields and confined workspace. In this paper, we propose a novel experimental platform that combines Functional MRI (fMRI) neuroimaging, haptic virtual simulation environments, and an fMRI-compatible haptic device for real-time haptic interaction across the scanner workspace (above torso ∼ .65×.40×.20m(3)). We implement this Haptic fMRI platform with a novel haptic device, the Haptic fMRI Interface (HFI), and demonstrate its suitability for motor neuroimaging studies. HFI has three degrees-of-freedom (DOF), uses electromagnetic motors to enable high-fidelity haptic rendering (>350Hz), integrates radio frequency (RF) shields to prevent electromagnetic interference with fMRI (temporal SNR >100), and is kinematically designed to minimize currents induced by the MRI scanner's magnetic field during motor displacement (<2cm). HFI possesses uniform inertial and force transmission properties across the workspace, and has low friction (.05-.30N). HFI's RF noise levels, in addition, are within a 3 Tesla fMRI scanner's baseline noise variation (∼.85±.1%). Finally, HFI is haptically transparent and does not interfere with human motor tasks (tested for .4m reaches). By allowing fMRI experiments involving complex three-dimensional manipulation with haptic interaction, Haptic fMRI enables-for the first time-non-invasive neuroscience experiments involving interactive motor tasks, object manipulation, tactile perception, and visuo-motor integration.

Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.

PubMed

Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis

2006-01-01

This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.

Neuroimaging in pedophilia.

PubMed

Wiebking, Christine; Northoff, Georg

2013-04-01

Paraphilia is a set of disorders characterized by abnormal sexual desires. Perhaps most discussed amongst them, pedophilia is a complex interaction of disturbances of the emotional, cognitive and sexual experience. Using new imaging techniques such as functional magnetic resonance imaging, neural correlates of emotional, sexual and cognitive abnormalities and interactions have been investigated. As described on the basis of current research, altered patterns of brain activity, especially in the frontal areas of the brain, are seen in pedophilia. Building on these results, the analysis of neural correlates of impaired psychological functions opens the opportunity to further explore sexual deviances, which may contribute ultimately to the development of tools for risk assessment, classification methods and new therapeutic approaches.

Dynamics of the brain: Mathematical models and non-invasive experimental studies

NASA Astrophysics Data System (ADS)

Toronov, V.; Myllylä, T.; Kiviniemi, V.; Tuchin, V. V.

2013-10-01

Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.

Does Functional Neuroimaging Solve the Questions of Neurolinguistics?

ERIC Educational Resources Information Center

Sidtis, Diana Van Lancker

2006-01-01

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

Default-Mode Network Functional Connectivity in Aphasia: Therapy-Induced Neuroplasticity

ERIC Educational Resources Information Center

Marcotte, Karine; Perlbarg, Vincent; Marrelec, Guillaume; Benali, Habib; Ansaldo, Ana Ines

2013-01-01

Previous research on participants with aphasia has mainly been based on standard functional neuroimaging analysis. Recent studies have shown that functional connectivity analysis can detect compensatory activity, not revealed by standard analysis. Little is known, however, about the default-mode network in aphasia. In the current study, we studied…

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.

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

PubMed

Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-02-01

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural responses to exclusion predict susceptibility to social influence

PubMed Central

Falk, Emily B.; Cascio, Christopher N.; O’Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J.; Bingham, C. Raymond; Shope, Jean T.; Ouimet, Marie Claude; Pradhan, Anuj K.; Simons-Morton, Bruce G.

2014-01-01

Purpose Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence, and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American teens, traffic-related crashes are leading causes of non-fatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents’ vulnerability to peer influence. Methods We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently-licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately one week after the neuroimaging session. Results Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside of the neuroimaging lab one week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. Conclusions These results speak to the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging lab. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. PMID:24759437

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

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.

Dynamic Connectivity Patterns in Conscious and Unconscious Brain

PubMed Central

Ma, Yuncong; Hamilton, Christina

2017-01-01

Abstract Brain functional connectivity undergoes dynamic changes from the awake to unconscious states. However, how the dynamics of functional connectivity patterns are linked to consciousness at the behavioral level remains elusive. In this study, we acquired resting-state functional magnetic resonance imaging data during wakefulness and graded levels of consciousness in rats. Data were analyzed using a dynamic approach combining the sliding window method and k-means clustering. Our results demonstrate that whole-brain networks contained several quasi-stable patterns that dynamically recurred from the awake state into anesthetized states. Remarkably, two brain connectivity states with distinct spatial similarity to the structure of anatomical connectivity were strongly biased toward high and low consciousness levels, respectively. These results provide compelling neuroimaging evidence linking the dynamics of whole-brain functional connectivity patterns and states of consciousness at the behavioral level. PMID:27846731

On whether mirror neurons play a significant role in processing affective prosody.

PubMed

Ramachandra, Vijayachandra

2009-02-01

Several behavioral and neuroimaging studies have indicated that both right and left cortical structures and a few subcortical ones are involved in processing affective prosody. Recent investigations have shown that the mirror neuron system plays a crucial role in several higher-level functions such as empathy, theory of mind, language, etc., but no studies so far link the mirror neuron system with affective prosody. In this paper is a speculation that the mirror neuron system, which serves as a common neural substrate for different higher-level functions, may play a significant role in processing affective prosody via its connections with the limbic lobe. Actual research must apply electrophysiological and neuroimaging techniques to assess whether the mirror neuron systems underly affective prosody in humans.

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.

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

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.

Development and Validation of the Cognition Test Battery for Spaceflight

PubMed Central

Basner, Mathias; Savitt, Adam; Moore, Tyler M.; Port, Allison M.; McGuire, Sarah; Ecker, Adrian J.; Nasrini, Jad; Mollicone, Daniel J.; Mott, Christopher M.; McCann, Thom; Dinges, David F.; Gur, Ruben C.

2015-01-01

Background Sustained high-level cognitive performance is of paramount importance for the success of space missions, which involve environmental, physiological and psychological stressors that may affect brain functions. Despite subjective symptom reports of cognitive fluctuations in spaceflight, the nature of neurobehavioral functioning in space has not been clarified. Methods We developed a computerized cognitive test battery (Cognition) that has sensitivity to multiple cognitive domains and was specifically designed for the high-performing astronaut population. Cognition consists of 15 unique forms of 10 neuropsychological tests that cover a range of cognitive domains including emotion processing, spatial orientation, and risk decision making. Cognition is based on tests known to engage specific brain regions as evidenced by functional neuroimaging. Here we describe the first normative and acute total sleep deprivation data on the Cognition test battery as well as several efforts underway to establish the validity, sensitivity, feasibility, and acceptability of Cognition. Results Practice effects and test-retest variability differed substantially between the 10 Cognition tests, illustrating the importance of normative data that both reflect practice effects and differences in stimulus set difficulty in the population of interest. After one night without sleep, medium to large effect sizes were observed for 3 of the 10 tests addressing vigilant attention (Cohen’s d=1.00), cognitive throughput (d=0.68), and abstract reasoning (d=0.65). Conclusions In addition to providing neuroimaging-based novel information on the effects of spaceflight on a range of cognitive functions, Cognition will facilitate comparing the effects of ground-based analogs to spaceflight, increase consistency across projects, and thus enable meta-analyses. PMID:26564759

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

Life-course blood pressure in relation to brain volumes

PubMed Central

Power, Melinda C.; Schneider, Andrea L. C.; Wruck, Lisa; Griswold, Michael; Coker, Laura H.; Alonso, Alvaro; Jack, Clifford R.; Knopman, David; Mosley, Thomas H.; Gottesman, Rebecca F

2016-01-01

INTRODUCTION The impact of blood pressure on brain volumes may be time- or pattern-dependent. METHODS In 1678 participants from the Atherosclerosis Risk in Communities Neurocognitive Study, we quantified the association between measures and patterns of blood pressure over three time points (~24 or ~15 years prior and concurrent with neuroimaging) with late life brain volumes. RESULTS Higher diastolic blood pressure ~24 years prior, higher systolic and pulse pressure ~15 years prior, and consistently elevated or rising systolic blood pressure from ~15 years prior to concurrent with neuroimaging, but not blood pressures measured concurrent with neuroimaging, were associated with smaller volumes. The pattern of hypertension ~15 years prior and hypotension concurrent with neuroimaging was associated with smaller volumes in regions preferentially affected by Alzheimer’s disease (e.g., hippocampus: −0.27 standard units, 95%CI:−0.51,−0.03). DISCUSSION Hypertension 15 to 24 years prior is relevant to current brain volumes. Hypertension followed by hypotension appears particularly detrimental. PMID:27139841

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.

Neurobiological Phenotypes Associated with a Family History of Alcoholism

PubMed Central

Cservenka, Anita

2015-01-01

Background Individuals with a family history of alcoholism are at much greater risk for developing an alcohol use disorder (AUD) than youth or adults without such history. A large body of research suggests that there are premorbid differences in brain structure and function in family history positive (FHP) individuals relative to their family history negative (FHN) peers. Methods This review summarizes the existing literature on neurobiological phenotypes present in FHP youth and adults by describing findings across neurophysiological and neuroimaging studies. Results Neuroimaging studies have shown FHP individuals differ from their FHN peers in amygdalar, hippocampal, basal ganglia, and cerebellar volume. Both increased and decreased white matter integrity has been reported in FHP individuals compared with FHN controls. Functional magnetic resonance imaging studies have found altered inhibitory control and working memory-related brain response in FHP youth and adults, suggesting neural markers of executive functioning may be related to increased vulnerability for developing AUDs in this population. Additionally, brain activity differences in regions involved in bottom-up reward and emotional processing, such as the nucleus accumbens and amygdala, have been shown in FHP individuals relative to their FHN peers. Conclusions It is critical to understand premorbid neural characteristics that could be associated with cognitive, reward-related, or emotional risk factors that increase risk for AUDs in FHP individuals. This information may lead to the development of neurobiologically informed prevention and intervention studies focused on reducing the incidence of AUDs in high-risk youth and adults. PMID:26559000

Incorporating modern neuroscience findings to improve brain-computer interfaces: tracking auditory attention.

PubMed

Wronkiewicz, Mark; Larson, Eric; Lee, Adrian Kc

2016-10-01

Brain-computer interface (BCI) technology allows users to generate actions based solely on their brain signals. However, current non-invasive BCIs generally classify brain activity recorded from surface electroencephalography (EEG) electrodes, which can hinder the application of findings from modern neuroscience research. In this study, we use source imaging-a neuroimaging technique that projects EEG signals onto the surface of the brain-in a BCI classification framework. This allowed us to incorporate prior research from functional neuroimaging to target activity from a cortical region involved in auditory attention. Classifiers trained to detect attention switches performed better with source imaging projections than with EEG sensor signals. Within source imaging, including subject-specific anatomical MRI information (instead of using a generic head model) further improved classification performance. This source-based strategy also reduced accuracy variability across three dimensionality reduction techniques-a major design choice in most BCIs. Our work shows that source imaging provides clear quantitative and qualitative advantages to BCIs and highlights the value of incorporating modern neuroscience knowledge and methods into BCI systems.

Dynamic causal modelling: a critical review of the biophysical and statistical foundations.

PubMed

Daunizeau, J; David, O; Stephan, K E

2011-09-15

The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. Copyright © 2009 Elsevier Inc. All rights reserved.

Disease progression model in subjects with mild cognitive impairment from the Alzheimer's disease neuroimaging initiative: CSF biomarkers predict population subtypes

PubMed Central

Samtani, Mahesh N; Raghavan, Nandini; Shi, Yingqi; Novak, Gerald; Farnum, Michael; Lobanov, Victor; Schultz, Tim; Yang, Eric; DiBernardo, Allitia; Narayan, Vaibhav A

2013-01-01

AIM The objective is to develop a semi-mechanistic disease progression model for mild cognitive impairment (MCI) subjects. The model aims to describe the longitudinal progression of ADAS-cog scores from the Alzheimer's disease neuroimaging initiative trial that had data from 198 MCI subjects with cerebrospinal fluid (CSF) information who were followed for 3 years. METHOD Various covariates were tested on disease progression parameters and these variables fell into six categories: imaging volumetrics, biochemical, genetic, demographic, cognitive tests and CSF biomarkers. RESULTS CSF biomarkers were associated with both baseline disease score and disease progression rate in subjects with MCI. Baseline disease score was also correlated with atrophy measured using hippocampal volume. Progression rate was also predicted by executive functioning as measured by the Trail B-test. CONCLUSION CSF biomarkers have the ability to discriminate MCI subjects into sub-populations that exhibit markedly different rates of disease progression on the ADAS-cog scale. These biomarkers can therefore be utilized for designing clinical trials enriched with subjects that carry the underlying disease pathology. PMID:22534009

Content-specific evidence accumulation in inferior temporal cortex during perceptual decision-making

PubMed Central

Tremel, Joshua J.; Wheeler, Mark E.

2015-01-01

During a perceptual decision, neuronal activity can change as a function of time-integrated evidence. Such neurons may serve as decision variables, signaling a choice when activity reaches a boundary. Because the signals occur on a millisecond timescale, translating to human decision-making using functional neuroimaging has been challenging. Previous neuroimaging work in humans has identified patterns of neural activity consistent with an accumulation account. However, the degree to which the accumulating neuroimaging signals reflect specific sources of perceptual evidence is unknown. Using an extended face/house discrimination task in conjunction with cognitive modeling, we tested whether accumulation signals, as measured using functional magnetic resonance imaging (fMRI), are stimulus-specific. Accumulation signals were defined as a change in the slope of the rising edge of activation corresponding with response time (RT), with higher slopes associated with faster RTs. Consistent with an accumulation account, fMRI activity in face- and house-selective regions in the inferior temporal cortex increased at a rate proportional to decision time in favor of the preferred stimulus. This finding indicates that stimulus-specific regions perform an evidence integrative function during goal-directed behavior and that different sources of evidence accumulate separately. We also assessed the decision-related function of other regions throughout the brain and found that several regions were consistent with classifications from prior work, suggesting a degree of domain generality in decision processing. Taken together, these results provide support for an integration-to-boundary decision mechanism and highlight possible roles of both domain-specific and domain-general regions in decision evidence evaluation. PMID:25562821

Neuroimaging of the Functional and Structural Networks Underlying Visuospatial vs. Linguistic Reasoning in High-Functioning Autism

ERIC Educational Resources Information Center

Sahyoun, Cherif P.; Belliveau, John W.; Soulieres, Isabelle; Schwartz, Shira; Mody, Maria

2010-01-01

High-functioning individuals with autism have been found to favor visuospatial processing in the face of typically poor language abilities. We aimed to examine the neurobiological basis of this difference using functional magnetic resonance imaging and diffusion tensor imaging. We compared 12 children with high functioning autism (HFA) to 12 age-…

Safety of tPA in stroke mimics and neuroimaging-negative cerebral ischemia(Podcast)(e–Pub ahead of print)(CME)

PubMed Central

Chernyshev, O.Y.; Martin-Schild, S.; Albright, K.C.; Barreto, A.; Misra, V.; Acosta, I.; Grotta, J.C.; Savitz, S.I.

2010-01-01

Background: Patients with acute neurologic symptoms may have other causes simulating ischemic stroke, called stroke mimics (SM), but they may also have averted strokes that do not appear as infarcts on neuroimaging, which we call neuroimaging-negative cerebral ischemia (NNCI). We determined the safety and outcome of IV thrombolysis within 3 hours of symptom onset in patients with SM and NNCI. Methods: Patients treated with IV tissue plasminogen activator (tPA) within 3 hours of symptom onset were identified from our stroke registry from June 2004 to October 2008. We collected admission NIH Stroke Scale (NIHSS) score, modified Rankin score (mRS), length of stay (LOS), symptomatic intracerebral hemorrhage (sICH), and discharge diagnosis. Results: Among 512 treated patients, 21% were found not to have an infarct on follow-up imaging. In the SM group (14%), average age was 55 years, median admission NIHSS was 7, median discharge NIHSS was 0, median LOS was 3 days, and there were no instances of sICH. The most common etiologies were seizure, complicated migraine, and conversion disorder. In the NNCI group (7%), average age was 61 years, median admission NIHSS was 7, median discharge NIHSS was 0, median LOS was 3 days, and there were no instances of sICH. Nearly all SM (87%) and NNCI (91%) patients were functionally independent on discharge (mRS 0–1). Conclusions: Our data support the safety of administering IV tissue plasminogen activator to patients with suspected acute cerebral ischemia within 3 hours of symptom onset, even when the diagnosis ultimately is found not to be stroke or imaging does not show an infarct. GLOSSARY AIS = acute ischemic stroke; CI = confidence interval; DWI = diffusion-weighted imaging; ED = emergency department; LOS = length of stay; mRS = modified Rankin score; NIHSS = NIH Stroke Scale; NNCI = neuroimaging-negative cerebral ischemia; OR = odds ratio; sICH = symptomatic intracerebral hemorrhage; SM = stroke mimics; tPA = tissue plasminogen activator. PMID:20335564

Multimodal neuroimaging of frontal white matter microstructure in early phase schizophrenia: the impact of early adolescent cannabis use

PubMed Central

2013-01-01

Background A disturbance in connectivity between different brain regions, rather than abnormalities within the separate regions themselves, could be responsible for the clinical symptoms and cognitive dysfunctions observed in schizophrenia. White matter, which comprises axons and their myelin sheaths, provides the physical foundation for functional connectivity in the brain. Myelin sheaths are located around the axons and provide insulation through the lipid membranes of oligodendrocytes. Empirical data suggests oligodendroglial dysfunction in schizophrenia, based on findings of abnormal myelin maintenance and repair in regions of deep white matter. The aim of this in vivo neuroimaging project is to assess the impact of early adolescent onset of regular cannabis use on brain white matter tissue integrity, and to differentiate this impact from the white matter abnormalities associated with schizophrenia. The ultimate goal is to determine the liability of early adolescent use of cannabis on brain white matter, in a vulnerable brain. Methods/Design Young adults with schizophrenia at the early stage of the illness (less than 5 years since diagnosis) will be the focus of this project. Four magnetic resonance imaging measurements will be used to assess different cellular aspects of white matter: a) diffusion tensor imaging, b) localized proton magnetic resonance spectroscopy with a focus on the neurochemical N-acetylaspartate, c) the transverse relaxation time constants of regional tissue water, d) and of N-acetylaspartate. These four neuroimaging indices will be assessed within the same brain region of interest, that is, a large white matter fibre bundle located in the frontal region, the left superior longitudinal fasciculus. Discussion We will expand our knowledge regarding current theoretical models of schizophrenia with a more comprehensive multimodal neuroimaging approach to studying the underlying cellular abnormalities of white matter, while taking into consideration the important confounding variable of early adolescent onset of regular cannabis use. PMID:24131511

Time-of-day differences and short-term stability of the neural response to monetary reward: a pilot study.

PubMed

Hasler, Brant P; Forbes, Erika E; Franzen, Peter L

2014-10-30

Human and animal studies indicate that reward function is modulated by the circadian clock that governs our daily sleep/wake rhythm. For example, a robust circadian rhythm exists in positive affect, which is lower in the morning hours and peaks in the afternoon. A handful of functional neuroimaging studies suggest that systematic diurnal variation exists in brain activity related to other functions, but no published human studies have examined daily variation in the neural processing of reward. In the present study, we attempt to advance this literature by using functional neuroimaging methods to examine time-of-day changes in the responsivity of the reward circuit. Using a within-person design and a functional magnetic resonance imaging (fMRI) monetary reward task, we compared morning and afternoon reward-related brain activation in a sample of healthy young adults within 24h. Region of interest analyses focused on the striatum, and we hypothesized greater reward activation in the afternoon, concordant with the circadian peak in positive affect. Results were consistent with our hypothesis. In addition, we counterbalanced the order of morning and afternoon scans in order to explore the short-term stability of the neural response. Whole-brain analyses showed a markedly higher reactivity to reward throughout the brain in the first scan relative to the second scan, consistent with habituation to the monetary reward stimuli. However, these effects did not appear to explain the time-of-day findings. In summary, we report the first preliminary evidence of circadian variation in the neural processing of reward. These findings have both methodological and theoretical implications. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A systematic literature review of neuroimaging research on developmental stuttering between 1995 and 2016.

PubMed

Etchell, Andrew C; Civier, Oren; Ballard, Kirrie J; Sowman, Paul F

2018-03-01

Stuttering is a disorder that affects millions of people all over the world. Over the past two decades, there has been a great deal of interest in investigating the neural basis of the disorder. This systematic literature review is intended to provide a comprehensive summary of the neuroimaging literature on developmental stuttering. It is a resource for researchers to quickly and easily identify relevant studies for their areas of interest and enable them to determine the most appropriate methodology to utilize in their work. The review also highlights gaps in the literature in terms of methodology and areas of research. We conducted a systematic literature review on neuroimaging studies on developmental stuttering according to the PRISMA guidelines. We searched for articles in the pubmed database containing "stuttering" OR "stammering" AND either "MRI", "PET", "EEG", "MEG", "TMS"or "brain" that were published between 1995/​01/​01 and 2016/​01/​01. The search returned a total of 359 items with an additional 26 identified from a manual search. Of these, there were a total of 111 full text articles that met criteria for inclusion in the systematic literature review. We also discuss neuroimaging studies on developmental stuttering published throughout 2016. The discussion of the results is organized first by methodology and second by population (i.e., adults or children) and includes tables that contain all items returned by the search. There are widespread abnormalities in the structural architecture and functional organization of the brains of adults and children who stutter. These are evident not only in speech tasks, but also non-speech tasks. Future research should make greater use of functional neuroimaging and noninvasive brain stimulation, and employ structural methodologies that have greater sensitivity. Newly planned studies should also investigate sex differences, focus on augmenting treatment, examine moments of dysfluency and longitudinally or cross-sectionally investigate developmental trajectories in stuttering. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Negative mood influences default mode network functional connectivity in patients with chronic low back pain: implications for functional neuroimaging biomarkers.

PubMed

Letzen, Janelle E; Robinson, Michael E

2017-01-01

The default mode network (DMN) has been proposed as a biomarker for several chronic pain conditions. Default mode network functional connectivity (FC) is typically examined during resting-state functional neuroimaging, in which participants are instructed to let thoughts wander. However, factors at the time of data collection (eg, negative mood) that might systematically impact pain perception and its brain activity, influencing the application of the DMN as a pain biomarker, are rarely reported. This study measured whether positive and negative moods altered DMN FC patterns in patients with chronic low back pain (CLBP), specifically focusing on negative mood because of its clinical relevance. Thirty-three participants (CLBP = 17) underwent resting-state functional magnetic resonance imaging scanning before and after sad and happy mood inductions, and rated levels of mood and pain intensity at the time of scanning. Two-way repeated-measures analysis of variances were conducted on resting-state functional connectivity data. Significant group (CLBP > healthy controls) × condition (sadness > baseline) interaction effects were identified in clusters spanning parietal operculum/postcentral gyrus, insular cortices, anterior cingulate cortex, frontal pole, and a portion of the cerebellum (PFDR < 0.05). However, only 1 significant cluster covering a portion of the cerebellum was identified examining a two-way repeated-measures analysis of variance for happiness > baseline (PFDR < 0.05). Overall, these findings suggest that DMN FC is affected by negative mood in individuals with and without CLBP. It is possible that DMN FC seen in patients with chronic pain is related to an affective dimension of pain, which is important to consider in future neuroimaging biomarker development and implementation.

Functional Magnetic Resonance Imaging of the Domestic Dog: Research, Methodology, and Conceptual Issues

PubMed Central

Thompkins, Andie M.; Deshpande, Gopikrishna; Waggoner, Paul; Katz, Jeffrey S.

2017-01-01

Neuroimaging of the domestic dog is a rapidly expanding research topic in terms of the cognitive domains being investigated. Because dogs have shared both a physical and social world with humans for thousands of years, they provide a unique and socially relevant means of investigating a variety of shared human and canine psychological phenomena. Additionally, their trainability allows for neuroimaging to be carried out noninvasively in an awake and unrestrained state. In this review, a brief overview of functional magnetic resonance imaging (fMRI) is followed by an analysis of recent research with dogs using fMRI. Methodological and conceptual concerns found across multiple studies are raised, and solutions to these issues are suggested. With the research capabilities brought by canine functional imaging, findings may improve our understanding of canine cognitive processes, identify neural correlates of behavioral traits, and provide early-life selection measures for dogs in working roles. PMID:29456781

Toward Dysfunctional Connectivity: A Review of Neuroimaging Findings in Pediatric Major Depressive Disorder

PubMed Central

Hulvershorn, Leslie; Cullen, Kathryn; Anand, Amit

2011-01-01

Child and adolescent psychiatric neuroimaging research typically lags behind similar advances in adult disorders. While the pediatric depression imaging literature is less developed, a recent surge in interest has created the need for a synthetic review of this work. Major findings from pediatric volumetric and functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and resting state functional connectivity studies converge to implicate a corticolimbic network of key areas that work together to mediate the task of emotion regulation. Imaging the brain of children and adolescents with unipolar depression began with volumetric studies of isolated brain regions that served to identify key prefrontal, cingulate and limbic nodes of depression-related circuitry elucidated from more recent advances in DTI and functional connectivity imaging. Systematic review of these studies preliminarily suggests developmental differences between findings in youth and adults, including prodromal neurobiological features, along with some continuity across development. PMID:21901425

Right brain, left brain in depressive disorders: Clinical and theoretical implications of behavioral, electrophysiological and neuroimaging findings.

PubMed

Bruder, Gerard E; Stewart, Jonathan W; McGrath, Patrick J

2017-07-01

The right and left side of the brain are asymmetric in anatomy and function. We review electrophysiological (EEG and event-related potential), behavioral (dichotic and visual perceptual asymmetry), and neuroimaging (PET, MRI, NIRS) evidence of right-left asymmetry in depressive disorders. Recent electrophysiological and fMRI studies of emotional processing have provided new evidence of altered laterality in depressive disorders. EEG alpha asymmetry and neuroimaging findings at rest and during cognitive or emotional tasks are consistent with reduced left prefrontal activity in depressed patients, which may impair downregulation of amygdala response to negative emotional information. Dichotic listening and visual hemifield findings for non-verbal or emotional processing have revealed abnormal perceptual asymmetry in depressive disorders, and electrophysiological findings have shown reduced right-lateralized responsivity to emotional stimuli in occipitotemporal or parietotemporal cortex. We discuss models of neural networks underlying these alterations. Of clinical relevance, individual differences among depressed patients on measures of right-left brain function are related to diagnostic subtype of depression, comorbidity with anxiety disorders, and clinical response to antidepressants or cognitive behavioral therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Comparison of Neuroimaging Abnormalities in Multiple Sclerosis, Major Depression and Chronic Fatigue Syndrome (Myalgic Encephalomyelitis): is There a Common Cause?

PubMed

Morris, Gerwyn; Berk, Michael; Puri, Basant K

2018-04-01

There is copious evidence of abnormalities in resting-state functional network connectivity states, grey and white matter pathology and impaired cerebral perfusion in patients afforded a diagnosis of multiple sclerosis, major depression or chronic fatigue syndrome (CFS) (myalgic encephalomyelitis). Systemic inflammation may well be a major element explaining such findings. Inter-patient and inter-illness variations in neuroimaging findings may arise at least in part from regional genetic, epigenetic and environmental variations in the functions of microglia and astrocytes. Regional differences in neuronal resistance to oxidative and inflammatory insults and in the performance of antioxidant defences in the central nervous system may also play a role. Importantly, replicated experimental findings suggest that the use of high-resolution SPECT imaging may have the capacity to differentiate patients afforded a diagnosis of CFS from those with a diagnosis of depression. Further research involving this form of neuroimaging appears warranted in an attempt to overcome the problem of aetiologically heterogeneous cohorts which probably explain conflicting findings produced by investigative teams active in this field. However, the ionising radiation and relative lack of sensitivity involved probably preclude its use as a routine diagnostic tool.

A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes.

PubMed

Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D

2013-01-01

Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

Assessing Language Dominance with Functional MRI: The Role of Control Tasks and Statistical Analysis

ERIC Educational Resources Information Center

Dodoo-Schittko, Frank; Rosengarth, Katharina; Doenitz, Christian; Greenlee, Mark W.

2012-01-01

There is a discrepancy between the brain regions revealed by functional neuroimaging techniques and those brain regions where a loss of function, either by lesion or by electrocortical stimulation, induces language disorders. To differentiate between essential and non-essential language-related processes, we investigated the effects of linguistic…

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.

Neurotoxic Effects of Alcohol in Adolescence

PubMed Central

Jacobus, Joanna; Tapert, Susan F.

2013-01-01

This review examines neuroimaging and neurocognitive findings on alcohol-related toxicity in adolescents. Teens who meet criteria for alcohol use disorders, as well as those who engage in subdiagnostic binge drinking behaviors, often show poorer neurocognitive performance, alterations in gray and white matter brain structure, and discrepant functional brain activation patterns when compared to nonusing and demographically matched controls. Abnormalities are also observed in teens with a family history of alcoholism, and such differences in neuromaturation may leave youths at increased risk for the development of an alcohol use disorder or increased substance use severity. More prospective investigations are needed, and future work should focus on disentangling preexisting differences from dose-dependent effects of alcohol on neurodevelopment. Intervention strategies that utilize neuroimag-ing findings (e.g., identified weaknesses in particular neural substrates and behavioral correlates) may be helpful in both prevention and intervention campaigns for teens both pre- and postinitiation of alcohol use. PMID:23245341

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.

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.

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study

PubMed Central

Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T

2018-01-01

Background Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Objective Our Medical Research Council–funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Methods Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. Results This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. Conclusions This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. PMID:29523503

Neuroimaging of Reading Intervention: A Systematic Review and Activation Likelihood Estimate Meta-Analysis

PubMed Central

Barquero, Laura A.; Davis, Nicole; Cutting, Laurie E.

2014-01-01

A growing number of studies examine instructional training and brain activity. The purpose of this paper is to review the literature regarding neuroimaging of reading intervention, with a particular focus on reading difficulties (RD). To locate relevant studies, searches of peer-reviewed literature were conducted using electronic databases to search for studies from the imaging modalities of fMRI and MEG (including MSI) that explored reading intervention. Of the 96 identified studies, 22 met the inclusion criteria for descriptive analysis. A subset of these (8 fMRI experiments with post-intervention data) was subjected to activation likelihood estimate (ALE) meta-analysis to investigate differences in functional activation following reading intervention. Findings from the literature review suggest differences in functional activation of numerous brain regions associated with reading intervention, including bilateral inferior frontal, superior temporal, middle temporal, middle frontal, superior frontal, and postcentral gyri, as well as bilateral occipital cortex, inferior parietal lobules, thalami, and insulae. Findings from the meta-analysis indicate change in functional activation following reading intervention in the left thalamus, right insula/inferior frontal, left inferior frontal, right posterior cingulate, and left middle occipital gyri. Though these findings should be interpreted with caution due to the small number of studies and the disparate methodologies used, this paper is an effort to synthesize across studies and to guide future exploration of neuroimaging and reading intervention. PMID:24427278

Unveiling molecular events in the brain by noninvasive imaging.

PubMed

Klohs, Jan; Rudin, Markus

2011-10-01

Neuroimaging allows researchers and clinicians to noninvasively assess structure and function of the brain. With the advances of imaging modalities such as magnetic resonance, nuclear, and optical imaging; the design of target-specific probes; and/or the introduction of reporter gene assays, these technologies are now capable of visualizing cellular and molecular processes in vivo. Undoubtedly, the system biological character of molecular neuroimaging, which allows for the study of molecular events in the intact organism, will enhance our understanding of physiology and pathophysiology of the brain and improve our ability to diagnose and treat diseases more specifically. Technical/scientific challenges to be faced are the development of highly sensitive imaging modalities, the design of specific imaging probe molecules capable of penetrating the CNS and reporting on endogenous cellular and molecular processes, and the development of tools for extracting quantitative, biologically relevant information from imaging data. Today, molecular neuroimaging is still an experimental approach with limited clinical impact; this is expected to change within the next decade. This article provides an overview of molecular neuroimaging approaches with a focus on rodent studies documenting the exploratory state of the field. Concepts are illustrated by discussing applications related to the pathophysiology of Alzheimer's disease.

Reviews of Functional MRI: The Ethical Dimensions of Methodological Critique

PubMed Central

Anderson, James; Mizgalewicz, Ania; Illes, Judy

2012-01-01

Neuroimaging studies involving human subjects raise a range of ethics issues. Many of these issues are heightened in the context of neuroimaging research involving persons with mental health disorders. There has been growing interest in these issues among legal scholars, philosophers, social scientists, and as well as neuroimagers over the last decade. Less clear, however, is the extent to which members of the neuroimaging community are engaged with these issues when they undertake their research and report results. In this study, we analyze the peer-reviewed review literature involving fMRI as applied to the study of mental health disorders. Our hypothesis is that, due to the critical orientation of reviews, and the vulnerability of mental health population, the penetrance of neuroethics will be higher in the review literature in this area than it is in the primary fMRI research literature more generally. We find that while authors of reviews do focus a great deal of attention on the methodological limitations of the studies they discussed, contrary to our hypothesis, they do not frame concerns in ethical terms despite their ethical significance. We argue that an ethics lens on such discussion would increase the knowledge-value of this scholarly work. PMID:22952615

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

NASA Astrophysics Data System (ADS)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Distinguishing between unipolar depression and bipolar depression: current and future clinical and neuroimaging perspectives.

PubMed

Cardoso de Almeida, Jorge Renner; Phillips, Mary Louise

2013-01-15

Differentiating bipolar disorder (BD) from recurrent unipolar depression (UD) is a major clinical challenge. Main reasons for this include the higher prevalence of depressive relative to hypo/manic symptoms during the course of BD illness and the high prevalence of subthreshold manic symptoms in both BD and UD depression. Identifying objective markers of BD might help improve accuracy in differentiating between BD and UD depression, to ultimately optimize clinical and functional outcome for all depressed individuals. Yet, only eight neuroimaging studies to date have directly compared UD and BD depressed individuals. Findings from these studies suggest more widespread abnormalities in white matter connectivity and white matter hyperintensities in BD than UD depression, habenula volume reductions in BD but not UD depression, and differential patterns of functional abnormalities in emotion regulation and attentional control neural circuitry in the two depression types. These findings suggest different pathophysiologic processes, especially in emotion regulation, reward, and attentional control neural circuitry in BD versus UD depression. This review thereby serves as a call to action to highlight the pressing need for more neuroimaging studies, using larger samples sizes, comparing BD and UD depressed individuals. These future studies should also include dimensional approaches, studies of at-risk individuals, and more novel neuroimaging approaches, such as connectivity analysis and machine learning. Ultimately, these approaches might provide biomarkers to identify individuals at future risk for BD versus UD and biological targets for more personalized treatment and new treatment developments for BD and UD depression. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Mechanistic comparisons of functional domains across pediatric and adult bipolar disorder highlight similarities, as well as differences, influenced by the developing brain.

PubMed

Wegbreit, Ezra; Pavuluri, Mani

2012-01-01

Recent neuroimaging studies have uncovered much about the specific neural deficits in adult bipolar disorder (ABD), but despite promising results, neuroimaging research for pediatric bipolar disorder (PBD) is still developing. The neuroimaging literature is highly heterogeneous, varying in the paradigms used and in participants' mood states and medication status. Despite this variability, several dominant patterns emerge. In response to emotional stimuli, both ABD and PBD show limbic hyperactivity coupled with hypoactivity in ventral prefrontal emotion regulation systems. This pattern occurred most robustly in response to negative incidental stimuli and was especially apparent in manic PBD. ABD showed more variability in ventral prefrontal activity, possibly due to maturational and medication factors. On numerous cognitive paradigms, PBD showed dorsal prefrontal hypoactivity linked to ventral dysfunction, whereas ABD showed compensatory frontal, parietal, and temporal activity with paradigm-specific variations. In emotion-cognition interaction paradigms, patients show dysregulation in regions interfacing between cognitive and emotional brain systems (e.g., ventral prefrontal and cingulate cortices), which expend extra effort to process emotional stimuli effectively and recruit additional posterior attention systems to cope with affective instability. In addition, novel functional connectivity techniques have uncovered connectivity deficits between frontal and limbic regions in ABD and PBD at rest and during active emotional and cognitive tasks. Finally, the neuroimaging literature currently lacks cross-sectional studies comparing PBD with ABD and longitudinal studies following children and adolescents with BD into adulthood. Such studies would provide important insights into patients' prognosis and would determine targets for early interventions in the evolving illness diathesis.

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.

In vivo optoacoustic monitoring of calcium activity in the brain (Conference Presentation)

NASA Astrophysics Data System (ADS)

Deán-Ben, Xose Luís.; Gottschalk, Sven; Sela, Gali; Lauri, Antonella; Kneipp, Moritz; Ntziachristos, Vasilis; Westmeyer, Gil G.; Shoham, Shy; Razansky, Daniel

2017-03-01

Non-invasive observation of spatio-temporal neural activity of large neural populations distributed over the entire brain of complex organisms is a longstanding goal of neuroscience [1,2]. Recently, genetically encoded calcium indicators (GECIs) have revolutionized neuroimaging by enabling mapping the activity of entire neuronal populations in vivo [3]. Visualization of these powerful sensors with fluorescence microscopy has however been limited to superficial regions while deep brain areas have so far remained unreachable [4]. We have developed a volumetric multispectral optoacoustic tomography platform for imaging neural activation deep in scattering brains [5]. The developed methodology can render 100 volumetric frames per second across scalable fields of view ranging between 50-1000 mm3 with respective spatial resolution of 35-150µm. Experiments performed in immobilized and freely swimming larvae and in adult zebrafish brains expressing the genetically-encoded calcium indicator GCaMP5G demonstrated, for the first time, the fundamental ability to directly track neural dynamics using optoacoustics while overcoming the depth barrier of optical imaging in scattering brains [6]. It was further possible to monitor calcium transients in a scattering brain of a living adult transgenic zebrafish expressing GCaMP5G calcium indicator [7]. Fast changes in optoacoustic traces associated to GCaMP5G activity were detectable in the presence of other strongly absorbing endogenous chromophores, such as hemoglobin. The results indicate that the optoacoustic signal traces generally follow the GCaMP5G fluorescence dynamics and further enable overcoming the longstanding optical-diffusion penetration barrier associated to scattering in biological tissues [6]. The new functional optoacoustic neuroimaging method can visualize neural activity at penetration depths and spatio-temporal resolution scales not covered with the existing neuroimaging techniques. Thus, in addition to the well-established capacity of optoacoustics to resolve vascular anatomy and multiple hemodynamic parameters deep in scattering tissues, the newly developed methodology offers unprecedented capabilities for functional whole brain observations of fast calcium dynamics.

Neural correlates of the natural observation of an emotionally loaded video

PubMed Central

Gonzalez-Santos, Leopoldo

2018-01-01

Studies based on a paradigm of free or natural viewing have revealed characteristics that allow us to know how the brain processes stimuli within a natural environment. This method has been little used to study brain function. With a connectivity approach, we examine the processing of emotions using an exploratory method to analyze functional magnetic resonance imaging (fMRI) data. This research describes our approach to modeling stress paradigms suitable for neuroimaging environments. We showed a short film (4.54 minutes) with high negative emotional valence and high arousal content to 24 healthy male subjects (36.42 years old; SD = 12.14) during fMRI. Independent component analysis (ICA) was used to identify networks based on spatial statistical independence. Through this analysis we identified the sensorimotor system and its influence on the dorsal attention and default-mode networks, which in turn have reciprocal activity and modulate networks described as emotional. PMID:29883494

An Improved Representation of Regional Boundaries on Parcellated Morphological Surfaces

PubMed Central

Hao, Xuejun; Xu, Dongrong; Bansal, Ravi; Liu, Jun; Peterson, Bradley S.

2010-01-01

Establishing the correspondences of brain anatomy with function is important for understanding neuroimaging data. Regional delineations on morphological surfaces define anatomical landmarks and help to visualize and interpret both functional data and morphological measures mapped onto the cortical surface. We present an efficient algorithm that accurately delineates the morphological surface of the cerebral cortex in real time during generation of the surface using information from parcellated 3D data. With this accurate region delineation, we then develop methods for boundary-preserved simplification and smoothing, as well as procedures for the automated correction of small, misclassified regions to improve the quality of the delineated surface. We demonstrate that our delineation algorithm, together with a new method for double-snapshot visualization of cortical regions, can be used to establish a clear correspondence between brain anatomy and mapped quantities, such as morphological measures, across groups of subjects. PMID:21144708

Neuroimaging Techniques: a Conceptual Overview of Physical Principles, Contribution and History

NASA Astrophysics Data System (ADS)

Minati, Ludovico

2006-06-01

This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Given the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.

Motion artifact removal in FNIR spectroscopy for real-world applications

NASA Astrophysics Data System (ADS)

Devaraj, Ajit; Izzetoglu, Meltem; Izzetoglu, Kurtulus; Bunce, Scott C.; Li, Connie Y.; Onaral, Banu

2004-12-01

Near infrared spectroscopy as a neuroimaging modality is a recent development. Near infrared neuroimagers are typically safe, portable, relatively affordable and non-invasive. The ease of sensor setup and non-intrusiveness make functional near infrared (fNIR) imaging an ideal candidate for monitoring human cortical function in a wide range of real world situations. However optical signals are susceptible to motion-artifacts, hindering the application of fNIR in studies where subject mobility cannot be controlled. In this paper, we present a filtering framework for motion-artifact cancellation to facilitate the deployment of fNIR imaging in real-world scenarios. We simulate a generic field environment by having subjects walk on a treadmill while performing a cognitive task and demonstrate that measurements can be effectively cleaned of motion-artifacts.

Representation of the speech effectors in the human motor cortex: somatotopy or overlap?

PubMed

Takai, Osamu; Brown, Steven; Liotti, Mario

2010-04-01

Somatotopy within the orofacial region of the human motor cortex has been a central concept in interpreting the results of neuroimaging and transcranial magnetic stimulation studies of normal and disordered speech. Yet, somatotopy has been challenged by studies showing overlap among the effectors within the homunculus. In order to address this dichotomy, we performed four voxel-based meta-analyses of 54 functional neuroimaging studies of non-speech tasks involving respiration, lip movement, tongue movement, and swallowing, respectively. While the centers of mass of the clusters supported the classic homuncular view of the motor cortex, there was significant variability in the locations of the activation-coordinates among studies, resulting in an overlapping arrangement. This "somatotopy with overlap" might reflect the intrinsic functional interconnectedness of the oral effectors for speech production.

Changes in the central nervous system during long-duration space flight: implications for neuro-imaging

NASA Astrophysics Data System (ADS)

Newberg, A. B.; Alavi, A.

The purpose of this paper is to review the potential functional and morphological effects of long duration space flight on the human central nervous system (CNS) and how current neuroimaging techniques may be utilized to study these effects. It must be determined if there will be any detrimental changes to the CNS from long term exposure to the space environment if human beings are to plan interplanetary missions or establish permanent space habitats. Research to date has focused primarily on the short term changes in the CNS as the result of space flight. The space environment has many factors such as weightlessness, electromagnetic fields, and radiation, that may impact upon the function and structure of the CNS. CNS changes known to occur during and after long term space flight include neurovestibular disturbances, cephalic fluid shifts, alterations in sensory perception, changes in proprioception, psychological disturbances, and cognitive changes. Animal studies have shown altered plasticity of the neural cytoarchitecture, decreased neuronal metabolism in the hypothalamus, and changes in neurotransmitter concentrations. Recent progress in the ability to study brain morphology, cerebral metabolism, and neurochemistry in vivo in the human brain would provide ample opportunity to investigate many of the changes that occur in the CNS as a result of space flight. These methods include positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI).

Imaging in Pediatric Concussion: A Systematic Review.

PubMed

Schmidt, Julia; Hayward, Kathryn S; Brown, Katlyn E; Zwicker, Jill G; Ponsford, Jennie; van Donkelaar, Paul; Babul, Shelina; Boyd, Lara A

2018-05-01

Pediatric mild traumatic brain injury (mTBI) is a common and poorly understood injury. Neuroimaging indexes brain injury and outcome after pediatric mTBI, but remains largely unexplored. To investigate the differences in neuroimaging findings in children/youth with mTBI. Measures of behavior, symptoms, time since injury, and age at injury were also considered. A systematic review was conducted up to July 6, 2016. Studies were independently screened by 2 authors and included if they met predetermined eligibility criteria: (1) children/youth (5-18 years of age), (2) diagnosis of mTBI, and (3) use of neuroimaging. Two authors independently appraised study quality and extracted demographic and outcome data. Twenty-two studies met the eligibility criteria, involving 448 participants with mTBI (mean age = 12.7 years ± 2.8). Time postinjury ranged from 1 day to 5 years. Seven different neuroimaging methods were investigated in included studies. The most frequently used method, diffusion tensor imaging (41%), had heterogeneous findings with respect to the specific regions and tracts that showed group differences. However, group differences were observed in many regions containing the corticospinal tract, portions of the corpus callosum, or frontal white-matter regions; fractional anisotropy was increased in 88% of the studies. This review included a heterogeneous sample with regard to participant ages, time since injury, symptoms, and imaging methods which prevented statistical pooling/modelling. These data highlight essential priorities for future research (eg, common data elements) that are foundational to progress the understanding of pediatric concussion. Copyright © 2018 by the American Academy of Pediatrics.

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation.

PubMed

Eickhoff, Simon B; Nichols, Thomas E; Laird, Angela R; Hoffstaedter, Felix; Amunts, Katrin; Fox, Peter T; Bzdok, Danilo; Eickhoff, Claudia R

2016-08-15

Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Behavior, Sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

PubMed Central

Eickhoff, Simon B.; Nichols, Thomas E.; Laird, Angela R.; Hoffstaedter, Felix; Amunts, Katrin; Fox, Peter T.

2016-01-01

Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis. PMID:27179606

Behavioral Interpretations of Intrinsic Connectivity Networks

ERIC Educational Resources Information Center

Laird, Angela R.; Fox, P. Mickle; Eickhoff, Simon B.; Turner, Jessica A.; Ray, Kimberly L.; McKay, D. Reese; Glahn, David C.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.

2011-01-01

An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific…

[Gender differences in cognitive functions and influence of sex hormones].

PubMed

Torres, A; Gómez-Gil, E; Vidal, A; Puig, O; Boget, T; Salamero, M

2006-01-01

To review scientific evidence on gender differences in cognitive functions and influence of sex hormones on cognitive performance. Systematical search of related studies identified in Medline. Women outperform men on verbal fluency, perceptual speed tasks, fine motor skills, verbal memory and verbal learning. Men outperform women on visuospatial ability, mathematical problem solving and visual memory. No gender differences on attention and working memory are found. Researchers distinguish four methods to investigate hormonal influence on cognitive performance: a) patient with hormonal disorders; b) neuroimaging in individuals during hormone administration; c) in women during different phases of menstrual cycle, and d) in patients receiving hormonal treatment (idiopathic hypogonadotropic hypogonadism, postmenopausal women and transsexuals). The findings mostly suggest an influence of sex hormones on some cognitive functions, but they are not conclusive because of limitations and scarcity of the studies. There are gender differences on cognitive functions. Sex hormones seem to influence cognitive performance.

Genetic impact on cognition and brain function in newly diagnosed Parkinson’s disease: ICICLE-PD study

PubMed Central

Rowe, James B.; Winder-Rhodes, Sophie E.; Hampshire, Adam; Owen, Adrian M.; Breen, David P.; Duncan, Gordon W.; Khoo, Tien K.; Yarnall, Alison J.; Firbank, Michael J.; Chinnery, Patrick F.; Robbins, Trevor W.; O’Brien, John T.; Brooks, David J.; Burn, David J.; Barker, Roger A.

2014-01-01

Parkinson’s disease is associated with multiple cognitive impairments and increased risk of dementia, but the extent of these deficits varies widely among patients. The ICICLE-PD study was established to define the characteristics and prevalence of cognitive change soon after diagnosis, in a representative cohort of patients, using a multimodal approach. Specifically, we tested the ‘Dual Syndrome’ hypothesis for cognitive impairment in Parkinson’s disease, which distinguishes an executive syndrome (affecting the frontostriatal regions due to dopaminergic deficits) from a posterior cortical syndrome (affecting visuospatial, mnemonic and semantic functions related to Lewy body pathology and secondary cholinergic loss). An incident Parkinson’s disease cohort (n = 168, median 8 months from diagnosis to participation) and matched control group (n = 85) were recruited to a neuroimaging study at two sites in the UK. All participants underwent clinical, neuropsychological and functional magnetic resonance imaging assessments. The three neuroimaging tasks (Tower of London, Spatial Rotations and Memory Encoding Tasks) were designed to probe executive, visuospatial and memory encoding domains, respectively. Patients were also genotyped for three polymorphisms associated with cognitive change in Parkinson’s disease and related disorders: (i) rs4680 for COMT Val158Met polymorphism; (ii) rs9468 for MAPT H1 versus H2 haplotype; and (iii) rs429358 for APOE-ε2, 3, 4. We identified performance deficits in all three cognitive domains, which were associated with regionally specific changes in cortical activation. Task-specific regional activations in Parkinson’s disease were linked with genetic variation: the rs4680 polymorphism modulated the effect of levodopa therapy on planning-related activations in the frontoparietal network; the MAPT haplotype modulated parietal activations associated with spatial rotations; and APOE allelic variation influenced the magnitude of activation associated with memory encoding. This study demonstrates that neurocognitive deficits are common even in recently diagnosed patients with Parkinson’s disease, and that the associated regional brain activations are influenced by genotype. These data further support the dual syndrome hypothesis of cognitive change in Parkinson’s disease. Longitudinal data will confirm the extent to which these early neurocognitive changes, and their genetic factors, influence the long-term risk of dementia in Parkinson’s disease. The combination of genetics and functional neuroimaging provides a potentially useful method for stratification and identification of candidate markers, in future clinical trials against cognitive decline in Parkinson’s disease. PMID:25080285

Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data.

PubMed

Grootswagers, Tijl; Wardle, Susan G; Carlson, Thomas A

2017-04-01

Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain-computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to "decode" different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

Neurobiology of Dyslexia

PubMed Central

Norton, Elizabeth S.; Beach, Sara D.; Gabrieli, John D. E.

2014-01-01

Dyslexia is one of the most common learning disabilities, yet its brain basis and core causes are not yet fully understood. Neuroimaging methods, including structural and functional magnetic resonance imaging, diffusion tensor imaging, and electrophysiology, have significantly contributed to knowledge about the neurobiology of dyslexia. Recent studies have discovered brain differences prior to formal instruction that likely encourage or discourage learning to read effectively, distinguished between brain differences that likely reflect the etiology of dyslexia versus brain differences that are the consequences of variation in reading experience, and identified distinct neural networks associated with specific psychological factors that are associated with dyslexia. PMID:25290881

Confidence intervals for differences between volumes under receiver operating characteristic surfaces (VUS) and generalized Youden indices (GYIs).

PubMed

Yin, Jingjing; Nakas, Christos T; Tian, Lili; Reiser, Benjamin

2018-03-01

This article explores both existing and new methods for the construction of confidence intervals for differences of indices of diagnostic accuracy of competing pairs of biomarkers in three-class classification problems and fills the methodological gaps for both parametric and non-parametric approaches in the receiver operating characteristic surface framework. The most widely used such indices are the volume under the receiver operating characteristic surface and the generalized Youden index. We describe implementation of all methods and offer insight regarding the appropriateness of their use through a large simulation study with different distributional and sample size scenarios. Methods are illustrated using data from the Alzheimer's Disease Neuroimaging Initiative study, where assessment of cognitive function naturally results in a three-class classification setting.

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

ERIC Educational Resources Information Center

Van Lancker Sidtis, Diana

2007-01-01

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

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 providing a useful way to conceptualize and measure task noncompliance and by providing simple cost effective tactics for improving the effectiveness of common reward-based protocols.

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

The role of the amygdala in the pathophysiology of panic disorder: evidence from neuroimaging studies

PubMed Central

2012-01-01

Although the neurobiological mechanisms underlying panic disorder (PD) are not yet clearly understood, increasing amount of evidence from animal and human studies suggests that the amygdala, which plays a pivotal role in neural network of fear and anxiety, has an important role in the pathogenesis of PD. This article aims to (1) review the findings of structural, chemical, and functional neuroimaging studies on PD, (2) relate the amygdala to panic attacks and PD development, (3) discuss the possible causes of amygdalar abnormalities in PD, (4) and suggest directions for future research. PMID:23168129

Internet and gaming addiction: a systematic literature review of neuroimaging studies.

PubMed

Kuss, Daria J; Griffiths, Mark D

2012-09-05

In the past decade, research has accumulated suggesting that excessive Internet use can lead to the development of a behavioral addiction. Internet addiction has been considered as a serious threat to mental health and the excessive use of the Internet has been linked to a variety of negative psychosocial consequences. The aim of this review is to identify all empirical studies to date that used neuroimaging techniques to shed light upon the emerging mental health problem of Internet and gaming addiction from a neuroscientific perspective. Neuroimaging studies offer an advantage over traditional survey and behavioral research because with this method, it is possible to distinguish particular brain areas that are involved in the development and maintenance of addiction. A systematic literature search was conducted, identifying 18 studies. These studies provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet and gaming addiction, on a variety of levels. On the molecular level, Internet addiction is characterized by an overall reward deficiency that entails decreased dopaminergic activity. On the level of neural circuitry, Internet and gaming addiction led to neuroadaptation and structural changes that occur as a consequence of prolonged increased activity in brain areas associated with addiction. On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their cognitive functioning in various domains. The paper shows that understanding the neuronal correlates associated with the development of Internet and gaming addiction will promote future research and will pave the way for the development of addiction treatment approaches.

Internet and Gaming Addiction: A Systematic Literature Review of Neuroimaging Studies

PubMed Central

Kuss, Daria J.; Griffiths, Mark D.

2012-01-01

In the past decade, research has accumulated suggesting that excessive Internet use can lead to the development of a behavioral addiction. Internet addiction has been considered as a serious threat to mental health and the excessive use of the Internet has been linked to a variety of negative psychosocial consequences. The aim of this review is to identify all empirical studies to date that used neuroimaging techniques to shed light upon the emerging mental health problem of Internet and gaming addiction from a neuroscientific perspective. Neuroimaging studies offer an advantage over traditional survey and behavioral research because with this method, it is possible to distinguish particular brain areas that are involved in the development and maintenance of addiction. A systematic literature search was conducted, identifying 18 studies. These studies provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet and gaming addiction, on a variety of levels. On the molecular level, Internet addiction is characterized by an overall reward deficiency that entails decreased dopaminergic activity. On the level of neural circuitry, Internet and gaming addiction led to neuroadaptation and structural changes that occur as a consequence of prolonged increased activity in brain areas associated with addiction. On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their cognitive functioning in various domains. The paper shows that understanding the neuronal correlates associated with the development of Internet and gaming addiction will promote future research and will pave the way for the development of addiction treatment approaches. PMID:24961198

Transdiagnostic dimensions of anxiety: Neural mechanisms, executive functions, and new directions.

PubMed

Sharp, Paul B; Miller, Gregory A; Heller, Wendy

2015-11-01

Converging neuroscientific and psychological evidence points to several transdiagnostic factors that cut across DSM-defined disorders, which both affect and are affected by executive dysfunction. Two of these factors, anxious apprehension and anxious arousal, have helped bridge the gap between psychological and neurobiological models of anxiety. The present integration of diverse findings advances an understanding of the relationships between these transdiagnostic anxiety dimensions, their interactions with each other and executive function, and their neural mechanisms. Additionally, a discussion is provided concerning how these constructs fit within the Research Domain Criteria (RDoC) matrix developed by the National Institutes of Mental Health and how they relate to other anxiety constructs studied with different methods and at other units of analysis. Suggestions for future research are offered, including how to (1) improve measurement and delineation of these constructs, (2) use new neuroimaging methods and theoretical approaches of how the brain functions to build neural mechanistic models of these constructs, and (3) advance understanding of the relationships of these constructs to diverse emotional phenomena and executive functions. Copyright © 2015 Elsevier B.V. All rights reserved.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review.

PubMed

Kamran, Muhammad A; Mannan, Malik M Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review

PubMed Central

Kamran, Muhammad A.; Mannan, Malik M. Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized. PMID:27375458

Neuroimaging studies of acute effects of THC and CBD in humans and animals: a systematic review.

PubMed

Batalla, A; Crippa, J A; Busatto, G F; Guimaraes, F S; Zuardi, A W; Valverde, O; Atakan, Z; McGuire, P K; Bhattacharyya, S; Martín-Santos, R

2014-01-01

In recent years, growing concerns about the effects of cannabis use on mental health have renewed interest in cannabis research. In particular, there has been a marked increase in the number of neuroimaging studies of the effects of cannabinoids. We conducted a systematic review to assess the impact of acute cannabis exposure on brain function in humans and in experimental animals. Papers published until June 2012 were included from EMBASE, Medline, PubMed and LILACS databases following a comprehensive search strategy and pre-determined set of criteria for article selection. Only pharmacological challenge studies involving the acute experimental administration of cannabinoids in occasional or naïve cannabis users, and naïve animals were considered. Two hundred and twenty-four studies were identified, of which 45 met our inclusion criteria. Twenty-four studies were in humans and 21 in animals. Most comprised studies of the acute effects of cannabinoids on brain functioning in the context of either resting state activity or activation during cognitive paradigms. In general, THC and CBD had opposite neurophysiological effects. There were also a smaller number of neurochemical imaging studies: overall, these did not support a central role for increased dopaminergic activity in THC-induced psychosis. There was a considerable degree of methodological heterogeneity in the imaging literature reviewed. Functional neuroimaging studies have provided extensive evidence for the acute modulation of brain function by cannabinoids, but further studies are needed in order to understand the neural mechanisms underlying these effects. Future studies should also consider the need for more standardised methodology and the replication of findings.

Elevated Amygdala Response to Faces following Early Deprivation

ERIC Educational Resources Information Center

Tottenham, N.; Hare, T. A.; Millner, A.; Gilhooly, T.; Zevin, J. D.; Casey, B. J.

2011-01-01

A functional neuroimaging study examined the long-term neural correlates of early adverse rearing conditions in humans as they relate to socio-emotional development. Previously institutionalized (PI) children and a same-aged comparison group were scanned using functional magnetic resonance imaging (fMRI) while performing an Emotional Face Go/Nogo…

Functional Brain Network Abnormalities during Verbal Working Memory Performance in Adolescents and Young Adults with Dyslexia

ERIC Educational Resources Information Center

Wolf, Robert Christian; Sambataro, Fabio; Lohr, Christina; Steinbrink, Claudia; Martin, Claudia; Vasic, Nenad

2010-01-01

Behavioral and functional neuroimaging studies indicate deficits in verbal working memory (WM) and frontoparietal dysfunction in individuals with dyslexia. Additionally, structural brain abnormalities in dyslexics suggest a dysconnectivity of brain regions associated with phonological processing. However, little is known about the functional…

Functional Neuroimaging of Social and Nonsocial Cognitive Control in Autism

ERIC Educational Resources Information Center

Sabatino, Antoinette; Rittenberg, Alison; Sasson, Noah J.; Turner-Brown, Lauren; Bodfish, James W.; Dichter, Gabriel S.

2013-01-01

This study investigated cognitive control of social and nonsocial information in autism using functional magnetic resonance imaging. Individuals with autism spectrum disorders (ASDs) and a neurotypical control group completed an oddball target detection task where target stimuli were either faces or nonsocial objects previously shown to be related…

Syntactic Processing in Bilinguals: An fNIRS Study

ERIC Educational Resources Information Center

Scherer, Lilian Cristine; Fonseca, Rochele Paz; Amiri, Mahnoush; Adrover-Roig, Daniel; Marcotte, Karine; Giroux, Francine; Senhadji, Noureddine; Benali, Habib; Lesage, Frederic; Ansaldo, Ana Ines

2012-01-01

The study of the neural basis of syntactic processing has greatly benefited from neuroimaging techniques. Research on syntactic processing in bilinguals has used a variety of techniques, including mainly functional magnetic resonance imaging (fMRI) and event-related potentials (ERP). This paper reports on a functional near-infrared spectroscopy…

Prefrontal Brain Activity Predicts Temporally Extended Decision-Making Behavior

ERIC Educational Resources Information Center

Yarkoni, Tal; Braver, Todd S.; Gray, Jeremy R.; Green, Leonard

2005-01-01

Although functional neuroimaging studies of human decision-making processes are increasingly common, most of the research in this area has relied on passive tasks that generate little individual variability. Relatively little attention has been paid to the ability of brain activity to predict overt behavior. Using functional magnetic resonance…

Source counting in MEG neuroimaging

NASA Astrophysics Data System (ADS)

Lei, Tianhu; Dell, John; Magee, Ralphy; Roberts, Timothy P. L.

2009-02-01

Magnetoencephalography (MEG) is a multi-channel, functional imaging technique. It measures the magnetic field produced by the primary electric currents inside the brain via a sensor array composed of a large number of superconducting quantum interference devices. The measurements are then used to estimate the locations, strengths, and orientations of these electric currents. This magnetic source imaging technique encompasses a great variety of signal processing and modeling techniques which include Inverse problem, MUltiple SIgnal Classification (MUSIC), Beamforming (BF), and Independent Component Analysis (ICA) method. A key problem with Inverse problem, MUSIC and ICA methods is that the number of sources must be detected a priori. Although BF method scans the source space on a point-to-point basis, the selection of peaks as sources, however, is finally made by subjective thresholding. In practice expert data analysts often select results based on physiological plausibility. This paper presents an eigenstructure approach for the source number detection in MEG neuroimaging. By sorting eigenvalues of the estimated covariance matrix of the acquired MEG data, the measured data space is partitioned into the signal and noise subspaces. The partition is implemented by utilizing information theoretic criteria. The order of the signal subspace gives an estimate of the number of sources. The approach does not refer to any model or hypothesis, hence, is an entirely data-led operation. It possesses clear physical interpretation and efficient computation procedure. The theoretical derivation of this method and the results obtained by using the real MEG data are included to demonstrates their agreement and the promise of the proposed approach.

Toward a functional near-infrared spectroscopy-based monitoring of pain assessment for nonverbal patients

NASA Astrophysics Data System (ADS)

Fernandez Rojas, Raul; Huang, Xu; Ou, Keng-Liang

2017-10-01

Pain diagnosis for nonverbal patients represents a challenge in clinical settings. Neuroimaging methods, such as functional magnetic resonance imaging and functional near-infrared spectroscopy (fNIRS), have shown promising results to assess neuronal function in response to nociception and pain. Recent studies suggest that neuroimaging in conjunction with machine learning models can be used to predict different cognitive tasks. The aim of this study is to expand previous studies by exploring the classification of fNIRS signals (oxyhaemoglobin) according to temperature level (cold and hot) and corresponding pain intensity (low and high) using machine learning models. Toward this aim, we used the quantitative sensory testing to determine pain threshold and pain tolerance to cold and heat in 18 healthy subjects (three females), mean age±standard deviation (31.9±5.5). The classification model is based on the bag-of-words approach, a histogram representation used in document classification based on the frequencies of extracted words and adapted for time series; two learning algorithms were used separately, K-nearest neighbor (K-NN) and support vector machines (SVM). A comparison between two sets of fNIRS channels was also made in the classification task, all 24 channels and 8 channels from the somatosensory region defined as our region of interest (RoI). The results showed that K-NN obtained slightly better results (92.08%) than SVM (91.25%) using the 24 channels; however, the performance slightly dropped using only channels from the RoI with K-NN (91.53%) and SVM (90.83%). These results indicate potential applications of fNIRS in the development of a physiologically based diagnosis of human pain that would benefit vulnerable patients who cannot self-report pain.

Cortical morphology as a shared neurobiological substrate of attention-deficit/hyperactivity symptoms and executive functioning: a population-based pediatric neuroimaging study

PubMed Central

Mous, Sabine E.; White, Tonya; Muetzel, Ryan L.; El Marroun, Hanan; Rijlaarsdam, Jolien; Polderman, Tinca J.C.; Jaddoe, Vincent W.; Verhulst, Frank C.; Posthuma, Danielle; Tiemeier, Henning

2017-01-01

Background Attention-deficit/hyperactivity symptoms have repeatedly been associated with poor cognitive functioning. Genetic studies have demonstrated a shared etiology of attention-deficit/hyperactivity disorder (ADHD) and cognitive ability, suggesting a common underlying neurobiology of ADHD and cognition. Further, neuroimaging studies suggest that altered cortical development is related to ADHD. In a large population-based sample we investigated whether cortical morphology, as a potential neurobiological substrate, underlies the association between attention-deficit/hyperactivity symptoms and cognitive problems. Methods The sample consisted of school-aged children with data on attention-deficit/hyperactivity symptoms, cognitive functioning and structural imaging. First, we investigated the association between attention-deficit/hyperactivity symptoms and different domains of cognition. Next, we identified cortical correlates of attention-deficit/hyperactivity symptoms and related cognitive domains. Finally, we studied the role of cortical thickness and gyrification in the behaviour–cognition associations. Results We included 776 children in our analyses. We found that attention-deficit/hyperactivity symptoms were associated specifically with problems in attention and executive functioning (EF; b = −0.041, 95% confidence interval [CI] −0.07 to −0.01, p = 0.004). Cortical thickness and gyrification were associated with both attention-deficit/hyperactivity symptoms and EF in brain regions that have been previously implicated in ADHD. This partly explained the association between attention-deficit/hyperactivity symptoms and EF (bindirect = −0.008, bias-corrected 95% CI −0.018 to −0.001). Limitations The nature of our study did not allow us to draw inferences regarding temporal associations; longitudinal studies are needed for clarification. Conclusion In a large, population-based sample of children, we identified a shared cortical morphology underlying attention-deficit/hyperactivity symptoms and EF. PMID:27673503

Using functional neuroimaging combined with a think-aloud protocol to explore clinical reasoning expertise in internal medicine.

PubMed

Durning, Steven J; Graner, John; Artino, Anthony R; Pangaro, Louis N; Beckman, Thomas; Holmboe, Eric; Oakes, Terrance; Roy, Michael; Riedy, Gerard; Capaldi, Vincent; Walter, Robert; van der Vleuten, Cees; Schuwirth, Lambert

2012-09-01

Clinical reasoning is essential to medical practice, but because it entails internal mental processes, it is difficult to assess. Functional magnetic resonance imaging (fMRI) and think-aloud protocols may improve understanding of clinical reasoning as these methods can more directly assess these processes. The objective of our study was to use a combination of fMRI and think-aloud procedures to examine fMRI correlates of a leading theoretical model in clinical reasoning based on experimental findings to date: analytic (i.e., actively comparing and contrasting diagnostic entities) and nonanalytic (i.e., pattern recognition) reasoning. We hypothesized that there would be functional neuroimaging differences between analytic and nonanalytic reasoning theory. 17 board-certified experts in internal medicine answered and reflected on validated U.S. Medical Licensing Exam and American Board of Internal Medicine multiple-choice questions (easy and difficult) during an fMRI scan. This procedure was followed by completion of a formal think-aloud procedure. fMRI findings provide some support for the presence of analytic and nonanalytic reasoning systems. Statistically significant activation of prefrontal cortex distinguished answering incorrectly versus correctly (p < 0.01), whereas activation of precuneus and midtemporal gyrus distinguished not guessing from guessing (p < 0.01). We found limited fMRI evidence to support analytic and nonanalytic reasoning theory, as our results indicate functional differences with correct vs. incorrect answers and guessing vs. not guessing. However, our findings did not suggest one consistent fMRI activation pattern of internal medicine expertise. This model of employing fMRI correlates offers opportunities to enhance our understanding of theory, as well as improve our teaching and assessment of clinical reasoning, a key outcome of medical education.

Platform for systems medicine research and diagnostic applications in psychotic disorders-The METSY project.

PubMed

Frank, Elisabeth; Maier, Dieter; Pajula, Juha; Suvitaival, Tommi; Borgan, Faith; Butz-Ostendorf, Markus; Fischer, Alexander; Hietala, Jarmo; Howes, Oliver; Hyötyläinen, Tuulia; Janssen, Joost; Laurikainen, Heikki; Moreno, Carmen; Suvisaari, Jaana; Van Gils, Mark; Orešič, Matej

2018-04-01

Psychotic disorders are associated with metabolic abnormalities including alterations in glucose and lipid metabolism. A major challenge in the treatment of psychosis is to identify patients with vulnerable metabolic profiles who may be at risk of developing cardiometabolic co-morbidities. It is established that both central and peripheral metabolic organs use lipids to control energy balance and regulate peripheral insulin sensitivity. The endocannabinoid system, implicated in the regulation of glucose and lipid metabolism, has been shown to be dysregulated in psychosis. It is currently unclear how these endocannabinoid abnormalities relate to metabolic changes in psychosis. Here we review recent research in the field of metabolic co-morbidities in psychotic disorders as well as the methods to study them and potential links to the endocannabinoid system. We also describe the bioinformatics platforms developed in the EU project METSY for the investigations of the biological etiology in patients at risk of psychosis and in first episode psychosis patients. The METSY project was established with the aim to identify and evaluate multi-modal peripheral and neuroimaging markers that may be able to predict the onset and prognosis of psychiatric and metabolic symptoms in patients at risk of developing psychosis and first episode psychosis patients. Given the intrinsic complexity and widespread role of lipid metabolism, a systems biology approach which combines molecular, structural and functional neuroimaging methods with detailed metabolic characterisation and multi-variate network analysis is essential in order to identify how lipid dysregulation may contribute to psychotic disorders. A decision support system, integrating clinical, neuropsychological and neuroimaging data, was also developed in order to aid clinical decision making in psychosis. Knowledge of common and specific mechanisms may aid the etiopathogenic understanding of psychotic and metabolic disorders, facilitate early disease detection, aid treatment selection and elucidate new targets for pharmacological treatments. Copyright © 2017. Published by Elsevier Masson SAS.

Robust Identification of Alzheimer's Disease subtypes based on cortical atrophy patterns.

PubMed

Park, Jong-Yun; Na, Han Kyu; Kim, Sungsoo; Kim, Hyunwook; Kim, Hee Jin; Seo, Sang Won; Na, Duk L; Han, Cheol E; Seong, Joon-Kyung

2017-03-09

Accumulating evidence suggests that Alzheimer's disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset. Our method categorized very mild AD into three clinically distinct subtypes with high reproducibility (>90%); the parietal-predominant (P), medial temporal-predominant (MT), and diffuse (D) atrophy subtype. The P subtype showed the worst clinical presentation throughout the cognitive domains, while the MT and D subtypes exhibited relatively mild presentation. The MT subtype revealed more impaired language and executive function compared to the D subtype.

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

NASA Astrophysics Data System (ADS)

Park, Jong-Yun; Na, Han Kyu; Kim, Sungsoo; Kim, Hyunwook; Kim, Hee Jin; Seo, Sang Won; Na, Duk L.; Han, Cheol E.; Seong, Joon-Kyung; Weiner, Michael; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowki, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Shaw, Leslie M.; Liu, Enchi; Montine, Tom; Thomas, Ronald G.; Donohue, Michael; Walter, Sarah; Gessert, Devon; Sather, Tamie; Jiminez, Gus; Harvey, Danielle; Bernstein, Matthew; Fox, Nick; Thompson, Paul; Schuff, Norbert; Decarli, Charles; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Koeppe, Robert A.; Foster, Norm; Reiman, Eric M.; Chen, Kewei; Mathis, Chet; Landau, Susan; Cairns, Nigel J.; Householder, Erin; Taylor Reinwald, Lisa; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Crawford, Karen; Neu, Scott; Foroud, Tatiana M.; Potkin, Steven G.; Shen, Li; Kelley, Faber; Kim, Sungeun; Nho, Kwangsik; Kachaturian, Zaven; Frank, Richard; Snyder, Peter J.; Molchan, Susan; Kaye, Jeffrey; Quinn, Joseph; Lind, Betty; Carter, Raina; Dolen, Sara; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Fleisher, Adam; Heidebrink, Judith L.; Lord, Joanne L.; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Doody, Rachelle S.; Villanueva Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Ances, Beau; Carroll, Maria; Leon, Sue; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Grossman, Hillel; Mitsis, Effie; de Toledo-Morrell, Leyla; Shah, Raj C.; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Albert, Marilyn; Onyike, Chiadi; D'Agostino, Daniel, II; Kielb, Stephanie; Galvin, James E.; Pogorelec, Dana M.; Cerbone, Brittany; Michel, Christina A.; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; de Santi, Susan; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Wong, Terence Z.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Lopez, Oscar L.; Oakley, Maryann; Simpson, Donna M.; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc Adams Ortiz, Catherine; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Diaz Arrastia, Ramon; King, Richard; Weiner, Myron; Martin Cook, Kristen; Devous, Michael; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Anderson, Heather S.; Swerdlow, Russell H.; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H. S.; Lu, Po H.; Bartzokis, George; Graff Radford, Neill R.; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Farlow, Martin R.; Marie Hake, Ann; Matthews, Brandy R.; Herring, Scott; Hunt, Cynthia; van Dyck, Christopher H.; Carson, Richard E.; Macavoy, Martha G.; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging Yuek; Feldman, Howard; Mudge, Benita; Assaly, Michele; Trost, Dick; Bernick, Charles; Munic, Donna; Kerwin, Diana; Marsel Mesulam, Marek; Lipowski, Kristine; Kuo Wu, Chuang; Johnson, Nancy; Sadowsky, Carl; Martinez, Walter; Villena, Teresa; Scott Turner, Raymond; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Frey, Meghan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan N.; Belden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Lynn Johnson, Patricia; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Hudson, Leon; Fletcher, Evan; Carmichael, Owen; Olichney, John; Kittur, Smita; Borrie, Michael; Lee, T. Y.; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Santulli, Robert B.; Kitzmiller, Tamar J.; Schwartz, Eben S.; Sink, Kaycee M.; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Mintzer, Jacobo; Spicer, Kenneth; Bachman, David; Finger, Elizabether; Pasternak, Stephen; Rachinsky, Irina; Rogers, John; Kertesz, Andrew; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Smith, Karen Elizabeth; Relkin, Norman; Chaing, Gloria; Raudin, Lisa; Smith, Amanda; Fargher, Kristin; Raj, Balebail Ashok

2017-03-01

Accumulating evidence suggests that Alzheimer’s disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset. Our method categorized very mild AD into three clinically distinct subtypes with high reproducibility (>90%) the parietal-predominant (P), medial temporal-predominant (MT), and diffuse (D) atrophy subtype. The P subtype showed the worst clinical presentation throughout the cognitive domains, while the MT and D subtypes exhibited relatively mild presentation. The MT subtype revealed more impaired language and executive function compared to the D subtype.

Theory and methods in cultural neuroscience

PubMed Central

Hariri, Ahmad R.; Harada, Tokiko; Mano, Yoko; Sadato, Norihiro; Parrish, Todd B.; Iidaka, Tetsuya

2010-01-01

Cultural neuroscience is an emerging research discipline that investigates cultural variation in psychological, neural and genomic processes as a means of articulating the bidirectional relationship of these processes and their emergent properties. Research in cultural neuroscience integrates theory and methods from anthropology, cultural psychology, neuroscience and neurogenetics. Here, we review a set of core theoretical and methodological challenges facing researchers when planning and conducting cultural neuroscience studies, and provide suggestions for overcoming these challenges. In particular, we focus on the problems of defining culture and culturally appropriate experimental tasks, comparing neuroimaging data acquired from different populations and scanner sites and identifying functional genetic polymorphisms relevant to culture. Implications of cultural neuroscience research for addressing current issues in population health disparities are discussed. PMID:20592044

Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model

PubMed Central

Abdelnour, A. Farras; Huppert, Theodore

2009-01-01

Near-infrared spectroscopy is a non-invasive neuroimaging method which uses light to measure changes in cerebral blood oxygenation associated with brain activity. In this work, we demonstrate the ability to record and analyze images of brain activity in real-time using a 16-channel continuous wave optical NIRS system. We propose a novel real-time analysis framework using an adaptive Kalman filter and a state–space model based on a canonical general linear model of brain activity. We show that our adaptive model has the ability to estimate single-trial brain activity events as we apply this method to track and classify experimental data acquired during an alternating bilateral self-paced finger tapping task. PMID:19457389

Non-invasive neuroimaging using near-infrared light

NASA Technical Reports Server (NTRS)

Strangman, Gary; Boas, David A.; Sutton, Jeffrey P.

2002-01-01

This article reviews diffuse optical brain imaging, a technique that employs near-infrared light to non-invasively probe the brain for changes in parameters relating to brain function. We describe the general methodology, including types of measurements and instrumentation (including the tradeoffs inherent in the various instrument components), and the basic theory required to interpret the recorded data. A brief review of diffuse optical applications is included, with an emphasis on research that has been done with psychiatric populations. Finally, we discuss some practical issues and limitations that are relevant when conducting diffuse optical experiments. We find that, while diffuse optics can provide substantial advantages to the psychiatric researcher relative to the alternative brain imaging methods, the method remains substantially underutilized in this field.

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

The hearing ear is always found close to the speaking tongue: Review of the role of the motor system in speech perception.

PubMed

Skipper, Jeremy I; Devlin, Joseph T; Lametti, Daniel R

2017-01-01

Does "the motor system" play "a role" in speech perception? If so, where, how, and when? We conducted a systematic review that addresses these questions using both qualitative and quantitative methods. The qualitative review of behavioural, computational modelling, non-human animal, brain damage/disorder, electrical stimulation/recording, and neuroimaging research suggests that distributed brain regions involved in producing speech play specific, dynamic, and contextually determined roles in speech perception. The quantitative review employed region and network based neuroimaging meta-analyses and a novel text mining method to describe relative contributions of nodes in distributed brain networks. Supporting the qualitative review, results show a specific functional correspondence between regions involved in non-linguistic movement of the articulators, covertly and overtly producing speech, and the perception of both nonword and word sounds. This distributed set of cortical and subcortical speech production regions are ubiquitously active and form multiple networks whose topologies dynamically change with listening context. Results are inconsistent with motor and acoustic only models of speech perception and classical and contemporary dual-stream models of the organization of language and the brain. Instead, results are more consistent with complex network models in which multiple speech production related networks and subnetworks dynamically self-organize to constrain interpretation of indeterminant acoustic patterns as listening context requires. Copyright © 2016. Published by Elsevier Inc.

Thalamic Mechanisms in Language: A Reconsideration Based on Recent Findings and Concepts

PubMed Central

Crosson, Bruce

2012-01-01

Recent literature on thalamic aphasia and thalamic activity during neuroimaging is selectively reviewed followed by a consideration of recent anatomic and physiological findings regarding thalamic structure and functions. It is concluded that four related corticothalamic and/or thalamocortical mechanisms impact language processing: (1) selective engagement of task-relevant cortical areas in a heightened state of responsiveness in part through the nucleus reticularis (NR), (2) passing information from one cortical area to another through corticothalamo-cortical mechanisms, (3) sharpening the focus on task-relevant information through corticothalamo-cortical feedback mechanisms, and (4) selection of one language unit over another in the expression of a concept, accomplished in concert with basal ganglia loops. The relationship and interaction of these mechanisms is discussed and integrated with thalamic aphasia and neuroimaging data into a theory of thalamic functions in language. PMID:22831779

Neuroimaging in aphasia treatment research: Standards for establishing the effects of treatment

PubMed Central

Kiran, Swathi; Ansaldo, Ana; Bastiaanse, Roelien; Cherney, Leora R.; Howard, David; Faroqi-Shah, Yasmeen; Meinzer, Marcus; Thompson, Cynthia K

2012-01-01

The goal of this paper is to discuss experimental design options available for establishing the effects of treatment in studies that aim to examine the neural mechanisms associated with treatment-induced language recovery in aphasia, using functional magnetic resonance imaging (fMRI). We present both group and single-subject experimental or case-series design options for doing this and address advantages and disadvantages of each. We also discuss general components of and requirements for treatment research studies, including operational definitions of variables, criteria for defining behavioral change and treatment efficacy, and reliability of measurement. Important considerations that are unique to neuroimaging-based treatment research are addressed, pertaining to the relation between the selected treatment approach and anticipated changes in language processes/functions and how such changes are hypothesized to map onto the brain. PMID:23063559

Immune function and brain abnormalities in patients with systemic lupus erythematosus without overt neuropsychiatric manifestations.

PubMed

Kozora, E; Filley, C M; Zhang, L; Brown, M S; Miller, D E; Arciniegas, D B; Pelzman, J L; West, S G

2012-04-01

This study examined the relationship between immune, cognitive and neuroimaging assessments in subjects with systemic lupus erythematosus (SLE) without histories of overt neuropsychiatric (NP) disorders. In total, 84 subjects with nonNPSLE and 37 healthy controls completed neuropsychological testing from the American College of Rheumatology SLE battery. Serum autoantibody and cytokine measures, volumetric magnetic resonance imaging, and magnetic resonance spectroscopy data were collected on a subset of subjects. NonNPSLE subjects had lower scores on measures of visual/complex attention, visuomotor speed and verbal memory compared with controls. No clinically significant differences between nonNPSLE patients and controls were found on serum measures of lupus anticoagulant, anticardiolipin antibodies, beta 2-glycoproteins, or pro-inflammatory cytokines (interleukin (IL)-1, IL-6, interferon alpha (IFN-alpha), and interferon gamma (IFN-gamma)). Higher scores on a global cognitive impairment index and a memory impairment index were correlated with lower IFN-alpha. Few associations between immune functions and neuroimaging parameters were found. Results indicated that nonNPSLE patients demonstrated cognitive impairment but not immune differences compared with controls. In these subjects, who were relatively young and with mild disease, no relationship between cognitive dysfunction, immune parameters, or previously documented neuroimaging abnormalities were noted. Immune measures acquired from cerebrospinal fluid instead of serum may yield stronger associations.

Variational Bayesian Parameter Estimation Techniques for the General Linear Model

PubMed Central

Starke, Ludger; Ostwald, Dirk

2017-01-01

Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation techniques are rarely covered in introductory statistical texts. Because of the widespread practical use of VB, VML, ReML, and ML in the neuroimaging community, we reasoned that a theoretical treatment of their relationships and their application in a basic modeling scenario may be helpful for both neuroimaging novices and practitioners alike. In this technical study, we thus revisit the conceptual and formal underpinnings of VB, VML, ReML, and ML and provide a detailed account of their mathematical relationships and implementational details. We further apply VB, VML, ReML, and ML to the general linear model (GLM) with non-spherical error covariance as commonly encountered in the first-level analysis of fMRI data. To this end, we explicitly derive the corresponding free energy objective functions and ensuing iterative algorithms. Finally, in the applied part of our study, we evaluate the parameter and model recovery properties of VB, VML, ReML, and ML, first in an exemplary setting and then in the analysis of experimental fMRI data acquired from a single participant under visual stimulation. PMID:28966572

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.

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data

PubMed Central

Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F

2007-01-01

Background Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. Results We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: . Conclusion MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine. PMID:17937818

Working memory deficits in high-functioning adolescents with autism spectrum disorders: neuropsychological and neuroimaging correlates.

PubMed

Barendse, Evelien M; Hendriks, Marc Ph; Jansen, Jacobus Fa; Backes, Walter H; Hofman, Paul Am; Thoonen, Geert; Kessels, Roy Pc; Aldenkamp, Albert P

2013-06-04

Working memory is a temporary storage system under attentional control. It is believed to play a central role in online processing of complex cognitive information and may also play a role in social cognition and interpersonal interactions. Adolescents with a disorder on the autism spectrum display problems in precisely these domains. Social impairments, communication difficulties, and repetitive interests and activities are core domains of autism spectrum disorders (ASD), and executive function problems are often seen throughout the spectrum. As the main cognitive theories of ASD, including the theory of mind deficit hypotheses, weak central coherence account, and the executive dysfunction theory, still fail to explain the broad spectrum of symptoms, a new perspective on the etiology of ASD is needed. Deficits in working memory are central to many theories of psychopathology, and are generally linked to frontal-lobe dysfunction. This article will review neuropsychological and (functional) brain imaging studies on working memory in adolescents with ASD. Although still disputed, it is concluded that within the working memory system specific problems of spatial working memory are often seen in adolescents with ASD. These problems increase when information is more complex and greater demands on working memory are made. Neuroimaging studies indicate a more global working memory processing or connectivity deficiency, rather than a focused deficit in the prefrontal cortex. More research is needed to relate these working memory difficulties and neuroimaging results in ASD to the behavioral difficulties as seen in individuals with a disorder on the autism spectrum.

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data.

PubMed

Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F

2007-10-15

Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: http://sig.biostr.washington.edu/projects/MindSeer. MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine.

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

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

PubMed Central

Auer, Tibor; Churchill, Nathan W.; Flandin, Guillaume; Guntupalli, J. Swaroop; Raffelt, David; Quirion, Pierre-Olivier; Smith, Robert E.; Strother, Stephen C.; Varoquaux, Gaël

2017-01-01

The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms. PMID:28278228

Contribution of the posterior parietal cortex in reaching, grasping, and using objects and tools

PubMed Central

Vingerhoets, Guy

2014-01-01

Neuropsychological and neuroimaging data suggest a differential contribution of posterior parietal regions during the different components of a transitive gesture. Reaching requires the integration of object location and body position coordinates and reaching tasks elicit bilateral activation in different foci along the intraparietal sulcus. Grasping requires a visuomotor match between the object's shape and the hand's posture. Lesion studies and neuroimaging confirm the importance of the anterior part of the intraparietal sulcus for human grasping. Reaching and grasping reveal bilateral activation that is generally more prominent on the side contralateral to the hand used or the hemifield stimulated. Purposeful behavior with objects and tools can be assessed in a variety of ways, including actual use, pantomimed use, and pure imagery of manipulation. All tasks have been shown to elicit robust activation over the left parietal cortex in neuroimaging, but lesion studies have not always confirmed these findings. Compared to pantomimed or imagined gestures, actual object and tool use typically produces activation over the left primary somatosensory region. Neuroimaging studies on pantomiming or imagery of tool use in healthy volunteers revealed neural responses in possibly separate foci in the left supramarginal gyrus. In sum, the parietal contribution of reaching and grasping of objects seems to depend on a bilateral network of intraparietal foci that appear organized along gradients of sensory and effector preferences. Dorsal and medial parietal cortex appears to contribute to the online monitoring/adjusting of the ongoing prehensile action, whereas the functional use of objects and tools seems to involve the inferior lateral parietal cortex. This functional input reveals a clear left lateralized activation pattern that may be tuned to the integration of acquired knowledge in the planning and guidance of the transitive movement. PMID:24634664

Contribution of the posterior parietal cortex in reaching, grasping, and using objects and tools.

PubMed

Vingerhoets, Guy

2014-01-01

Neuropsychological and neuroimaging data suggest a differential contribution of posterior parietal regions during the different components of a transitive gesture. Reaching requires the integration of object location and body position coordinates and reaching tasks elicit bilateral activation in different foci along the intraparietal sulcus. Grasping requires a visuomotor match between the object's shape and the hand's posture. Lesion studies and neuroimaging confirm the importance of the anterior part of the intraparietal sulcus for human grasping. Reaching and grasping reveal bilateral activation that is generally more prominent on the side contralateral to the hand used or the hemifield stimulated. Purposeful behavior with objects and tools can be assessed in a variety of ways, including actual use, pantomimed use, and pure imagery of manipulation. All tasks have been shown to elicit robust activation over the left parietal cortex in neuroimaging, but lesion studies have not always confirmed these findings. Compared to pantomimed or imagined gestures, actual object and tool use typically produces activation over the left primary somatosensory region. Neuroimaging studies on pantomiming or imagery of tool use in healthy volunteers revealed neural responses in possibly separate foci in the left supramarginal gyrus. In sum, the parietal contribution of reaching and grasping of objects seems to depend on a bilateral network of intraparietal foci that appear organized along gradients of sensory and effector preferences. Dorsal and medial parietal cortex appears to contribute to the online monitoring/adjusting of the ongoing prehensile action, whereas the functional use of objects and tools seems to involve the inferior lateral parietal cortex. This functional input reveals a clear left lateralized activation pattern that may be tuned to the integration of acquired knowledge in the planning and guidance of the transitive movement.

Further fMRI Validation of the Visual Half Field Technique as an Indicator of Language Laterality: A Large-Group Analysis

ERIC Educational Resources Information Center

Van der Haegen, Lise; Cai, Qing; Seurinck, Ruth; Brysbaert, Marc

2011-01-01

The best established lateralized cerebral function is speech production, with the majority of the population having left hemisphere dominance. An important question is how to best assess the laterality of this function. Neuroimaging techniques such as functional Magnetic Resonance Imaging (fMRI) are increasingly used in clinical settings to…

Efficient, graph-based white matter connectivity from orientation distribution functions via multi-directional graph propagation

NASA Astrophysics Data System (ADS)

Boucharin, Alexis; Oguz, Ipek; Vachet, Clement; Shi, Yundi; Sanchez, Mar; Styner, Martin

2011-03-01

The use of regional connectivity measurements derived from diffusion imaging datasets has become of considerable interest in the neuroimaging community in order to better understand cortical and subcortical white matter connectivity. Current connectivity assessment methods are based on streamline fiber tractography, usually applied in a Monte-Carlo fashion. In this work we present a novel, graph-based method that performs a fully deterministic, efficient and stable connectivity computation. The method handles crossing fibers and deals well with multiple seed regions. The computation is based on a multi-directional graph propagation method applied to sampled orientation distribution function (ODF), which can be computed directly from the original diffusion imaging data. We show early results of our method on synthetic and real datasets. The results illustrate the potential of our method towards subjectspecific connectivity measurements that are performed in an efficient, stable and reproducible manner. Such individual connectivity measurements would be well suited for application in population studies of neuropathology, such as Autism, Huntington's Disease, Multiple Sclerosis or leukodystrophies. The proposed method is generic and could easily be applied to non-diffusion data as long as local directional data can be derived.

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls

PubMed Central

Chou, Yi-Yu; Leporé, Natasha; Avedissian, Christina; Madsen, Sarah K.; Parikshak, Neelroop; Hua, Xue; Shaw, Leslie M.; Trojanowski, John Q.; Weiner, Michael W.; Toga, Arthur W.; Thompson, Paul M.

2009-01-01

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer’s disease, NeuroImage 40(2): 615–630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimer’s disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimer’s Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Aβ1–42 protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials. PMID:19236926

On the role of general system theory for functional neuroimaging.

PubMed

Stephan, Klaas Enno

2004-12-01

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

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

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

Frontal lobe function in temporal lobe epilepsy

PubMed Central

Stretton, J.; Thompson, P.J.

2012-01-01

Summary Temporal lobe epilepsy (TLE) is typically associated with long-term memory dysfunction. The frontal lobes support high-level cognition comprising executive skills and working memory that is vital for daily life functioning. Deficits in these functions have been increasingly reported in TLE. Evidence from both the neuropsychological and neuroimaging literature suggests both executive function and working memory are compromised in the presence of TLE. In relation to executive impairment, particular focus has been paid to set shifting as measured by the Wisconsin Card Sorting Task. Other discrete executive functions such as decision-making and theory of mind also appear vulnerable but have received little attention. With regard to working memory, the medial temporal lobe structures appear have a more critical role, but with emerging evidence of hippocampal dependent and independent processes. The relative role of underlying pathology and seizure spread is likely to have considerable bearing upon the cognitive phenotype and trajectory in TLE. The identification of the nature of frontal lobe dysfunction in TLE thus has important clinical implications for prognosis and surgical management. Longitudinal neuropsychological and neuroimaging studies assessing frontal lobe function in TLE patients pre- and postoperatively will improve our understanding further. PMID:22100147

Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning.

PubMed

Chein, Jason M; Schneider, Walter

2005-12-01

Functional magnetic resonance imaging and a meta-analysis of prior neuroimaging studies were used to characterize cortical changes resulting from extensive practice and to evaluate a dual-processing account of the neural mechanisms underlying human learning. Three core predictions of the dual processing theory are evaluated: 1) that practice elicits generalized reductions in regional activity by reducing the load on the cognitive control mechanisms that scaffold early learning; 2) that these control mechanisms are domain-general; and 3) that no separate processing pathway emerges as skill develops. To evaluate these predictions, a meta-analysis of prior neuroimaging studies and a within-subjects fMRI experiment contrasting unpracticed to practiced performance in a paired-associate task were conducted. The principal effect of practice was found to be a reduction in the extent and magnitude of activity in a cortical network spanning bilateral dorsal prefrontal, left ventral prefrontal, medial frontal (anterior cingulate), left insular, bilateral parietal, and occipito-temporal (fusiform) areas. These activity reductions are shown to occur in common regions across prior neuroimaging studies and for both verbal and nonverbal paired-associate learning in the present fMRI experiment. The implicated network of brain regions is interpreted as a domain-general system engaged specifically to support novice, but not practiced, performance.

Imaging or Imagining? A Neuroethics Challenge Informed by Genetics

PubMed Central

Illes, Judy; Racine, Eric

2006-01-01

From a twenty-first century partnership between bioethics and neuroscience, the modern field of neuroethics is emerging, and technologies enabling functional neuroimaging with unprecedented sensitivity have brought new ethical, social and legal issues to the forefront. Some issues, akin to those surrounding modern genetics, raise critical questions regarding prediction of disease, privacy and identity. However, with new and still-evolving insights into our neurobiology and previously unquantifiable features of profoundly personal behaviors such as social attitude, value and moral agency, the difficulty of carefully and properly interpreting the relationship between brain findings and our own self-concept is unprecedented. Therefore, while the ethics of genetics provides a legitimate starting point—even a backbone—for tackling ethical issues in neuroimaging, they do not suffice. Drawing on recent neuroimaging findings and their plausible real-world applications, we argue that interpretation of neuroimaging data is a key epistemological and ethical challenge. This challenge is two-fold. First, at the scientific level, the sheer complexity of neuroscience research poses challenges for integration of knowledge and meaningful interpretation of data. Second, at the social and cultural level, we find that interpretations of imaging studies are bound by cultural and anthropological frameworks. In particular, the introduction of concepts of self and personhood in neuroimaging illustrates the interaction of interpretation levels and is a major reason why ethical reflection on genetics will only partially help settle neuroethical issues. Indeed, ethical interpretation of such findings will necessitate not only traditional bioethical input but also a wider perspective on the construction of scientific knowledge. PMID:16036688

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.…

Sex/Gender Differences in Neural Correlates of Food Stimuli: A Systematic Review of Functional Neuroimaging Studies

PubMed Central

Chao, Ariana M.; Loughead, James; Bakizada, Zayna M.; Hopkins, Christina M.; Geliebter, Allan; Gur, Ruben C.; Wadden, Thomas A.

2017-01-01

Sex and gender differences in food perceptions and eating behaviors have been reported in psychological and behavioral studies. The aim of this systematic review was to synthesize studies that examined sex/gender differences in neural correlates of food stimuli, as assessed by functional neuroimaging. Published studies to 2016 were retrieved and included if they used food or eating stimuli, assessed patients with functional magnetic resonance imaging (fMRI) or positron emission tomography (PET), and compared activation between males and females. Fifteen studies were identified. In response to visual food cues, females, compared to males, showed increased activation in the frontal, limbic, and striatal areas of the brain as well as the fusiform gyrus. Differences in neural response to gustatory stimuli were inconsistent. This body of literature suggests that females may be more reactive to visual food stimuli. However, findings are based on a small number of studies and additional research is needed to establish a more definitive explanation and conclusion. PMID:28371180

Biomarkers for Success: Using Neuroimaging to Predict Relapse and Develop Brain Stimulation Treatments for Cocaine-Dependent Individuals.

PubMed

Hanlon, C A; Dowdle, L T; Jones, J L

2016-01-01

Cocaine dependence is one of the most difficult substance use disorders to treat. While the powerful effects of cocaine use on behavior were documented in the 19th century, it was not until the late 20th century that we realized cocaine use was affecting brain tissue and function. Following a brief introduction (Section 1), this chapter will summarize our current knowledge regarding alterations in neural circuit function typically observed in chronic cocaine users (Section 2) and highlight an emerging body of literature which suggests that pretreatment limbic circuit activity may be a reliable predictor of clinical outcomes among individuals seeking treatment for cocaine (Section 3). Finally, as the field of addiction research strives to translate this neuroimaging data into something clinically meaningful, we will highlight several new brain stimulation approaches which utilize functional brain imaging data to design noninvasive brain stimulation interventions for individuals seeking treatment for substance dependence disorders (Section 4). © 2016 Elsevier Inc. All rights reserved.

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

A new epileptic seizure classification based exclusively on ictal semiology.

PubMed

Lüders, H; Acharya, J; Baumgartner, C; Benbadis, S; Bleasel, A; Burgess, R; Dinner, D S; Ebner, A; Foldvary, N; Geller, E; Hamer, H; Holthausen, H; Kotagal, P; Morris, H; Meencke, H J; Noachtar, S; Rosenow, F; Sakamoto, A; Steinhoff, B J; Tuxhorn, I; Wyllie, E

1999-03-01

Historically, seizure semiology was the main feature in the differential diagnosis of epileptic syndromes. With the development of clinical EEG, the definition of electroclinical complexes became an essential tool to define epileptic syndromes, particularly focal epileptic syndromes. Modern advances in diagnostic technology, particularly in neuroimaging and molecular biology, now permit better definitions of epileptic syndromes. At the same time detailed studies showed that there does not necessarily exist a one-to-one relationship between epileptic seizures or electroclinical complexes and epileptic syndromes. These developments call for the reintroduction of an epileptic seizure classification based exclusively on clinical semiology, similar to the seizure classifications which were used by neurologists before the introduction of the modern diagnostic methods. This classification of epileptic seizures should always be complemented by an epileptic syndrome classification based on all the available clinical information (clinical history, neurological exam, ictal semiology, EEG, anatomical and functional neuroimaging, etc.). Such an approach is more consistent with mainstream clinical neurology and would avoid the current confusion between the classification of epileptic seizures (which in the International Seizure Classification is actually a classification of electroclinical complexes) and the classification of epileptic syndromes.

Dispositional fear, negative affectivity, and neuroimaging response to visually suppressed emotional faces.

PubMed

Vizueta, Nathalie; Patrick, Christopher J; Jiang, Yi; Thomas, Kathleen M; He, Sheng

2012-01-02

"Invisible" stimulus paradigms provide a method for investigating basic affective processing in clinical and non-clinical populations. Neuroimaging studies utilizing continuous flash suppression (CFS) have shown increased amygdala response to invisible fearful versus neutral faces. The current study used CFS in conjunction with functional MRI to test for differences in brain reactivity to visible and invisible emotional faces in relation to two distinct trait dimensions relevant to psychopathology: negative affectivity (NA) and fearfulness. Subjects consisted of college students (N=31) assessed for fear/fearlessness along with dispositional NA. The main brain regions of interest included the fusiform face area (FFA), superior temporal sulcus (STS), and amygdala. Higher NA, but not trait fear, was associated with enhanced response to fearful versus neutral faces in STS and right amygdala (but not FFA), within the invisible condition specifically. The finding that NA rather than fearfulness predicted degree of amygdala reactivity to suppressed faces implicates the input subdivision of the amygdala in the observed effects. Given the central role of NA in anxiety and mood disorders, the current data also support use of the CFS methodology for investigating the neurobiology of these disorders. Copyright © 2011 Elsevier Inc. All rights reserved.

The macro-structural variability of the human neocortex.

PubMed

Kruggel, Frithjof

2018-05-15

The human neocortex shows a considerable individual structural variability. While primary gyri and sulci are found in all normally developed brains and bear clear-cut gross structural descriptions, secondary structures are highly variable and not present in all brains. The blend of common and individual structures poses challenges when comparing structural and functional results from quantitative neuroimaging studies across individuals, and sets limits on the precision of location information much above the spatial resolution of current neuroimaging methods. This work aimed at quantifying structural variability on the neocortex, and at assessing the spatial relationship between regions common to all brains and their individual structural variants. Based on structural MRI data provided as the "900 Subjects Release" of the Human Connectome Project, a data-driven analytic approach was employed here from which the definition of seven cortical "communities" emerged. Apparently, these communities comprise common regions of structural features, while the individual variability is confined within a community. Similarities between the community structure and the state of the brain development at gestation week 32 lead suggest that communities are segregated early. Subdividing the neocortex into communities is suggested as anatomically more meaningful than the traditional lobar structure. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural Coding for Effective Rehabilitation

PubMed Central

2014-01-01

Successful neurological rehabilitation depends on accurate diagnosis, effective treatment, and quantitative evaluation. Neural coding, a technology for interpretation of functional and structural information of the nervous system, has contributed to the advancements in neuroimaging, brain-machine interface (BMI), and design of training devices for rehabilitation purposes. In this review, we summarized the latest breakthroughs in neuroimaging from microscale to macroscale levels with potential diagnostic applications for rehabilitation. We also reviewed the achievements in electrocorticography (ECoG) coding with both animal models and human beings for BMI design, electromyography (EMG) interpretation for interaction with external robotic systems, and robot-assisted quantitative evaluation on the progress of rehabilitation programs. Future rehabilitation would be more home-based, automatic, and self-served by patients. Further investigations and breakthroughs are mainly needed in aspects of improving the computational efficiency in neuroimaging and multichannel ECoG by selection of localized neuroinformatics, validation of the effectiveness in BMI guided rehabilitation programs, and simplification of the system operation in training devices. PMID:25258708

Imaging the pathophysiology of major depressive disorder - from localist models to circuit-based analysis

PubMed Central

2014-01-01

The neuroimaging literature of Major Depressive Disorder (MDD) has grown substantially over the last several decades, facilitating great advances in the identification of specific brain regions, neurotransmitter systems and networks associated with depressive illness. Despite this progress, fundamental questions remain about the pathophysiology and etiology of MDD. More importantly, this body of work has yet to directly influence clinical practice. It has long been a goal for the fields of clinical psychology and psychiatry to have a means of making objective diagnoses of mental disorders. Frustratingly little movement has been achieved on this front, however, and the 'gold-standard’ of diagnostic validity and reliability remains expert consensus. In light of this challenge, the focus of the current review is to provide a critical summary of key findings from different neuroimaging approaches in MDD research, including structural, functional and neurochemical imaging studies. Following this summary, we discuss some of the current conceptual obstacles to better understanding the pathophysiology of depression, and conclude with recommendations for future neuroimaging research. PMID:24606595

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

Mechanisms of Aphasia Recovery after Stroke and the Role of Noninvasive Brain Stimulation

ERIC Educational Resources Information Center

Hamilton, Roy H.; Chrysikou, Evangelia G.; Coslett, Branch

2011-01-01

One of the most frequent symptoms of unilateral stroke is aphasia, the impairment or loss of language functions. Over the past few years, behavioral and neuroimaging studies have shown that rehabilitation interventions can promote neuroplastic changes in aphasic patients that may be associated with the improvement of language functions. Following…