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.

Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

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.

Current state of the use of neuroimaging techniques to understand and alter appetite control in humans.

PubMed

Spetter, Maartje S

2018-06-20

It is in the brain where the decision is made what and how much to eat. In the last decades neuroimaging research has contributed extensively to new knowledge about appetite control by revealing the underlying brain processes. Interestingly, there is the fast growing idea of using these methods to develop new treatments for obesity and eating disorders. In this review, we summarize the findings of the importance of the use of neuropharmacology and neuroimaging techniques in understanding and modifying appetite control. Appetite control is a complex interplay between homeostatic, hedonic, and cognitive processes. Administration of the neuropeptides insulin and oxytocin curb food intake and alter brain responses in reward and cognitive control areas. Additionally, these areas can be targeted for neuromodulation or neurofeedback to reduce food cravings and increase self-control to alter food intake. The recent findings reveal the potential of intranasal administration of hormones or modifying appetite control brain networks to reduce food consumption in volunteers with overweight and obesity or individuals with an eating disorder. Although long-term clinical studies are still needed.

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.

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.

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

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

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.

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

ERIC Educational Resources Information Center

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

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

Neuroimaging 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.

Functional neuroimaging: technical, logical, and social perspectives.

PubMed

Aguirre, Geoffrey K

2014-01-01

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

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.

Neuroimaging of Cerebrovascular Disease in the Aging Brain

PubMed Central

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

2012-01-01

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

MR connectomics: a conceptual framework for studying the developing brain

PubMed Central

Hagmann, Patric; Grant, Patricia E.; Fair, Damien A.

2012-01-01

The combination of advanced neuroimaging techniques and major developments in complex network science, have given birth to a new framework for studying the brain: “connectomics.” This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research. PMID:22707934

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.

Neuroimaging Insights into the Pathophysiology of Sleep Disorders

PubMed Central

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

2008-01-01

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

Neuroimaging 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.

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.

An Event-Related Potential (ERP) Investigation of Filler-Gap Processing in Native and Second Language Speakers

ERIC Educational Resources Information Center

Dallas, Andrea; DeDe, Gayle; Nicol, Janet

2013-01-01

The current study employed a neuro-imaging technique, Event-Related Potentials (ERP), to investigate real-time processing of sentences containing filler-gap dependencies by late-learning speakers of English as a second language (L2) with a Chinese native language background. An individual differences approach was also taken to examine the role of…

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.

Neuroimaging and Research into Second Language Acquisition

ERIC Educational Resources Information Center

Sabourin, Laura

2009-01-01

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

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.

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.

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

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

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.

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

PubMed

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

2014-01-01

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

The 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

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

Systematic Redaction for Neuroimage Data

PubMed Central

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

2013-01-01

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

The Status of the Quality Control in Acupuncture-Neuroimaging Studies

PubMed Central

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

2016-01-01

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

[Recent progress of neuroimaging studies on sleeping brain].

PubMed

Sasaki, Yuka

2012-06-01

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

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.

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

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

PubMed Central

Risacher, Shannon L.; Saykin, Andrew J.

2014-01-01

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

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.

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.

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.

Multimodal neuroimaging in presurgical evaluation of drug-resistant epilepsy☆

PubMed Central

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

2013-01-01

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

[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.

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.

[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.

How Acute Total Sleep Loss Affects the Attending Brain: A Meta-Analysis of Neuroimaging Studies

PubMed Central

Ma, Ning; Dinges, David F.; Basner, Mathias; Rao, Hengyi

2015-01-01

Study Objectives: Attention is a cognitive domain that can be severely affected by sleep deprivation. Previous neuroimaging studies have used different attention paradigms and reported both increased and reduced brain activation after sleep deprivation. However, due to large variability in sleep deprivation protocols, task paradigms, experimental designs, characteristics of subject populations, and imaging techniques, there is no consensus regarding the effects of sleep loss on the attending brain. The aim of this meta-analysis was to identify brain activations that are commonly altered by acute total sleep deprivation across different attention tasks. Design: Coordinate-based meta-analysis of neuroimaging studies of performance on attention tasks during experimental sleep deprivation. Methods: The current version of the activation likelihood estimation (ALE) approach was used for meta-analysis. The authors searched published articles and identified 11 sleep deprivation neuroimaging studies using different attention tasks with a total of 185 participants, equaling 81 foci for ALE analysis. Results: The meta-analysis revealed significantly reduced brain activation in multiple regions following sleep deprivation compared to rested wakefulness, including bilateral intraparietal sulcus, bilateral insula, right prefrontal cortex, medial frontal cortex, and right parahippocampal gyrus. Increased activation was found only in bilateral thalamus after sleep deprivation compared to rested wakefulness. Conclusion: Acute total sleep deprivation decreases brain activation in the fronto-parietal attention network (prefrontal cortex and intraparietal sulcus) and in the salience network (insula and medial frontal cortex). Increased thalamic activation after sleep deprivation may reflect a complex interaction between the de-arousing effects of sleep loss and the arousing effects of task performance on thalamic activity. Citation: Ma N, Dinges DF, Basner M, Rao H. How acute total sleep loss affects the attending brain: a meta-analysis of neuroimaging studies. SLEEP 2015;38(2):233–240. PMID:25409102

Human Fear Conditioning and Extinction in Neuroimaging: A Systematic Review

PubMed Central

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

2009-01-01

Fear conditioning and extinction are basic forms of associative learning that have gained considerable clinical relevance in enhancing our understanding of anxiety disorders and facilitating their treatment. Modern neuroimaging techniques have significantly aided the identification of anatomical structures and networks involved in fear conditioning. On closer inspection, there is considerable variation in methodology and results between studies. This systematic review provides an overview of the current neuroimaging literature on fear conditioning and extinction on healthy subjects, taking into account methodological issues such as the conditioning paradigm. A Pubmed search, as of December 2008, was performed and supplemented by manual searches of bibliographies of key articles. Two independent reviewers made the final study selection and data extraction. A total of 46 studies on cued fear conditioning and/or extinction on healthy volunteers using positron emission tomography or functional magnetic resonance imaging were reviewed. The influence of specific experimental factors, such as contingency and timing parameters, assessment of conditioned responses, and characteristics of conditioned and unconditioned stimuli, on cerebral activation patterns was examined. Results were summarized descriptively. A network consisting of fear-related brain areas, such as amygdala, insula, and anterior cingulate cortex, is activated independently of design parameters. However, some neuroimaging studies do not report these findings in the presence of methodological heterogeneities. Furthermore, other brain areas are differentially activated, depending on specific design parameters. These include stronger hippocampal activation in trace conditioning and tactile stimulation. Furthermore, tactile unconditioned stimuli enhance activation of pain related, motor, and somatosensory areas. Differences concerning experimental factors may partly explain the variance between neuroimaging investigations on human fear conditioning and extinction and should, therefore, be taken into serious consideration in the planning and the interpretation of research projects. PMID:19517024

Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning.

PubMed

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

2018-04-22

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

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

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.

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

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.

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

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.

Recent neuroimaging techniques in mild traumatic brain injury.

PubMed

Belanger, Heather G; Vanderploeg, Rodney D; Curtiss, Glenn; Warden, Deborah L

2007-01-01

Mild traumatic brain injury (TBI) is characterized by acute physiological changes that result in at least some acute cognitive difficulties and typically resolve by 3 months postinjury. Because the majority of mild TBI patients have normal structural magnetic resonance imaging (MRI)/computed tomography (CT) scans, there is increasing attention directed at finding objective physiological correlates of persistent cognitive and neuropsychiatric symptoms through experimental neuroimaging techniques. The authors review studies utilizing these techniques in patients with mild TBI; these techniques may provide more sensitive assessment of structural and functional abnormalities following mild TBI. Particular promise is evident with fMRI, PET, and SPECT scanning, as demonstrated by associations between brain activation and clinical outcomes.

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

Gray Matter Pathology in MS: Neuroimaging and Clinical Correlations

PubMed Central

Honce, Justin Morris

2013-01-01

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

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

PubMed Central

Kelley, Daniel J; Johnson, Sterling C

2007-01-01

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

Fusing DTI and FMRI Data: A Survey of Methods and Applications

PubMed Central

Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

2014-01-01

The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849

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.

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

PubMed Central

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

2013-01-01

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

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 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

Neuroimaging of amblyopia and binocular vision: a review

PubMed Central

Joly, Olivier; Frankó, Edit

2014-01-01

Amblyopia is a cerebral visual impairment considered to derive from abnormal visual experience (e.g., strabismus, anisometropia). Amblyopia, first considered as a monocular disorder, is now often seen as a primarily binocular disorder resulting in more and more studies examining the binocular deficits in the patients. The neural mechanisms of amblyopia are not completely understood even though they have been investigated with electrophysiological recordings in animal models and more recently with neuroimaging techniques in humans. In this review, we summarize the current knowledge about the brain regions that underlie the visual deficits associated with amblyopia with a focus on binocular vision using functional magnetic resonance imaging. The first studies focused on abnormal responses in the primary and secondary visual areas whereas recent evidence shows that there are also deficits at higher levels of the visual pathways within the parieto-occipital and temporal cortices. These higher level areas are part of the cortical network involved in 3D vision from binocular cues. Therefore, reduced responses in these areas could be related to the impaired binocular vision in amblyopic patients. Promising new binocular treatments might at least partially correct the activation in these areas. Future neuroimaging experiments could help to characterize the brain response changes associated with these treatments and help devise them. PMID:25147511

Neuroimaging of amblyopia and binocular vision: a review.

PubMed

Joly, Olivier; Frankó, Edit

2014-01-01

Amblyopia is a cerebral visual impairment considered to derive from abnormal visual experience (e.g., strabismus, anisometropia). Amblyopia, first considered as a monocular disorder, is now often seen as a primarily binocular disorder resulting in more and more studies examining the binocular deficits in the patients. The neural mechanisms of amblyopia are not completely understood even though they have been investigated with electrophysiological recordings in animal models and more recently with neuroimaging techniques in humans. In this review, we summarize the current knowledge about the brain regions that underlie the visual deficits associated with amblyopia with a focus on binocular vision using functional magnetic resonance imaging. The first studies focused on abnormal responses in the primary and secondary visual areas whereas recent evidence shows that there are also deficits at higher levels of the visual pathways within the parieto-occipital and temporal cortices. These higher level areas are part of the cortical network involved in 3D vision from binocular cues. Therefore, reduced responses in these areas could be related to the impaired binocular vision in amblyopic patients. Promising new binocular treatments might at least partially correct the activation in these areas. Future neuroimaging experiments could help to characterize the brain response changes associated with these treatments and help devise them.

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.

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.

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

PubMed Central

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

2014-01-01

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

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.

How acute total sleep loss affects the attending brain: a meta-analysis of neuroimaging studies.

PubMed

Ma, Ning; Dinges, David F; Basner, Mathias; Rao, Hengyi

2015-02-01

Attention is a cognitive domain that can be severely affected by sleep deprivation. Previous neuroimaging studies have used different attention paradigms and reported both increased and reduced brain activation after sleep deprivation. However, due to large variability in sleep deprivation protocols, task paradigms, experimental designs, characteristics of subject populations, and imaging techniques, there is no consensus regarding the effects of sleep loss on the attending brain. The aim of this meta-analysis was to identify brain activations that are commonly altered by acute total sleep deprivation across different attention tasks. Coordinate-based meta-analysis of neuroimaging studies of performance on attention tasks during experimental sleep deprivation. The current version of the activation likelihood estimation (ALE) approach was used for meta-analysis. The authors searched published articles and identified 11 sleep deprivation neuroimaging studies using different attention tasks with a total of 185 participants, equaling 81 foci for ALE analysis. The meta-analysis revealed significantly reduced brain activation in multiple regions following sleep deprivation compared to rested wakefulness, including bilateral intraparietal sulcus, bilateral insula, right prefrontal cortex, medial frontal cortex, and right parahippocampal gyrus. Increased activation was found only in bilateral thalamus after sleep deprivation compared to rested wakefulness. Acute total sleep deprivation decreases brain activation in the fronto-parietal attention network (prefrontal cortex and intraparietal sulcus) and in the salience network (insula and medial frontal cortex). Increased thalamic activation after sleep deprivation may reflect a complex interaction between the de-arousing effects of sleep loss and the arousing effects of task performance on thalamic activity. © 2015 Associated Professional Sleep Societies, LLC.

The Evolution of Neuroimaging Research and Developmental Language Disorders.

ERIC Educational Resources Information Center

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

2001-01-01

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

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.

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-01-01

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

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.

Functional brain imaging in neuropsychology over the past 25 years.

PubMed

Roalf, David R; Gur, Ruben C

2017-11-01

Outline effects of functional neuroimaging on neuropsychology over the past 25 years. Functional neuroimaging methods and studies will be described that provide a historical context, offer examples of the utility of neuroimaging in specific domains, and discuss the limitations and future directions of neuroimaging in neuropsychology. Tracking the history of publications on functional neuroimaging related to neuropsychology indicates early involvement of neuropsychologists in the development of these methodologies. Initial progress in neuropsychological application of functional neuroimaging has been hampered by costs and the exposure to ionizing radiation. With rapid evolution of functional methods-in particular functional MRI (fMRI)-neuroimaging has profoundly transformed our knowledge of the brain. Its current applications span the spectrum of normative development to clinical applications. The field is moving toward applying sophisticated statistical approaches that will help elucidate distinct neural activation networks associated with specific behavioral domains. The impact of functional neuroimaging on clinical neuropsychology is more circumscribed, but the prospects remain enticing. The theoretical insights and empirical findings of functional neuroimaging have been led by many neuropsychologists and have transformed the field of behavioral neuroscience. Thus far they have had limited effects on the clinical practices of neuropsychologists. Perhaps it is time to add training in functional neuroimaging to the clinical neuropsychologist's toolkit and from there to the clinic or bedside. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Concurrent application of TMS and near-infrared optical imaging: methodological considerations and potential artifacts

PubMed Central

Parks, Nathan A.

2013-01-01

The simultaneous application of transcranial magnetic stimulation (TMS) with non-invasive neuroimaging provides a powerful method for investigating functional connectivity in the human brain and the causal relationships between areas in distributed brain networks. TMS has been combined with numerous neuroimaging techniques including, electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET). Recent work has also demonstrated the feasibility and utility of combining TMS with non-invasive near-infrared optical imaging techniques, functional near-infrared spectroscopy (fNIRS) and the event-related optical signal (EROS). Simultaneous TMS and optical imaging affords a number of advantages over other neuroimaging methods but also involves a unique set of methodological challenges and considerations. This paper describes the methodology of concurrently performing optical imaging during the administration of TMS, focusing on experimental design, potential artifacts, and approaches to controlling for these artifacts. PMID:24065911

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.

Using personality neuroscience to study personality disorder.

PubMed

Abram, Samantha V; DeYoung, Colin G

2017-01-01

Personality neuroscience integrates techniques from personality psychology and neuroscience to elucidate the neural basis of individual differences in cognition, emotion, motivation, and behavior. This endeavor is pertinent not only to our understanding of healthy personality variation, but also to the aberrant trait manifestations present in personality disorders and severe psychopathology. In the current review, we focus on the advances and limitations of neuroimaging methods with respect to personality neuroscience. We discuss the value of personality theory as a means to link specific neural mechanisms with various traits (e.g., the neural basis of the "Big Five"). Given the overlap between dimensional models of normal personality and psychopathology, we also describe how researchers can reconceptualize psychopathological disorders along key dimensions, and, in turn, formulate specific neural hypotheses, extended from personality theory. Examples from the borderline personality disorder literature are used to illustrate this approach. We provide recommendations for utilizing neuroimaging methods to capture the neural mechanisms that underlie continuous traits across the spectrum from healthy to maladaptive. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Human Orbitofrontal Cortex Represents a Cognitive Map of State Space.

PubMed

Schuck, Nicolas W; Cai, Ming Bo; Wilson, Robert C; Niv, Yael

2016-09-21

Although the orbitofrontal cortex (OFC) has been studied intensely for decades, its precise functions have remained elusive. We recently hypothesized that the OFC contains a "cognitive map" of task space in which the current state of the task is represented, and this representation is especially critical for behavior when states are unobservable from sensory input. To test this idea, we apply pattern-classification techniques to neuroimaging data from humans performing a decision-making task with 16 states. We show that unobservable task states can be decoded from activity in OFC, and decoding accuracy is related to task performance and the occurrence of individual behavioral errors. Moreover, similarity between the neural representations of consecutive states correlates with behavioral accuracy in corresponding state transitions. These results support the idea that OFC represents a cognitive map of task space and establish the feasibility of decoding state representations in humans using non-invasive neuroimaging. Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trends.

PubMed

Haller, Sven; Lovblad, Karl-Olof; Giannakopoulos, Panteleimon; Van De Ville, Dimitri

2014-05-01

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

Neuroeconomics: A bridge for translational research

PubMed Central

Sharp, Carla; Monterosso, John; Montague, Read

2014-01-01

Neuroeconomic methods combine behavioral economic experiments to parameterize aspects of reward-related decision-making with neuroimaging techniques to record corresponding brain activity. In this introductory paper to the current special issue, we propose that neuroeconomics is a potential bridge for translational research in psychiatry for several reasons. First, neuroeconomics-derived theoretical predictions about optimal adaptation in a changing environment provide an objective metric to examine psychopathology. Second, neuroeconomics provides a ‘multi-level’ research approach that combines performance (behavioral) measures with intermediate measures between behavior and neurobiology (e.g, neuroimaging) and uses a common metaphor to describe decision-making across multiple levels of explanation. As such, ecologically valid behavioral paradigms closely mirror the physical mechanisms of reward processing. Third, neuroeconomics provides a platform for investigators from neuroscience, economics, psychiatry and social and clinical psychology to develop a common language for studying reward-related decision making in psychiatric disorders. Therefore, neuroeconomics can provide promising candidate endophenotypes that may help clarify the basis of high heritability associated with psychiatric disorders and that may, in turn, inform treatment. PMID:22727459

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

PubMed Central

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

2013-01-01

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

[Social neuroscience and psychiatry].

PubMed

Takahashi, Hidehiko

2013-01-01

The topics of emotion, decision-making, and consciousness have been traditionally dealt with in the humanities and social sciences. With the dissemination of noninvasive human neuroimaging techniques such as fMRI and the advancement of cognitive science, neuroimaging studies focusing on emotions, social cognition, and decision-making have become established. I overviewed the history of social neurosciences. The emerging field of social brain research or social neuroscience will greatly contribute to clinical psychiatry. In the first part. I introduced our early fMRI studies on social emotions such as guilt, embarrassment, pride, and envy. Dysfunction of social emotions can be observed in various forms of psychiatric disorder, and the findings should contribute to a better understanding of the pathophysiology of psychiatric conditions. In the second part, I introduced our recent interdisciplinary neuroscience approach combining molecular neuroimaging techniques(positron emission tomography: PET), cognitive sciences, and economics to understand the neural as well as molecular basis of altered decision-making in neuropsychiatric disorders. An interdisciplinary approach combing molecular imaging techniques and cognitive neuroscience and clinical psychiatry will provide new perspectives for understanding the neurobiology of impaired decision-making in neuropsychiatric disorders and drug development.

Thrombosis of the superior sagittal sinus.

PubMed

Kabashi, Serbeze; Muçaj, Sefedin; Ahmetgjekaj, Ilir; Dreshaj, Shemsedin; Ymeri, Halit; Hundozi, Hajrije; Vranica, Sylen; Hasani, Antigona; Shala, Nexhmedin

2010-01-01

Thrombosis of the sinuses is a distinct cerebrovascular disorder that, unlike arterial stroke, most often affects young adults and children. The symptoms and clinical course are highly variable. During the past decade, increased awareness of the diagnosis, improved neuro-imaging techniques, and more effective treatment have improved the prognosis. More than 80% of all patients now have a good neurologic outcome. This review summarizes recent insights into the pathogenesis of sinus thrombosis, risk factors, and clinical and radiological diagnosis and discusses the current evidence and controversies about the best treatment.

[One decade of functional imaging in schizophrenia research. From visualisation of basic information processing steps to molecular-genetic oriented imaging].

PubMed

Tost, H; Meyer-Lindenberg, A; Ruf, M; Demirakça, T; Grimm, O; Henn, F A; Ende, G

2005-02-01

Modern neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have contributed tremendously to our current understanding of psychiatric disorders in the context of functional, biochemical and microstructural alterations of the brain. Since the mid-nineties, functional MRI has provided major insights into the neurobiological correlates of signs and symptoms in schizophrenia. The current paper reviews important fMRI studies of the past decade in the domains of motor, visual, auditory, attentional and working memory function. Special emphasis is given to new methodological approaches, such as the visualisation of medication effects and the functional characterisation of risk genes.

Terminology development towards harmonizing multiple clinical neuroimaging research repositories.

PubMed

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

2015-07-01

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

Terminology development towards harmonizing multiple clinical neuroimaging research repositories

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2013-01-01

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

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

Molecular neuroimaging of emotional decision-making.

PubMed

Takahashi, Hidehiko

2013-04-01

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

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

Neural modeling and functional neuroimaging.

PubMed

Horwitz, B; Sporns, O

1994-01-01

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

Adolescent Schizophrenia: A Methodologic Review of the Current Neuroimaging and Neuropsychologic Literature.

ERIC Educational Resources Information Center

Findling, Robert L.; And Others

1995-01-01

This paper reviews the methodology in articles that have reported structural neuroimaging or neuropsychological data in adolescent patients with schizophrenia. Identification of methodological issues led to the finding that, at present, no conclusions can be made regarding the presence or absence of neuropsychologic dysfunction or structural…

Cerebellar and Brainstem Malformations.

PubMed

Poretti, Andrea; Boltshauser, Eugen; Huisman, Thierry A G M

2016-08-01

The frequency and importance of the evaluation of the posterior fossa have increased significantly over the past 20 years owing to advances in neuroimaging. Conventional and advanced neuroimaging techniques allow detailed evaluation of the complex anatomic structures within the posterior fossa. A wide spectrum of cerebellar and brainstem malformations has been shown. Familiarity with the spectrum of cerebellar and brainstem malformations and their well-defined diagnostic criteria is crucial for optimal therapy, an accurate prognosis, and correct genetic counseling. This article discusses cerebellar and brainstem malformations, with emphasis on neuroimaging findings (including diagnostic criteria), neurologic presentation, systemic involvement, prognosis, and recurrence. Copyright © 2016 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

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.

Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review.

PubMed

Dallora, Ana Luiza; Eivazzadeh, Shahryar; Mendes, Emilia; Berglund, Johan; Anderberg, Peter

2017-01-01

Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patients and public entities in dealing with this disorder. Thus, health data, machine learning and microsimulation techniques could be employed in developing prognostic estimates for dementia. The goal of this paper is to present evidence on the state of the art of studies investigating and the prognosis of dementia using machine learning and microsimulation techniques. To achieve our goal we carried out a systematic literature review, in which three large databases-Pubmed, Socups and Web of Science were searched to select studies that employed machine learning or microsimulation techniques for the prognosis of dementia. A single backward snowballing was done to identify further studies. A quality checklist was also employed to assess the quality of the evidence presented by the selected studies, and low quality studies were removed. Finally, data from the final set of studies were extracted in summary tables. In total 37 papers were included. The data summary results showed that the current research is focused on the investigation of the patients with mild cognitive impairment that will evolve to Alzheimer's disease, using machine learning techniques. Microsimulation studies were concerned with cost estimation and had a populational focus. Neuroimaging was the most commonly used variable. Prediction of conversion from MCI to AD is the dominant theme in the selected studies. Most studies used ML techniques on Neuroimaging data. Only a few data sources have been recruited by most studies and the ADNI database is the one most commonly used. Only two studies have investigated the prediction of epidemiological aspects of Dementia using either ML or MS techniques. Finally, care should be taken when interpreting the reported accuracy of ML techniques, given studies' different contexts.

Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review

PubMed Central

Mendes, Emilia; Berglund, Johan; Anderberg, Peter

2017-01-01

Background Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patients and public entities in dealing with this disorder. Thus, health data, machine learning and microsimulation techniques could be employed in developing prognostic estimates for dementia. Objective The goal of this paper is to present evidence on the state of the art of studies investigating and the prognosis of dementia using machine learning and microsimulation techniques. Method To achieve our goal we carried out a systematic literature review, in which three large databases—Pubmed, Socups and Web of Science were searched to select studies that employed machine learning or microsimulation techniques for the prognosis of dementia. A single backward snowballing was done to identify further studies. A quality checklist was also employed to assess the quality of the evidence presented by the selected studies, and low quality studies were removed. Finally, data from the final set of studies were extracted in summary tables. Results In total 37 papers were included. The data summary results showed that the current research is focused on the investigation of the patients with mild cognitive impairment that will evolve to Alzheimer’s disease, using machine learning techniques. Microsimulation studies were concerned with cost estimation and had a populational focus. Neuroimaging was the most commonly used variable. Conclusions Prediction of conversion from MCI to AD is the dominant theme in the selected studies. Most studies used ML techniques on Neuroimaging data. Only a few data sources have been recruited by most studies and the ADNI database is the one most commonly used. Only two studies have investigated the prediction of epidemiological aspects of Dementia using either ML or MS techniques. Finally, care should be taken when interpreting the reported accuracy of ML techniques, given studies’ different contexts. PMID:28662070

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

PubMed

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

2016-08-01

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

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.

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

Advances in neuroimaging of traumatic brain injury and posttraumatic stress disorder

PubMed Central

Van Boven, Robert W.; Harrington, Greg S.; Hackney, David B.; Ebel, Andreas; Gauger, Grant; Bremner, J. Douglas; D’Esposito, Mark; Detre, John A.; Haacke, E. Mark; Jack, Clifford R.; Jagust, William J.; Le Bihan, Denis; Mathis, Chester A.; Mueller, Susanne; Mukherjee, Pratik; Schuff, Norbert; Chen, Anthony; Weiner, Michael W.

2011-01-01

Improved diagnosis and treatment of traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are needed for our military and veterans, their families, and society at large. Advances in brain imaging offer important biomarkers of structural, functional, and metabolic information concerning the brain. This article reviews the application of various imaging techniques to the clinical problems of TBI and PTSD. For TBI, we focus on findings and advances in neuroimaging that hold promise for better detection, characterization, and monitoring of objective brain changes in symptomatic patients with combat-related, closed-head brain injuries not readily apparent by standard computed tomography or conventional magnetic resonance imaging techniques. PMID:20104401

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

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.

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.

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

PubMed Central

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

2015-01-01

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

Neural and mental hierarchies.

PubMed

Wiest, Gerald

2012-01-01

The history of the sciences of the human brain and mind has been characterized from the beginning by two parallel traditions. The prevailing theory that still influences the way current neuroimaging techniques interpret brain function, can be traced back to classical localizational theories, which in turn go back to early phrenological theories. The other approach has its origins in the hierarchical neurological theories of Hughlings-Jackson, which have been influenced by the philosophical conceptions of Herbert Spencer. Another hallmark of the hierarchical tradition, which is also inherent to psychoanalytic metapsychology, is its deeply evolutionary perspective by taking both ontogenetic and phylogenetic trajectories into consideration. This article provides an outline on hierarchical concepts in brain and mind sciences, which contrast with current cognitivistic and non-hierarchical theories in the neurosciences.

Neural and Mental Hierarchies

PubMed Central

Wiest, Gerald

2012-01-01

The history of the sciences of the human brain and mind has been characterized from the beginning by two parallel traditions. The prevailing theory that still influences the way current neuroimaging techniques interpret brain function, can be traced back to classical localizational theories, which in turn go back to early phrenological theories. The other approach has its origins in the hierarchical neurological theories of Hughlings-Jackson, which have been influenced by the philosophical conceptions of Herbert Spencer. Another hallmark of the hierarchical tradition, which is also inherent to psychoanalytic metapsychology, is its deeply evolutionary perspective by taking both ontogenetic and phylogenetic trajectories into consideration. This article provides an outline on hierarchical concepts in brain and mind sciences, which contrast with current cognitivistic and non-hierarchical theories in the neurosciences. PMID:23189066

Can understanding the neurobiology of body dysmorphic disorder (BDD) inform treatment?

PubMed

Rossell, Susan L; Harrison, Ben J; Castle, David

2015-08-01

We aim to provide a clinically focused review of the neurobiological literature in body dysmorphic disorder (BDD), with a focus on structural and functional neuroimaging. There has been a recent influx of studies examining the underlying neurobiology of BDD using structural and functional neuroimaging methods. Despite obvious symptom similarities with obsessive-compulsive disorder (OCD), no study to date has directly compared the two groups using neuroimaging techniques. Studies have established that there are limbic and visual cortex abnormalities in BDD, in contrast to fronto-striatal differences in OCD. Such data suggests affect or visual training maybe useful in BDD. © The Royal Australian and New Zealand College of Psychiatrists 2015.

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

Pharmacological imaging as a tool to visualise dopaminergic neurotoxicity.

PubMed

Schrantee, A; Reneman, L

2014-09-01

Dopamine abnormalities underlie a wide variety of psychopathologies, including ADHD and schizophrenia. A new imaging technique, pharmacological magnetic resonance imaging (phMRI), is a promising non-invasive technique to visualize the dopaminergic system in the brain. In this review we explore the clinical potential of phMRI in detecting dopamine dysfunction or neurotoxicity, assess its strengths and weaknesses and identify directions for future research. Preclinically, phMRI is able to detect severe dopaminergic abnormalities quite similar to conventional techniques such as PET and SPECT. phMRI benefits from its high spatial resolution and the possibility to visualize both local and downstream effects of dopaminergic neurotransmission. In addition, it allows for repeated measurements and assessments in vulnerable populations. The major challenge is the complex interpretation of phMRI results. Future studies in patients with dopaminergic abnormalities need to confirm the currently reviewed preclinical findings to validate the technique in a clinical setting. Eventually, based on the current review we expect that phMRI can be of use in a clinical setting involving vulnerable populations (such as children and adolescents) for diagnosis and monitoring treatment efficacy. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Copyright © 2013 Elsevier Ltd. All rights reserved.

“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

[Savant or idiot savant syndrome].

PubMed

Muñoz-Yunta, J A; Ortiz-Alonso, T; Amo, C; Fernández-Lucas, A; Maestú, F; Palau-Baduell, M

2003-02-01

Savant syndrome is currently still very mysterious, yet, thanks to the progress made in neuroimaging studies and especially MSI (Magnetic Source Imaging) techniques, a little more is now known about it. The theory, formulated many years ago, about damage to the left hemisphere of the brain has been supported by functional neuroimaging. Its relation to developmental disorders or to autism spectrum disorders is far more justified today and can be explained on the basis of its neuropathology. We present a study based on a review of the scientific literature concerning the syndrome, from the first time it was described back in 1789 by Benjamin Rush up to the present day. We comment on its epidemiology and positive clinical manifestations, involving brilliant artistic talent and dazzling memory, but also the negative aspects suffered by these autistic patients. The most important theories are discussed together with the clinical coincidence with frontotemporal dementia and the responsibility of the right hemisphere when there are alterations in the contralateral hemisphere. The latest contributions made by Positron Emission Tomography and magnetoencephalography will be discussed and a mini-video of a personal case will be projected.

Across the consciousness continuum—from unresponsive wakefulness to sleep

PubMed Central

Blume, Christine; del Giudice, Renata; Wislowska, Malgorzata; Lechinger, Julia; Schabus, Manuel

2015-01-01

Advances in the development of new paradigms as well as in neuroimaging techniques nowadays enable us to make inferences about the level of consciousness patients with disorders of consciousness (DOC) retain. They, moreover, allow to predict their probable development. Today, we know that certain brain responses (e.g., event-related potentials or oscillatory changes) to stimulation, circadian rhythmicity, the presence or absence of sleep patterns as well as measures of resting state brain activity can serve the diagnostic and prognostic evaluation process. Still, the paradigms we are using nowadays do not allow to disentangle VS/UWS and minimally conscious state (MCS) patients with the desired reliability and validity. Furthermore, even rather well-established methods have, unfortunately, not found their way into clinical routine yet. We here review current literature as well as recent findings from our group and discuss how neuroimaging methods (fMRI, PET) and particularly electroencephalography (EEG) can be used to investigate cognition in DOC or even to assess the degree of residual awareness. We, moreover, propose that circadian rhythmicity and sleep in brain-injured patients are promising fields of research in this context. PMID:25805982

Music Performance As an Experimental Approach to Hyperscanning Studies

PubMed Central

Acquadro, Michaël A. S.; Congedo, Marco; De Riddeer, Dirk

2016-01-01

Humans are fundamentally social and tend to create emergent organizations when interacting with each other; from dyads to families, small groups, large groups, societies, and civilizations. The study of the neuronal substrate of human social behavior is currently gaining momentum in the young field of social neuroscience. Hyperscanning is a neuroimaging technique by which we can study two or more brains simultaneously while participants interact with each other. The aim of this article is to discuss several factors that we deem important in designing hyperscanning experiments. We first review hyperscanning studies performed by means of electroencephalography (EEG) that have been relying on a continuous interaction paradigm. Then, we provide arguments for favoring ecological paradigms, for studying the emotional component of social interactions and for performing longitudinal studies, the last two aspects being largely neglected so far in the hyperscanning literature despite their paramount importance in social sciences. Based on these premises, we argue that music performance is a suitable experimental setting for hyperscanning and that for such studies EEG is an appropriate choice as neuroimaging modality. PMID:27252641

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…

[Non-medical applications for brain MRI: Ethical considerations].

PubMed

Sarrazin, S; Fagot-Largeault, A; Leboyer, M; Houenou, J

2015-04-01

The recent neuroimaging techniques offer the possibility to better understand complex cognitive processes that are involved in mental disorders and thus have become cornerstone tools for research in psychiatry. The performances of functional magnetic resonance imaging are not limited to medical research and are used in non-medical fields. These recent applications represent new challenges for bioethics. In this article we aim at discussing the new ethical issues raised by the applications of the latest neuroimaging technologies to non-medical fields. We included a selection of peer-reviewed English medical articles after a search on NCBI Pubmed database and Google scholar from 2000 to 2013. We screened bibliographical tables for supplementary references. Websites of governmental French institutions implicated in ethical questions were also screened for governmental reports. Findings of brain areas supporting emotional responses and regulation have been used for marketing research, also called neuromarketing. The discovery of different brain activation patterns in antisocial disorder has led to changes in forensic psychiatry with the use of imaging techniques with unproven validity. Automated classification algorithms and multivariate statistical analyses of brain images have been applied to brain-reading techniques, aiming at predicting unconscious neural processes in humans. We finally report the current position of the French legislation recently revised and discuss the technical limits of such techniques. In the near future, brain imaging could find clinical applications in psychiatry as diagnostic or predictive tools. However, the latest advances in brain imaging are also used in non-scientific fields raising key ethical questions. Involvement of neuroscientists, psychiatrists, physicians but also of citizens in neuroethics discussions is crucial to challenge the risk of unregulated uses of brain imaging. Copyright © 2014 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

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

Minati, Ludovico

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. Givenmore » 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.« less

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

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.

Gray matter abnormalities in opioid-dependent patients: A neuroimaging meta-analysis.

PubMed

Wollman, Scott C; Alhassoon, Omar M; Hall, Matthew G; Stern, Mark J; Connors, Eric J; Kimmel, Christine L; Allen, Kenneth E; Stephan, Rick A; Radua, Joaquim

2017-09-01

Prior research utilizing whole-brain neuroimaging techniques has identified structural differences in gray matter in opioid-dependent individuals. However, the results have been inconsistent. The current study meta-analytically examines the neuroimaging findings of studies published before 2016 comparing opioid-dependent individuals to drug-naïve controls. Exhaustive search of five databases yielded 12 studies that met inclusion criteria. Anisotropic Effect-Size Seed-Based d Mapping (AES-SDM) was used to analyze the data extracted by three independent researchers. Voxel-based AES-SDM distinguishes increases and decreases in brain matter significant at the whole-brain level. AES-SDM identified the fronto-temporal region, bilaterally, as being the primary site of gray matter deficits associated with opioid use. Moderator analysis revealed that length of opioid use was negatively associated with gray matter in the left cerebellar vermis and the right Rolandic operculum, including the insula. Meta-regression revealed no remaining significant areas of gray matter reductions, except in the precuneus, following longer abstinence from opioids. Opioid-dependent individuals had significantly less gray matter in several regions that play a key role in cognitive and affective processing. The findings provide evidence that opioid dependence may result in the breakdown of two distinct yet highly overlapping structural and functional systems. These are the fronto-cerebellar system that might be more responsible for impulsivity, compulsive behaviors, and affective disturbances and the fronto-insular system that might account more for the cognitive and decision-making impairments.

A three-wavelength multi-channel brain functional imager based on digital lock-in photon-counting technique

NASA Astrophysics Data System (ADS)

Ding, Xuemei; Wang, Bingyuan; Liu, Dongyuan; Zhang, Yao; He, Jie; Zhao, Huijuan; Gao, Feng

2018-02-01

During the past two decades there has been a dramatic rise in the use of functional near-infrared spectroscopy (fNIRS) as a neuroimaging technique in cognitive neuroscience research. Diffuse optical tomography (DOT) and optical topography (OT) can be employed as the optical imaging techniques for brain activity investigation. However, most current imagers with analogue detection are limited by sensitivity and dynamic range. Although photon-counting detection can significantly improve detection sensitivity, the intrinsic nature of sequential excitations reduces temporal resolution. To improve temporal resolution, sensitivity and dynamic range, we develop a multi-channel continuous-wave (CW) system for brain functional imaging based on a novel lock-in photon-counting technique. The system consists of 60 Light-emitting device (LED) sources at three wavelengths of 660nm, 780nm and 830nm, which are modulated by current-stabilized square-wave signals at different frequencies, and 12 photomultiplier tubes (PMT) based on lock-in photon-counting technique. This design combines the ultra-high sensitivity of the photon-counting technique with the parallelism of the digital lock-in technique. We can therefore acquire the diffused light intensity for all the source-detector pairs (SD-pairs) in parallel. The performance assessments of the system are conducted using phantom experiments, and demonstrate its excellent measurement linearity, negligible inter-channel crosstalk, strong noise robustness and high temporal resolution.

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

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.

Open Science CBS Neuroimaging Repository: Sharing ultra-high-field MR images of the brain.

PubMed

Tardif, Christine Lucas; Schäfer, Andreas; Trampel, Robert; Villringer, Arno; Turner, Robert; Bazin, Pierre-Louis

2016-01-01

Magnetic resonance imaging at ultra high field opens the door to quantitative brain imaging at sub-millimeter isotropic resolutions. However, novel image processing tools to analyze these new rich datasets are lacking. In this article, we introduce the Open Science CBS Neuroimaging Repository: a unique repository of high-resolution and quantitative images acquired at 7 T. The motivation for this project is to increase interest for high-resolution and quantitative imaging and stimulate the development of image processing tools developed specifically for high-field data. Our growing repository currently includes datasets from MP2RAGE and multi-echo FLASH sequences from 28 and 20 healthy subjects respectively. These datasets represent the current state-of-the-art in in-vivo relaxometry at 7 T, and are now fully available to the entire neuroimaging community. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Functions of the human frontoparietal attention network: Evidence from neuroimaging

PubMed Central

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

2016-01-01

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

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

PubMed

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

2014-06-01

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

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

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

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

Neuroinformatics challenges to the structural, connectomic, functional and electrophysiological multimodal imaging of human traumatic brain injury

PubMed Central

Goh, S. Y. Matthew; Irimia, Andrei; Torgerson, Carinna M.; Horn, John D. Van

2014-01-01

Throughout the past few decades, the ability to treat and rehabilitate traumatic brain injury (TBI) patients has become critically reliant upon the use of neuroimaging to acquire adequate knowledge of injury-related effects upon brain function and recovery. As a result, the need for TBI neuroimaging analysis methods has increased in recent years due to the recognition that spatiotemporal computational analyses of TBI evolution are useful for capturing the effects of TBI dynamics. At the same time, however, the advent of such methods has brought about the need to analyze, manage, and integrate TBI neuroimaging data using informatically inspired approaches which can take full advantage of their large dimensionality and informational complexity. Given this perspective, we here discuss the neuroinformatics challenges for TBI neuroimaging analysis in the context of structural, connectivity, and functional paradigms. Within each of these, the availability of a wide range of neuroimaging modalities can be leveraged to fully understand the heterogeneity of TBI pathology; consequently, large-scale computer hardware resources and next-generation processing software are often required for efficient data storage, management, and analysis of TBI neuroimaging data. However, each of these paradigms poses challenges in the context of informatics such that the ability to address them is critical for augmenting current capabilities to perform neuroimaging analysis of TBI and to improve therapeutic efficacy. PMID:24616696

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

Neuroimaging of the Periaqueductal Gray: State of the Field

PubMed Central

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

2011-01-01

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

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.

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

Current Trends in Intraoperative Optical Imaging for Functional Brain Mapping and Delineation of Lesions of Language Cortex

PubMed Central

Prakash, Neal; Uhleman, Falk; Sheth, Sameer A.; Bookheimer, Susan; Martin, Neil; Toga, Arthur W.

2009-01-01

Resection of a cerebral arteriovenous malformation (AVM), epileptic focus, or glioma, ideally has a prerequisite of microscopic delineation of the lesion borders in relation to the normal gray and white matter that mediate critical functions. Currently, Wada testing and functional magnetic resonance imaging (fMRI) are used for preoperative mapping of critical function, whereas electrical stimulation mapping (ESM) is used for intraoperative mapping. For lesion delineation, MRI and positron emission tomography (PET) are used preoperatively, whereas microscopy and histological sectioning are used intraoperatively. However, for lesions near eloquent cortex, these imaging techniques may lack sufficient resolution to define the relationship between the lesion and language function, and thus not accurately determine which patients will benefit from neurosurgical resection of the lesion without iatrogenic aphasia. Optical techniques such as intraoperative optical imaging of intrinsic signals (iOIS) show great promise for the precise functional mapping of cortices, as well as delineation of the borders of AVMs, epileptic foci, and gliomas. Here we first review the physiology of neuroimaging, and then progress towards the validation and justification of using intraoperative optical techniques, especially in relation to neurosurgical planning of resection AVMs, epileptic foci, and gliomas near or in eloquent cortex. We conclude with a short description of potential novel intraoperative optical techniques. PMID:18786643

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

PubMed Central

Davis, Tyler; Love, Bradley C.; Preston, Alison R.

2012-01-01

Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust their representations to support behavior in future encounters. Many techniques that are available to understand the neural basis of category learning assume that the multiple processes that subserve it can be neatly separated between different trials of an experiment. Model-based functional magnetic resonance imaging offers a promising tool to separate multiple, simultaneously occurring processes and bring the analysis of neuroimaging data more in line with category learning’s dynamic and multifaceted nature. We use model-based imaging to explore the neural basis of recognition and entropy signals in the medial temporal lobe and striatum that are engaged while participants learn to categorize novel stimuli. Consistent with theories suggesting a role for the anterior hippocampus and ventral striatum in motivated learning in response to uncertainty, we find that activation in both regions correlates with a model-based measure of entropy. Simultaneously, separate subregions of the hippocampus and striatum exhibit activation correlated with a model-based recognition strength measure. Our results suggest that model-based analyses are exceptionally useful for extracting information about cognitive processes from neuroimaging data. Models provide a basis for identifying the multiple neural processes that contribute to behavior, and neuroimaging data can provide a powerful test bed for constraining and testing model predictions. PMID:22746951

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

PubMed

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

2016-10-01

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

The role of cerebral spinal fluid in light propagation through the mouse head: improving fluorescence tomography with Monte Carlo modeling

NASA Astrophysics Data System (ADS)

Ancora, Daniele; Zacharopoulos, Athanasios; Ripoll, Jorge; Zacharakis, Giannis

2016-03-01

Optical Neuroimaging is a highly dynamical field of research owing to the combination of many advanced imaging techniques and computational tools that uncovered unexplored paths through the functioning of the brain. Light propagation modelling through such complicated structures has always played a crucial role as the basis for a high resolution and quantitative imaging where even the slightest improvement could lead to significant results. Fluorescence Diffuse Optical Tomography (fDOT), a widely used technique for three dimensional imaging of small animals and tissues, has been proved to be inaccurate for neuroimaging the mouse head without the knowledge of a-priori anatomical information of the subject. Commonly a normalized Born approximation model is used in fDOT reconstruction based on forward photon propagation using Diffusive Equation (DE) which has strong limitations in the optically clear regime. The presence of the Cerebral Spinal Fluid (CSF) instead, a thin optically clear layer surrounding the brain, can be more accurately taken into account using Monte Carlo approaches which nowadays is becoming more usable thanks to parallelized GPU algorithms. In this work we discuss the results of a synthetic experimental comparison, resulting to the increase of the accuracy for the Born approximation by introducing the CSF layer in a realistic mouse head structure with respect to the current model. We point out the importance of such clear layer for complex geometrical models, while for simple slab phantoms neglecting it does not introduce a significant error.

Bio-image warehouse system: concept and implementation of a diagnosis-based data warehouse for advanced imaging modalities in neuroradiology.

PubMed

Minati, L; Ghielmetti, F; Ciobanu, V; D'Incerti, L; Maccagnano, C; Bizzi, A; Bruzzone, M G

2007-03-01

Advanced neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), chemical shift spectroscopy imaging (CSI), diffusion tensor imaging (DTI), and perfusion-weighted imaging (PWI) create novel challenges in terms of data storage and management: huge amounts of raw data are generated, the results of analysis may depend on the software and settings that have been used, and most often intermediate files are inherently not compliant with the current DICOM (digital imaging and communication in medicine) standard, as they contain multidimensional complex and tensor arrays and various other types of data structures. A software architecture, referred to as Bio-Image Warehouse System (BIWS), which can be used alongside a radiology information system/picture archiving and communication system (RIS/PACS) system to store neuroimaging data for research purposes, is presented. The system architecture is conceived with the purpose of enabling to query by diagnosis according to a predefined two-layered classification taxonomy. The operational impact of the system and the time needed to get acquainted with the web-based interface and with the taxonomy are found to be limited. The development of modules enabling automated creation of statistical templates is proposed.

A Review of Neuroimaging Findings in Repetitive Brain Trauma

PubMed Central

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

2017-01-01

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

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

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

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…

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.

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.

Resting-state Abnormalities in Heroin-dependent Individuals.

PubMed

Pandria, Niki; Kovatsi, Leda; Vivas, Ana B; Bamidis, Panagiotis D

2018-05-15

Drug addiction is a major health problem worldwide. Recent neuroimaging studies have shed light into the underlying mechanisms of drug addiction as well as its consequences to the human brain. The most vulnerable, to heroin addiction, brain regions have been reported to be specific prefrontal, parietal, occipital, and temporal regions, as well as, some subcortical regions. The brain regions involved are usually linked with reward, motivation/drive, memory/learning, inhibition as well as emotional control and seem to form circuits that interact with each other. So, along with neuroimaging studies, recent advances in resting-state dynamics might allow further assessments upon the multilayer complexity of addiction. In the current manuscript, we comprehensively review and discuss existing resting-state neuroimaging findings classified into three overlapping and interconnected groups: functional connectivity alterations, structural deficits and abnormal topological properties. Moreover, behavioral traits of heroin-addicted individuals as well as the limitations of the currently available studies are also reviewed. Finally, in need of a contemporary therapy a multimodal therapeutic approach is suggested using classical treatment practices along with current neurotechonologies, such as neurofeedback and goal-oriented video-games. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

Smucny, Jason; Tregellas, Jason R

2018-01-01

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

Neuroimaging of Human Balance Control: A Systematic Review

PubMed Central

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

2017-01-01

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

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.

[The nature, diagnosis and treatment of post-concussion syndrome].

PubMed

Muñoz-Céspedes, J M; Pelegrín-Valero, C; Tirapu-Ustarroz, J; Fernández-Guinea, S

1998-11-01

The relationship between brief loss of consciousness, subsequent cognitive and emotional complaints, and impact on daily functioning continues to be hotly debated. In this paper the strong variability about prevalence of the postconcussional syndrome found in several studies is outstanding and the main issues of this disagreement are suggested. Recent neuroimaging techniques are discussed and some neuropsychological measures are suggested. Currents models (organic/psychogenic) of postconcussional symptoms are reviewed, and a multifactorial model which integrates biological factors with the relevance of neuropsychological deficits--attention, memory, speed of information processing--and coping process is proposed. Finally, according with this model, we conclude with some suggestions to improve neuropsychological intervention and medical treatment of these patients.

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

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.

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

Parvaz M. A.; Parvaz, M.A.; Alia-Klein, N.

In this review, we highlight the role of neuroimaging techniques in studying the emotional and cognitive-behavioral components of the addiction syndrome by focusing on the neural substrates subserving them. The phenomenology of drug addiction can be characterized by a recurrent pattern of subjective experiences that includes drug intoxication, craving, bingeing, and withdrawal with the cycle culminating in a persistent preoccupation with obtaining, consuming, and recovering from the drug. In the past two decades, imaging studies of drug addiction have demonstrated deficits in brain circuits related to reward and impulsivity. The current review focuses on studies employing positron emission tomography (PET),more » functional magnetic resonance imaging (fMRI), and electroencephalography (EEG) to investigate these behaviors in drug-addicted human populations. We begin with a brief account of drug addiction followed by a technical account of each of these imaging modalities. We then discuss how these techniques have uniquely contributed to a deeper understanding of addictive behaviors.« less

Is advanced neuroimaging for neuroradiologists? A systematic review of the scientific literature of the last decade.

PubMed

Cocozza, Sirio; Russo, Camilla; Pontillo, Giuseppe; Ugga, Lorenzo; Macera, Antonio; Cervo, Amedeo; De Liso, Maria; Di Paolo, Nilde; Ginocchio, Maria Isabella; Giordano, Flavio; Leone, Giuseppe; Rusconi, Giovanni; Stanzione, Arnaldo; Briganti, Francesco; Quarantelli, Mario; Caranci, Ferdinando; D'Amico, Alessandra; Elefante, Andrea; Tedeschi, Enrico; Brunetti, Arturo

2016-12-01

To evaluate if advanced neuroimaging research is mainly conducted by imaging specialists, we investigated the number of first authorships by radiologists and non-radiologist scientists in articles published in the field of advanced neuroimaging in the past 10 years. Articles in the field of advanced neuroimaging identified in this retrospective bibliometric analysis were divided in four groups, depending on the imaging technique used. For all included studies, educational background of the first authors was recorded (based on available online curriculum vitae) and classified in subgroups, depending on their specialty. Finally, journal impact factors were recorded and comparatively assessed among subgroups as a metric of research quality. A total number of 3831 articles were included in the study. Radiologists accounted as first authors for only 12.8 % of these publications, while 56.9 % of first authors were researchers without a medical degree. Mean impact factor (IF) of journals with non-MD researchers as first authors was significantly higher than the MD subgroup (p < 10 -20 ), while mean IF of journals with radiologists as first authors was significantly lower than articles authored by other MD specialists (p < 10 -11 ). The majority of the studies in the field of advanced neuroimaging in the last decade is conducted by professional figures other than radiologists, who account for less than the 13 % of the publications. Furthermore, the mean IF value of radiologists-authored articles was the lowest among all subgroups. These results, taken together, should question the radiology community about its future role in the development of advanced neuroimaging.

Imaging of Hemorrhagic Stroke.

PubMed

Hakimi, Ryan; Garg, Ankur

2016-10-01

Hemorrhagic stroke comprises approximately 15% to 20% of all strokes. This article provides readers with an understanding of the indications and significance of various neuroimaging techniques available for patients presenting with hemorrhagic strokes of distinct causes. The most common initial neuroimaging study is a noncontrast head CT, which allows for the identification of hemorrhage. Once an intracranial hemorrhage has been identified, the pattern of blood and the patient's medical history, neurologic examination, and laboratory studies lead the practitioner to pursue further neuroimaging studies to guide the medical, surgical, and interventional management. Given that hemorrhagic stroke constitutes a heterogeneous collection of diagnoses, the subsequent neuroimaging pathway necessary to better evaluate and care for these patients is variable based on the etiology.With an increasing incidence and prevalence of atrial fibrillation associated with the aging population and the introduction of three new direct factor Xa inhibitors and one direct thrombin inhibitor to complement vitamin K antagonists, oral anticoagulant use continues to increase. Patients on oral anticoagulants have a sevenfold to tenfold increased risk for intracerebral hemorrhage (ICH). Furthermore, patients who have an ICH associated with oral anticoagulant use have a higher mortality rate than those with primary ICH. Despite the reduced incidence of hypertension-related ICH over the past decade, it is expected that the incidence of ICH will continue to increase. Neuroimaging studies are integral to the identification of hemorrhagic stroke, determination of the underlying etiology, prevention of hematoma expansion, treatment of acute complications, and treatment of the underlying etiology, if indicated. Neuroimaging is essential for prognostication and thus directly impacts patient care.

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

Distinguished Neuropsychologist Award Lecture 1999. The lesion(s) in traumatic brain injury: implications for clinical neuropsychology.

PubMed

Bigler, E D

2001-02-01

This paper overviews the current status of neuroimaging in neuropsychological outcome in traumatic brain injury (TBI). The pathophysiology of TBI is reviewed and integrated with expected neuroimaging and neuropsychological findings. The integration of clinical and quantitative magnetic resonance (QMR) imaging is the main topic of review, but these findings are integrated with single photon emission computed tomography (SPECT) and magnetoencephalography (MEG). Various clinical caveats are offered for the clinician.

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies.

PubMed

Heggdal, Peder O Laugen; Brännström, Jonas; Aarstad, Hans Jørgen; Vassbotn, Flemming S; Specht, Karsten

2016-02-01

This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss. A literature search was performed in PubMed. Search criterions were peer reviewed original research papers in English completed by the 11th of March 2015. Twelve studies were found to use neuroimaging in subjects with unilateral hearing loss. An additional five papers not identified by the literature search were provided by a reviewer. Thus, a total of 17 studies were included in the review. Four different neuroimaging methods were used in these studies: Functional magnetic resonance imaging (fMRI) (n = 11), diffusion tensor imaging (DTI) (n = 4), T1/T2 volumetric images (n = 2), magnetic resonance spectroscopy (MRS) (n = 1). One study utilized two imaging methods (fMRI and T1 volumetric images). Neuroimaging techniques could provide valuable information regarding the effects of unilateral hearing loss on both auditory and non-auditory performance. fMRI-studies showing a bilateral BOLD-response in patients with unilateral hearing loss have not yet been followed by DTI studies confirming their microstructural correlates. In addition, the review shows that an auditory modality-specific deficit could affect multi-modal brain regions and their connections. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Understanding the impact of TV commercials: electrical neuroimaging.

PubMed

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

2012-01-01

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

Neuroimaging the Effectiveness of Substance Use Disorder Treatments.

PubMed

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

2016-09-01

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

[Functional neuroimaging of the brain structures associated with language in healthy individuals and patients with post-stroke aphasia].

PubMed

Alferova, V V; Mayorova, L A; Ivanova, E G; Guekht, A B; Shklovskij, V M

2017-01-01

The introduction of non-invasive functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI), in the practice of scientific and clinical research can increase our knowledge about the organization of cognitive processes, including language, in normal and reorganization of these cognitive functions in post-stroke aphasia. The article discusses the results of fMRI studies of functional organization of the cortex of a healthy adult's brain in the processing of various voice information as well as the main types of speech reorganization after post-stroke aphasia in different stroke periods. The concepts of 'effective' and 'ineffective' brain plasticity in post-stroke aphasia were considered. It was concluded that there was an urgent need for further comprehensive studies, including neuropsychological testing and several complementary methods of functional neuroimaging, to develop a phased treatment plan and neurorehabilitation of patients with post-stroke aphasia.

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.

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

Usefulness of the advanced neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state images for gamma knife radiosurgery and planning microsurgical procedures for skull base tumors.

PubMed

Hayashi, Motohiro; Chernov, Mikhail F; Tamura, Noriko; Yomo, Shoji; Tamura, Manabu; Horiba, Ayako; Izawa, Masahiro; Muragaki, Yoshihiro; Iseki, Hiroshi; Okada, Yoshikazu; Ivanov, Pavel; Régis, Jean; Takakura, Kintomo

2013-01-01

Gamma Knife radiosurgery (GKS) is currently performed with 0.1 mm preciseness, which can be designated microradiosurgery. It requires advanced methods for visualizing the target, which can be effectively attained by a neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state (CISS) images. Since 2003, the following thin-sliced images are routinely obtained before GKS of skull base lesions in our practice: axial CISS, gadolinium-enhanced axial CISS, gadolinium-enhanced axial modified time-of-flight (TOF), and axial computed tomography (CT). Fusion of "bone window" CT and magnetic resonance imaging (MRI), and detailed three-dimensional (3D) delineation of the anatomical structures are performed with the Leksell GammaPlan (Elekta Instruments AB). Recently, a similar technique has been also applied to evaluate neuroanatomy before open microsurgical procedures. Plain CISS images permit clear visualization of the cranial nerves in the subarachnoid space. Gadolinium-enhanced CISS images make the tumor "lucid" but do not affect the signal intensity of the cranial nerves, so they can be clearly delineated in the vicinity to the lesion. Gadolinium-enhanced TOF images are useful for 3D evaluation of the interrelations between the neoplasm and adjacent vessels. Fusion of "bone window" CT and MRI scans permits simultaneous assessment of both soft tissue and bone structures and allows 3D estimation and correction of MRI distortion artifacts. Detailed understanding of the neuroanatomy based on application of the advanced neuroimaging protocol permits performance of highly conformal and selective radiosurgical treatment. It also allows precise planning of the microsurgical procedures for skull base tumors.

A Review of Magnetic Resonance Imaging and Diffusion Tensor Imaging Findings in Mild Traumatic Brain Injury

PubMed Central

Shenton, ME; Hamoda, HM; Schneiderman, JS; Bouix, S; Pasternak, O; Rathi, Y; M-A, Vu; Purohit, MP; Helmer, K; Koerte, I; Lin, AP; C-F, Westin; Kikinis, R; Kubicki, M; Stern, RA; Zafonte, R

2013-01-01

Mild traumatic brain injury (mTBI), also referred to as concussion, remains a controversial diagnosis because the brain often appears quite normal on conventional computed tomography (CT) and magnetic resonance imaging (MRI) scans. Such conventional tools, however, do not adequately depict brain injury in mTBI because they are not sensitive to detecting diffuse axonal injuries (DAI), also described as traumatic axonal injuries (TAI), the major brain injuries in mTBI. Furthermore, for the 15 to 30% of those diagnosed with mTBI on the basis of cognitive and clinical symptoms, i.e., the “miserable minority,” the cognitive and physical symptoms do not resolve following the first three months post-injury. Instead, they persist, and in some cases lead to long-term disability. The explanation given for these chronic symptoms, i.e., postconcussive syndrome, particularly in cases where there is no discernible radiological evidence for brain injury, has led some to posit a psychogenic origin. Such attributions are made all the easier since both post-traumatic stress disorder (PTSD) and depression are frequently co-morbid with mTBI. The challenge is thus to use neuroimaging tools that are sensitive to DAI/TAI, such as diffusion tensor imaging (DTI), in order to detect brain injuries in mTBI. Of note here, recent advances in neuroimaging techniques, such as DTI, make it possible to characterize better extant brain abnormalities in mTBI. These advances may lead to the development of biomarkers of injury, as well as to staging of reorganization and reversal of white matter changes following injury, and to the ability to track and to characterize changes in brain injury over time. Such tools will likely be used in future research to evaluate treatment efficacy, given their enhanced sensitivity to alterations in the brain. In this article we review the incidence of mTBI and the importance of characterizing this patient population using objective radiological measures. Evidence is presented for detecting brain abnormalities in mTBI based on studies that use advanced neuroimaging techniques. Taken together, these findings suggest that more sensitive neuroimaging tools improve the detection of brain abnormalities (i.e., diagnosis) in mTBI. These tools will likely also provide important information relevant to outcome (prognosis), as well as play an important role in longitudinal studies that are needed to understand the dynamic nature of brain injury in mTBI. Additionally, summary tables of MRI and DTI findings are included. We believe that the enhanced sensitivity of newer and more advanced neuroimaging techniques for identifying areas of brain damage in mTBI will be important for documenting the biological basis of postconcussive symptoms, which are likely associated with subtle brain alterations, alterations that have heretofore gone undetected due to the lack of sensitivity of earlier neuroimaging techniques. Nonetheless, it is noteworthy to point out that detecting brain abnormalities in mTBI does not mean that other disorders of a more psychogenic origin are not co-morbid with mTBI and equally important to treat. They arguably are. The controversy of psychogenic versus physiogenic, however, is not productive because the psychogenic view does not carefully consider the limitations of conventional neuroimaging techniques in detecting subtle brain injuries in mTBI, and the physiogenic view does not carefully consider the fact that PTSD and depression, and other co-morbid conditions, may be present in those suffering from mTBI. Finally, we end with a discussion of future directions in research that will lead to the improved care of patients diagnosed with mTBI. PMID:22438191

A Training Program in Breast Cancer Research Using NMR Techniques

DTIC Science & Technology

2005-07-01

to explore the application NMR molecular imaging techniques developed in this program in detection of amyloid plaques in the Alzheimer diseased mouse...one is to utilize the molecular imaging technique to exploit new application in imaging of amyloid plaques in Alzheimer disease. A abridge of each...matched, non-demented elderly suggests that volumetric studies of ante-mortem neuroimages may provide an early marker of AD in aging populations. In

cTBS disruption of the supplementary motor area perturbs cortical sequence representation but not behavioural performance.

PubMed

Solopchuk, Oleg; Alamia, Andrea; Dricot, Laurence; Duque, Julie; Zénon, Alexandre

2017-12-01

Neuroimaging studies have repeatedly emphasized the role of the supplementary motor area (SMA) in motor sequence learning, but interferential approaches have led to inconsistent findings. Here, we aimed to test the role of the SMA in motor skill learning by combining interferential and neuroimaging techniques. Sixteen subjects were trained on simple finger movement sequences for 4 days. Afterwards, they underwent two neuroimaging sessions, in which they executed both trained and novel sequences. Prior to entering the scanner, the subjects received inhibitory transcranial magnetic stimulation (TMS) over the SMA or a control site. Using multivariate fMRI analysis, we confirmed that motor training enhances the neural representation of motor sequences in the SMA, in accordance with previous findings. However, although SMA inhibition altered sequence representation (i.e. between-sequence decoding accuracy) in this area, behavioural performance remained unimpaired. Our findings question the causal link between the neuroimaging correlate of elementary motor sequence representation in the SMA and sequence generation, calling for a more thorough investigation of the role of this region in performance of learned motor sequences. Copyright © 2017 Elsevier Inc. All rights reserved.

The Image and Data Archive at the Laboratory of Neuro Imaging.

PubMed

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

2016-01-01

The LONI Image and Data Archive (IDA)(1) is a repository for sharing and long-term preservation of neuroimaging and biomedical research data. Originally designed to archive strictly medical image files, the IDA has evolved over the last ten years and now encompasses the storage and dissemination of neuroimaging, clinical, biospecimen, and genetic data. In this article, we report upon the genesis of the IDA and how it currently securely manages data and protects data ownership. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Clinical neuroimaging in the preterm infant: Diagnosis and prognosis.

PubMed

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

2017-01-01

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

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 brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

PubMed

Gorgolewski, Krzysztof J; Auer, Tibor; Calhoun, Vince D; Craddock, R Cameron; Das, Samir; Duff, Eugene P; Flandin, Guillaume; Ghosh, Satrajit S; Glatard, Tristan; Halchenko, Yaroslav O; Handwerker, Daniel A; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B Nolan; Nichols, Thomas E; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A; Varoquaux, Gaël; Poldrack, Russell A

2016-06-21

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments

PubMed Central

Gorgolewski, Krzysztof J.; Auer, Tibor; Calhoun, Vince D.; Craddock, R. Cameron; Das, Samir; Duff, Eugene P.; Flandin, Guillaume; Ghosh, Satrajit S.; Glatard, Tristan; Halchenko, Yaroslav O.; Handwerker, Daniel A.; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B. Nolan; Nichols, Thomas E.; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A.; Varoquaux, Gaël; Poldrack, Russell A.

2016-01-01

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations. PMID:27326542

Mindfulness meditation-related pain relief: Evidence for unique brain mechanisms in the regulation of pain

PubMed Central

Zeidan, F.; Grant, J.A.; Brown, C.A.; McHaffie, J.G.; Coghill, R.C.

2013-01-01

The cognitive modulation of pain is influenced by a number of factors ranging from attention, beliefs, conditioning, expectations, mood, and the regulation of emotional responses to noxious sensory events. Recently, mindfulness meditation has been found attenuate pain through some of these mechanisms including enhanced cognitive and emotional control, as well as altering the contextual evaluation of sensory events. This review discusses the brain mechanisms involved in mindfulness meditation-related pain relief across different meditative techniques, expertise and training levels, experimental procedures, and neuroimaging methodologies. Converging lines of neuroimaging evidence reveal that mindfulness meditation-related pain relief is associated with unique appraisal cognitive processes depending on expertise level and meditation tradition. Moreover, it is postulated that mindfulness meditation-related pain relief may share a common final pathway with other cognitive techniques in the modulation of pain. PMID:22487846

[Possibilities of modern imaging technologies in early diagnosis of Alzheimer disease].

PubMed

Unschuld, Paul G

2015-04-01

Recent advances in neuroimaging technology and image analysis algorithms have significantly contributed to a better understanding of spatial and temporal aspects of brain change associated with Alzheimer Disease. The current review will demonstrate how functional (fMRI) and structural magnetic resonance imaging (MRI) techniques may be used to identify distinct patterns of brain change associated with disease progression and also increased risk for Alzheimer Disease. Moreover, Positron Emission Tomography (PET) based measures of glucosemetabolism (Fluorodeoxyglucose, FDG) and Amyloid-beta plaque density (11-C-Pittsburgh Compound B, PiB and 18-F) will be reviewed regarding their diagnostic value for assessing the individual degree of Alzheimer -pathology and thus complement the information provided by MRI and other clinical measures.

A Neurogenetic Approach to Impulsivity

PubMed Central

Congdon, Eliza; Canli, Turhan

2008-01-01

Impulsivity is a complex and multidimensional trait that is of interest to both personality psychologists and to clinicians. For investigators seeking the biological basis of personality traits, the use of neuroimaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) revolutionized personality psychology in less than a decade. Now, another revolution is under way, and it originates from molecular biology. Specifically, new findings in molecular genetics, the detailed mapping and the study of the function of genes, have shown that individual differences in personality traits can be related to individual differences within specific genes. In this article, we will review the current state of the field with respect to the neural and genetic basis of trait impulsivity. PMID:19012655

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

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…

Non-invasive brain stimulation in neurorehabilitation: local and distant effects for motor recovery

PubMed Central

Liew, Sook-Lei; Santarnecchi, Emilliano; Buch, Ethan R.; Cohen, Leonardo G.

2014-01-01

Non-invasive brain stimulation (NIBS) may enhance motor recovery after neurological injury through the causal induction of plasticity processes. Neurological injury, such as stroke, often results in serious long-term physical disabilities, and despite intensive therapy, a large majority of brain injury survivors fail to regain full motor function. Emerging research suggests that NIBS techniques, such as transcranial magnetic (TMS) and direct current (tDCS) stimulation, in association with customarily used neurorehabilitative treatments, may enhance motor recovery. This paper provides a general review on TMS and tDCS paradigms, the mechanisms by which they operate and the stimulation techniques used in neurorehabilitation, specifically stroke. TMS and tDCS influence regional neural activity underlying the stimulation location and also distant interconnected network activity throughout the brain. We discuss recent studies that document NIBS effects on global brain activity measured with various neuroimaging techniques, which help to characterize better strategies for more accurate NIBS stimulation. These rapidly growing areas of inquiry may hold potential for improving the effectiveness of NIBS-based interventions for clinical rehabilitation. PMID:25018714

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

PubMed

Pustilnik, Amanda C

2012-05-01

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

The development of neural correlates for memory formation

PubMed Central

Ofen, Noa

2012-01-01

A growing body of literature considers the development of episodic memory systems in the brain; the majority are neuroimaging studies conducted during memory encoding in order to explore developmental trajectories in memory formation. This review considers evidence from behavioral studies of memory development, neural correlates of memory formation in adults, and structural brain development, all of which form the foundation of a developmental cognitive neuroscience approach to memory development. I then aim to integrate the current evidence from developmental functional neuroimaging studies of memory formation with respect to three hypotheses. First, memory development reflects the development in the use of memory strategies, linked to prefrontal cortex. Second, developmental effects within the medial temporal lobes are more complex, and correspond to current notions about the nature in which the MTL support the formation of memory. Third, neurocognitive changes in content representation influence memory. Open issues and current directions are discussed. PMID:22414608

Venous compressions of the nerves in the lower limbs.

PubMed

Artico, M; Stevanato, G; Ionta, B; Cesaroni, A; Bianchi, E; Morselli, C; Grippaudo, F R

2012-06-01

The lower limbs are frequently involved in neurovascular compression syndromes, owing to their anatomical, vascular and muscular characteristics and to the orthostatic position. These syndromes were identified by exclusion, using neuroimaging techniques and treated by microsurgical techniques. Eight patients with a neurovascular compression syndrome due to venous vascular lesions in the lower limbs (popliteal fossa, proximal and medial third of the inferior limb, tarsal tunnel) were selected. The symptomatology was characterized by pain, Tinel's sign, hyperalgesia, allodynia, numbness along the nerve course and foot weakness: all were exacerbated by the standing position, thus suggesting a neurovascular compression syndrome. Diagnostic tools comprised Doppler ultrasonography, Electromyography, CT 3D and MRI. Treatment consisted of microsurgery with neurovascular dissection. Following surgical treatment, rapid pain relief and a partial recovery of neurological deficits (including the ability to walk) was observed within 8-10 months. An early diagnosis of NCS using various neuroimaging techniques and prompt treatment may improve the response to surgical therapy. The aim of the case studies described is to improve understanding of these pathologies thus enabling correct clinical decisions.

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

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

Neural mechanisms for the cannabinoid modulation of cognition and affect in man: a critical review of neuroimaging studies.

PubMed

Bhattacharyya, Sagnik; Atakan, Zerrin; Martin-Santos, Rocio; Crippa, Jose A; McGuire, Philip K

2012-01-01

Pharmacological challenge in conjunction with neuroimaging techniques has been employed for over two decades now to understand the neural basis of the cognitive, emotional and symptomatic effects of the main ingredients of cannabis, the most widely used illicit drug in the world. This selective critical review focuses on the human neuroimaging studies investigating the effects of delta-9- tetrahydrocannabinol (THC) and cannabidiol (CBD), the two main cannabinoids of interest present in the extract of the cannabis plant. These studies suggest that consistent with the polymorphic and heterogeneous nature of the effects of cannabis, THC and CBD have distinct and often opposing effects on widely distributed neural networks that include medial temporal and prefrontal cortex and striatum, brain regions that are rich in cannabinoid receptors and implicated in the pathophysiology of psychosis. They help elucidate the neurocognitive mechanisms underlying the acute induction of psychotic symptoms by cannabis and provide mechanistic understanding underlying the potential role of CBD as an anxiolytic and antipsychotic. Although there are ethical and methodological caveats, pharmacological neuroimaging studies such as those reviewed here may not only help model different aspects of the psychopathology of mental disorders such as schizophrenia and offer insights into their underlying mechanisms, but may suggest potentially new therapeutic targets for drug discovery.

The Psychology of Music: Rhythm and Movement.

PubMed

Levitin, Daniel J; Grahn, Jessica A; London, Justin

2018-01-04

The urge to move to music is universal among humans. Unlike visual art, which is manifest across space, music is manifest across time. When listeners get carried away by the music, either through movement (such as dancing) or through reverie (such as trance), it is usually the temporal qualities of the music-its pulse, tempo, and rhythmic patterns-that put them in this state. In this article, we review studies addressing rhythm, meter, movement, synchronization, entrainment, the perception of groove, and other temporal factors that constitute a first step to understanding how and why music literally moves us. The experiments we review span a range of methodological techniques, including neuroimaging, psychophysics, and traditional behavioral experiments, and we also summarize the current studies of animal synchronization, engaging an evolutionary perspective on human rhythmic perception and cognition.

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

Plasticity following early-life brain injury: Insights from quantitative MRI.

PubMed

Fiori, Simona; Guzzetta, Andrea

2015-03-01

Over the last decade, the application of novel advanced neuroimaging techniques to study congenital brain damage has provided invaluable insights into the mechanisms underlying early neuroplasticity. The concept that is clearly emerging, both from human and nun-human studies, is that functional reorganization in the immature brain is substantially different from that of the more mature, developed brain. This applies to the reorganization of language, the sensorimotor system, and the visual system. The rapid implementation and development of higher order imaging methods will offer increased, currently unavailable knowledge about the specific mechanisms of cerebral plasticity in infancy, which is essential to support the development of early therapeutic interventions aimed at supporting and enhancing functional reorganization during a time of greatest potential brain plasticity. Copyright © 2015. Published by Elsevier Inc.

Theories of Memory and Aging: A Look at the Past and a Glimpse of the Future

PubMed Central

Festini, Sara B.

2017-01-01

The present article reviews theories of memory and aging over the past 50 years. Particularly notable is a progression from early single-mechanism perspectives to complex multifactorial models proposed to account for commonly observed age deficits in memory function. The seminal mechanistic theories of processing speed, limited resources, and inhibitory deficits are discussed and viewed as especially important theories for understanding age-related memory decline. Additionally, advances in multivariate techniques including structural equation modeling provided new tools that led to the development of more complex multifactorial theories than existed earlier. The important role of neuroimaging is considered, along with the current prevalence of intervention studies. We close with predictions about new directions that future research on memory and aging will take. PMID:27257229

Aphasia: Current Concepts in Theory and Practice

PubMed Central

Tippett, Donna C.; Niparko, John K.; Hillis, Argye E.

2014-01-01

Recent advances in neuroimaging contribute to a new insights regarding brain-behavior relationships and expand understanding of the functional neuroanatomy of language. Modern concepts of the functional neuroanatomy of language invoke rich and complex models of language comprehension and expression, such as dual stream networks. Increasingly, aphasia is seen as a disruption of cognitive processes underlying language. Rehabilitation of aphasia incorporates evidence based and person-centered approaches. Novel techniques, such as methods of delivering cortical brain stimulation to modulate cortical excitability, such as repetitive transcranial magnetic stimulation and transcranial direct current stimulation, are just beginning to be explored. In this review, we discuss the historical context of the foundations of neuroscientific approaches to language. We sample the emergent theoretical models of the neural substrates of language and cognitive processes underlying aphasia that contribute to more refined and nuanced concepts of language. Current concepts of aphasia rehabilitation are reviewed, including the promising role of cortical stimulation as an adjunct to behavioral therapy and changes in therapeutic approaches based on principles of neuroplasticity and evidence-based/person-centered practice to optimize functional outcomes. PMID:24904925

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

Multimodal MRI for early diabetic mild cognitive impairment: study protocol of a prospective diagnostic trial.

PubMed

Yu, Ying; Sun, Qian; Yan, Lin-Feng; Hu, Yu-Chuan; Nan, Hai-Yan; Yang, Yang; Liu, Zhi-Cheng; Wang, Wen; Cui, Guang-Bin

2016-08-24

Type 2 diabetes mellitus (T2DM) is a risk factor for dementia. Mild cognitive impairment (MCI), an intermediary state between normal cognition and dementia, often occurs during the prodromal diabetic stage, making early diagnosis and intervention of MCI very important. Latest neuroimaging techniques revealed some underlying microstructure alterations for diabetic MCI, from certain aspects. But there still lacks an integrated multimodal MRI system to detect early neuroimaging changes in diabetic MCI patients. Thus, we intended to conduct a diagnostic trial using multimodal MRI techniques to detect early diabetic MCI that is determined by the Montreal Cognitive Assessment (MoCA). In this study, healthy controls, prodromal diabetes and diabetes subjects (53 subjects/group) aged 40-60 years will be recruited from the physical examination center of Tangdu Hospital. The neuroimaging and psychometric measurements will be repeated at a 0.5 year-interval for 2.5 years' follow-up. The primary outcome measures are 1) Microstructural and functional alterations revealed with multimodal MRI scans including structure magnetic resonance imaging (sMRI), resting state functional magnetic resonance imaging (rs-fMRI), diffusion kurtosis imaging (DKI), and three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL); 2) Cognition evaluation with MoCA. The second outcome measures are obesity, metabolic characteristics, lifestyle and quality of life. The study will provide evidence for the potential use of multimodal MRI techniques with psychometric evaluation in diagnosing MCI at prodromal diabetic stage so as to help decision making in early intervention and improve the prognosis of T2DM. This study has been registered to ClinicalTrials.gov ( NCT02420470 ) on April 2, 2015 and published on July 29, 2015.

[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.

Neuroimaging biomarkers of preterm brain injury: toward developing the preterm connectome

PubMed Central

Panigrahy, Ashok; Wisnowski, Jessica L.; Furtado, Andre; Lepore, Natasha; Paquette, Lisa; Bluml, Stefan

2013-01-01

For typically developing infants, the last trimester of fetal development extending into the first post-natal months is a period of rapid brain development. Infants who are born premature face significant risk of brain injury (e.g., intraventricular or germinal matrix hemorrhage and periventricular leukomalacia) from complications in the perinatal period and also potential long-term neurodevelopmental disabilities because these early injuries can interrupt normal brain maturation. Neuroimaging has played an important role in the diagnosis and management of the preterm infant. Both cranial US and conventional MRI techniques are useful in diagnostic and prognostic evaluation of preterm brain development and injury. Cranial US is highly sensitive for intraventricular hemorrhage IVH and provides prognostic information regarding cerebral palsy. Data are limited regarding the utility of MRI as a routine screening instrument for brain injury for all preterm infants. However, MRI might provide diagnostic or prognostic information regarding PVL and other types of preterm brain injury in the setting of specific clinical indications and risk factors. Further development of advanced MR techniques like volumetric MR imaging, diffusion tensor imaging, metabolic imaging (MR spectroscopy) and functional connectivity are necessary to provide additional insight into the molecular, cellular and systems processes that underlie brain development and outcome in the preterm infant. The adult concept of the “connectome” is also relevant in understanding brain networks that underlie the preterm brain. Knowledge of the preterm connectome will provide a framework for understanding preterm brain function and dysfunction, and potentially even a roadmap for brain plasticity. By combining conventional imaging techniques with more advanced techniques, neuroimaging findings will likely be used not only as diagnostic and prognostic tools, but also as biomarkers for long-term neurodevelopmental outcomes, instruments to assess the efficacy of neuroprotective agents and maneuvers in the NICU, and as screening instruments to appropriately select infants for longitudinal developmental interventions. PMID:22395719

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

PubMed

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

2013-01-15

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

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).

Brain Imaging in Children with Neurodevelopmental Disorders.

ERIC Educational Resources Information Center

Mantovani, John F.

1994-01-01

This article reviews neuroimaging techniques such as cranial ultrasound, computed tomography scanning, and magnetic resonance imaging. Their roles in the care of children with neurodevelopmental disabilities include identification of high-risk infants, establishment of the diagnosis and prognosis in affected children, and enhancement of discussion…

The addicted brain: imaging neurological complications of recreational drug abuse.

PubMed

Montoya-Filardi, A; Mazón, M

Recreational drug abuse represents a serious public health problem. Neuroimaging traditionally played a secondary role in this scenario, where it was limited to detecting acute vascular events. However, thanks to advances in knowledge about disease and in morphological and functional imaging techniques, radiologists have now become very important in the diagnosis of acute and chronic neurological complications of recreational drug abuse. The main complications are neurovascular disease, infection, toxicometabolic disorders, and brain atrophy. The nonspecific symptoms and denial of abuse make the radiologist's involvement fundamental in the management of these patients. Neuroimaging makes it possible to detect early changes and to suggest an etiological diagnosis in cases with specific patterns of involvement. We aim to describe the pattern of abuse and the pathophysiological mechanisms of the drugs with the greatest neurological repercussions as well as to illustrate the depiction of the acute and chronic cerebral complications on conventional and functional imaging techniques. Copyright © 2016 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

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.

Contemporary imaging of mild TBI: the journey toward diffusion tensor imaging to assess neuronal damage.

PubMed

Fox, W Christopher; Park, Min S; Belverud, Shawn; Klugh, Arnett; Rivet, Dennis; Tomlin, Jeffrey M

2013-04-01

To follow the progression of neuroimaging as a means of non-invasive evaluation of mild traumatic brain injury (mTBI) in order to provide recommendations based on reproducible, defined imaging findings. A comprehensive literature review and analysis of contemporary published articles was performed to study the progression of neuroimaging findings as a non-invasive 'biomarker' for mTBI. Multiple imaging modalities exist to support the evaluation of patients with mTBI, including ultrasound (US), computed tomography (CT), single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI). These techniques continue to evolve with the development of fractional anisotropy (FA), fiber tractography (FT), and diffusion tensor imaging (DTI). Modern imaging techniques, when applied in the appropriate clinical setting, may serve as a valuable tool for diagnosis and management of patients with mTBI. An understanding of modern neuroanatomical imaging will enhance our ability to analyse injury and recognize the manifestations of mTBI.

Intention, false beliefs, and delusional jealousy: insights into the right hemisphere from neurological patients and neuroimaging studies.

PubMed

Ortigue, Stephanie; Bianchi-Demicheli, Francesco

2011-01-01

Jealousy sits high atop of a list comprised of the most human emotional experiences, although its nature, rationale, and origin are poorly understood. In the past decade, a series of neurological case reports and neuroimaging findings have been particularly helpful in piecing together jealousy's puzzle. In order to understand and quantify the neurological factors that might be important in jealousy, we reviewed the current literature in this specific field. We made an electronic search, and examined all literature with at least an English abstract, through Mars 2010. The search identified a total of 20 neurological patients, who experienced jealousy in relation with a neurological disorder; and 22 healthy individuals, who experienced jealousy under experimental neuroimaging settings. Most of the clinical cases of reported jealousy after a stroke had delusional-type jealousy. Right hemispheric stroke was the most frequently reported neurological disorder in these patients, although there was a wide range of more diffuse neurological disorders that may be reported to be associated with different other types of jealousy. This is in line with recent neuroimaging data on false beliefs, moral judgments, and intention [mis]understanding. Together the present findings provide physicians and psychologists with a potential for high impact in understanding the neural mechanisms and treatment of jealousy. By combining findings from case reports and neuroimaging data, the present article allows for a novel and unique perspective, and explores new directions into the neurological jealous mind.

Intention, false beliefs, and delusional jealousy: Insights into the right hemisphere from neurological patients and neuroimaging studies

PubMed Central

Ortigue, Stephanie; Bianchi-Demicheli, Francesco

2011-01-01

Summary Jealousy sits high atop of a list comprised of the most human emotional experiences, although its nature, rationale, and origin are poorly understood. In the past decade, a series of neurological case reports and neuroimaging findings have been particularly helpful in piecing together jealousy’s puzzle. In order to understand and quantify the neurological factors that might be important in jealousy, we reviewed the current literature in this specific field. We made an electronic search, and examined all literature with at least an English abstract, through Mars 2010. The search identified a total of 20 neurological patients, who experienced jealousy in relation with a neurological disorder; and 22 healthy individuals, who experienced jealousy under experimental neuroimaging settings. Most of the clinical cases of reported jealousy after a stroke had delusional-type jealousy. Right hemispheric stroke was the most frequently reported neurological disorder in these patients, although there was a wide range of more diffuse neurological disorders that may be reported to be associated with different other types of jealousy. This is in line with recent neuroimaging data on false beliefs, moral judgments, and intention [mis]understanding. Together the present findings provide physicians and psychologists with a potential for high impact in understanding the neural mechanisms and treatment of jealousy. By combining findings from case reports and neuroimaging data, the present article allows for a novel and unique perspective, and explores new directions into the neurological jealous mind. PMID:21169919

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.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

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.

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

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

Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play

PubMed Central

Savitz, J B; Rauch, S L; Drevets, W C

2013-01-01

In response to queries about whether brain imaging technology has reached the point where it is useful for making a clinical diagnosis and for helping to guide treatment selection, the American Psychiatric Association (APA) has recently written a position paper on the Clinical Application of Brain Imaging in Psychiatry. The following perspective piece is based on our contribution to this APA position paper, which specifically emphasized the application of neuroimaging in mood disorders. We present an introductory overview of the challenges faced by researchers in developing valid and reliable biomarkers for psychiatric disorders, followed by a synopsis of the extant neuroimaging findings in mood disorders, and an evidence-based review of the current research on brain imaging biomarkers in adult mood disorders. Although there are a number of promising results, by the standards proposed below, we argue that there are currently no brain imaging biomarkers that are clinically useful for establishing diagnosis or predicting treatment outcome in mood disorders. PMID:23546169

Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play.

PubMed

Savitz, J B; Rauch, S L; Drevets, W C

2013-05-01

In response to queries about whether brain imaging technology has reached the point where it is useful for making a clinical diagnosis and for helping to guide treatment selection, the American Psychiatric Association (APA) has recently written a position paper on the Clinical Application of Brain Imaging in Psychiatry. The following perspective piece is based on our contribution to this APA position paper, which specifically emphasized the application of neuroimaging in mood disorders. We present an introductory overview of the challenges faced by researchers in developing valid and reliable biomarkers for psychiatric disorders, followed by a synopsis of the extant neuroimaging findings in mood disorders, and an evidence-based review of the current research on brain imaging biomarkers in adult mood disorders. Although there are a number of promising results, by the standards proposed below, we argue that there are currently no brain imaging biomarkers that are clinically useful for establishing diagnosis or predicting treatment outcome in mood disorders.

Wearable functional near infrared spectroscopy (fNIRS) and transcranial direct current stimulation (tDCS): expanding vistas for neurocognitive augmentation

PubMed Central

McKendrick, Ryan; Parasuraman, Raja; Ayaz, Hasan

2015-01-01

Contemporary studies with transcranial direct current stimulation (tDCS) provide a growing base of evidence for enhancing cognition through the non-invasive delivery of weak electric currents to the brain. The main effect of tDCS is to modulate cortical excitability depending on the polarity of the applied current. However, the underlying mechanism of neuromodulation is not well understood. A new generation of functional near infrared spectroscopy (fNIRS) systems is described that are miniaturized, portable, and include wearable sensors. These developments provide an opportunity to couple fNIRS with tDCS, consistent with a neuroergonomics approach for joint neuroimaging and neurostimulation investigations of cognition in complex tasks and in naturalistic conditions. The effects of tDCS on complex task performance and the use of fNIRS for monitoring cognitive workload during task performance are described. Also explained is how fNIRS + tDCS can be used simultaneously for assessing spatial working memory. Mobile optical brain imaging is a promising neuroimaging tool that has the potential to complement tDCS for realistic applications in natural settings. PMID:25805976

Neuroimaging in adult penetrating brain injury: a guide for radiographers

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

Temple, Nikki; Donald, Cortny; Skora, Amanda

Penetrating brain injuries (PBI) are a medical emergency, often resulting in complex damage and high mortality rates. Neuroimaging is essential to evaluate the location and extent of injuries, and to manage them accordingly. Currently, a myriad of imaging modalities are included in the diagnostic workup for adult PBI, including skull radiography, computed tomography (CT), magnetic resonance imaging (MRI) and angiography, with each modality providing their own particular benefits. This literature review explores the current modalities available for investigating PBI and aims to assist in decision making for the appropriate use of diagnostic imaging when presented with an adult PBI. Basedmore » on the current literature, the authors have developed an imaging pathway for adult penetrating brain injury that functions as both a learning tool and reference guide for radiographers and other health professionals. Currently, CT is recommended as the imaging modality of choice for the initial assessment of PBI patients, while MRI is important in the sub-acute setting where it aids prognosis prediction and rehabilitation planning, Additional follow-up imaging, such as angiography, should be dependent upon clinical findings.« less

Neuroimaging is a novel tool to understand the impact of environmental chemicals on neurodevelopment.

PubMed

Horton, Megan K; Margolis, Amy E; Tang, Cheuk; Wright, Robert

2014-04-01

The prevalence of childhood neurodevelopmental disorders has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of neurodevelopmental disorders. Very little information is known about the mechanistic processes by which environmental chemicals alter brain development. We review the recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Neuroimaging techniques (volumetric and functional MRI, diffusor tensor imaging, and magnetic resonance spectroscopy) have opened unprecedented access to study the developing human brain. These techniques are noninvasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. MRI is a powerful tool that allows in-vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure.

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

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

Cognitive Abilities Independent of IQ Correlate with Regional Brain Structure

ERIC Educational Resources Information Center

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

2008-01-01

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

Neuroanatomical Substrates of Social Cognition Dysfunction in Autism

ERIC Educational Resources Information Center

Pelphrey, Kevin; Adolphs, Ralph; Morris, James P.

2004-01-01

In this review article, we summarize recent progress toward understanding the neural structures and circuitry underlying dysfunctional social cognition in autism. We review selected studies from the growing literature that has used the functional neuroimaging techniques of cognitive neuroscience to map out the neuroanatomical substrates of social…

Neurobiology Research Findings: How the Brain Works during Reading

ERIC Educational Resources Information Center

Kweldju, Siusana

2015-01-01

In the past, neurobiology for reading was identical with neuropathology. Today, however, the advancement of modern neuroimaging techniques has contributed to the understanding of the reading processes of normal individuals. Neurobiology findings today have uncovered and illuminated the fundamental neural mechanism of reading. The findings have…

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury.

PubMed

Amyot, Franck; Arciniegas, David B; Brazaitis, Michael P; Curley, Kenneth C; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R; Manley, Geoffrey T; Pacifico, Anthony; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G; Stocker, Derek

2015-11-15

The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI.

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury

PubMed Central

Amyot, Franck; Arciniegas, David B.; Brazaitis, Michael P.; Curley, Kenneth C.; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R.; Manley, Geoffrey T.; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G.; Stocker, Derek

2015-01-01

Abstract The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI. PMID:26176603

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

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.

Non-invasive brain stimulation of the aging brain: State of the art and future perspectives.

PubMed

Tatti, Elisa; Rossi, Simone; Innocenti, Iglis; Rossi, Alessandro; Santarnecchi, Emiliano

2016-08-01

Favored by increased life expectancy and reduced birth rate, worldwide demography is rapidly shifting to older ages. The golden age of aging is not only an achievement but also a big challenge because of the load of the elderly on social and medical health care systems. Moreover, the impact of age-related decline of attention, memory, reasoning and executive functions on self-sufficiency emphasizes the need of interventions to maintain cognitive abilities at a useful degree in old age. Recently, neuroscientific research explored the chance to apply Non-Invasive Brain Stimulation (NiBS) techniques (as transcranial electrical and magnetic stimulation) to healthy aging population to preserve or enhance physiologically-declining cognitive functions. The present review will update and address the current state of the art on NiBS in healthy aging. Feasibility of NiBS techniques will be discussed in light of recent neuroimaging (either structural or functional) and neurophysiological models proposed to explain neural substrates of the physiologically aging brain. Further, the chance to design multidisciplinary interventions to maximize the efficacy of NiBS techniques will be introduced as a necessary future direction. Copyright © 2016 Elsevier B.V. All rights reserved.

Language mapping in children using resting-state functional connectivity: comparison with a task-based approach

NASA Astrophysics Data System (ADS)

Gallagher, Anne; Tremblay, Julie; Vannasing, Phetsamone

2016-12-01

Patients with brain tumor or refractory epilepsy may be candidates for neurosurgery. Presurgical evaluation often includes language investigation to prevent or reduce the risk of postsurgical language deficits. Current techniques involve significant limitations with pediatric populations. Recently, near-infrared spectroscopy (NIRS) has been shown to be a valuable neuroimaging technique for language localization in children. However, it typically requires the child to perform a task (task-based NIRS), which may constitute a significant limitation. Resting-state functional connectivity NIRS (fcNIRS) is an approach that can be used to identify language networks at rest. This study aims to assess the utility of fcNIRS in children by comparing fcNIRS to more conventional task-based NIRS for language mapping in 33 healthy participants: 25 children (ages 3 to 16) and 8 adults. Data were acquired at rest and during a language task. Results show very good concordance between both approaches for language localization (Dice similarity coefficient=0.81±0.13) and hemispheric language dominance (kappa=0.86, p<0.006). The fcNIRS technique may be a valuable tool for language mapping in clinical populations, including children and patients with cognitive and behavioral impairments.

Magnetoencephalography as a Tool in Psychiatric Research: Current Status and Perspective.

PubMed

Uhlhaas, Peter J; Liddle, Peter; Linden, David E J; Nobre, Anna C; Singh, Krish D; Gross, Joachim

2017-04-01

The application of neuroimaging to provide mechanistic insights into circuit dysfunctions in major psychiatric conditions and the development of biomarkers are core challenges in current psychiatric research. We propose that recent technological and analytic advances in magnetoencephalography (MEG), a technique that allows measurement of neuronal events directly and noninvasively with millisecond resolution, provides novel opportunities to address these fundamental questions. Because of its potential in delineating normal and abnormal brain dynamics, we propose that MEG provides a crucial tool to advance our understanding of pathophysiological mechanisms of major neuropsychiatric conditions, such as schizophrenia, autism spectrum disorders, and the dementias. We summarize the mechanisms underlying the generation of MEG signals and the tools available to reconstruct generators and underlying networks using advanced source-reconstruction techniques. We then surveyed recent studies that have used MEG to examine aberrant rhythmic activity in neuropsychiatric disorders. This was followed by links with preclinical research that has highlighted possible neurobiological mechanisms, such as disturbances in excitation/inhibition parameters, that could account for measured changes in neural oscillations. Finally, we discuss challenges as well as novel methodological developments that could pave the way for widespread application of MEG in translational research with the aim of developing biomarkers for early detection and diagnosis.

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.

Neuroimaging in ophthalmology

PubMed Central

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

2012-01-01

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

[Neuroscience in the Courtroom: From responsibility to dangerousness, ethical issues raised by the new French law].

PubMed

Gkotsi, G-M; Moulin, V; Gasser, J

2015-10-01

In the past few years, spectacular progress in neuroscience has led to the emergence of a new interdisciplinary field, the so-called "neurolaw" whose goal is to explore the effects of neuroscientific discoveries on legal proceedings and legal rules and standards. In the United States, a number of neuroscientific researches are designed specifically to explore legally relevant topics and a case-law has already been developed. In Europe, neuroscientific evidence is increasingly being used in criminal courtrooms, as part of psychiatric testimony, nourishing the debate about the legal implications of brain research in psychiatric-legal settings. Though largely debated, up to now the use of neuroscience in legal contexts had not specifically been regulated by any legislation. In 2011, with the new bioethics law, France has become the first country to admit by law the use of brain imaging in judicial expertise. According to the new law, brain imaging techniques can be used only for medical purposes, or scientific research, or in the context of judicial expertise. This study aims to give an overview of the current state of the neurolaw in the US and Europe, and to investigate the ethical issues raised by this new law and its potential impact on the rights and civil liberties of the offenders. An overview of the emergence and development of "neurolaw" in the United States and Europe is given. Then, the new French law is examined in the light of the relevant debates in the French parliament. Consequently, we outline the current tendencies in Neurolaw literature to focus on assessments of responsibility, rather than dangerousness. This tendency is analysed notably in relation to the legal context relevant to criminal policies in France, where recent changes in the legislation and practice of forensic psychiatry show that dangerousness assessments have become paramount in the process of judicial decision. Finally, the potential interpretations of neuroscientific data introduced into psychiatric testimonies by judges are explored. The examination of parliamentary debates showed that the new French law allowing neuroimaging techniques in judicial expertise was introduced in the aim to provide a legal framework that would protect the subject against potential misuses of neuroscience. The underlying fear above all, was that this technology be used as a lie detector, or as a means to predict the subject's behaviour. However, the possibility of such misuse remains open. Contrary to the legislator's wish, the defendant is not fully guaranteed against uses of neuroimaging techniques in criminal courts that would go against their interests and rights. In fact, the examination of the recently adopted legislation in France shows that assessments of dangerousness and of risk of recidivism have become central elements of the criminal policy, which makes it possible, if not likely that neuroimaging techniques be used for the evaluation of the dangerousness of the defendant. This could entail risks for the latter, as judges could perceive neuroscientific data as hard evidence, more scientific and reliable than the soft data of traditional psychiatry. If such neuroscientific data are interpreted as signs of potential dangerousness of a subject rather than as signs of criminal responsibility, defendants may become subjected to longer penalties or measures aiming to ensure public safety in the detriment of their freedom. In the current context of accentuated societal need for security, the judge and the expert-psychiatrist are increasingly asked to evaluate the dangerousness of a subject, regardless of their responsibility. Influenced by this policy model, the judge might tend to use neuroscientific data introduced by an expert as signs of dangerousness. Such uses, especially when they subjugate an individual's interest to those of society, might entail serious threats to an individual's freedom and civil liberties. Copyright © 2014 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Neuroscience, Education and Special Education

ERIC Educational Resources Information Center

Goswami, Usha

2004-01-01

The discipline of neuroscience draws from the fields of neurology, psychology, physiology and biology, but is best understood in the wider world as brain science. Of particular interest for education is the development of techniques for imaging the brain as it performs different cognitive functions. Cognitive neuroimaging has already led to…

Plasticity during Childhood and Adolescence: Innovative Approaches to Investigating Neurocognitive Development

ERIC Educational Resources Information Center

Cohen Kadosh, Kathrin; Linden, David E. J.; Lau, Jennifer Y. F.

2013-01-01

Adolescence is a period of profound change, which holds substantial developmental milestones, but also unique challenges to the individual. In this opinion paper, we highlight the potential of combining two recently developed behavioural and neural training techniques (cognitive bias modification and functional magnetic neuroimaging-based…

Sub-Centimeter Language Organization in the Human Temporal Lobe

ERIC Educational Resources Information Center

Flinker, A.; Chang, E. F.; Barbaro, N. M.; Berger, M. S.; Knight, R. T.

2011-01-01

The human temporal lobe is well known to be critical for language comprehension. Previous physiological research has focused mainly on non-invasive neuroimaging and electrophysiological techniques with each approach requiring averaging across many trials and subjects. The results of these studies have implicated extended anatomical regions in…

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

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

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

PubMed

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

2017-02-15

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

Adherence to standard of care in the diagnosis and treatment of suspected bacterial meningitis.

PubMed

Chia, David; Yavari, Youness; Kirsanov, Eugeny; Aronin, Steven I; Sadigh, Majid

2015-01-01

Acute bacterial meningitis (ABM) is a rare but deadly neurological emergency. Accordingly, Infectious Diseases Society of America (IDSA) guidelines summarize current evidence into a straightforward algorithm for its management. The goal of this study is to evaluate the overall compliance with these guidelines in patients with suspected ABM. A retrospective cross-sectional study was conducted of adult patients who underwent lumbar puncture for suspected ABM to ascertain local adherence patterns to IDSA guidelines for bacterial meningitis. Primary outcomes included appropriate utilization of neuroimaging, blood cultures, antibiotics, corticosteroids, and lumbar puncture. In all, 160 patients were included in the study. Overall IDSA compliance was only 0.6%. Neuroimaging and blood cultures were appropriately utilized in 54.3% and 47.5% of patients, respectively. Steroids and antibiotics were appropriately administered in only 7.5% and 5.6% of patients, respectively. Adherence to IDSA guidelines is poor. Antibiotic choice is often incorrect, corticosteroids are rarely administered, and there is an overutilization of neuroimaging. © The Author(s) 2014.

Neuroimaging of Narcolepsy and Kleine-Levin Syndrome.

PubMed

Hong, Seung Bong

2017-09-01

Narcolepsy is a chronic neurologic disorder with the abnormal regulation of the sleep-wake cycle, resulting in excessive daytime sleepiness, disturbed nocturnal sleep, and manifestations related to rapid eye movement sleep, such as cataplexy, sleep paralysis, and hypnagogic hallucination. Over the past decade, numerous neuroimaging studies have been performed to characterize the pathophysiology and various clinical features of narcolepsy. This article reviews structural and functional brain imaging findings in narcolepsy and Kleine-Levin syndrome. Based on the current state of research, brain imaging is a useful tool to investigate and understand the neuroanatomic correlates and brain abnormalities of narcolepsy and other hypersomnia. Copyright © 2017 Elsevier Inc. All rights reserved.

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

The Use of Non-invasive Brain Stimulation Techniques to Facilitate Recovery from Post-stroke Aphasia

PubMed Central

Marchina, Sarah; Wan, Catherine Y.

2011-01-01

Aphasia is a common symptom after left hemispheric stroke. Neuroimaging techniques over the last 10–15 years have described two general trends: Patients with small left hemisphere strokes tend to recruit perilesional areas, while patients with large left hemisphere lesions recruit mainly homotopic regions in the right hemisphere. Non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have been employed to facilitate recovery by stimulating lesional and contralesional regions. The majority of these brain stimulation studies have attempted to block homotopic regions in the right posterior inferior frontal gyrus (IFG) to affect a presumed disinhibited right IFG (triangular portion). Other studies have used anodal or excitatory tDCS to stimulate the contralesional (right) fronto-temporal region or parts of the intact left IFG and perilesional regions to improve speech-motor output. It remains unclear whether the interhemispheric disinhibition model, which is the basis for motor cortex stimulation studies, also applies to the language system. Future studies could address a number of issues, including: the effect of lesion location on current density distribution, timing of the intervention with regard to stroke onset, whether brain stimulation should be combined with behavioral therapy, and whether multiple brain sites should be stimulated. A better understanding of the predictors of recovery from natural outcome studies would also help to inform study design, and the selection of clinically meaningful outcome measures in future studies. PMID:21842404

A 2D spiral turbo-spin-echo technique.

PubMed

Li, Zhiqiang; Karis, John P; Pipe, James G

2018-03-09

2D turbo-spin-echo (TSE) is widely used in the clinic for neuroimaging. However, the long refocusing radiofrequency pulse train leads to high specific absorption rate (SAR) and alters the contrast compared to conventional spin-echo. The purpose of this work is to develop a robust 2D spiral TSE technique for fast T 2 -weighted imaging with low SAR and improved contrast. A spiral-in/out readout is incorporated into 2D TSE to fully take advantage of the acquisition efficiency of spiral sampling while avoiding potential off-resonance-related artifacts compared to a typical spiral-out readout. A double encoding strategy and a signal demodulation method are proposed to mitigate the artifacts because of the T 2 -decay-induced signal variation. An adapted prescan phase correction as well as a concomitant phase compensation technique are implemented to minimize the phase errors. Phantom data demonstrate the efficacy of the proposed double encoding/signal demodulation, as well as the prescan phase correction and concomitant phase compensation. Volunteer data show that the proposed 2D spiral TSE achieves fast scan speed with high SNR, low SAR, and improved contrast compared to conventional Cartesian TSE. A robust 2D spiral TSE technique is feasible and provides a potential alternative to conventional 2D Cartesian TSE for T 2 -weighted neuroimaging. © 2018 International Society for Magnetic Resonance in Medicine.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

PubMed Central

Giordano, Bruno L.; Kayser, Christoph; Rousselet, Guillaume A.; Gross, Joachim; Schyns, Philippe G.

2016-01-01

Abstract We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc. PMID:27860095

Pharyngeal electrical stimulation device for the treatment of neurogenic dysphagia: technology update.

PubMed

Restivo, Domenico A; Hamdy, Shaheen

2018-01-01

Neurogenic dysphagia (ND) can occur in patients with nervous system diseases of varying etiologies. Moreover, recovery from ND is not guaranteed. The therapeutic approaches for oropharyngeal ND have drastically changed over the last decade, mainly due to a better knowledge of the neurophysiology of swallowing along with the progress of neuroimaging and neurophysiological studies. For this reason, it is a priority to develop a treatment that is repeatable, safe, and can be carried out at the bedside as well as for outpatients. Pharyngeal electrical stimulation (PES) is a novel rehabilitation treatment for ND. PES is carried out via location-specific intraluminal catheters that are introduced transnasally and enable clinicians to stimulate the pharynx directly. This technique has demonstrated increasingly promising evidence in improving swallowing performance in patients with ND associated with stroke and multiple sclerosis, probably by increasing the corticobulbar excitability and inducing cortical reorganization of swallowing motor cortex. In this article, we update the reader as to both the physiologic background and past and current studies of PES in an effort to highlight the clinical progress of this important technique.

Neuroimaging Assessment of Cerebrovascular Reactivity in Concussion: Current Concepts, Methodological Considerations, and Review of the Literature

PubMed Central

Ellis, Michael J.; Ryner, Lawrence N.; Sobczyk, Olivia; Fierstra, Jorn; Mikulis, David J.; Fisher, Joseph A.; Duffin, James; Mutch, W. Alan C.

2016-01-01

Concussion is a form of traumatic brain injury (TBI) that presents with a wide spectrum of subjective symptoms and few objective clinical findings. Emerging research suggests that one of the processes that may contribute to concussion pathophysiology is dysregulation of cerebral blood flow (CBF) leading to a mismatch between CBF delivery and the metabolic needs of the injured brain. Cerebrovascular reactivity (CVR) is defined as the change in CBF in response to a measured vasoactive stimulus. Several magnetic resonance imaging (MRI) techniques can be used as a surrogate measure of CBF in clinical and laboratory studies. In order to provide an accurate assessment of CVR, these sequences must be combined with a reliable, reproducible vasoactive stimulus that can manipulate CBF. Although CVR imaging currently plays a crucial role in the diagnosis and management of many cerebrovascular diseases, only recently have studies begun to apply this assessment tool in patients with concussion. In order to evaluate the quality, reliability, and relevance of CVR studies in concussion, it is important that clinicians and researchers have a strong foundational understanding of the role of CBF regulation in health, concussion, and more severe forms of TBI, and an awareness of the advantages and limitations of currently available CVR measurement techniques. Accordingly, in this review, we (1) discuss the role of CVR in TBI and concussion, (2) examine methodological considerations for MRI-based measurement of CVR, and (3) provide an overview of published CVR studies in concussion patients. PMID:27199885

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

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…

Is Insight Always the Same? A Protocol Analysis of Insight in Compound Remote Associate Problems

ERIC Educational Resources Information Center

Cranford, Edward A.; Moss, Jarrod

2012-01-01

Compound Remote Associate (CRA) problems have been used to investigate insight problem solving using both behavioral and neuroimaging techniques. However, it is unclear to what extent CRA problems exhibit characteristics of insight such as impasses and restructuring. CRA problem-solving characteristics were examined in a study in which…

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

Bayesian multi-task learning for decoding multi-subject neuroimaging data.

PubMed

Marquand, Andre F; Brammer, Michael; Williams, Steven C R; Doyle, Orla M

2014-05-15

Decoding models based on pattern recognition (PR) are becoming increasingly important tools for neuroimaging data analysis. In contrast to alternative (mass-univariate) encoding approaches that use hierarchical models to capture inter-subject variability, inter-subject differences are not typically handled efficiently in PR. In this work, we propose to overcome this problem by recasting the decoding problem in a multi-task learning (MTL) framework. In MTL, a single PR model is used to learn different but related "tasks" simultaneously. The primary advantage of MTL is that it makes more efficient use of the data available and leads to more accurate models by making use of the relationships between tasks. In this work, we construct MTL models where each subject is modelled by a separate task. We use a flexible covariance structure to model the relationships between tasks and induce coupling between them using Gaussian process priors. We present an MTL method for classification problems and demonstrate a novel mapping method suitable for PR models. We apply these MTL approaches to classifying many different contrasts in a publicly available fMRI dataset and show that the proposed MTL methods produce higher decoding accuracy and more consistent discriminative activity patterns than currently used techniques. Our results demonstrate that MTL provides a promising method for multi-subject decoding studies by focusing on the commonalities between a group of subjects rather than the idiosyncratic properties of different subjects. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Is a picture worth a thousand (forgotten) words?: neuroimaging evidence for the cognitive deficits in 'chemo-fog'/'chemo-brain'.

PubMed

Raffa, R B

2010-02-01

The diminution in cognitive function reported to occur in patients treated with adjuvant cancer chemotherapy (a phenomenon known as 'chemo-fog, 'chemo-brain' or similar designation) is supported with varying degrees of evidence by prospective and retrospective clinical studies. However, the cognitive deficits are often subtle and the methodologies used to measure them not consistent. Additionally, patients might be able to compensate for the deficits, thereby leading to underestimates of the problem by this type of assessment. For these reasons, direct neuroimaging techniques might provide additional insight. The relatively few such studies, and fewer electrophysiological studies, offer an alternative way to evaluate changes that might be related to cognitive deficits in patients treated with cancer chemotherapeutic regimens.

The missing link: evolution of the primate cerebellum.

PubMed

MacLeod, Carol

2012-01-01

The cerebellum has too often been seen as the "little brain," subservient to the "big brain," the cerebrum. That is changing, as neuroimaging uncovers the cerebellum as the "missing link" in the neurological underpinnings of many cognitive domains. Connections between the neocortex and the cerebellum are now more precisely defined, with functionally localized areas of cerebellar cortex understood for cognitive tasks in humans. Comparative volumetric studies of the primate cerebellum have isolated some elements of circuitry, and our field is moving toward a better integration with the neurosciences in a systematic comparative framework. The next decade may show great advances, as relatively noninvasive techniques of neuroimaging have the potential to build a comparative model of the evolution of primate neurocircuitry. Copyright © 2012 Elsevier B.V. All rights reserved.

Human Neuroimaging of Oxytocin and Vasopressin in Social Cognition

PubMed Central

Zink, Caroline F; Meyer-Lindenberg, Andreas

2012-01-01

The neuropeptides oxytocin and vasopressin have increasingly been identified as modulators of human social behaviors and associated with neuropsychiatric disorders characterized by social dysfunction, such as autism. Identifying the human brain regions that are impacted by oxytocin and vasopressin in a social context is essential to fully characterize the role of oxytocin and vasopressin in complex human social cognition. Advances in human non-invasive neuroimaging techniques and genetics have enabled scientists to begin to elucidate the neurobiological basis of the influence of oxytocin and vasopressin on human social behaviors. Here we review the findings to-date from investigations of the acute and chronic effects of oxytocin and vasopressin on neural activity underlying social cognitive processes using “pharmacological fMRI” and “imaging genetics”, respectively. PMID:22326707

[Mechanism of pain sensation].

PubMed

Gyulaházi, Judit

2009-11-15

Pain, as subjective content of consciousness, is an essential attention-calling sign that helps to survive. Pain relieve is obligatory for every physician, thus, its individual appearance can make the analgesia difficult to carry out. The improving neuroimaging techniques allow understanding the development of pain sensation. Through the 24 articles on the PubMed found with keywords 'pain' and 'neuroimaging', we review here the parts of the pain neuron matrix, their tasks and the assumed mechanism of the acute pain sensation. The mechanism of the individual pain sensation is illustrated by the view of the modular function of the medial part of the pain matrix. Experimental results of empathic pain suggest that pain sensation may occur without real damage of the tissues, as well. The pain network plays main role in chronic pain.

Extensive cerebral Sinovenous Thrombosis in a 5 Year Old Girl, Following Mild Dehydration. (Case Report and Review of Literature).

PubMed

Ashrafzadeh, Farah; Akhondian, Javad; Beiraghi Toosi, Mehran; Hashemi, Nargess

2013-12-01

Cerebral sinovenous thrombosis (CSVT) in children has rarely been reported in the literature, especially without underlying disorder. It has increasingly been diagnosed due to clinical awareness and sensitive neuroimaging techniques. The aim of this article was to report a case of cerebral sinovenous thrombosis without underlying disorder. We reported a 5 year old girl, presented with severe headache and seizure. She had a history of fever and diarrhea before the onset of headache. Neuroimaging showed evidence of CSVT on MRI and magnetic resonance venography. Investigations showed no inherited thrombophilia. The patient was treated with low molecular weight heparin (LMWH) which continued by warfarin. This case illustrated severe complications of dehydration in pediatrics without any evidence of underlying disorders.

Structured illumination diffuse optical tomography for noninvasive functional neuroimaging in mice.

PubMed

Reisman, Matthew D; Markow, Zachary E; Bauer, Adam Q; Culver, Joseph P

2017-04-01

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 superficial cortical tissues. Diffuse optical tomography (DOT) techniques provide noninvasive imaging, but previous DOT systems for rodent neuroimaging have been limited either by sparse spatial sampling or by slow speed. Here, we develop a DOT system with asymmetric source-detector sampling that combines the high-density spatial sampling (0.4 mm) detection of a scientific complementary metal-oxide-semiconductor camera with the rapid (2 Hz) imaging of a few ([Formula: see text]) structured illumination (SI) patterns. Analysis techniques are developed to take advantage of the system's flexibility and optimize trade-offs among spatial sampling, imaging speed, and signal-to-noise ratio. An effective source-detector separation for the SI patterns was developed and compared with light intensity for a quantitative assessment of data quality. The light fall-off versus effective distance was also used for in situ empirical optimization of our light model. We demonstrated the feasibility of this technique by noninvasively mapping the functional response in the somatosensory cortex of the mouse following electrical stimulation of the forepaw.

Neuroimaging is a novel tool to understand the impact of environmental chemicals on neurodevelopment

PubMed Central

Horton, Megan K.; Margolis, Amy E.; Tang, Cheuk; Wright, Robert

2014-01-01

Purpose of review The prevalence of childhood neurodevelopmental disorders (ND) has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of NDs. Very little is known about the mechanistic processes by which environmental chemicals alter brain development. We review recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Recent findings Neuroimaging techniques (volumetric and functional magnetic resonance imaging (MRI), diffusor tensor imaging (DTI), magnetic resonance spectroscopy (MRS)) have opened unprecedented access to study the developing human brain. These techniques are non-invasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. Summary MRI is a powerful tool that allows in vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure. PMID:24535497

The Perfect Neuroimaging-Genetics-Computation Storm: Collision of Petabytes of Data, Millions of Hardware Devices and Thousands of Software Tools

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Zamanyan, Alen; Torri, Federica; Macciardi, Fabio; Hobel, Sam; Moon, Seok Woo; Sung, Young Hee; Jiang, Zhiguo; Labus, Jennifer; Kurth, Florian; Ashe-McNalley, Cody; Mayer, Emeran; Vespa, Paul M.; Van Horn, John D.; Toga, Arthur W.

2013-01-01

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. PMID:23975276

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.

Utilization of a multimedia PACS workstation for surgical planning of epilepsy

NASA Astrophysics Data System (ADS)

Soo Hoo, Kent; Wong, Stephen T.; Hawkins, Randall A.; Knowlton, Robert C.; Laxer, Kenneth D.; Rowley, Howard A.

1997-05-01

Surgical treatment of temporal lobe epilepsy requires the localization of the epileptogenic zone for surgical resection. Currently, clinicians utilize electroencephalography, various neuroimaging modalities, and psychological tests together to determine the location of this zone. We investigate how a multimedia neuroimaging workstation built on top of the UCSF Picture Archiving and Communication System can be used to aid surgical planning of epilepsy and related brain diseases. This usage demonstrates the ability of the workstation to retrieve image and textural data from PACS and other image sources, register multimodality images, visualize and render 3D data sets, analyze images, generate new image and text data from the analysis, and organize all data in a relational database management system.

Central Processing of the Chemical Senses: An Overview

PubMed Central

2010-01-01

Our knowledge regarding the neural processing of the three chemical senses has been considerably lagging behind that of our other senses. It is only during the last 25 years that significant advances have been made in our understanding of where in the human brain odors, tastants, and trigeminal stimuli are processed. Here, we provide an overview of the current knowledge of how the human brain processes chemical stimuli based on findings in neuroimaging studies using positron emission tomography and functional magnetic resonance imaging. Additionally, we provide new insights from recent meta-analyses, on the basis of all published neuroimaging studies of the chemical senses, of where the chemical senses converge in the brain. PMID:21503268

Smaller Hippocampal Volume in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study: Subcortical Volumetry Results From Posttraumatic Stress Disorder Consortia.

PubMed

Logue, Mark W; van Rooij, Sanne J H; Dennis, Emily L; Davis, Sarah L; Hayes, Jasmeet P; Stevens, Jennifer S; Densmore, Maria; Haswell, Courtney C; Ipser, Jonathan; Koch, Saskia B J; Korgaonkar, Mayuresh; Lebois, Lauren A M; Peverill, Matthew; Baker, Justin T; Boedhoe, Premika S W; Frijling, Jessie L; Gruber, Staci A; Harpaz-Rotem, Ilan; Jahanshad, Neda; Koopowitz, Sheri; Levy, Ifat; Nawijn, Laura; O'Connor, Lauren; Olff, Miranda; Salat, David H; Sheridan, Margaret A; Spielberg, Jeffrey M; van Zuiden, Mirjam; Winternitz, Sherry R; Wolff, Jonathan D; Wolf, Erika J; Wang, Xin; Wrocklage, Kristen; Abdallah, Chadi G; Bryant, Richard A; Geuze, Elbert; Jovanovic, Tanja; Kaufman, Milissa L; King, Anthony P; Krystal, John H; Lagopoulos, Jim; Bennett, Maxwell; Lanius, Ruth; Liberzon, Israel; McGlinchey, Regina E; McLaughlin, Katie A; Milberg, William P; Miller, Mark W; Ressler, Kerry J; Veltman, Dick J; Stein, Dan J; Thomaes, Kathleen; Thompson, Paul M; Morey, Rajendra A

2018-02-01

Many studies report smaller hippocampal and amygdala volumes in posttraumatic stress disorder (PTSD), but findings have not always been consistent. Here, we present the results of a large-scale neuroimaging consortium study on PTSD conducted by the Psychiatric Genomics Consortium (PGC)-Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) PTSD Working Group. We analyzed neuroimaging and clinical data from 1868 subjects (794 PTSD patients) contributed by 16 cohorts, representing the largest neuroimaging study of PTSD to date. We assessed the volumes of eight subcortical structures (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, and lateral ventricle). We used a standardized image-analysis and quality-control pipeline established by the ENIGMA consortium. In a meta-analysis of all samples, we found significantly smaller hippocampi in subjects with current PTSD compared with trauma-exposed control subjects (Cohen's d = -0.17, p = .00054), and smaller amygdalae (d = -0.11, p = .025), although the amygdala finding did not survive a significance level that was Bonferroni corrected for multiple subcortical region comparisons (p < .0063). Our study is not subject to the biases of meta-analyses of published data, and it represents an important milestone in an ongoing collaborative effort to examine the neurobiological underpinnings of PTSD and the brain's response to trauma. Published by Elsevier Inc.

Smaller Hippocampal Volume in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study: Subcortical Volumetry Results From Posttraumatic Stress Disorder Consortia

PubMed Central

Logue, Mark W.; van Rooij, Sanne J.H.; Dennis, Emily L.; Davis, Sarah L.; Hayes, Jasmeet P.; Stevens, Jennifer S.; Densmore, Maria; Haswell, Courtney C.; Ipser, Jonathan; Koch, Saskia B.J.; Korgaonkar, Mayuresh; Lebois, Lauren A.M.; Peverill, Matthew; Baker, Justin T.; Boedhoe, Premika S.W.; Frijling, Jessie L.; Gruber, Staci A.; Harpaz-Rotem, Ilan; Jahanshad, Neda; Koopowitz, Sheri; Levy, Ifat; Nawijn, Laura; O’Connor, Lauren; Olff, Miranda; Salat, David H.; Sheridan, Margaret A.; Spielberg, Jeffrey M.; van Zuiden, Mirjam; Winternitz, Sherry R.; Wolff, Jonathan D.; Wolf, Erika J.; Wang, Xin; Wrocklage, Kristen; Abdallah, Chadi G.; Bryant, Richard A.; Geuze, Elbert; Jovanovic, Tanja; Kaufman, Milissa L.; King, Anthony P.; Krystal, John H.; Lagopoulos, Jim; Bennett, Maxwell; Lanius, Ruth; Liberzon, Israel; McGlinchey, Regina E.; McLaughlin, Katie A.; Milberg, William P.; Miller, Mark W.; Ressler, Kerry J.; Veltman, Dick J.; Stein, Dan J.; Thomaes, Kathleen; Thompson, Paul M.; Morey, Rajendra A.

2018-01-01

BACKGROUND Many studies report smaller hippocampal and amygdala volumes in posttraumatic stress disorder (PTSD), but findings have not always been consistent. Here, we present the results of a large-scale neuroimaging consortium study on PTSD conducted by the Psychiatric Genomics Consortium (PGC)–Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) PTSD Working Group. METHODS We analyzed neuroimaging and clinical data from 1868 subjects (794 PTSD patients) contributed by 16 cohorts, representing the largest neuroimaging study of PTSD to date. We assessed the volumes of eight subcortical structures (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, and lateral ventricle). We used a standardized image-analysis and quality-control pipeline established by the ENIGMA consortium. RESULTS In a meta-analysis of all samples, we found significantly smaller hippocampi in subjects with current PTSD compared with trauma-exposed control subjects (Cohen’s d = −0.17, p = .00054), and smaller amygdalae (d = −0.11, p = .025), although the amygdala finding did not survive a significance level that was Bonferroni corrected for multiple subcortical region comparisons (p < .0063). CONCLUSIONS Our study is not subject to the biases of meta-analyses of published data, and it represents an important milestone in an ongoing collaborative effort to examine the neurobiological underpinnings of PTSD and the brain’s response to trauma. PMID:29217296

Nelson Syndrome: Update on Therapeutic Approaches.

PubMed

Azad, Tej D; Veeravagu, Anand; Kumar, Sunny; Katznelson, Laurence

2015-06-01

To review the pathophysiology and therapeutic modalities availble for Nelson syndrome. We reviewed the current literature including managment for Nelson syndrome. For patients with NS, surgical intervention is often the first-line therapy. With refractory NS or tumors with extrasellar involvement, radiosurgery offers an important alternative or adjuvant option. Pharmacologic interventions have demonstrated limited usefulness, although recent evidence supports the feasibility of a novel somatostatin analog for patients with NS. Modern neuroimaging, improved surgical techniques, and the advent of stereotactic radiotherapy have transformed the management of NS. An up-to-date understanding of the pathophysiology underlying Nelson Syndrome and evidence-based management is imperative. Early detection may allow for more successful therapy in patients with Nelson Syndrome. Improved radiotherapeutic interventions and rapidly evolving pharmacologic therapies offer an opportunity to create targeted, multifocal treatment regiments for patients with Nelson Syndrome. Copyright © 2015 Elsevier Inc. All rights reserved.

Understanding Overbidding: Using the Neural Circuitry of Reward to Design Economic Auctions

PubMed Central

Delgado, Mauricio R.; Schotter, Andrew; Ozbay, Erkut Y.; Phelps, Elizabeth A.

2011-01-01

We take advantage of our knowledge of the neural circuitry of reward to investigate a puzzling economic phenomenon: Why do people overbid in auctions? Using functional magnetic resonance imaging (fMRI), we observed that the social competition inherent in an auction results in a more pronounced blood oxygen level–dependent (BOLD) response to loss in the striatum, with greater overbidding correlated with the magnitude of this response. Leveraging these neuroimaging results, we design a behavioral experiment that demonstrates that framing an experimental auction to emphasize loss increases overbidding. These results highlight a role for the contemplation of loss in understanding the tendency to bid “too high.” Current economic theories suggest overbidding may result from either “joy of winning” or risk aversion. By combining neuroeconomic and behavioral economic techniques, we find that another factor, namely loss contemplation in a social context, may mediate overbidding in auctions. PMID:18818362

Understanding overbidding: using the neural circuitry of reward to design economic auctions.

PubMed

Delgado, Mauricio R; Schotter, Andrew; Ozbay, Erkut Y; Phelps, Elizabeth A

2008-09-26

We take advantage of our knowledge of the neural circuitry of reward to investigate a puzzling economic phenomenon: Why do people overbid in auctions? Using functional magnetic resonance imaging (fMRI), we observed that the social competition inherent in an auction results in a more pronounced blood oxygen level-dependent (BOLD) response to loss in the striatum, with greater overbidding correlated with the magnitude of this response. Leveraging these neuroimaging results, we design a behavioral experiment that demonstrates that framing an experimental auction to emphasize loss increases overbidding. These results highlight a role for the contemplation of loss in understanding the tendency to bid "too high." Current economic theories suggest overbidding may result from either "joy of winning" or risk aversion. By combining neuroeconomic and behavioral economic techniques, we find that another factor, namely loss contemplation in a social context, may mediate overbidding in auctions.

Individual differences and the characterization of animal models of psychopathology: a strong challenge and a good opportunity.

PubMed

Armario, Antonio; Nadal, Roser

2013-01-01

Despite the development of valuable new techniques (i.e., genetics, neuroimage) for the study of the neurobiological substrate of psychiatric diseases, there are strong limitations in the information that can be gathered from human studies. It is thus critical to develop appropriate animal models of psychiatric diseases to characterize their putative biological bases and the development of new therapeutic strategies. The present review tries to offer a general perspective and several examples of how individual differences in animals can contribute to explain differential susceptibility to develop behavioral alterations, but also emphasizes methodological problems that can lead to inappropriate or over-simplistic interpretations. A critical analysis of the approaches currently used could contribute to obtain more reliable data and allow taking full advantage of new and sophisticated technologies. The discussion is mainly focused on anxiety-like and to a lower extent on depression-like behavior in rodents.

Individual differences and the characterization of animal models of psychopathology: a strong challenge and a good opportunity

PubMed Central

Armario, Antonio; Nadal, Roser

2013-01-01

Despite the development of valuable new techniques (i.e., genetics, neuroimage) for the study of the neurobiological substrate of psychiatric diseases, there are strong limitations in the information that can be gathered from human studies. It is thus critical to develop appropriate animal models of psychiatric diseases to characterize their putative biological bases and the development of new therapeutic strategies. The present review tries to offer a general perspective and several examples of how individual differences in animals can contribute to explain differential susceptibility to develop behavioral alterations, but also emphasizes methodological problems that can lead to inappropriate or over-simplistic interpretations. A critical analysis of the approaches currently used could contribute to obtain more reliable data and allow taking full advantage of new and sophisticated technologies. The discussion is mainly focused on anxiety-like and to a lower extent on depression-like behavior in rodents. PMID:24265618

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

PubMed Central

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

2016-01-01

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there are extensive evidences showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. PMID:27012503

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.

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

PubMed

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

2017-01-15

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. Copyright © 2016 Elsevier Inc. All rights reserved.

Assessing the effects of common variation in the FOXP2 gene on human brain structure.

PubMed

Hoogman, Martine; Guadalupe, Tulio; Zwiers, Marcel P; Klarenbeek, Patricia; Francks, Clyde; Fisher, Simon E

2014-01-01

The FOXP2 transcription factor is one of the most well-known genes to have been implicated in developmental speech and language disorders. Rare mutations disrupting the function of this gene have been described in different families and cases. In a large three-generation family carrying a missense mutation, neuroimaging studies revealed significant effects on brain structure and function, most notably in the inferior frontal gyrus, caudate nucleus, and cerebellum. After the identification of rare disruptive FOXP2 variants impacting on brain structure, several reports proposed that common variants at this locus may also have detectable effects on the brain, extending beyond disorder into normal phenotypic variation. These neuroimaging genetics studies used groups of between 14 and 96 participants. The current study assessed effects of common FOXP2 variants on neuroanatomy using voxel-based morphometry (VBM) and volumetric techniques in a sample of >1300 people from the general population. In a first targeted stage we analyzed single nucleotide polymorphisms (SNPs) claimed to have effects in prior smaller studies (rs2253478, rs12533005, rs2396753, rs6980093, rs7784315, rs17137124, rs10230558, rs7782412, rs1456031), beginning with regions proposed in the relevant papers, then assessing impact across the entire brain. In the second gene-wide stage, we tested all common FOXP2 variation, focusing on volumetry of those regions most strongly implicated from analyses of rare disruptive mutations. Despite using a sample that is more than 10 times that used for prior studies of common FOXP2 variation, we found no evidence for effects of SNPs on variability in neuroanatomy in the general population. Thus, the impact of this gene on brain structure may be largely limited to extreme cases of rare disruptive alleles. Alternatively, effects of common variants at this gene exist but are too subtle to be detected with standard volumetric techniques.

Neural Signature of DCD: A Critical Review of MRI Neuroimaging Studies

PubMed Central

Biotteau, Maëlle; Chaix, Yves; Blais, Mélody; Tallet, Jessica; Péran, Patrice; Albaret, Jean-Michel

2016-01-01

The most common neurodevelopmental disorders (e.g., developmental dyslexia (DD), autism, attention-deficit hyperactivity disorder (ADHD)) have been the subject of numerous neuroimaging studies, leading to certain brain regions being identified as neural correlates of these conditions, referring to a neural signature of disorders. Developmental coordination disorder (DCD), however, remains one of the least understood and studied neurodevelopmental disorders. Given the acknowledged link between motor difficulties and brain features, it is surprising that so few research studies have systematically explored the brains of children with DCD. The aim of the present review was to ascertain whether it is currently possible to identify a neural signature for DCD, based on the 14 magnetic resonance imaging neuroimaging studies that have been conducted in DCD to date. Our results indicate that several brain areas are unquestionably linked to DCD: cerebellum, basal ganglia, parietal lobe, and parts of the frontal lobe (medial orbitofrontal cortex and dorsolateral prefrontal cortex). However, research has been too sparse and studies have suffered from several limitations that constitute a serious obstacle to address the question of a well-established neural signature for DCD. PMID:28018285

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.

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.

The Washington University Central Neuroimaging Data Archive

PubMed Central

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

2016-01-01

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

Big Data Approaches for the Analysis of Large-Scale fMRI Data Using Apache Spark and GPU Processing: A Demonstration on Resting-State fMRI Data from the Human Connectome Project

PubMed Central

Boubela, Roland N.; Kalcher, Klaudius; Huf, Wolfgang; Našel, Christian; Moser, Ewald

2016-01-01

Technologies for scalable analysis of very large datasets have emerged in the domain of internet computing, but are still rarely used in neuroimaging despite the existence of data and research questions in need of efficient computation tools especially in fMRI. In this work, we present software tools for the application of Apache Spark and Graphics Processing Units (GPUs) to neuroimaging datasets, in particular providing distributed file input for 4D NIfTI fMRI datasets in Scala for use in an Apache Spark environment. Examples for using this Big Data platform in graph analysis of fMRI datasets are shown to illustrate how processing pipelines employing it can be developed. With more tools for the convenient integration of neuroimaging file formats and typical processing steps, big data technologies could find wider endorsement in the community, leading to a range of potentially useful applications especially in view of the current collaborative creation of a wealth of large data repositories including thousands of individual fMRI datasets. PMID:26778951

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

ANALYSIS OF SAMPLING TECHNIQUES FOR IMBALANCED DATA: AN N=648 ADNI STUDY

PubMed Central

Dubey, Rashmi; Zhou, Jiayu; Wang, Yalin; Thompson, Paul M.; Ye, Jieping

2013-01-01

Many neuroimaging applications deal with imbalanced imaging data. For example, in Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, the mild cognitive impairment (MCI) cases eligible for the study are nearly two times the Alzheimer’s disease (AD) patients for structural magnetic resonance imaging (MRI) modality and six times the control cases for proteomics modality. Constructing an accurate classifier from imbalanced data is a challenging task. Traditional classifiers that aim to maximize the overall prediction accuracy tend to classify all data into the majority class. In this paper, we study an ensemble system of feature selection and data sampling for the class imbalance problem. We systematically analyze various sampling techniques by examining the efficacy of different rates and types of undersampling, oversampling, and a combination of over and under sampling approaches. We thoroughly examine six widely used feature selection algorithms to identify significant biomarkers and thereby reduce the complexity of the data. The efficacy of the ensemble techniques is evaluated using two different classifiers including Random Forest and Support Vector Machines based on classification accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity measures. Our extensive experimental results show that for various problem settings in ADNI, (1). a balanced training set obtained with K-Medoids technique based undersampling gives the best overall performance among different data sampling techniques and no sampling approach; and (2). sparse logistic regression with stability selection achieves competitive performance among various feature selection algorithms. Comprehensive experiments with various settings show that our proposed ensemble model of multiple undersampled datasets yields stable and promising results. PMID:24176869

Analysis of sampling techniques for imbalanced data: An n = 648 ADNI study.

PubMed

Dubey, Rashmi; Zhou, Jiayu; Wang, Yalin; Thompson, Paul M; Ye, Jieping

2014-02-15

Many neuroimaging applications deal with imbalanced imaging data. For example, in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, the mild cognitive impairment (MCI) cases eligible for the study are nearly two times the Alzheimer's disease (AD) patients for structural magnetic resonance imaging (MRI) modality and six times the control cases for proteomics modality. Constructing an accurate classifier from imbalanced data is a challenging task. Traditional classifiers that aim to maximize the overall prediction accuracy tend to classify all data into the majority class. In this paper, we study an ensemble system of feature selection and data sampling for the class imbalance problem. We systematically analyze various sampling techniques by examining the efficacy of different rates and types of undersampling, oversampling, and a combination of over and undersampling approaches. We thoroughly examine six widely used feature selection algorithms to identify significant biomarkers and thereby reduce the complexity of the data. The efficacy of the ensemble techniques is evaluated using two different classifiers including Random Forest and Support Vector Machines based on classification accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity measures. Our extensive experimental results show that for various problem settings in ADNI, (1) a balanced training set obtained with K-Medoids technique based undersampling gives the best overall performance among different data sampling techniques and no sampling approach; and (2) sparse logistic regression with stability selection achieves competitive performance among various feature selection algorithms. Comprehensive experiments with various settings show that our proposed ensemble model of multiple undersampled datasets yields stable and promising results. © 2013 Elsevier Inc. All rights reserved.

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.

Gamma knife radiosurgery in movement disorders: Indications and limitations.

PubMed

Higuchi, Yoshinori; Matsuda, Shinji; Serizawa, Toru

2017-01-01

Functional radiosurgery has advanced steadily during the past half century since the development of the gamma knife technique for treating intractable cancer pain. Applications of radiosurgery for intracranial diseases have increased with a focus on understanding radiobiology. Currently, the use of gamma knife radiosurgery to ablate deep brain structures is not widespread because visualization of the functional targets remains difficult despite the increased availability of advanced neuroimaging technology. Moreover, most existing reports have a small sample size or are retrospective. However, increased experience with intraoperative neurophysiological evaluations in radiofrequency thalamotomy and deep brain stimulation supports anatomical and neurophysiological approaches to the ventralis intermedius nucleus. Two recent prospective studies have promoted the clinical application of functional radiosurgery for movement disorders. For example, unilateral gamma knife thalamotomy is a potential alternative to radiofrequency thalamotomy and deep brain stimulation techniques for intractable tremor patients with contraindications for surgery. Despite the promising efficacy of gamma knife thalamotomy, however, these studies did not include sufficient follow-up to confirm long-term effects. Herein, we review the radiobiology literature, various techniques, and the treatment efficacy of gamma knife radiosurgery for patients with movement disorders. Future research should focus on randomized controlled studies and long-term effects. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Sliding-slab three-dimensional TSE imaging with a spiral-In/Out readout.

PubMed

Li, Zhiqiang; Wang, Dinghui; Robison, Ryan K; Zwart, Nicholas R; Schär, Michael; Karis, John P; Pipe, James G

2016-02-01

T2 -weighted imaging is of great diagnostic value in neuroimaging. Three-dimensional (3D) Cartesian turbo spin echo (TSE) scans provide high signal-to-noise ratio (SNR) and contiguous slice coverage. The purpose of this preliminary work is to implement a novel 3D spiral TSE technique with image quality comparable to 2D/3D Cartesian TSE. The proposed technique uses multislab 3D TSE imaging. To mitigate the slice boundary artifacts, a sliding-slab method is extended to spiral imaging. A spiral-in/out readout is adopted to minimize the artifacts that may be present with the conventional spiral-out readout. Phase errors induced by B0 eddy currents are measured and compensated to allow for the combination of the spiral-in and spiral-out images. A nonuniform slice encoding scheme is used to reduce the truncation artifacts while preserving the SNR performance. Preliminary results show that each of the individual measures contributes to the overall performance, and the image quality of the results obtained with the proposed technique is, in general, comparable to that of 2D or 3D Cartesian TSE. 3D sliding-slab TSE with a spiral-in/out readout provides good-quality T2 -weighted images, and, therefore, may become a promising alternative to Cartesian TSE. © 2015 Wiley Periodicals, Inc.

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.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

PubMed

Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G

2017-03-01

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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

The practical and fundamental limits of optical imaging in mammalian brains.

PubMed

Ji, Na

2014-09-17

Advances in chemistry and physics have profound effects on neuroimaging. Current and future progress in these disciplines will continue to aid in efforts to visualize neural circuitry, particularly in deeper layers of the brain. Copyright © 2014 Elsevier Inc. All rights reserved.

The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement.

PubMed

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

2017-05-01

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI-3, which began on August 1, 2016, is a 5-year renewal of the current ADNI-2 study. ADNI-3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning will be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition. Multimodal analyses will provide insight into AD pathophysiology and disease progression. ADNI-3 will aim to inform AD treatment trials and facilitate development of AD disease-modifying treatments. Copyright © 2016 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.

PubMed

Hasson, Uri; Skipper, Jeremy I; Wilde, Michael J; Nusbaum, Howard C; Small, Steven L

2008-01-15

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.

The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement

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

Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.

Overall, the goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI-3, which began on August 1, 2016, is a 5-year renewal of the current ADNI-2 study. ADNI-3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning willmore » be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition. Multimodal analyses will provide insight into AD pathophysiology and disease progression. Finally, ADNI-3 will aim to inform AD treatment trials and facilitate development of AD disease-modifying treatments.« less

Improving the Analysis, Storage and Sharing of Neuroimaging Data using Relational Databases and Distributed Computing

PubMed Central

Hasson, Uri; Skipper, Jeremy I.; Wilde, Michael J.; Nusbaum, Howard C.; Small, Steven L.

2007-01-01

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data. PMID:17964812

HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain

PubMed Central

Huppert, Theodore J.; Diamond, Solomon G.; Franceschini, Maria A.; Boas, David A.

2009-01-01

Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging tool for studying evoked hemodynamic changes within the brain. By this technique, changes in the optical absorption of light are recorded over time and are used to estimate the functionally evoked changes in cerebral oxyhemoglobin and deoxyhemoglobin concentrations that result from local cerebral vascular and oxygen metabolic effects during brain activity. Over the past three decades this technology has continued to grow, and today NIRS studies have found many niche applications in the fields of psychology, physiology, and cerebral pathology. The growing popularity of this technique is in part associated with a lower cost and increased portability of NIRS equipment when compared with other imaging modalities, such as functional magnetic resonance imaging and positron emission tomography. With this increasing number of applications, new techniques for the processing, analysis, and interpretation of NIRS data are continually being developed. We review some of the time-series and functional analysis techniques that are currently used in NIRS studies, we describe the practical implementation of various signal processing techniques for removing physiological, instrumental, and motion-artifact noise from optical data, and we discuss the unique aspects of NIRS analysis in comparison with other brain imaging modalities. These methods are described within the context of the MATLAB-based graphical user interface program, HomER, which we have developed and distributed to facilitate the processing of optical functional brain data. PMID:19340120

Fusing EEG and fMRI based on a bottom-up model: inferring activation and effective connectivity in neural masses

PubMed Central

Riera, J; Aubert, E; Iwata, K; Kawashima, R; Wan, X; Ozaki, T

2005-01-01

The elucidation of the complex machinery used by the human brain to segregate and integrate information while performing high cognitive functions is a subject of imminent future consequences. The most significant contributions to date in this field, known as cognitive neuroscience, have been achieved by using innovative neuroimaging techniques, such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), which measure variations in both the time and the space of some interpretable physical magnitudes. Extraordinary maps of cerebral activation involving function-restricted brain areas, as well as graphs of the functional connectivity between them, have been obtained from EEG and fMRI data by solving some spatio-temporal inverse problems, which constitutes a top-down approach. However, in many cases, a natural bridge between these maps/graphs and the causal physiological processes is lacking, leading to some misunderstandings in their interpretation. Recent advances in the comprehension of the underlying physiological mechanisms associated with different cerebral scales have provided researchers with an excellent scenario to develop sophisticated biophysical models that permit an integration of these neuroimage modalities, which must share a common aetiology. This paper proposes a bottom-up approach, involving physiological parameters in a specific mesoscopic dynamic equations system. Further observation equations encapsulating the relationship between the mesostates and the EEG/fMRI data are obtained on the basis of the physical foundations of these techniques. A methodology for the estimation of parameters from fused EEG/fMRI data is also presented. In this context, the concepts of activation and effective connectivity are carefully revised. This new approach permits us to examine and discuss some future prospects for the integration of multimodal neuroimages. PMID:16087446

Multivariate decoding of brain images using ordinal regression.

PubMed

Doyle, O M; Ashburner, J; Zelaya, F O; Williams, S C R; Mehta, M A; Marquand, A F

2013-11-01

Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states. In these examples, the variable (target) we want to predict is ordinal in nature. Conventional classification schemes assume that the targets are nominal and hence ignore their ranked nature, whereas parametric and/or non-parametric regression models enforce a metric notion of distance between classes. Here, we propose a novel, alternative multivariate approach that overcomes these limitations - whole brain probabilistic ordinal regression using a Gaussian process framework. We applied this technique to two data sets of pharmacological neuroimaging data from healthy volunteers. The first study was designed to investigate the effect of ketamine on brain activity and its subsequent modulation with two compounds - lamotrigine and risperidone. The second study investigates the effect of scopolamine on cerebral blood flow and its modulation using donepezil. We compared ordinal regression to multi-class classification schemes and metric regression. Considering the modulation of ketamine with lamotrigine, we found that ordinal regression significantly outperformed multi-class classification and metric regression in terms of accuracy and mean absolute error. However, for risperidone ordinal regression significantly outperformed metric regression but performed similarly to multi-class classification both in terms of accuracy and mean absolute error. For the scopolamine data set, ordinal regression was found to outperform both multi-class and metric regression techniques considering the regional cerebral blood flow in the anterior cingulate cortex. Ordinal regression was thus the only method that performed well in all cases. Our results indicate the potential of an ordinal regression approach for neuroimaging data while providing a fully probabilistic framework with elegant approaches for model selection. Copyright © 2013. Published by Elsevier Inc.

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.

Nonvisual Multisensory Impairment of Body Perception in Anorexia Nervosa: A Systematic Review of Neuropsychological Studies

PubMed Central

Gaudio, Santino; Brooks, Samantha Jane; Riva, Giuseppe

2014-01-01

Background Body image distortion is a central symptom of Anorexia Nervosa (AN). Even if corporeal awareness is multisensory majority of AN studies mainly investigated visual misperception. We systematically reviewed AN studies that have investigated different nonvisual sensory inputs using an integrative multisensory approach to body perception. We also discussed the findings in the light of AN neuroimaging evidence. Methods PubMed and PsycINFO were searched until March, 2014. To be included in the review, studies were mainly required to: investigate a sample of patients with current or past AN and a control group and use tasks that directly elicited one or more nonvisual sensory domains. Results Thirteen studies were included. They studied a total of 223 people with current or past AN and 273 control subjects. Overall, results show impairment in tactile and proprioceptive domains of body perception in AN patients. Interoception and multisensory integration have been poorly explored directly in AN patients. A limitation of this review is the relatively small amount of literature available. Conclusions Our results showed that AN patients had a multisensory impairment of body perception that goes beyond visual misperception and involves tactile and proprioceptive sensory components. Furthermore, impairment of tactile and proprioceptive components may be associated with parietal cortex alterations in AN patients. Interoception and multisensory integration have been weakly explored directly. Further research, using multisensory approaches as well as neuroimaging techniques, is needed to better define the complexity of body image distortion in AN. Key Findings The review suggests an altered capacity of AN patients in processing and integration of bodily signals: body parts are experienced as dissociated from their holistic and perceptive dimensions. Specifically, it is likely that not only perception but memory, and in particular sensorimotor/proprioceptive memory, probably shapes bodily experience in patients with AN. PMID:25303480

Adolescents with Major Depression Demonstrate Increased Amygdala Activation

ERIC Educational Resources Information Center

Yang, Tony T.; Simmons, Alan N.; Matthews, Scott C.; Tapert, Susan F.; Frank, Guido K.; Max, Jeffrey E.; Bischoff-Grethe, Amanda; Lansing, Amy E.; Brown, Gregory; Strigo, Irina A.; Wu, Jing; Paulus, Martin P.

2010-01-01

Objective: Functional neuroimaging studies have led to a significantly deeper understanding of the underlying neural correlates and the development of several mature models of depression in adults. In contrast, our current understanding of the underlying neural substrates of adolescent depression is very limited. Although numerous studies have…

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

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.

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced. Copyright © 2015 Elsevier Ltd. All rights reserved.

Functional neuroanatomy of meditation: A review and meta-analysis of 78 functional neuroimaging investigations.

PubMed

Fox, Kieran C R; Dixon, Matthew L; Nijeboer, Savannah; Girn, Manesh; Floman, James L; Lifshitz, Michael; Ellamil, Melissa; Sedlmeier, Peter; Christoff, Kalina

2016-06-01

Meditation is a family of mental practices that encompasses a wide array of techniques employing distinctive mental strategies. We systematically reviewed 78 functional neuroimaging (fMRI and PET) studies of meditation, and used activation likelihood estimation to meta-analyze 257 peak foci from 31 experiments involving 527 participants. We found reliably dissociable patterns of brain activation and deactivation for four common styles of meditation (focused attention, mantra recitation, open monitoring, and compassion/loving-kindness), and suggestive differences for three others (visualization, sense-withdrawal, and non-dual awareness practices). Overall, dissociable activation patterns are congruent with the psychological and behavioral aims of each practice. Some brain areas are recruited consistently across multiple techniques-including insula, pre/supplementary motor cortices, dorsal anterior cingulate cortex, and frontopolar cortex-but convergence is the exception rather than the rule. A preliminary effect-size meta-analysis found medium effects for both activations (d=0.59) and deactivations (d=-0.74), suggesting potential practical significance. Our meta-analysis supports the neurophysiological dissociability of meditation practices, but also raises many methodological concerns and suggests avenues for future research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Resting state functional connectivity: its physiological basis and application in neuropharmacology.

PubMed

Lu, Hanbing; Stein, Elliot A

2014-09-01

Brain structures do not work in isolation; they work in concert to produce sensory perception, motivation and behavior. Systems-level network activity can be investigated by resting state magnetic resonance imaging (rsMRI), an emerging neuroimaging technique that assesses the synchrony of the brain's ongoing spontaneous activity. Converging evidence reveals that rsMRI is able to consistently identify distinct spatiotemporal patterns of large-scale brain networks. Dysregulation within and between these networks has been implicated in a number of neurodegenerative and neuropsychiatric disorders, including Alzheimer's disease and drug addiction. Despite wide application of this approach in systems neuroscience, the physiological basis of these fluctuations remains incompletely understood. Here we review physiological studies in electrical, metabolic and hemodynamic fluctuations that are most pertinent to the rsMRI signal. We also review recent applications to neuropharmacology - specifically drug effects on resting state fluctuations. We speculate that the mechanisms governing spontaneous fluctuations in regional oxygenation availability likely give rise to the observed rsMRI signal. We conclude by identifying several open questions surrounding this technique. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Published by Elsevier Ltd.

Automatic Semantic Facilitation in Anterior Temporal Cortex Revealed through Multimodal Neuroimaging

PubMed Central

Gramfort, Alexandre; Hämäläinen, Matti S.; Kuperberg, Gina R.

2013-01-01

A core property of human semantic processing is the rapid, facilitatory influence of prior input on extracting the meaning of what comes next, even under conditions of minimal awareness. Previous work has shown a number of neurophysiological indices of this facilitation, but the mapping between time course and localization—critical for separating automatic semantic facilitation from other mechanisms—has thus far been unclear. In the current study, we used a multimodal imaging approach to isolate early, bottom-up effects of context on semantic memory, acquiring a combination of electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) measurements in the same individuals with a masked semantic priming paradigm. Across techniques, the results provide a strikingly convergent picture of early automatic semantic facilitation. Event-related potentials demonstrated early sensitivity to semantic association between 300 and 500 ms; MEG localized the differential neural response within this time window to the left anterior temporal cortex, and fMRI localized the effect more precisely to the left anterior superior temporal gyrus, a region previously implicated in semantic associative processing. However, fMRI diverged from early EEG/MEG measures in revealing semantic enhancement effects within frontal and parietal regions, perhaps reflecting downstream attempts to consciously access the semantic features of the masked prime. Together, these results provide strong evidence that automatic associative semantic facilitation is realized as reduced activity within the left anterior superior temporal cortex between 300 and 500 ms after a word is presented, and emphasize the importance of multimodal neuroimaging approaches in distinguishing the contributions of multiple regions to semantic processing. PMID:24155321

INVITED REVIEW – NEUROIMAGING RESPONSE ASSESSMENT CRITERIA FOR BRAIN TUMORS IN VETERINARY PATIENTS

PubMed Central

Rossmeisl, John H.; Garcia, Paulo A.; Daniel, Gregory B.; Bourland, John Daniel; Debinski, Waldemar; Dervisis, Nikolaos; Klahn, Shawna

2013-01-01

The evaluation of therapeutic response using cross-sectional imaging techniques, particularly gadolinium-enhanced MRI, is an integral part of the clinical management of brain tumors in veterinary patients. Spontaneous canine brain tumors are increasingly recognized and utilized as a translational model for the study of human brain tumors. However, no standardized neuroimaging response assessment criteria have been formulated for use in veterinary clinical trials. Previous studies have found that the pathophysiologic features inherent to brain tumors and the surrounding brain complicate the use of the Response Evaluation Criteria in Solid Tumors (RECIST) assessment system. Objectives of this review are to describe strengths and limitations of published imaging-based brain tumor response criteria and propose a system for use in veterinary patients. The widely used human Macdonald and Response Assessment in Neuro-oncology (RANO) criteria are reviewed and described as to how they can be applied to veterinary brain tumors. Discussion points will include current challenges associated with the interpretation of brain tumor therapeutic responses such as imaging pseudophenomena and treatment-induced necrosis, and how advancements in perfusion imaging, positron emission tomography, and magnetic resonance spectroscopy have shown promise in differentiating tumor progression from therapy-induced changes. Finally, although objective endpoints such as MR-imaging and survival estimates will likely continue to comprise the foundations for outcome measures in veterinary brain tumor clinical trials, we propose that in order to provide a more relevant therapeutic response metric for veterinary patients, composite response systems should be formulated and validated that combine imaging and clinical assessment criteria. PMID:24219161

Voxel-based correlation between coregistered single-photon emission computed tomography and dynamic susceptibility contrast magnetic resonance imaging in subjects with suspected Alzheimer disease.

PubMed

Cavallin, L; Axelsson, R; Wahlund, L O; Oksengard, A R; Svensson, L; Juhlin, P; Wiberg, M Kristoffersen; Frank, A

2008-12-01

Current diagnosis of Alzheimer disease is made by clinical, neuropsychologic, and neuroimaging assessments. Neuroimaging techniques such as magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT) could be valuable in the differential diagnosis of Alzheimer disease, as well as in assessing prognosis. To compare SPECT and MRI in a cohort of patients examined for suspected dementia, including patients with no objective cognitive impairment (control group), mild cognitive impairment (MCI), and Alzheimer disease (AD). 24 patients, eight with AD, 10 with MCI, and six controls, were investigated with SPECT using (99m)Tc-hexamethylpropyleneamine oxime (HMPAO, Ceretec; GE Healthcare Ltd., Little Chalsont UK) and dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a contrast-enhancing gadobutrol formula (Gadovist; Bayer Schering Pharma, Berlin, Germany). Voxel-based correlation between coregistered SPECT and DSC-MR images was calculated. Region-of-interest (ROI) analyses were then performed in 24 different brain areas using brain registration and analysis of SPECT studies (BRASS; Nuclear Diagnostics AB, Stockholm, Sweden) on both SPECT and DSC-MRI. Voxel-based correlation between coregistered SPECT and DSC-MR showed a high correlation, with a mean correlation coefficient of 0.94. ROI analyses of 24 regions showed significant differences between the control group and AD patients in 10 regions using SPECT and five regions in DSC-MR. SPECT remains superior to DSC-MRI in differentiating normal from pathological perfusion, and DSC-MRI could not replace SPECT in the diagnosis of patients with Alzheimer disease.

Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.

PubMed

Douglas, P K; Harris, Sam; Yuille, Alan; Cohen, Mark S

2011-05-15

Machine learning (ML) has become a popular tool for mining functional neuroimaging data, and there are now hopes of performing such analyses efficiently in real-time. Towards this goal, we compared accuracy of six different ML algorithms applied to neuroimaging data of persons engaged in a bivariate task, asserting their belief or disbelief of a variety of propositional statements. We performed unsupervised dimension reduction and automated feature extraction using independent component (IC) analysis and extracted IC time courses. Optimization of classification hyperparameters across each classifier occurred prior to assessment. Maximum accuracy was achieved at 92% for Random Forest, followed by 91% for AdaBoost, 89% for Naïve Bayes, 87% for a J48 decision tree, 86% for K*, and 84% for support vector machine. For real-time decoding applications, finding a parsimonious subset of diagnostic ICs might be useful. We used a forward search technique to sequentially add ranked ICs to the feature subspace. For the current data set, we determined that approximately six ICs represented a meaningful basis set for classification. We then projected these six IC spatial maps forward onto a later scanning session within subject. We then applied the optimized ML algorithms to these new data instances, and found that classification accuracy results were reproducible. Additionally, we compared our classification method to our previously published general linear model results on this same data set. The highest ranked IC spatial maps show similarity to brain regions associated with contrasts for belief > disbelief, and disbelief < belief. Copyright © 2010 Elsevier Inc. All rights reserved.

Molecular neuroimaging in degenerative dementias.

PubMed

Jiménez Bonilla, J F; Carril Carril, J M

2013-01-01

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

The human parental brain: In vivo neuroimaging

PubMed Central

Swain, James E.

2015-01-01

Interacting parenting thoughts and behaviors, supported by key brain circuits, critically shape human infants’ current and future behavior. Indeed, the parent–infant relationship provides infants with their first social environment, forming templates for what they can expect from others, how to interact with them and ultimately how they go on to themselves to be parents. This review concentrates on magnetic resonance imaging experiments of the human parent brain, which link brain physiology with parental thoughts and behaviors. After reviewing brain imaging techniques, certain social cognitive and affective concepts are reviewed, including empathy and trust—likely critical to parenting. Following that is a thorough study-by-study review of the state-of-the-art with respect to human neuroimaging studies of the parental brain—from parent brain responses to salient infant stimuli, including emotionally charged baby cries and brief visual stimuli to the latest structural brain studies. Taken together, this research suggests that networks of highly conserved hypothalamic–midbrain–limbic–paralimbic–cortical circuits act in concert to support parental brain responses to infants, including circuits for limbic emotion response and regulation. Thus, a model is presented in which infant stimuli activate sensory analysis brain regions, affect corticolimbic limbic circuits that regulate emotional response, motivation and reward related to their infant, ultimately organizing parenting impulses, thoughts and emotions into coordinated behaviors as a map for future studies. Finally, future directions towards integrated understanding of the brain basis of human parenting are outlined with profound implications for understanding and contributing to long term parent and infant mental health. PMID:21036196

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

PubMed

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

Subtle changes in myelination due to childhood experiences: label-free microscopy to infer nerve fibers morphology and myelination in brain (Conference Presentation)

NASA Astrophysics Data System (ADS)

Gasecka, Alicja; Tanti, Arnaud; Lutz, Pierre-Eric; Mechawar, Naguib; Cote, Daniel C.

2017-02-01

Adverse childhood experiences have lasting detrimental effects on mental health and are strongly associated with impaired cognition and increased risk of developing psychopathologies. Preclinical and neuroimaging studies have suggested that traumatic events during brain development can affect cerebral myelination particularly in areas and tracts implicated in mood and emotion. Although current neuroimaging techniques are quite powerful, they lack the resolution to infer myelin integrity at the cellular level. Recently demonstrated coherent Raman microscopy has accomplished cellular level imaging of myelin sheaths in the nervous system. However, a quantitative morphometric analysis of nerve fibers still remains a challenge. In particular, in brain, where fibres exhibit small diameters and varying local orientation. In this work, we developed an automated myelin identification and analysis method that is capable of providing a complete picture of axonal myelination and morphology in brain samples. This method performs three main procedures 1) detects molecular anisotropy of membrane phospholipids based on polarization resolved coherent Raman microscopy, 2) identifies regions of different molecular organization, 3) calculates morphometric features of myelinated axons (e.g. myelin thickness, g-ratio). We applied this method to monitor white matter areas from suicides adults that suffered from early live adversity and depression compared to depressed suicides adults and psychiatrically healthy controls. We demonstrate that our method allows for the rapid acquisition and automated analysis of neuronal networks morphology and myelination. This is especially useful for clinical and comparative studies, and may greatly enhance the understanding of processes underlying the neurobiological and psychopathological consequences of child abuse.

CONTRIBUTIONS OF NEUROPSYCHOLOGY AND NEUROIMAGING TO UNDERSTANDING CLINICAL SUBTYPES OF MILD COGNITIVE IMPAIRMENT

PubMed Central

Jak, Amy J.; Bangen, Katherine J.; Wierenga, Christina E.; Delano-Wood, Lisa; Corey-Bloom, Jody; Bondi, Mark W.

2010-01-01

The original conceptualization of mild cognitive impairment (MCI) was primarily as an amnestic disorder representing an intermediate stage between normal aging and Alzheimer’s dementia (AD). More recently, broader conceptualizations of MCI have emerged that also encompass cognitive domains other than memory. These characterizations delineate clinical subtypes that commonly include amnestic and non-amnestic forms, and that involve single and multiple cognitive domains. With the advent of these broader classifications, more specific information is emerging regarding the neuropsychological presentation of individuals with MCI, risk for dementia associated with different subtypes of MCI, and neuropathologic substrates connected to the clinical subtypes. This review provides an overview of this burgeoning literature specific to clinical subtypes of MCI. Focus is primarily on neuropsychological and structural neuroimaging findings specific to clinical subtypes of MCI as well as the issue of daily functioning. Although investigations of non-amnestic subtypes using advanced neuroimaging techniques and clinical trials are quite limited, we briefly review these topics in MCI because these data provide a framework for future investigations specifically examining additional clinical subtypes of MCI. Finally, the review comments on select methodological issues involved in studying this heterogeneous population, and future directions to continue to improve our understanding of MCI and its clinical subtypes are offered. PMID:19501714

Control of end-tidal PCO2 reduces middle cerebral artery blood velocity variability: implications for physiological neuroimaging.

PubMed

Harris, Ashley D; Ide, Kojiro; Poulin, Marc J; Frayne, Richard

2006-02-15

Breath-by-breath variability of the end-tidal partial pressure of CO2 (Pet(CO2)) has been shown to be associated with cerebral blood flow (CBF) fluctuations. These fluctuations can impact neuroimaging techniques that depend on cerebrovascular blood flow. We hypothesized that controlling Pet(CO2) would reduce CBF variability. Dynamic end-tidal forcing was used to control Pet(CO2) at 1.5 mm Hg above the resting level and to hold the end-tidal partial pressure of oxygen (Pet(O2)) at the resting level. Peak blood velocity in the middle cerebral artery (MCA) was measured by transcranial Doppler ultrasound (TCD) as an index of CBF. Blood velocity parameters and timing features were determined on each waveform and the variance of these parameters was compared between Normal (air breathing) and Forcing (end-tidal gas control) sessions. The variability of all velocity parameters was significantly reduced in the Forcing session. In particular, the variability of the average velocity over the cardiac cycle was decreased by 18.2% (P < 0.001). For the most part, the variability of the timing parameters was unchanged. Thus, we conclude that controlling Pet(CO2) is effective in reducing CBF variability, which would have important implications for physiologic neuroimaging.

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

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging.

PubMed

Rosa, Maria J; Mehta, Mitul A; Pich, Emilio M; Risterucci, Celine; Zelaya, Fernando; Reinders, Antje A T S; Williams, Steve C R; Dazzan, Paola; Doyle, Orla M; Marquand, Andre F

2015-01-01

An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow.

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.

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.

Effects of Tasks on BOLD Signal Responses to Sentence Contrasts: Review and Commentary

ERIC Educational Resources Information Center

Caplan, David; Gow, David

2012-01-01

Functional neuroimaging studies of syntactic processing have been interpreted as identifying the neural locations of parsing and interpretive operations. However, current behavioral studies of sentence processing indicate that many operations occur simultaneously with parsing and interpretation. In this review, we point to issues that arise in…

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…

Biomarkers for Cognitive Impairment in Parkinson Disease

PubMed Central

Shi, Min; Huber, Bertrand R.; Zhang, Jing

2010-01-01

Cognitive impairment, including dementia, is commonly seen in those afflicted with Parkinson disease (PD), particularly at advanced disease stages. Pathologically, PD with dementia (PD-D) is most often associated with the presence of cortical Lewy bodies, as is the closely related dementia with Lewy bodies (DLB). Both PD-D and DLB are also frequently complicated by the presence of neurofibrillary tangles and amyloid plaques, features most often attributed to Alzheimer disease. Biomarkers are urgently needed to differentiate among these disease processes and predict dementia in PD as well as monitor responses of patients to new therapies. A few clinical assessments, along with structural and functional neuroimaging, have been utilized in the last few years with some success in this area. Additionally, a number of other strategies have been employed to identify biochemical/molecular biomarkers associated with cognitive impairment and dementia in PD, e.g., targeted analysis of candidate proteins known to be important to PD pathogenesis and progression in cerebrospinal fluid or blood. Finally, interesting results are emerging from preliminary studies with unbiased and high throughput genomic, proteomic and metabolomic techniques. The current findings and perspectives of applying these strategies and techniques are reviewed in this article, together with potential areas of advancement. PMID:20522092

Innovative biomarkers in psychiatric disorders: a major clinical challenge in psychiatry.

PubMed

Lozupone, Madia; Seripa, Davide; Stella, Eleonora; La Montagna, Maddalena; Solfrizzi, Vincenzo; Quaranta, Nicola; Veneziani, Federica; Cester, Alberto; Sardone, Rodolfo; Bonfiglio, Caterina; Giannelli, Gianluigi; Bisceglia, Paola; Bringiotti, Roberto; Daniele, Antonio; Greco, Antonio; Bellomo, Antonello; Logroscino, Giancarlo; Panza, Francesco

2017-09-01

Currently, the diagnosis of psychiatric illnesses is based upon DSM-5 criteria. Although endophenotype-specificity for a particular disorder is discussed, the identification of objective biomarkers is ongoing for aiding diagnosis, prognosis, or clinical response to treatment. We need to improve the understanding of the biological abnormalities in psychiatric illnesses across conventional diagnostic boundaries. The present review investigates the innovative post-genomic knowledge used for psychiatric illness diagnostics and treatment response, with a particular focus on proteomics. Areas covered: This review underlines the contribution that psychiatric innovative biomarkers have reached in relation to diagnosis and theragnosis of psychiatric illnesses. Furthermore, it encompasses a reliable representation of their involvement in disease through proteomics, metabolomics/pharmacometabolomics and lipidomics techniques, including the possible role that gut microbiota and CYP2D6 polimorphisms may play in psychiatric illnesses. Expert opinion: Etiologic heterogeneity, variable expressivity, and epigenetics may impact clinical manifestations, making it difficult for a single measurement to be pathognomonic for multifaceted psychiatric disorders. Academic, industry, or government's partnerships may successfully identify and validate new biomarkers so that unfailing clinical tests can be developed. Proteomics, metabolomics, and lipidomics techniques are considered to be helpful tools beyond neuroimaging and neuropsychology for the phenotypic characterization of brain diseases.

The social evaluation of faces: a meta-analysis of functional neuroimaging studies

PubMed Central

Mende-Siedlecki, Peter; Said, Christopher P.

2013-01-01

Neuroscience research on the social evaluation of faces has accumulated over the last decade, yielding divergent results. We used a meta-analytic technique, multi-level kernel density analysis (MKDA), to analyze 29 neuroimaging studies on face evaluation. Across negative face evaluations, we observed the most consistent activations in bilateral amygdala. Across positive face evaluations, we observed the most consistent activations in medial prefrontal cortex, pregenual anterior cingulate cortex (pgACC), medial orbitofrontal cortex (mOFC), left caudate and nucleus accumbens (NAcc). Based on additional analyses comparing linear and non-linear responses, we propose a ventral/dorsal dissociation within the amygdala, wherein separate populations of neurons code for face valence and intensity, respectively. Finally, we argue that some of the differences between studies are attributable to differences in the typicality of face stimuli. Specifically, extremely attractive faces are more likely to elicit responses in NAcc/caudate and mOFC. PMID:22287188

Brain Connectivity Networks and the Aesthetic Experience of Music.

PubMed

Reybrouck, Mark; Vuust, Peter; Brattico, Elvira

2018-06-12

Listening to music is above all a human experience, which becomes an aesthetic experience when an individual immerses himself/herself in the music, dedicating attention to perceptual-cognitive-affective interpretation and evaluation. The study of these processes where the individual perceives, understands, enjoys and evaluates a set of auditory stimuli has mainly been focused on the effect of music on specific brain structures, as measured with neurophysiology and neuroimaging techniques. The very recent application of network science algorithms to brain research allows an insight into the functional connectivity between brain regions. These studies in network neuroscience have identified distinct circuits that function during goal-directed tasks and resting states. We review recent neuroimaging findings which indicate that music listening is traceable in terms of network connectivity and activations of target regions in the brain, in particular between the auditory cortex, the reward brain system and brain regions active during mind wandering.

Imaging brain development: the adolescent brain.

PubMed

Blakemore, Sarah-Jayne

2012-06-01

The past 15 years have seen a rapid expansion in the number of studies using neuroimaging techniques to investigate maturational changes in the human brain. In this paper, I review MRI studies on structural changes in the developing brain, and fMRI studies on functional changes in the social brain during adolescence. Both MRI and fMRI studies point to adolescence as a period of continued neural development. In the final section, I discuss a number of areas of research that are just beginning and may be the subject of developmental neuroimaging in the next twenty years. Future studies might focus on complex questions including the development of functional connectivity; how gender and puberty influence adolescent brain development; the effects of genes, environment and culture on the adolescent brain; development of the atypical adolescent brain; and implications for policy of the study of the adolescent brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Mapping Cortical Laminar Structure in the 3D BigBrain.

PubMed

Wagstyl, Konrad; Lepage, Claude; Bludau, Sebastian; Zilles, Karl; Fletcher, Paul C; Amunts, Katrin; Evans, Alan C

2018-07-01

Histological sections offer high spatial resolution to examine laminar architecture of the human cerebral cortex; however, they are restricted by being 2D, hence only regions with sufficiently optimal cutting planes can be analyzed. Conversely, noninvasive neuroimaging approaches are whole brain but have relatively low resolution. Consequently, correct 3D cross-cortical patterns of laminar architecture have never been mapped in histological sections. We developed an automated technique to identify and analyze laminar structure within the high-resolution 3D histological BigBrain. We extracted white matter and pial surfaces, from which we derived histologically verified surfaces at the layer I/II boundary and within layer IV. Layer IV depth was strongly predicted by cortical curvature but varied between areas. This fully automated 3D laminar analysis is an important requirement for bridging high-resolution 2D cytoarchitecture and in vivo 3D neuroimaging. It lays the foundation for in-depth, whole-brain analyses of cortical layering.

Hydrocephalus and mucopolysaccharidoses: what do we know and what do we not know?

PubMed

Dalla Corte, Amauri; de Souza, Carolina F M; Anés, Maurício; Giugliani, Roberto

2017-07-01

The precise incidence of hydrocephalus in patients with mucopolysaccharidoses (MPS) is hard to determine, because the condition lacks a formal, consensus-based definition. The diagnosis of hydrocephalus depends on symptom profile, presence of neuroimaging features, and the outcome of diagnostic tests. Although numerous techniques are used to identify MPS patients who are most likely to have hydrocephalus and respond to treatment, no definitive method exists to prove diagnosis. The authors propose an algorithm to aid in the diagnosis and management of hydrocephalus in MPS patients. The theory of venous hypertension associated with the morphological changes in the skull base and craniocervical junction indicate the need for future neuroimaging studies including cerebrospinal fluid (CSF) and venous flow measurements to monitor hydrocephalus progression and select therapeutic interventions in MPS patients. Preoperative planning should also be based on the increased risk of intraoperative and postoperative hemorrhagic complications.

[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.

Automatic analysis (aa): efficient neuroimaging workflows and parallel processing using Matlab and XML.

PubMed

Cusack, Rhodri; Vicente-Grabovetsky, Alejandro; Mitchell, Daniel J; Wild, Conor J; Auer, Tibor; Linke, Annika C; Peelle, Jonathan E

2014-01-01

Recent years have seen neuroimaging data sets becoming richer, with larger cohorts of participants, a greater variety of acquisition techniques, and increasingly complex analyses. These advances have made data analysis pipelines complicated to set up and run (increasing the risk of human error) and time consuming to execute (restricting what analyses are attempted). Here we present an open-source framework, automatic analysis (aa), to address these concerns. Human efficiency is increased by making code modular and reusable, and managing its execution with a processing engine that tracks what has been completed and what needs to be (re)done. Analysis is accelerated by optional parallel processing of independent tasks on cluster or cloud computing resources. A pipeline comprises a series of modules that each perform a specific task. The processing engine keeps track of the data, calculating a map of upstream and downstream dependencies for each module. Existing modules are available for many analysis tasks, such as SPM-based fMRI preprocessing, individual and group level statistics, voxel-based morphometry, tractography, and multi-voxel pattern analyses (MVPA). However, aa also allows for full customization, and encourages efficient management of code: new modules may be written with only a small code overhead. aa has been used by more than 50 researchers in hundreds of neuroimaging studies comprising thousands of subjects. It has been found to be robust, fast, and efficient, for simple-single subject studies up to multimodal pipelines on hundreds of subjects. It is attractive to both novice and experienced users. aa can reduce the amount of time neuroimaging laboratories spend performing analyses and reduce errors, expanding the range of scientific questions it is practical to address.

The neurologist's dilemma: a comprehensive clinical review of Bell's palsy, with emphasis on current management trends.

PubMed

Zandian, Anthony; Osiro, Stephen; Hudson, Ryan; Ali, Irfan M; Matusz, Petru; Tubbs, Shane R; Loukas, Marios

2014-01-20

Recent advances in Bell's palsy (BP) were reviewed to assess the current trends in its management and prognosis. We retrieved the literature on BP using the Cochrane Database of Systematic Reviews, PubMed, and Google Scholar. Key words and phrases used during the search included 'Bell's palsy', 'Bell's phenomenon', 'facial palsy', and 'idiopathic facial paralysis'. Emphasis was placed on articles and randomized controlled trails (RCTs) published within the last 5 years. BP is currently considered the leading disorder affecting the facial nerve. The literature is replete with theories of its etiology, but the reactivation of herpes simplex virus isoform 1 (HSV-1) and/or herpes zoster virus (HZV) from the geniculate ganglia is now the most strongly suspected cause. Despite the advancements in neuroimaging techniques, the diagnosis of BP remains one of exclusion. In addition, most patients with BP recover spontaneously within 3 weeks. Corticosteroids are currently the drug of choice when medical therapy is needed. Antivirals, in contrast, are not superior to placebo according to most reliable studies. At the time of publication, there is no consensus as to the benefit of acupuncture or surgical decompression of the facial nerve. Long-term therapeutic agents and adjuvant medications for BP are necessary due to recurrence and intractable cases. In the future, large RCTs will be required to determine whether BP is associated with an increased risk of stroke.

Beyond the neuropsychology of dreaming: Insights into the neural basis of dreaming with new techniques of sleep recording and analysis.

PubMed

Cipolli, Carlo; Ferrara, Michele; De Gennaro, Luigi; Plazzi, Giuseppe

2017-10-01

Recent advances in electrophysiological [e.g., surface high-density electroencephalographic (hd-EEG) and intracranial recordings], video-polysomnography (video-PSG), transcranial stimulation and neuroimaging techniques allow more in-depth and more accurate investigation of the neural correlates of dreaming in healthy individuals and in patients with brain-damage, neurodegenerative diseases, sleep disorders or parasomnias. Convergent evidence provided by studies using these techniques in healthy subjects has led to a reformulation of several unresolved issues of dream generation and recall [such as the inter- and intra-individual differences in dream recall and the predictivity of specific EEG rhythms, such as theta in rapid eye movement (REM) sleep, for dream recall] within more comprehensive models of human consciousness and its variations across sleep/wake states than the traditional models, which were largely based on the neurophysiology of REM sleep in animals. These studies are casting new light on the neural bases (in particular, the activity of dorsal medial prefrontal cortex regions and hippocampus and amygdala areas) of the inter- and intra-individual differences in dream recall, the temporal location of specific contents or properties (e.g., lucidity) of dream experience and the processing of memories accessed during sleep and incorporated into dream content. Hd-EEG techniques, used on their own or in combination with neuroimaging, appear able to provide further important insights into how the brain generates not only dreaming during sleep but also some dreamlike experiences in waking. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Clinical application of functional near-infrared spectroscopy in rehabilitation medicine].

PubMed

Mihara, Masahito; Yagura, Hajime; Hatakenaka, Megumi; Hattori, Noriaki; Miyai, Ichiro

2010-02-01

Functional near-infrared spectroscopy (fNIRS) is an effective tool to non-invasively investigate cerebral oxygenation and hemodynamics. fNIRS as well as other functional neuroimaging techniques including functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) have been used for investigating the neural mechanisms of functional recovery after a stroke or a traumatic brain injury. fNIRS has several advantages over other neuroimaging techniques in terms of clinical application in the field of rehabilitation medicine. In addition to its portability and low equipment cost, fNIRS does not require strict motion restriction during measurement, unlike other functional imaging techniques. Therefore, this technique enables the examination of cortical activation during physically dynamic activities, like gait or balance perturbation. Studies using fNIRS have revealed several implications for gait recovery after stroke. These studies have shown that the medial sensorimotor cortex (SMC) and the supplementary motor area (SMA) are mainly involved in steadying gait and that the prefrontal cortex (PFC) is involved in the adjustment of walking speed. In hemiparetic patients, lateralization of SMC activation during gait is reduced, and additional cortical activations in the premotor cortex and PFC during gait became evident after focused rehabilitation for several months. The cortical activation pattern may be modified after different types of rehabilitative interventions. These results imply that fNIRS data is a potential biomarker for functional recovery and the response to rehabilitative interventions. Although further studies are required, fNIRS might provide useful information for customizing rehabilitation programs in order to enhance functional recovery.

UNC-Utah NA-MIC framework for DTI fiber tract analysis.

PubMed

Verde, Audrey R; Budin, Francois; Berger, Jean-Baptiste; Gupta, Aditya; Farzinfar, Mahshid; Kaiser, Adrien; Ahn, Mihye; Johnson, Hans; Matsui, Joy; Hazlett, Heather C; Sharma, Anuja; Goodlett, Casey; Shi, Yundi; Gouttard, Sylvain; Vachet, Clement; Piven, Joseph; Zhu, Hongtu; Gerig, Guido; Styner, Martin

2014-01-01

Diffusion tensor imaging has become an important modality in the field of neuroimaging to capture changes in micro-organization and to assess white matter integrity or development. While there exists a number of tractography toolsets, these usually lack tools for preprocessing or to analyze diffusion properties along the fiber tracts. Currently, the field is in critical need of a coherent end-to-end toolset for performing an along-fiber tract analysis, accessible to non-technical neuroimaging researchers. The UNC-Utah NA-MIC DTI framework represents a coherent, open source, end-to-end toolset for atlas fiber tract based DTI analysis encompassing DICOM data conversion, quality control, atlas building, fiber tractography, fiber parameterization, and statistical analysis of diffusion properties. Most steps utilize graphical user interfaces (GUI) to simplify interaction and provide an extensive DTI analysis framework for non-technical researchers/investigators. We illustrate the use of our framework on a small sample, cross sectional neuroimaging study of eight healthy 1-year-old children from the Infant Brain Imaging Study (IBIS) Network. In this limited test study, we illustrate the power of our method by quantifying the diffusion properties at 1 year of age on the genu and splenium fiber tracts.

UNC-Utah NA-MIC framework for DTI fiber tract analysis

PubMed Central

Verde, Audrey R.; Budin, Francois; Berger, Jean-Baptiste; Gupta, Aditya; Farzinfar, Mahshid; Kaiser, Adrien; Ahn, Mihye; Johnson, Hans; Matsui, Joy; Hazlett, Heather C.; Sharma, Anuja; Goodlett, Casey; Shi, Yundi; Gouttard, Sylvain; Vachet, Clement; Piven, Joseph; Zhu, Hongtu; Gerig, Guido; Styner, Martin

2014-01-01

Diffusion tensor imaging has become an important modality in the field of neuroimaging to capture changes in micro-organization and to assess white matter integrity or development. While there exists a number of tractography toolsets, these usually lack tools for preprocessing or to analyze diffusion properties along the fiber tracts. Currently, the field is in critical need of a coherent end-to-end toolset for performing an along-fiber tract analysis, accessible to non-technical neuroimaging researchers. The UNC-Utah NA-MIC DTI framework represents a coherent, open source, end-to-end toolset for atlas fiber tract based DTI analysis encompassing DICOM data conversion, quality control, atlas building, fiber tractography, fiber parameterization, and statistical analysis of diffusion properties. Most steps utilize graphical user interfaces (GUI) to simplify interaction and provide an extensive DTI analysis framework for non-technical researchers/investigators. We illustrate the use of our framework on a small sample, cross sectional neuroimaging study of eight healthy 1-year-old children from the Infant Brain Imaging Study (IBIS) Network. In this limited test study, we illustrate the power of our method by quantifying the diffusion properties at 1 year of age on the genu and splenium fiber tracts. PMID:24409141

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.

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

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

PubMed

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

2017-05-01

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

The intersection of pharmacology, imaging, and genetics in the development of personalized medicine

PubMed Central

Gerretsen, Philip; Müller, Daniel J.; Tiwari, Arun; Mamo, David; Pollock, Bruce G.

2009-01-01

We currently rely on large randomized trials and meta-analyses to make clinical decisions; this places us at a risk of discarding subgroup or individually specific treatment options owing to their failure to prove efficacious across entire populations. There is a new era emerging in personalized medicine that will focus on individual differences that are not evident phenomenologically. Much research is directed towards identifying genes, endophenotypes, and biomarkers of disease that will facilitate diagnosis and predict treatment outcome. We are at the threshold of being able to predict treatment response, primarily through genetics and neuroimaging. In this review we discuss the most promising markers of treatment response and adverse effects emerging from the areas of pharmacogenetics and neuroimaging in depression and schizophrenia. PMID:20135894

Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury

DTIC Science & Technology

2012-09-01

fMRI, DTI , cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a...techniques [task-activated functional MRI (fMRI) and diffusion tensor imaging ( DTI )] to gain a comprehensive understanding of the neural changes...orthopedic injuries. We accomplished this goal by conducting advanced neuroimaging (task-activated fMRI and DTI fiber tracking) and neurobehavioral

Motor-Auditory-Visual Integration: The Role of the Human Mirror Neuron System in Communication and Communication Disorders

ERIC Educational Resources Information Center

Le Bel, Ronald M.; Pineda, Jaime A.; Sharma, Anu

2009-01-01

The mirror neuron system (MNS) is a trimodal system composed of neuronal populations that respond to motor, visual, and auditory stimulation, such as when an action is performed, observed, heard or read about. In humans, the MNS has been identified using neuroimaging techniques (such as fMRI and mu suppression in the EEG). It reflects an…

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.

Comparison of eye lens dose on neuroimaging protocols between 16- and 64-section multidetector CT: achieving the lowest possible dose.

PubMed

Tan, J S P; Tan, K-L; Lee, J C L; Wan, C-M; Leong, J-L; Chan, L-L

2009-02-01

To our knowledge, there has been no study that compares the radiation dose delivered to the eye lens by 16- and 64-section multidetector CT (MDCT) for standard clinical neuroimaging protocols. Our aim was to assess radiation-dose differences between 16- and 64-section MDCT from the same manufacturer, by using near-identical neuroimaging protocols. Three cadaveric heads were scanned on 16- and 64-section MDCT by using standard neuroimaging CT protocols. Eye lens dose was measured by using thermoluminescent dosimeters (TLD), and each scanning was repeated to reduce random error. The dose-length product, volume CT dose index (CTDI(vol)), and TLD readings for each imaging protocol were averaged and compared between scanners and protocols, by using the paired Student t test. Statistical significance was defined at P < .05. The radiation dose delivered and eye lens doses were lower by 28.1%-45.7% (P < .000) on the 64-section MDCT for near-identical imaging protocols. On the 16-section MDCT, lens dose reduction was greatest (81.1%) on a tilted axial mode, compared with a nontilted helical mode for CT brain scans. Among the protocols studied, CT of the temporal bone delivered the greatest radiation dose to the eye lens. Eye lens radiation doses delivered by the 64-section MDCT are significantly lower, partly due to improvements in automatic tube current modulation technology. However, where applicable, protection of the eyes from the radiation beam by either repositioning the head or tilting the gantry remains the best way to reduce eye lens dose.

Multimodal neuroimaging investigations of alterations to consciousness: the relationship between absence epilepsy and sleep.

PubMed

Bagshaw, Andrew P; Rollings, David T; Khalsa, Sakh; Cavanna, Andrea E

2014-01-01

The link between epilepsy and sleep is well established on many levels. The focus of the current review is on recent neuroimaging investigations into the alterations of consciousness that are observed during absence seizures and the descent into sleep. Functional neuroimaging provides simultaneous cortical and subcortical recording of activity throughout the brain, allowing a detailed definition and characterization of large-scale brain networks and the interactions between them. This has led to the identification of a set of regions which collectively form the consciousness system, which includes contributions from the default mode network (DMN), ascending arousal systems, and the thalamus. Electrophysiological and neuroimaging investigations have also clearly demonstrated the importance of thalamocortical and corticothalamic networks in the evolution of sleep and absence epilepsy, two phenomena in which the subject experiences an alteration to the conscious state and a disconnection from external input. However, the precise relationship between the consciousness system, thalamocortical networks, and consciousness itself remains to be clarified. One of the fundamental challenges is to understand how distributed brain networks coordinate their activity in order to maintain and implement complex behaviors such as consciousness and how modifications to this network activity lead to alterations in consciousness. By taking into account not only the level of activation of individual brain regions but also their connectivity within specific networks and the activity and connectivity of other relevant networks, a more specific quantification of brain states can be achieved. This, in turn, may provide a more fundamental understanding of the alterations to consciousness experienced in sleep and epilepsy. © 2013.

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

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.

Adaptive Plasticity in the Healthy Language Network: Implications for Language Recovery after Stroke

PubMed Central

2016-01-01

Across the last three decades, the application of noninvasive brain stimulation (NIBS) has substantially increased the current knowledge of the brain's potential to undergo rapid short-term reorganization on the systems level. A large number of studies applied transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) in the healthy brain to probe the functional relevance and interaction of specific areas for different cognitive processes. NIBS is also increasingly being used to induce adaptive plasticity in motor and cognitive networks and shape cognitive functions. Recently, NIBS has been combined with electrophysiological techniques to modulate neural oscillations of specific cortical networks. In this review, we will discuss recent advances in the use of NIBS to modulate neural activity and effective connectivity in the healthy language network, with a special focus on the combination of NIBS and neuroimaging or electrophysiological approaches. Moreover, we outline how these results can be transferred to the lesioned brain to unravel the dynamics of reorganization processes in poststroke aphasia. We conclude with a critical discussion on the potential of NIBS to facilitate language recovery after stroke and propose a phase-specific model for the application of NIBS in language rehabilitation. PMID:27830094

Differential Neural Activity during Search of Specific and General Autobiographical Memories Elicited by Musical Cues

ERIC Educational Resources Information Center

Ford, Jaclyn Hennessey; Addis, Donna Rose; Giovanello, Kelly S.

2011-01-01

Previous neuroimaging studies that have examined autobiographical memory specificity have utilized retrieval cues associated with prior searches of the event, potentially changing the retrieval processes being investigated. In the current study, musical cues were used to naturally elicit memories from multiple levels of specificity (i.e., lifetime…

Revealing and Quantifying the Impaired Phonological Analysis Underpinning Impaired Comprehension in Wernicke's Aphasia

ERIC Educational Resources Information Center

Robson, Holly; Keidel, James L.; Lambon Ralph, Matthew A.; Sage, Karen

2012-01-01

Wernicke's aphasia is a condition which results in severely disrupted language comprehension following a lesion to the left temporo-parietal region. A phonological analysis deficit has traditionally been held to be at the root of the comprehension impairment in Wernicke's aphasia, a view consistent with current functional neuroimaging which finds…

A Functional Neuroimaging Study of the Clinical Reasoning of Medical Students

ERIC Educational Resources Information Center

Chang, Hyung-Joo; Kang, June; Ham, Byung-Joo; Lee, Young-Mee

2016-01-01

As clinical reasoning is a fundamental competence of physicians for good clinical practices, medical academics have endeavored to teach reasoning skills to undergraduate students. However, our current understanding of student-level clinical reasoning is limited, mainly because of the lack of evaluation tools for this internal cognitive process.…

Mind, Brain, and Literacy: Biomarkers as Usable Knowledge for Education

ERIC Educational Resources Information Center

Goswami, Usha

2009-01-01

Neuroscience has the potential to make some very exciting contributions to education and pedagogy. However, it is important to ask whether the insights from neuroscience studies can provide "usable knowledge" for educators. With respect to literacy, for example, current neuroimaging methods allow us to ask research questions about how the brain…

Functional Neuroimaging of Speech Perception during a Pivotal Period in Language Acquisition

ERIC Educational Resources Information Center

Redcay, Elizabeth; Haist, Frank; Courchesne, Eric

2008-01-01

A pivotal period in the development of language occurs in the second year of life, when language comprehension undergoes rapid acceleration. However, the brain bases of these advances remain speculative as there is currently no functional magnetic resonance imaging (fMRI) data from healthy, typically developing toddlers at this age. We…

Electrical Stimulation of Broca's Area Enhances Implicit Learning of an Artificial Grammar

ERIC Educational Resources Information Center

de Vries, Meinou H.; Barth, Andre C. R.; Maiworm, Sandra; Knecht, Stefan; Zwitserlood, Pienie; Floel, Agnes

2010-01-01

Artificial grammar learning constitutes a well-established model for the acquisition of grammatical knowledge in a natural setting. Previous neuroimaging studies demonstrated that Broca's area (left BA 44/45) is similarly activated by natural syntactic processing and artificial grammar learning. The current study was conducted to investigate the…

Personalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project.

PubMed

Winterer, G; Androsova, G; Bender, O; Boraschi, D; Borchers, F; Dschietzig, T B; Feinkohl, I; Fletcher, P; Gallinat, J; Hadzidiakos, D; Haynes, J D; Heppner, F; Hetzer, S; Hendrikse, J; Ittermann, B; Kant, I M J; Kraft, A; Krannich, A; Krause, R; Kühn, S; Lachmann, G; van Montfort, S J T; Müller, A; Nürnberg, P; Ofosu, K; Pietsch, M; Pischon, T; Preller, J; Renzulli, E; Scheurer, K; Schneider, R; Slooter, A J C; Spies, C; Stamatakis, E; Volk, H D; Weber, S; Wolf, A; Yürek, F; Zacharias, N

2018-04-01

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation. Copyright © 2017. Published by Elsevier Masson SAS.

Is the Sense of Agency in Schizophrenia Influenced by Resting-State Variation in Self-Referential Regions of the Brain?

PubMed Central

Wagner, Nils-Frederic; Northoff, Georg

2016-01-01

Schizophrenia is a disturbance of the self, of which the attribution of agency is a major component. In this article, we review current theories of the Sense of Agency, their relevance to schizophrenia, and propose a novel framework for future research. We explore some of the models of agency, in which both bottom-up and top-down processes are implicated in the genesis of agency. We further this line of inquiry by suggesting that ongoing neurological activity (the brain’s resting state) in self-referential regions of the brain can provide a deeper level of influence beyond what the current models capture. Based on neuroimaging studies, we suggest that aberrant activity in regions such as the default mode network of individuals with schizophrenia can lead to a misattribution of internally/externally generated stimuli. This can result in symptoms such as thought insertion and delusions of control. Consequently, neuroimaging can contribute to a more comprehensive conceptualization and measurement of agency and potential treatment implications. PMID:26221048

The neurobiological basis of binge-eating disorder.

PubMed

Kessler, Robert M; Hutson, Peter H; Herman, Barry K; Potenza, Marc N

2016-04-01

Relatively little is known about the neuropathophysiology of binge-eating disorder (BED). Here, the evidence from neuroimaging, neurocognitive, genetics, and animal studies are reviewed to synthesize our current understanding of the pathophysiology of BED. Binge-eating disorder may be conceptualized as an impulsive/compulsive disorder, with altered reward sensitivity and food-related attentional biases. Neuroimaging studies suggest there are corticostriatal circuitry alterations in BED similar to those observed in substance abuse, including altered function of prefrontal, insular, and orbitofrontal cortices and the striatum. Human genetics and animal studies suggest that there are changes in neurotransmitter networks, including dopaminergic and opioidergic systems, associated with binge-eating behaviors. Overall, the current evidence suggests that BED may be related to maladaptation of the corticostriatal circuitry regulating motivation and impulse control similar to that found in other impulsive/compulsive disorders. Further studies are needed to understand the genetics of BED and how neurotransmitter activity and neurocircuitry function are altered in BED and how pharmacotherapies may influence these systems to reduce BED symptoms. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Lexical is as lexical does: computational approaches to lexical representation

PubMed Central

Woollams, Anna M.

2015-01-01

In much of neuroimaging and neuropsychology, regions of the brain have been associated with ‘lexical representation’, with little consideration as to what this cognitive construct actually denotes. Within current computational models of word recognition, there are a number of different approaches to the representation of lexical knowledge. Structural lexical representations, found in original theories of word recognition, have been instantiated in modern localist models. However, such a representational scheme lacks neural plausibility in terms of economy and flexibility. Connectionist models have therefore adopted distributed representations of form and meaning. Semantic representations in connectionist models necessarily encode lexical knowledge. Yet when equipped with recurrent connections, connectionist models can also develop attractors for familiar forms that function as lexical representations. Current behavioural, neuropsychological and neuroimaging evidence shows a clear role for semantic information, but also suggests some modality- and task-specific lexical representations. A variety of connectionist architectures could implement these distributed functional representations, and further experimental and simulation work is required to discriminate between these alternatives. Future conceptualisations of lexical representations will therefore emerge from a synergy between modelling and neuroscience. PMID:25893204

Non-invasive brain stimulation: an interventional tool for enhancing behavioral training after stroke.

PubMed

Wessel, Maximilian J; Zimerman, Máximo; Hummel, Friedhelm C

2015-01-01

Stroke is the leading cause of disability among adults. Motor deficit is the most common impairment after stroke. Especially, deficits in fine motor skills impair numerous activities of daily life. Re-acquisition of motor skills resulting in improved or more accurate motor performance is paramount to regain function, and is the basis of behavioral motor therapy after stroke. Within the past years, there has been a rapid technological and methodological development in neuroimaging leading to a significant progress in the understanding of the neural substrates that underlie motor skill acquisition and functional recovery in stroke patients. Based on this and the development of novel non-invasive brain stimulation (NIBS) techniques, new adjuvant interventional approaches that augment the response to behavioral training have been proposed. Transcranial direct current, transcranial magnetic, and paired associative (PAS) stimulation are NIBS techniques that can modulate cortical excitability, neuronal plasticity and interact with learning and memory in both healthy individuals and stroke patients. These techniques can enhance the effect of practice and facilitate the retention of tasks that mimic daily life activities. The purpose of the present review is to provide a comprehensive overview of neuroplastic phenomena in the motor system during learning of a motor skill, recovery after brain injury, and of interventional strategies to enhance the beneficial effects of customarily used neurorehabilitation after stroke.

Non-Invasive Brain Stimulation: An Interventional Tool for Enhancing Behavioral Training after Stroke

PubMed Central

Wessel, Maximilian J.; Zimerman, Máximo; Hummel, Friedhelm C.

2015-01-01

Stroke is the leading cause of disability among adults. Motor deficit is the most common impairment after stroke. Especially, deficits in fine motor skills impair numerous activities of daily life. Re-acquisition of motor skills resulting in improved or more accurate motor performance is paramount to regain function, and is the basis of behavioral motor therapy after stroke. Within the past years, there has been a rapid technological and methodological development in neuroimaging leading to a significant progress in the understanding of the neural substrates that underlie motor skill acquisition and functional recovery in stroke patients. Based on this and the development of novel non-invasive brain stimulation (NIBS) techniques, new adjuvant interventional approaches that augment the response to behavioral training have been proposed. Transcranial direct current, transcranial magnetic, and paired associative (PAS) stimulation are NIBS techniques that can modulate cortical excitability, neuronal plasticity and interact with learning and memory in both healthy individuals and stroke patients. These techniques can enhance the effect of practice and facilitate the retention of tasks that mimic daily life activities. The purpose of the present review is to provide a comprehensive overview of neuroplastic phenomena in the motor system during learning of a motor skill, recovery after brain injury, and of interventional strategies to enhance the beneficial effects of customarily used neurorehabilitation after stroke. PMID:26029083

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

Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the american heart association/american stroke association.

PubMed

Gorelick, Philip B; Scuteri, Angelo; Black, Sandra E; Decarli, Charles; Greenberg, Steven M; Iadecola, Costantino; Launer, Lenore J; Laurent, Stephane; Lopez, Oscar L; Nyenhuis, David; Petersen, Ronald C; Schneider, Julie A; Tzourio, Christophe; Arnett, Donna K; Bennett, David A; Chui, Helena C; Higashida, Randall T; Lindquist, Ruth; Nilsson, Peter M; Roman, Gustavo C; Sellke, Frank W; Seshadri, Sudha

2011-09-01

This scientific statement provides an overview of the evidence on vascular contributions to cognitive impairment and dementia. Vascular contributions to cognitive impairment and dementia of later life are common. Definitions of vascular cognitive impairment (VCI), neuropathology, basic science and pathophysiological aspects, role of neuroimaging and vascular and other associated risk factors, and potential opportunities for prevention and treatment are reviewed. This statement serves as an overall guide for practitioners to gain a better understanding of VCI and dementia, prevention, and treatment. Writing group members were nominated by the writing group co-chairs on the basis of their previous work in relevant topic areas and were approved by the American Heart Association Stroke Council Scientific Statement Oversight Committee, the Council on Epidemiology and Prevention, and the Manuscript Oversight Committee. The writing group used systematic literature reviews (primarily covering publications from 1990 to May 1, 2010), previously published guidelines, personal files, and expert opinion to summarize existing evidence, indicate gaps in current knowledge, and, when appropriate, formulate recommendations using standard American Heart Association criteria. All members of the writing group had the opportunity to comment on the recommendations and approved the final version of this document. After peer review by the American Heart Association, as well as review by the Stroke Council leadership, Council on Epidemiology and Prevention Council, and Scientific Statements Oversight Committee, the statement was approved by the American Heart Association Science Advisory and Coordinating Committee. The construct of VCI has been introduced to capture the entire spectrum of cognitive disorders associated with all forms of cerebral vascular brain injury-not solely stroke-ranging from mild cognitive impairment through fully developed dementia. Dysfunction of the neurovascular unit and mechanisms regulating cerebral blood flow are likely to be important components of the pathophysiological processes underlying VCI. Cerebral amyloid angiopathy is emerging as an important marker of risk for Alzheimer disease, microinfarction, microhemorrhage and macrohemorrhage of the brain, and VCI. The neuropathology of cognitive impairment in later life is often a mixture of Alzheimer disease and microvascular brain damage, which may overlap and synergize to heighten the risk of cognitive impairment. In this regard, magnetic resonance imaging and other neuroimaging techniques play an important role in the definition and detection of VCI and provide evidence that subcortical forms of VCI with white matter hyperintensities and small deep infarcts are common. In many cases, risk markers for VCI are the same as traditional risk factors for stroke. These risks may include but are not limited to atrial fibrillation, hypertension, diabetes mellitus, and hypercholesterolemia. Furthermore, these same vascular risk factors may be risk markers for Alzheimer disease. Carotid intimal-medial thickness and arterial stiffness are emerging as markers of arterial aging and may serve as risk markers for VCI. Currently, no specific treatments for VCI have been approved by the US Food and Drug Administration. However, detection and control of the traditional risk factors for stroke and cardiovascular disease may be effective in the prevention of VCI, even in older people. Vascular contributions to cognitive impairment and dementia are important. Understanding of VCI has evolved substantially in recent years, based on preclinical, neuropathologic, neuroimaging, physiological, and epidemiological studies. Transdisciplinary, translational, and transactional approaches are recommended to further our understanding of this entity and to better characterize its neuropsychological profile. There is a need for prospective, quantitative, clinical-pathological-neuroimaging studies to improve knowledge of the pathological basis of neuroimaging change and the complex interplay between vascular and Alzheimer disease pathologies in the evolution of clinical VCI and Alzheimer disease. Long-term vascular risk marker interventional studies beginning as early as midlife may be required to prevent or postpone the onset of VCI and Alzheimer disease. Studies of intensive reduction of vascular risk factors in high-risk groups are another important avenue of research.

Vascular Contributions to Cognitive Impairment and Dementia

PubMed Central

Gorelick, Philip B.; Scuteri, Angelo; Black, Sandra E.; DeCarli, Charles; Greenberg, Steven M.; Iadecola, Costantino; Launer, Lenore J.; Laurent, Stephane; Lopez, Oscar L.; Nyenhuis, David; Petersen, Ronald C.; Schneider, Julie A.; Tzourio, Christophe; Arnett, Donna K.; Bennett, David A.; Chui, Helena C.; Higashida, Randall T.; Lindquist, Ruth; Nilsson, Peter M.; Roman, Gustavo C.; Sellke, Frank W.; Seshadri, Sudha

2013-01-01

Background and Purpose This scientific statement provides an overview of the evidence on vascular contributions to cognitive impairment and dementia. Vascular contributions to cognitive impairment and dementia of later life are common. Definitions of vascular cognitive impairment (VCI), neuropathology, basic science and pathophysiological aspects, role of neuroimaging and vascular and other associated risk factors, and potential opportunities for prevention and treatment are reviewed. This statement serves as an overall guide for practitioners to gain a better understanding of VCI and dementia, prevention, and treatment. Methods Writing group members were nominated by the writing group co-chairs on the basis of their previous work in relevant topic areas and were approved by the American Heart Association Stroke Council Scientific Statement Oversight Committee, the Council on Epidemiology and Prevention, and the Manuscript Oversight Committee. The writing group used systematic literature reviews (primarily covering publications from 1990 to May 1, 2010), previously published guidelines, personal files, and expert opinion to summarize existing evidence, indicate gaps in current knowledge, and, when appropriate, formulate recommendations using standard American Heart Association criteria. All members of the writing group had the opportunity to comment on the recommendations and approved the final version of this document. After peer review by the American Heart Association, as well as review by the Stroke Council leadership, Council on Epidemiology and Prevention Council, and Scientific Statements Oversight Committee, the statement was approved by the American Heart Association Science Advisory and Coordinating Committee. Results The construct of VCI has been introduced to capture the entire spectrum of cognitive disorders associated with all forms of cerebral vascular brain injury—not solely stroke—ranging from mild cognitive impairment through fully developed dementia. Dysfunction of the neurovascular unit and mechanisms regulating cerebral blood flow are likely to be important components of the pathophysiological processes underlying VCI. Cerebral amyloid angiopathy is emerging as an important marker of risk for Alzheimer disease, microinfarction, microhemorrhage and macrohemorrhage of the brain, and VCI. The neuropathology of cognitive impairment in later life is often a mixture of Alzheimer disease and microvascular brain damage, which may overlap and synergize to heighten the risk of cognitive impairment. In this regard, magnetic resonance imaging and other neuroimaging techniques play an important role in the definition and detection of VCI and provide evidence that subcortical forms of VCI with white matter hyperintensities and small deep infarcts are common. In many cases, risk markers for VCI are the same as traditional risk factors for stroke. These risks may include but are not limited to atrial fibrillation, hypertension, diabetes mellitus, and hypercholesterolemia. Furthermore, these same vascular risk factors may be risk markers for Alzheimer disease. Carotid intimal-medial thickness and arterial stiffness are emerging as markers of arterial aging and may serve as risk markers for VCI. Currently, no specific treatments for VCI have been approved by the US Food and Drug Administration. However, detection and control of the traditional risk factors for stroke and cardiovascular disease may be effective in the prevention of VCI, even in older people. Conclusions Vascular contributions to cognitive impairment and dementia are important. Understanding of VCI has evolved substantially in recent years, based on preclinical, neuropathologic, neuroimaging, physiological, and epidemiological studies. Transdisciplinary, translational, and transactional approaches are recommended to further our understanding of this entity and to better characterize its neuropsychological profile. There is a need for prospective, quantitative, clinical-pathological-neuroimaging studies to improve knowledge of the pathological basis of neuroimaging change and the complex interplay between vascular and Alzheimer disease pathologies in the evolution of clinical VCI and Alzheimer disease. Long-term vascular risk marker interventional studies beginning as early as midlife may be required to prevent or postpone the onset of VCI and Alzheimer disease. Studies of intensive reduction of vascular risk factors in high-risk groups are another important avenue of research. PMID:21778438

MicroV Technology to Improve Transcranial Color Coded Doppler Examinations.

PubMed

Malferrari, Giovanni; Pulito, Giuseppe; Pizzini, Attilia Maria; Carraro, Nicola; Meneghetti, Giorgio; Sanzaro, Enzo; Prati, Patrizio; Siniscalchi, Antonio; Monaco, Daniela

2018-05-04

The purpose of this review is to provide an update on technology related to Transcranial Color Coded Doppler Examinations. Microvascularization (MicroV) is an emerging Power Doppler technology which can allow visualization of low and weak blood flows even at high depths, thus providing a suitable technique for transcranial ultrasound analysis. With MicroV, reconstruction of the vessel shape can be improved, without any overestimation. Furthermore, by analyzing the Doppler signal, MicroV allows a global image of the Circle of Willis. Transcranial Doppler was originally developed for the velocimetric analysis of intracranial vessels, in particular to detect stenoses and the assessment of collateral circulation. Doppler velocimetric analysis was then compared to other neuroimaging techniques, thus providing a cut-off threshold. Transcranial Color Coded Doppler sonography allowed the characterization of vessel morphology. In both Color Doppler and Power Doppler, the signal overestimated the shape of the intracranial vessels, mostly in the presence of thin vessels and high depths of study. In further neurosonology technology development efforts, attempts have been made to address morphology issues and overcome technical limitations. The use of contrast agents has helped in this regard by introducing harmonics and subtraction software, which allowed better morphological studies of vessels, due to their increased signal-to-noise ratio. Having no limitations in the learning curve, in time and contrast agent techniques, and due to its high signal-to-noise ratio, MicroV has shown great potential to obtain the best morphological definition. Copyright © 2018 by the American Society of Neuroimaging.

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.

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

PubMed

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

2017-07-01

This study was intended to describe and correlate the neuroimaging findings in pediatric patients after sepsis. Retrospective chart review. Single tertiary care PICU. Patients admitted to Cincinnati Children's Hospital Medical Center with a discharge diagnosis of sepsis or septic shock between 2004 and 2013 were crossmatched with patients who underwent neuroimaging during the same time period. All neuroimaging studies that occurred during or subsequent to a septic event were reviewed, and all new imaging findings were recorded and classified. As many patients experienced multiple septic events and/or had multiple neuroimaging studies after sepsis, our statistical analysis utilized the most recent or "final" imaging study available for each patient so that only brain imaging findings that persisted were included. A total of 389 children with sepsis and 1,705 concurrent or subsequent neuroimaging studies were included in the study. Median age at first septic event was 3.4 years (interquartile range, 0.7-11.5). Median time from first sepsis event to final neuroimaging was 157 days (interquartile range, 10-1,054). The most common indications for final imaging were follow-up (21%), altered mental status (18%), and fever/concern for infection (15%). Sixty-three percentage (n = 243) of final imaging studies demonstrated abnormal findings, the most common of which were volume loss (39%) and MRI signal and/or CT attenuation abnormalities (21%). On multivariable logistic regression, highest Pediatric Risk of Mortality score and presence of oncologic diagnosis/organ transplantation were independently associated with any abnormal final neuroimaging study findings (odds ratio, 1.032; p = 0.048 and odds ratio, 1.632; p = 0.041), although early timing of neuroimaging demonstrated a negative association (odds ratio, 0.606; p = 0.039). The most common abnormal finding of volume loss was independently associated with highest Pediatric Risk of Mortality score (odds ratio, 1.037; p = 0.016) and oncologic diagnosis/organ transplantation (odds ratio, 2.207; p = 0.001) and was negatively associated with early timing of neuroimaging (odds ratio, 0.575; p = 0.037). The majority of pediatric patients with sepsis and concurrent or subsequent neuroimaging have abnormal neuroimaging findings. The implications of this high incidence for long-term neurologic outcomes and follow-up require further exploration.

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.

The thalamus and multiple sclerosis

PubMed Central

Minagar, Alireza; Barnett, Michael H.; Benedict, Ralph H.B.; Pelletier, Daniel; Pirko, Istvan; Sahraian, Mohamad Ali; Frohman, Elliott

2013-01-01

The paired thalamic nuclei are gray matter (GM) structures on both sides of the third ventricle that play major roles in cortical activation, relaying sensory information to the higher cortical centers that influence cognition. Multiple sclerosis (MS) is an immune-mediated disease of the human CNS that affects both the white matter (WM) and GM. A number of clinical observations as well as recent neuropathologic and neuroimaging studies have clearly demonstrated extensive involvement of the thalamus, basal ganglia, and neocortex in patients with MS. Modern MRI techniques permit visualization of GM lesions and measurement of atrophy. These contemporary methods have fundamentally altered our understanding of the pathophysiologic nature of MS. Evidence confirms the contention that GM injury can be detected in the earliest phases of MS, and that iron deposition and atrophy of deep gray nuclei are closely related to the magnitude of inflammation. Extensive involvement of GM, and particularly of the thalamus, is associated with a wide range of clinical manifestations including cognitive decline, motor deficits, fatigue, painful syndromes, and ocular motility disturbances in patients with MS. In this review, we characterize the neuropathologic, neuroimaging, and clinical features of thalamic involvement in MS. Further, we underscore the contention that neuropathologic and neuroimaging correlative investigations of thalamic derangements in MS may elucidate not heretofore considered pathobiological underpinnings germane to understanding the ontogeny, magnitude, and progression of the disease process. PMID:23296131

The thalamus and multiple sclerosis: modern views on pathologic, imaging, and clinical aspects.

PubMed

Minagar, Alireza; Barnett, Michael H; Benedict, Ralph H B; Pelletier, Daniel; Pirko, Istvan; Sahraian, Mohamad Ali; Frohman, Elliott; Zivadinov, Robert

2013-01-08

The paired thalamic nuclei are gray matter (GM) structures on both sides of the third ventricle that play major roles in cortical activation, relaying sensory information to the higher cortical centers that influence cognition. Multiple sclerosis (MS) is an immune-mediated disease of the human CNS that affects both the white matter (WM) and GM. A number of clinical observations as well as recent neuropathologic and neuroimaging studies have clearly demonstrated extensive involvement of the thalamus, basal ganglia, and neocortex in patients with MS. Modern MRI techniques permit visualization of GM lesions and measurement of atrophy. These contemporary methods have fundamentally altered our understanding of the pathophysiologic nature of MS. Evidence confirms the contention that GM injury can be detected in the earliest phases of MS, and that iron deposition and atrophy of deep gray nuclei are closely related to the magnitude of inflammation. Extensive involvement of GM, and particularly of the thalamus, is associated with a wide range of clinical manifestations including cognitive decline, motor deficits, fatigue, painful syndromes, and ocular motility disturbances in patients with MS. In this review, we characterize the neuropathologic, neuroimaging, and clinical features of thalamic involvement in MS. Further, we underscore the contention that neuropathologic and neuroimaging correlative investigations of thalamic derangements in MS may elucidate not heretofore considered pathobiological underpinnings germane to understanding the ontogeny, magnitude, and progression of the disease process.

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.

Toward sophisticated basal ganglia neuromodulation: Review on basal ganglia deep brain stimulation.

PubMed

Da Cunha, Claudio; Boschen, Suelen L; Gómez-A, Alexander; Ross, Erika K; Gibson, William S J; Min, Hoon-Ki; Lee, Kendall H; Blaha, Charles D

2015-11-01

This review presents state-of-the-art knowledge about the roles of the basal ganglia (BG) in action-selection, cognition, and motivation, and how this knowledge has been used to improve deep brain stimulation (DBS) treatment of neurological and psychiatric disorders. Such pathological conditions include Parkinson's disease, Huntington's disease, Tourette syndrome, depression, and obsessive-compulsive disorder. The first section presents evidence supporting current hypotheses of how the cortico-BG circuitry works to select motor and emotional actions, and how defects in this circuitry can cause symptoms of the BG diseases. Emphasis is given to the role of striatal dopamine on motor performance, motivated behaviors and learning of procedural memories. Next, the use of cutting-edge electrochemical techniques in animal and human studies of BG functioning under normal and disease conditions is discussed. Finally, functional neuroimaging studies are reviewed; these works have shown the relationship between cortico-BG structures activated during DBS and improvement of disease symptoms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Toward sophisiticated basal ganglia neuromodulation: review on basal gaglia deep brain stimulation

PubMed Central

Da Cunha, Claudio; Boschen, Suelen L.; Gómez-A, Alexander; Ross, Erika K.; Gibson, William S. J.; Min, Hoon-Ki; Lee, Kendall H.; Blaha, Charles D.

2015-01-01

This review presents state-of-the-art knowledge about the roles of the basal ganglia (BG) in action-selection, cognition, and motivation, and how this knowledge has been used to improve deep brain stimulation (DBS) treatment of neurological and psychiatric disorders. Such pathological conditions include Parkinson’s disease, Huntington’s disease, Tourette syndrome, depression, and obsessive-compulsive disorder. The first section presents evidence supporting current hypotheses of how the cortico-BG circuitry works to select motor and emotional actions, and how defects in this circuitry can cause symptoms of the BG diseases. Emphasis is given to the role of striatal dopamine on motor performance, motivated behaviors and learning of procedural memories. Next, the use of cutting-edge electrochemical techniques in animal and human studies of BG functioning under normal and disease conditions is discussed. Finally, functional neuroimaging studies are reviewed; these works have shown the relationship between cortico-BG structures activated during DBS and improvement of disease symptoms. PMID:25684727

Age-Related Effects of Alcohol from Adolescent, Adult, and Aged Populations Using Human and Animal Models

PubMed Central

Squeglia, Lindsay M.; Boissoneault, Jeff; Van Skike, Candice E.; Nixon, Sara Jo; Matthews, Douglas B.

2014-01-01

Background This review incorporates current research examining alcohol's differential effects on adolescents, adults, and aged populations in both animal and clinical models. Methods The studies presented range from cognitive, behavioral, molecular, and neuroimaging techniques, leading to a more comprehensive understanding of how acute and chronic alcohol use affects the brain throughout the life span. Results Age of life is a significant factor in determining the effect of alcohol on brain functioning. Adolescents and aged populations may be more negatively affected by heavy alcohol use when compared to adults. Conclusions Investigations limiting alcohol effects to a single age group constrains understanding of differential trajectories and outcomes following acute and chronic use. To meaningfully address the sequencing and interaction effects of alcohol and age, the field must incorporate collaborative and integrated research efforts focused on interdisciplinary questions facilitated by engaging basic and applied scientists with expertise in a range of disciplines including alcohol, neurodevelopment, and aging. PMID:25156779

Delay discounting as emotional processing: an electrophysiological study.

PubMed

Blackburn, Marianna; Mason, Liam; Hoeksma, Marco; Zandstra, Elizabeth H; El-Deredy, Wael

2012-01-01

Both theoretical models and functional imaging studies implicate the involvement of emotions within the delay discounting process. However, defining this role has been difficult to establish with neuroimaging techniques given the automaticity of emotional responses. To address this, the current study examined electrophysiological correlates involved in the detection and evaluation of immediate and delayed monetary outcomes. Our results showed that modulation of both early and later ERP components previously associated with affective stimuli processing are sensitive to the signalling of delayed rewards. Together with behavioural reaction times that favoured immediacy, we demonstrated, for the first time, that time delays modify the incentive value of monetary rewards via mechanisms of emotional bias and selective visual attention. Furthermore, our data are consistent with the hypothesis that delayed and thus intangible rewards are perceived less saliently, and rely on emotion as a common currency within decision making. This study provides a new approach to delay discounting and highlights a potential novel route through which delay discounting may be investigated.

Variability in Reward Responsivity and Obesity: Evidence from Brain Imaging Studies

PubMed Central

Burger, Kyle S.; Stice, Eric

2012-01-01

Advances in neuroimaging techniques have provided insight into the role of the brain in the regulation of food intake and weight. Growing evidence demonstrate that energy dense, palatable foods elicit similar responses in reward-related brain regions that mimic those of addictive substances. Currently, various models of obesity’s relation to reward from food have been theorized. There is evidence to support a theory of hypo-responsivity of reward regions to food, where individuals consume excess amounts to overcome this reward deficit. There is also data to support a theory of hyper-responsivity of reward regions, where individuals who experience greater reward from food intake are at risk for overeating. However, these seemingly discordant theories are static in nature and do not account for the possible effects of repeated overeating on brain responsivity to food and initial vulnerability factors. Here we review data that support these theories and propose a dynamic vulnerability model of obesity that appears to offer a parsimonious theory that accommodates extant findings. PMID:21999692

[Genetic and neuroendocrine aspects in autism spectrum disorder].

PubMed

Oviedo, Norma; Manuel-Apolinar, Leticia; de la Chesnaye, Elsa; Guerra-Araiza, Christian

The autism spectrum disorder (ASD) was described in 1943 and is defined as a developmental disorder that affects social interaction and communication. It is usually identified in early stages of development from 18 months of age. Currently, autism is considered a neurological disorder with a spectrum covering cases of different degrees, which is associated with genetic factors, not genetic and environmental. Among the genetic factors, various syndromes have been described that are associated with this disorder. Also, the neurobiology of autism has been studied at the genetic, neurophysiological, neurochemical and neuropathological levels. Neuroimaging techniques have shown multiple structural abnormalities in these patients. There have also been changes in the serotonergic, GABAergic, catecholaminergic and cholinergic systems related to this disorder. This paper presents an update of the information presented in the genetic and neuroendocrine aspects of autism spectrum disorder. Copyright © 2014 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Neonatal hemodynamic response to visual cortex activity: high-density near-infrared spectroscopy study

NASA Astrophysics Data System (ADS)

Liao, Steve M.; Gregg, Nick M.; White, Brian R.; Zeff, Benjamin W.; Bjerkaas, Katelin A.; Inder, Terrie E.; Culver, Joseph P.

2010-03-01

The neurodevelopmental outcome of neonatal intensive care unit (NICU) infants is a major clinical concern with many infants displaying neurobehavioral deficits in childhood. Functional neuroimaging may provide early recognition of neural deficits in high-risk infants. Near-infrared spectroscopy (NIRS) has the advantage of providing functional neuroimaging in infants at the bedside. However, limitations in traditional NIRS have included contamination from superficial vascular dynamics in the scalp. Furthermore, controversy exists over the nature of normal vascular, responses in infants. To address these issues, we extend the use of novel high-density NIRS arrays with multiple source-detector distances and a superficial signal regression technique to infants. Evaluations of healthy term-born infants within the first three days of life are performed without sedation using a visual stimulus. We find that the regression technique significantly improves brain activation signal quality. Furthermore, in six out of eight infants, both oxy- and total hemoglobin increases while deoxyhemoglobin decreases, suggesting that, at term, the neurovascular coupling in the visual cortex is similar to that found in healthy adults. These results demonstrate the feasibility of using high-density NIRS arrays in infants to improve signal quality through superficial signal regression, and provide a foundation for further development of high-density NIRS as a clinical tool.

The Meditative Mind: A Comprehensive Meta-Analysis of MRI Studies

PubMed Central

2015-01-01

Over the past decade mind and body practices, such as yoga and meditation, have raised interest in different scientific fields; in particular, the physiological mechanisms underlying the beneficial effects observed in meditators have been investigated. Neuroimaging studies have studied the effects of meditation on brain structure and function and findings have helped clarify the biological underpinnings of the positive effects of meditation practice and the possible integration of this technique in standard therapy. The large amount of data collected thus far allows drawing some conclusions about the neural effects of meditation practice. In the present study we used activation likelihood estimation (ALE) analysis to make a coordinate-based meta-analysis of neuroimaging data on the effects of meditation on brain structure and function. Results indicate that meditation leads to activation in brain areas involved in processing self-relevant information, self-regulation, focused problem-solving, adaptive behavior, and interoception. Results also show that meditation practice induces functional and structural brain modifications in expert meditators, especially in areas involved in self-referential processes such as self-awareness and self-regulation. These results demonstrate that a biological substrate underlies the positive pervasive effect of meditation practice and suggest that meditation techniques could be adopted in clinical populations and to prevent disease. PMID:26146618

Functional neuroimaging of amphetamine-induced striatal neurotoxicity in the pleiotrophin knockout mouse model.

PubMed

Soto-Montenegro, María Luisa; Vicente-Rodríguez, Marta; Pérez-García, Carmen; Gramage, Esther; Desco, Manuel; Herradón, Gonzalo

2015-03-30

Amphetamine-induced neurotoxic effects have traditionally been studied using immunohistochemistry and other post-mortem techniques, which have proven invaluable for the definition of amphetamine-induced dopaminergic damage in the nigrostriatal pathway. However, these approaches are limited in that they require large numbers of animals and do not provide the temporal data that can be collected in longitudinal studies using functional neuroimaging techniques. Unfortunately, functional imaging studies in rodent models of drug-induced neurotoxicity are lacking. The aim of this study was to evaluate in vivo the changes in brain glucose metabolism caused by amphetamine in the pleiotrophin knockout mouse (PTN-/-), a genetic model with increased vulnerability to amphetamine-induced neurotoxic effects. We showed that administration of amphetamine causes a significantly greater loss of striatal tyrosine hydroxylase content in PTN-/- mice than in wild-type (WT) mice. In addition, [(18)F]-FDG-PET shows that amphetamine produces a significant decrease in glucose metabolism in the striatum and prefrontal cortex in the PTN-/- mice, compared to WT mice. These findings suggest that [(18)F]-FDG uptake measured by PET is useful for detecting amphetamine-induced changes in glucose metabolism in vivo in specific brain areas, including the striatum, a key feature of amphetamine-induced neurotoxicity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging

PubMed Central

Lauzon, Carolyn B.; Asman, Andrew J.; Esparza, Michael L.; Burns, Scott S.; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W.; Davis, Nicole; Cutting, Laurie E.; Landman, Bennett A.

2013-01-01

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible. PMID:23637895

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.

Neuroimaging and Neuromodulation: Complementary Approaches for Identifying the Neuronal Correlates of Tinnitus

PubMed Central

Langguth, Berthold; Schecklmann, Martin; Lehner, Astrid; Landgrebe, Michael; Poeppl, Timm Benjamin; Kreuzer, Peter Michal; Schlee, Winfried; Weisz, Nathan; Vanneste, Sven; De Ridder, Dirk

2012-01-01

An inherent limitation of functional imaging studies is their correlational approach. More information about critical contributions of specific brain regions can be gained by focal transient perturbation of neural activity in specific regions with non-invasive focal brain stimulation methods. Functional imaging studies have revealed that tinnitus is related to alterations in neuronal activity of central auditory pathways. Modulation of neuronal activity in auditory cortical areas by repetitive transcranial magnetic stimulation (rTMS) can reduce tinnitus loudness and, if applied repeatedly, exerts therapeutic effects, confirming the relevance of auditory cortex activation for tinnitus generation and persistence. Measurements of oscillatory brain activity before and after rTMS demonstrate that the same stimulation protocol has different effects on brain activity in different patients, presumably related to interindividual differences in baseline activity in the clinically heterogeneous study cohort. In addition to alterations in auditory pathways, imaging techniques also indicate the involvement of non-auditory brain areas, such as the fronto-parietal “awareness” network and the non-tinnitus-specific distress network consisting of the anterior cingulate cortex, anterior insula, and amygdale. Involvement of the hippocampus and the parahippocampal region putatively reflects the relevance of memory mechanisms in the persistence of the phantom percept and the associated distress. Preliminary studies targeting the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the parietal cortex with rTMS and with transcranial direct current stimulation confirm the relevance of the mentioned non-auditory networks. Available data indicate the important value added by brain stimulation as a complementary approach to neuroimaging for identifying the neuronal correlates of the various clinical aspects of tinnitus. PMID:22509155

Neurobiology of dynamic psychotherapy: an integration possible?

PubMed

Mundo, Emanuela

2006-01-01

In the last decades, Kandel's innovative experiments have demonstrated that brain structures and synaptic connections are dynamic. Synapses can be modified by a wide variety of environmental factors, including learning and memory processes. The hypothesis that dynamic psychotherapy process involves memory and learning processes has opened the possibility of a dialogue between neuroscience and psychoanalysis and related psychotherapy techniques. The primary aim of the present article is to critically review the more recent data on neurobiological effects of dynamic psychotherapy in psychiatric disorders. Relevant literature has been selected using the databases currently available online (i.e., PubMed). The literature search has been limited to the past 10 years and to genetic, molecular biology, and neuroimaging studies that have addressed the issue of changes induced by psychotherapy. Most of the genetic studies on mental disorders have demonstrated that psychiatric conditions result from a complex interaction of genetic susceptibility and environmental effects. For none of the many psychiatric conditions investigated has a purely genetic background been found. Molecular biology studies have indicated that gene expression is influenced by several environmental factors, including early experiences, traumas, learning, and memory processes. Neuroimaging studies (using fMRI and PET) have found that not only cognitive but also dynamic psychotherapy has measurable effects on the brain. In addition, psychotherapy may modify brain function and metabolism in specific brain areas. Most of these studies have considered patients with major depressive disorders and compared the effects of psychotherapy with the effect of standard pharmacotherapy. In conclusion, recent results from neuroscience studies have suggested that dynamic psychotherapy has a significant impact on brain function and metabolism in specific brain areas. The possible applications and developments of this new area of research toward the conceptualization of an integrative approach to treatment of psychiatric disorders are discussed.

Simultaneous analysis and quality assurance for diffusion tensor imaging.

PubMed

Lauzon, Carolyn B; Asman, Andrew J; Esparza, Michael L; Burns, Scott S; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W; Davis, Nicole; Cutting, Laurie E; Landman, Bennett A

2013-01-01

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible.

Computational neuroscience approach to biomarkers and treatments for mental disorders.

PubMed

Yahata, Noriaki; Kasai, Kiyoto; Kawato, Mitsuo

2017-04-01

Psychiatry research has long experienced a stagnation stemming from a lack of understanding of the neurobiological underpinnings of phenomenologically defined mental disorders. Recently, the application of computational neuroscience to psychiatry research has shown great promise in establishing a link between phenomenological and pathophysiological aspects of mental disorders, thereby recasting current nosology in more biologically meaningful dimensions. In this review, we highlight recent investigations into computational neuroscience that have undertaken either theory- or data-driven approaches to quantitatively delineate the mechanisms of mental disorders. The theory-driven approach, including reinforcement learning models, plays an integrative role in this process by enabling correspondence between behavior and disorder-specific alterations at multiple levels of brain organization, ranging from molecules to cells to circuits. Previous studies have explicated a plethora of defining symptoms of mental disorders, including anhedonia, inattention, and poor executive function. The data-driven approach, on the other hand, is an emerging field in computational neuroscience seeking to identify disorder-specific features among high-dimensional big data. Remarkably, various machine-learning techniques have been applied to neuroimaging data, and the extracted disorder-specific features have been used for automatic case-control classification. For many disorders, the reported accuracies have reached 90% or more. However, we note that rigorous tests on independent cohorts are critically required to translate this research into clinical applications. Finally, we discuss the utility of the disorder-specific features found by the data-driven approach to psychiatric therapies, including neurofeedback. Such developments will allow simultaneous diagnosis and treatment of mental disorders using neuroimaging, thereby establishing 'theranostics' for the first time in clinical psychiatry. © 2016 The Authors. Psychiatry and Clinical Neurosciences © 2016 Japanese Society of Psychiatry and Neurology.

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

Body Schematics: On the Role of the Body Schema in Embodied Lexical-Semantic Representations

ERIC Educational Resources Information Center

Rueschemeyer, Shirley-Ann; Pfeiffer, Christian; Bekkering, Harold

2010-01-01

Words denoting manipulable objects activate sensorimotor brain areas, likely reflecting action experience with the denoted objects. In particular, these sensorimotor lexical representations have been found to reflect the way in which an object is used. In the current paper we present data from two experiments (one behavioral and one neuroimaging)…

Differential Diagnosis of Dysgraphia, Dyslexia, and OWL LD: Behavioral and Neuroimaging Evidence

ERIC Educational Resources Information Center

Berninger, Virginia W.; Richards, Todd L.; Abbott, Robert D.

2015-01-01

In Study 1, children in grades 4-9 (N = 88, 29 females and 59 males) with persisting reading and/or writing disabilities, despite considerable prior specialized instruction in and out of school, were given an evidence-based comprehensive assessment battery at the university while parents completed questionnaires regarding past and current history…

Is Relational Reasoning Dependent on Language? A Voxel-Based Lesion Symptom Mapping Study

ERIC Educational Resources Information Center

Baldo, Juliana V.; Bunge, Silvia A.; Wilson, Stephen M.; Dronkers, Nina F.

2010-01-01

Previous studies with brain-injured patients have suggested that language abilities are necessary for complex problem-solving, even when tasks are non-verbal. In the current study, we tested this notion by analyzing behavioral and neuroimaging data from a large group of left-hemisphere stroke patients (n = 107) suffering from a range of language…

Brain Basis of Early Parent-Infant Interactions: Psychology, Physiology, and "in vivo" Functional Neuroimaging Studies

ERIC Educational Resources Information Center

Swain, James E.; Lorberbaum, Jeffrey P.; Kose, Samet; Strathearn, Lane

2007-01-01

Parenting behavior critically shapes human infants' current and future behavior. The parent-infant relationship provides infants with their first social experiences, forming templates of what they can expect from others and how to best meet others' expectations. In this review, we focus on the neurobiology of parenting behavior, including our own…

Annual Research Review: Understudied Populations within the Autism Spectrum--Current Trends and Future Directions in Neuroimaging Research

ERIC Educational Resources Information Center

Jack, Allison; Pelphrey, Kevin A.

2017-01-01

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…

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

Prediction of Driving Safety in Individuals with Homonymous Hemianopia and Quadrantanopia from Clinical Neuroimaging

PubMed Central

Vaphiades, Michael S.; Kline, Lanning B.; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M.

2014-01-01

Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from −0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions. PMID:24683493

Prediction of driving safety in individuals with homonymous hemianopia and quadrantanopia from clinical neuroimaging.

PubMed

Vaphiades, Michael S; Kline, Lanning B; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M

2014-01-01

Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from -0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions.

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.

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.

Measurement tools for assessment of older age bipolar disorder: A systematic review of the recent global literature.

PubMed

Rej, Soham; Quayle, William; Forester, Brent P; Dols, Annemiek; Gatchel, Jennifer; Chen, Peijun; Gough, Sarah; Fox, Rebecca; Sajatovic, Martha; Strejilevich, Sergio A; Eyler, Lisa T

2018-06-01

More than 50% of people with bipolar disorder will be age 60 years or older by 2030. There is a need for more data to guide assessment and treatment in older age bipolar disorder (OABD); however, interpretation of findings from small, single-site studies may not be generalizable and there are few large trials. As a step in the direction of coordinated large-scale OABD data collection, it is critical to identify which measurements are currently used and identify potential gaps in domains typically assessed. An international group of OABD experts performed a systematic literature review to identify studies examining OABD in the past 6 years. Relevant articles were assessed to categorize the types of clinical, cognitive, biomarker, and neuroimaging OABD tools routinely used in OABD studies. A total of 53 papers were identified, with a broad range of assessments. Most studies evaluated demographic and clinical domains, with fewer studies assessing cognition. There are relatively few biomarker and neuroimaging data, and data collection methods were less comprehensively covered. Assessment tools used in the recent OABD literature may help to identify both a minimum and a comprehensive dataset that should be evaluated in OABD. Our review also highlights gaps where key clinical outcomes have not been routinely assessed. Biomarker and neuroimaging assessment could be further developed and standardized. Clinical data could be combined with neuroimaging, genetic, and other biomarkers in large-scale coordinated data collection to further improve our understanding of OABD phenomenology and biology, thereby contributing to research that advances care. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The clinical outcome and neuroimaging of acute encephalopathy after status epilepticus in Dravet syndrome.

PubMed

Tian, Xiaojuan; Ye, Jintang; Zeng, Qi; Zhang, Jing; Yang, Xiaoling; Liu, Aijie; Yang, Zhixian; Liu, Xiaoyan; Wu, Xiru; Zhang, Yuehua

2018-06-01

To analyze the clinical outcome and neuroimaging over a long duration follow-up in the currently largest series of acute encephalopathy after status epilepticus in patients with Dravet syndrome. Clinical and neuroimaging data of patients with Dravet syndrome with a history of acute encephalopathy (coma >24h) after status epilepticus from February 2005 to December 2016 at Peking University First Hospital were reviewed retrospectively. Thirty-five patients (15 males, 20 females) with a history of acute encephalopathy were enrolled from a total of 624 patients with Dravet syndrome (5.6%). The median onset age of acute encephalopathy was 3 years 1 month. The duration of status epilepticus varied between 40 minutes to 12 hours. Thirty-four patients had a high fever when status epilepticus occurred, and only one had a normal temperature. Coma lasted from 2 to 20 days. Twelve patients died and 23 survived with massive neurological regression. The median follow-up time was 2 years 1 month. Neuroimaging of 20 out of 23 survivors during the recovery phase showed diverse degrees of cortical atrophy with or without subcortical lesions. Acute encephalopathy after status epilepticus is more prone to occur in patients with Dravet syndrome who had a high fever. The mortality rate is high in severe cases. Survivors are left with severe neurological sequelae but often with either no seizure or low seizure frequency. Acute encephalopathy is more prone to occur in patients with Dravet syndrome with a high fever. The mortality rate is high for acute encephalopathy after status epilepticus in patients with Dravet syndrome. Survivors have neurological sequelae. © 2018 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.

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

The neurologist’s dilemma: A comprehensive clinical review of Bell’s palsy, with emphasis on current management trends

PubMed Central

Zandian, Anthony; Osiro, Stephen; Hudson, Ryan; Ali, Irfan M.; Matusz, Petru; Tubbs, Shane R.; Loukas, Marios

2014-01-01

Background Recent advances in Bell’s palsy (BP) were reviewed to assess the current trends in its management and prognosis. Material/Methods We retrieved the literature on BP using the Cochrane Database of Systematic Reviews, PubMed, and Google Scholar. Key words and phrases used during the search included ‘Bell’s palsy’, ‘Bell’s phenomenon’, ‘facial palsy’, and ‘idiopathic facial paralysis’. Emphasis was placed on articles and randomized controlled trails (RCTs) published within the last 5 years. Results BP is currently considered the leading disorder affecting the facial nerve. The literature is replete with theories of its etiology, but the reactivation of herpes simplex virus isoform 1 (HSV-1) and/or herpes zoster virus (HZV) from the geniculate ganglia is now the most strongly suspected cause. Despite the advancements in neuroimaging techniques, the diagnosis of BP remains one of exclusion. In addition, most patients with BP recover spontaneously within 3 weeks. Conclusions Corticosteroids are currently the drug of choice when medical therapy is needed. Antivirals, in contrast, are not superior to placebo according to most reliable studies. At the time of publication, there is no consensus as to the benefit of acupuncture or surgical decompression of the facial nerve. Long-term therapeutic agents and adjuvant medications for BP are necessary due to recurrence and intractable cases. In the future, large RCTs will be required to determine whether BP is associated with an increased risk of stroke. PMID:24441932

Early visual analysis tool using magnetoencephalography for treatment and recovery of neuronal dysfunction.

PubMed

Rasheed, Waqas; Neoh, Yee Yik; Bin Hamid, Nor Hisham; Reza, Faruque; Idris, Zamzuri; Tang, Tong Boon

2017-10-01

Functional neuroimaging modalities play an important role in deciding the diagnosis and course of treatment of neuronal dysfunction and degeneration. This article presents an analytical tool with visualization by exploiting the strengths of the MEG (magnetoencephalographic) neuroimaging technique. The tool automates MEG data import (in tSSS format), channel information extraction, time/frequency decomposition, and circular graph visualization (connectogram) for simple result inspection. For advanced users, the tool also provides magnitude squared coherence (MSC) values allowing personalized threshold levels, and the computation of default model from MEG data of control population. Default model obtained from healthy population data serves as a useful benchmark to diagnose and monitor neuronal recovery during treatment. The proposed tool further provides optional labels with international 10-10 system nomenclature in order to facilitate comparison studies with EEG (electroencephalography) sensor space. Potential applications in epilepsy and traumatic brain injury studies are also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neurophysiology of action anticipation in athletes: A systematic review.

PubMed

Smith, Daniel M

2016-01-01

The purpose of this study was to provide a systematic review of action anticipation studies using functional neuroimaging or brain stimulation during a sport-specific anticipation task. A total of 15 studies from 2008 to 2014 were evaluated and are reported in four sections: expert-novice samples, action anticipation tasks, neuroimaging and stimulation techniques, and key findings. Investigators examined a wide range of action anticipation scenarios specific to eight different sports and utilized functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and transcranial magnetic stimulation (TMS). Expert-novice comparisons were commonly used to investigate differences in action anticipation performance and neurophysiology. Experts tended to outperform novices, and an extensive array of brain structures were reported to be involved differently for experts and novices during action anticipation. However, these neurophysiological findings were generally inconsistent across the studies reviewed. The discussion focuses on strengths and four key limitations. The conclusion posits remaining questions and recommendations for future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neurophysiological, metabolic and cellular compartments that drive neurovascular coupling and neuroimaging signals

PubMed Central

Moreno, Andrea; Jego, Pierrick; de la Cruz, Feliberto; Canals, Santiago

2013-01-01

Complete understanding of the mechanisms that coordinate work and energy supply of the brain, the so called neurovascular coupling, is fundamental to interpreting brain energetics and their influence on neuronal coding strategies, but also to interpreting signals obtained from brain imaging techniques such as functional magnetic resonance imaging. Interactions between neuronal activity and cerebral blood flow regulation are largely compartmentalized. First, there exists a functional compartmentalization in which glutamatergic peri-synaptic activity and its electrophysiological events occur in close proximity to vascular responses. Second, the metabolic processes that fuel peri-synaptic activity are partially segregated between glycolytic and oxidative compartments. Finally, there is cellular segregation between astrocytic and neuronal compartments, which has potentially important implications on neurovascular coupling. Experimental data is progressively showing a tight interaction between the products of energy consumption and neurotransmission-driven signaling molecules that regulate blood flow. Here, we review some of these issues in light of recent findings with special attention to the neuron-glia interplay on the generation of neuroimaging signals. PMID:23543907

Body position alters human resting-state: Insights from multi-postural magnetoencephalography.

PubMed

Thibault, Robert T; Lifshitz, Michael; Raz, Amir

2016-09-01

Neuroimaging researchers tacitly assume that body-position scantily affects neural activity. However, whereas participants in most psychological experiments sit upright, many modern neuroimaging techniques (e.g., fMRI) require participants to lie supine. Sparse findings from electroencephalography and positron emission tomography suggest that body position influences cognitive processes and neural activity. Here we leverage multi-postural magnetoencephalography (MEG) to further unravel how physical stance alters baseline brain activity. We present resting-state MEG data from 12 healthy participants in three orthostatic conditions (i.e., lying supine, reclined at 45°, and sitting upright). Our findings demonstrate that upright, compared to reclined or supine, posture increases left-hemisphere high-frequency oscillatory activity over common speech areas. This proof-of-concept experiment establishes the feasibility of using MEG to examine the influence of posture on brain dynamics. We highlight the advantages and methodological challenges inherent to this approach and lay the foundation for future studies to further investigate this important, albeit little-acknowledged, procedural caveat.

Neurobiological bases of reading comprehension: Insights from neuroimaging studies of word level and text level processing in skilled and impaired readers

PubMed Central

Landi, Nicole; Frost, Stephen J.; Menc, W. Einar; Sandak, Rebecca; Pugh, Kenneth R.

2012-01-01

For accurate reading comprehension, readers must first learn to map letters to their corresponding speech sounds and meaning and then they must string the meanings of many words together to form a representation of the text. Furthermore, readers must master the complexities involved in parsing the relevant syntactic and pragmatic information necessary for accurate interpretation. Failure in this process can occur at multiple levels and cognitive neuroscience has been helpful in identifying the underlying causes of success and failure in reading single words and in reading comprehension. In general, neurobiological studies of skilled reading comprehension indicate a highly overlapping language circuit for single word reading, reading comprehension and listening comprehension with largely quantitative differences in a number of reading and language related areas. This paper reviews relevant research from studies employing neuroimaging techniques to study reading with a focus on the relationship between reading skill, single word reading, and text comprehension. PMID:23662034

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.

The Brain's Response to Digital Math Apps: A Pilot Study Examining Children's Cortical Responses during Touch-Screen Interactions

ERIC Educational Resources Information Center

Baker, Joseph M.; Moyer-Packenham, Patricia S.; Tucker, Stephen I.; Shumway, Jessica F.; Jordan, Kerry E.; Gillam, Ronald B.

2018-01-01

Functional near-infrared spectroscopy (fNIRS) is an easy to use neuroimaging technique that is portable and maintains a liberal tolerance to movement. As such, fNIRS represents an ideal tool to observe children's neural activity as they engage in real-world classroom activities, such as the interaction with digital math apps on an iPad. Here, we…

Emotion, Cognition, and Behavior

NASA Astrophysics Data System (ADS)

Dolan, R. J.

2002-11-01

Emotion is central to the quality and range of everyday human experience. The neurobiological substrates of human emotion are now attracting increasing interest within the neurosciences motivated, to a considerable extent, by advances in functional neuroimaging techniques. An emerging theme is the question of how emotion interacts with and influences other domains of cognition, in particular attention, memory, and reasoning. The psychological consequences and mechanisms underlying the emotional modulation of cognition provide the focus of this article.

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

PubMed

Jasińska, Kaja K; Guei, Sosthène

2018-02-02

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

Insights from neuropsychology: pinpointing the role of the posterior parietal cortex in episodic and working memory

PubMed Central

Berryhill, Marian E.

2012-01-01

The role of posterior parietal cortex (PPC) in various forms of memory is a current topic of interest in the broader field of cognitive neuroscience. This large cortical region has been linked with a wide range of mnemonic functions affecting each stage of memory processing: encoding, maintenance, and retrieval. Yet, the precise role of the PPC in memory remains mysterious and controversial. Progress in understanding PPC function will require researchers to incorporate findings in a convergent manner from multiple experimental techniques rather than emphasizing a particular type of data. To facilitate this process, here, we review findings from the human neuropsychological research and examine the consequences to memory following PPC damage. Recent patient-based research findings have investigated two typically disconnected fields: working memory (WM) and episodic memory. The findings from patient participants with unilateral and bilateral PPC lesions performing diverse experimental paradigms are summarized. These findings are then related to findings from other techniques including neurostimulation (TMS and tDCS) and the influential and more abundant functional neuroimaging literature. We then review the strengths and weaknesses of hypotheses proposed to account for PPC function in these forms of memory. Finally, we address what missing evidence is needed to clarify the role(s) of the PPC in memory. PMID:22701406

Moving magnetoencephalography towards real-world applications with a wearable system

NASA Astrophysics Data System (ADS)

Boto, Elena; Holmes, Niall; Leggett, James; Roberts, Gillian; Shah, Vishal; Meyer, Sofie S.; Muñoz, Leonardo Duque; Mullinger, Karen J.; Tierney, Tim M.; Bestmann, Sven; Barnes, Gareth R.; Bowtell, Richard; Brookes, Matthew J.

2018-03-01

Imaging human brain function with techniques such as magnetoencephalography typically requires a subject to perform tasks while their head remains still within a restrictive scanner. This artificial environment makes the technique inaccessible to many people, and limits the experimental questions that can be addressed. For example, it has been difficult to apply neuroimaging to investigation of the neural substrates of cognitive development in babies and children, or to study processes in adults that require unconstrained head movement (such as spatial navigation). Here we describe a magnetoencephalography system that can be worn like a helmet, allowing free and natural movement during scanning. This is possible owing to the integration of quantum sensors, which do not rely on superconducting technology, with a system for nulling background magnetic fields. We demonstrate human electrophysiological measurement at millisecond resolution while subjects make natural movements, including head nodding, stretching, drinking and playing a ball game. Our results compare well to those of the current state-of-the-art, even when subjects make large head movements. The system opens up new possibilities for scanning any subject or patient group, with myriad applications such as characterization of the neurodevelopmental connectome, imaging subjects moving naturally in a virtual environment and investigating the pathophysiology of movement disorders.

Memory assessment in patients with temporal lobe epilepsy to predict memory impairment after surgery: A systematic review.

PubMed

Parra-Díaz, P; García-Casares, N

2017-04-19

Given that surgical treatment of refractory mesial temporal lobe epilepsy may cause memory impairment, determining which patients are eligible for surgery is essential. However, there is little agreement on which presurgical memory assessment methods are best able to predict memory outcome after surgery and identify those patients with a greater risk of surgery-induced memory decline. We conducted a systematic literature review to determine which presurgical memory assessment methods best predict memory outcome. The literature search of PubMed gathered articles published between January 2005 and December 2015 addressing pre- and postsurgical memory assessment in mesial temporal lobe epilepsy patients by means of neuropsychological testing, functional MRI, and other neuroimaging techniques. We obtained 178 articles, 31 of which were included in our review. Most of the studies used neuropsychological tests and fMRI; these methods are considered to have the greatest predictive ability for memory impairment. Other less frequently used techniques included the Wada test and FDG-PET. Current evidence supports performing a presurgical assessment of memory function using both neuropsychological tests and functional MRI to predict memory outcome after surgery. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Translation of near infrared brain imaging to assess children with cerebral palsy

NASA Astrophysics Data System (ADS)

Alexandrakis, George; Khan, Bilal; Tian, Fenghua; Asanani, Nayan; Behbehani, Khosrow; Delgado, Mauricio R.; Liu, Hanli

2009-02-01

Cerebral palsy (CP) is the most common motor disorder of central origin in childhood and affects at least 2 children per 1000 live births every year. Neuroimaging techniques are needed to study neuroplastic rearrangements in the human brain in vivo as a result of CP. Unfortunately, accurate imaging from currently available techniques often requires the patients' complete body confinement, steadiness and minimal noise for a long period of time, which limits the success rate to less than 50% for normal children and worse for CP-affected ones. In this work we show that functional near infrared (fNIR) imaging is robust to motion artifacts and has excellent potential as a sensitive diagnostic tool for this motor disorder. We have analyzed data from pediatric normal and CP patients performing finger-tapping and handwaving motor cortex activation tasks. From these analyses we have identified both spatial and temporal metrics of NIR-based motor cortex activation patterns that can clearly distinguish between normal and CP patients. We also present data from additional patients where signal processing methods are applied to filter out concurrently recorded hemodynamic signals due to breathing and cardiac pulsation. It is shown that filtering can substantially improve the quality of activation data, thus enabling more accurate comparison of activation patterns between normal and CP-affected children.

in vivo quantification of white matter microstructure for use in aging: A focus on two emerging techniques

PubMed Central

Lamar, Melissa; Zhou, Xiaohong Joe; Charlton, Rebecca A.; Dean, Douglas; Little, Deborah; Deoni, Sean C

2013-01-01

Human brain imaging has seen many advances in the quantification of white matter in vivo. For example, these advances have revealed the association between white matter damage and vascular disease as well as their impact on risk for and development of dementia and depression in an aging population. Current neuroimaging methods to quantify white matter damage provide a foundation for understanding such age-related neuropathology; however, these methods are not as adept at determining the underlying microstructural abnormalities signaling at risk tissue or driving white matter damage in the aging brain. This review will begin with a brief overview of the use of diffusion tensor imaging (DTI) in understanding white matter alterations in aging before focusing in more detail on select advances in both diffusion-based methods and multi-component relaxometry techniques for imaging white matter microstructural integrity within myelin sheaths and the axons they encase. While DTI greatly extended the field of white matter interrogation, these more recent technological advances will add clarity to the underlying microstructural mechanisms that contribute to white matter damage. More specifically, the methods highlighted in this review may prove more sensitive (and specific) for determining the contribution of myelin versus axonal integrity to the aging of white matter in brain. PMID:24080382

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.

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.

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.

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

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

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.

Near-Infrared Spectroscopy – Electroencephalography-Based Brain-State-Dependent Electrotherapy: A Computational Approach Based on Excitation–Inhibition Balance Hypothesis

PubMed Central

Dagar, Snigdha; Chowdhury, Shubhajit Roy; Bapi, Raju Surampudi; Dutta, Anirban; Roy, Dipanjan

2016-01-01

Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The poststroke chronic disability may be ameliorated with early neuro rehabilitation where non-invasive brain stimulation (NIBS) techniques can be used as an adjuvant treatment to hasten the effects. However, the heterogeneity in the lesioned brain will require individualized NIBS intervention where innovative neuroimaging technologies of portable electroencephalography (EEG) and functional-near-infrared spectroscopy (fNIRS) can be leveraged for Brain State Dependent Electrotherapy (BSDE). In this hypothesis and theory article, we propose a computational approach based on excitation–inhibition (E–I) balance hypothesis to objectively quantify the poststroke individual brain state using online fNIRS–EEG joint imaging. One of the key events that occurs following Stroke is the imbalance in local E–I (that is the ratio of Glutamate/GABA), which may be targeted with NIBS using a computational pipeline that includes individual “forward models” to predict current flow patterns through the lesioned brain or brain target region. The current flow will polarize the neurons, which can be captured with E–I-based brain models. Furthermore, E–I balance hypothesis can be used to find the consequences of cellular polarization on neuronal information processing, which can then be implicated in changes in function. We first review the evidence that shows how this local imbalance between E–I leading to functional dysfunction can be restored in targeted sites with NIBS (motor cortex and somatosensory cortex) resulting in large-scale plastic reorganization over the cortex, and probably facilitating recovery of functions. Second, we show evidence how BSDE based on E–I balance hypothesis may target a specific brain site or network as an adjuvant treatment. Hence, computational neural mass model-based integration of neurostimulation with online neuroimaging systems may provide less ambiguous, robust optimization of NIBS, and its application in neurological conditions and disorders across individual patients. PMID:27551273

Verbal fluency in research conducted with PET technique under conditions of extended cognitive activation with the use of 18F-fluorodeoxyglucose (FDG) tracer.

PubMed

Zając-Lamparska, Ludmiła; Wiłkość, Monika; Markowska, Anita; Laskowska-Levy, Ilona Paulina; Wróbel, Marek; Małkowski, Bogdan

2017-08-29

Functional neuroimaging of the brain is a widely used method to study cognitive functions. The aim of this study was to compare the activity of the brain during performance of the tasks of phonemic and semantic fluency with the paced-overt technique in terms of prolonged activation of the brain. The study included 17 patients aged 20-40 years who were treated in the past for Hodgkin'slymphoma, now in remission. Due to the type of task, the subjectswere divided into two groups. Nine people performed the phonemic fluency task, and eight semantic. Due to the disease, all subjects were subject to neuropsychological diagnosis. The diagnosis of any cognitive impairment was an exclusion criterion. Neuroimaging was performed using PET technique with 18F-fluorodeoxyglucose (FDG) tracer. Performance of a verbal fluency test, regardless of the version of the task, was associated with greater activity of the left hemisphere of the brain. The most involved areas compared with other areas of key importance for the performance of verbal fluency tasks were frontal lobes. An increased activity of parietal structures was also shown. The study did not reveal differences in brain activity depending on the type of task. Performing the test in both phonemic and semantic form for a long time, in terms of increased cognitive control resulting from the test procedure, could result in significant advantage of prefrontal lobe activityin both types of tasks and made it impossible to observe the processes specific to each of them.

Getting to the Heart of the Brain: Using Cognitive Neuroscience to Explore the Nature of Human Ability and Performance

ERIC Educational Resources Information Center

Kalbfleisch, M. Layne

2008-01-01

This article serves as a primer to make the neuroimaging literature more accessible to the lay reader and to increase the evaluative capability of the educated consumer of cognitive neuroscience. This special issue gives gifted education practitioners and researchers a primary source view of current neuroscience relevant to modern definitions and…

Neuroimaging findings in pediatric sports-related concussion.

PubMed

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

2015-09-01

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

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.

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.

Childhood-Onset Schizophrenia: Insights from Neuroimaging Studies

ERIC Educational Resources Information Center

Gogtay, Nitin; Rapoport, Judith L.

2008-01-01

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

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

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.

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

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.

Advances in the Study of the Middle Cranial Fossa through Cutting Edge Neuroimaging Techniques.

PubMed

Juanes Méndez, Juan A; Ruisoto, Pablo; Paniagua, Juan C; Prats, Alberto

2018-01-16

The objective of this paper is to present a morphometric study of the middle cranial fossa from the study of 87 patients using cutting edge multislice computed tomography scans (32 detectors) and Magnetic Resonance Imaging. The study presents a detailed anatomical-radiological and morphometric analysis of the middle cranial fossa as well as its neurovascular elements in normal conditions. The implications of this investigation in training and clinical contexts are discussed.

[Dementia and small vessel diseases of the brain].

PubMed

Damulin, I V

2014-01-01

Clinical and pathogenetic characteristics of dementia caused by small vessel lesions are presented. It is emphasized that this variant of vascular dementia is the most frequent in clinical practice. Clinical examination, accurate assessment of the disease history and using of modern neuroimaging techniques are important for the diagnosis. The drugs that impact on risk factors, including disaggregants, and metabolic drugs (nicergoline) are widely used in the treatment of dementia. These drugs are highly effective and safe.

Diagnostic Yield and Safety of Brain Biopsy for Suspected Primary Central Nervous System Angiitis.

PubMed

Torres, Jose; Loomis, Caitlin; Cucchiara, Brett; Smith, Michelle; Messé, Steven

2016-08-01

The utility and safety of brain biopsy for suspected primary angiitis of the central nervous system (PACNS) are uncertain. Factors predictive of a positive biopsy have not been well described. Our aim was to evaluate the diagnostic yield and safety of brain biopsy in suspected PACNS and determine whether any prebiopsy variables are associated with a positive biopsy. This is a retrospective study of consecutive patients who underwent diagnostic brain biopsy for PACNS at a single institution. The relationship between biopsy yield and patient demographics, surgical technique, laboratory testing, neuroimaging, biopsy characteristics, and prebiopsy immunosuppressive therapy were examined. PACNS was confirmed in 9 of 79 patients (11%). Biopsy identified alternative diagnoses in 24 patients (30%), with cerebral amyloid angiopathy (8 patients), encephalitis (5 patients), demyelination (3 patients), and CNS lymphoma (3 patients) most commonly found. There was no correlation between a positive biopsy and cerebrospinal fluid results, neuroimaging, surgical technique, biopsy characteristics, or preoperative immunosuppressive therapy. Smaller biopsies (P=0.02) and closed procedures (P=0.013) were less likely to yield a diagnosis. Postoperative complications occurred in 13 patients (16%), 3 (4%) of which were serious. Brain biopsy leads to pathological confirmation of vasculitis in a minority of suspected PACNS cases but alternative diagnoses are often identified. Importantly, rare but meaningful complications may occur. © 2016 American Heart Association, Inc.

Psychological and physical pain as predictors of suicide risk: evidence from clinical and neuroimaging findings.

PubMed

Rizvi, Sakina J; Iskric, Adam; Calati, Raffaella; Courtet, Philippe

2017-03-01

Suicide is a multidimensional clinical phenomenon with complex biological, social and psychological risk factors. Therefore, it is imperative for studies to focus on developing a unified understanding of suicide risk that integrates current clinical and neurobiological findings. A recent line of research has implicated different classifications of pain in understanding suicide risk, including the concepts of psychache and pain tolerance. Although psychache is defined as the experience of unbearable psychological pain, pain tolerance refers to the greatest duration or intensity of painful stimuli that one is able to bear. This review will focus on integrating current clinical and neurobiological findings by which psychache and pain tolerance confer suicide risk. Results indicate that psychache has been identified as a significant risk factor for suicide and that psychache may be associated with the neurocircuitry involved in the modulation of physical pain. Converging evidence has also been found linking pain tolerance to self-injurious behaviours and suicide risk. The experience of psychache and physical pain in relation to other predictors of suicide, including reward processing, hopelessness and depression, are further discussed. Future research examining the pain-suicide connection is required to understand the mechanism behind clinically relevant risk factors for suicide, which can ultimately inform the construction of empirically supported suicide risk assessment and intervention techniques.

Insights into molecular therapy of glioma: current challenges and next generation blueprint

PubMed Central

Rajesh, Y; Pal, Ipsita; Banik, Payel; Chakraborty, Sandipan; Borkar, Sachin A; Dey, Goutam; Mukherjee, Ahona; Mandal, Mahitosh

2017-01-01

Glioma accounts for the majority of human brain tumors. With prevailing treatment regimens, the patients have poor survival rates. In spite of current development in mainstream glioma therapy, a cure for glioma appears to be out of reach. The infiltrative nature of glioma and acquired resistance substancially restrict the therapeutic options. Better elucidation of the complicated pathobiology of glioma and proteogenomic characterization might eventually open novel avenues for the design of more sophisticated and effective combination regimens. This could be accomplished by individually tailoring progressive neuroimaging techniques, terminating DNA synthesis with prodrug-activating genes, silencing gliomagenesis genes (gene therapy), targeting miRNA oncogenic activity (miRNA-mRNA interaction), combining Hedgehog-Gli/Akt inhibitors with stem cell therapy, employing tumor lysates as antigen sources for efficient depletion of tumor-specific cancer stem cells by cytotoxic T lymphocytes (dendritic cell vaccination), adoptive transfer of chimeric antigen receptor-modified T cells, and combining immune checkpoint inhibitors with conventional therapeutic modalities. Thus, the present review captures the latest trends associated with the molecular mechanisms involved in glial tumorigenesis as well as the limitations of surgery, radiation and chemotherapy. In this article we also critically discuss the next generation molecular therapeutic strategies and their mechanisms for the successful treatment of glioma. PMID:28317871

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…

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…

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…

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…

A very simple, re-executable neuroimaging publication

PubMed Central

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

2017-01-01

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

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

Revival of Historical Kana Orthography in a Patient with Allographic Agraphia.

PubMed

Maeda, Kengo; Shiraishi, Tomoyuki

2018-01-01

Japanese people born before World War II learned Japanese kana (Japanese syllabograms) writing in a style that is not currently used. These individuals had to learn the current style of kana orthography after the war. An 85-year-old man was taken to our hospital by his family who were surprised by his diary. It was written with kanji (Japanese ideograms) and katakana using the prewar style. A neuropsychological examination revealed impaired recall of hiragana. Neuroimaging studies revealed atrophy of the left fronto-parietal lobe and hypoperfusion of the left frontal lobe. His allographic agraphia might have resulted from the disturbance of the current style of kana orthography.

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

Advances in magnetic resonance neuroimaging techniques in the evaluation of neonatal encephalopathy.

PubMed

Panigrahy, Ashok; Blüml, Stefan

2007-02-01

Magnetic resonance (MR) imaging has become an essential tool in the evaluation of neonatal encephalopathy. Magnetic resonance-compatible neonatal incubators allow sick neonates to be transported to the MR scanner, and neonatal head coils can improve signal-to-noise ratio, critical for advanced MR imaging techniques. Refinement of conventional imaging techniques include the use of PROPELLER techniques for motion correction. Magnetic resonance spectroscopic imaging and diffusion tensor imaging provide quantitative assessment of both brain development and brain injury in the newborn with respect to metabolite abnormalities and hypoxic-ischemic injury. Knowledge of normal developmental changes in MR spectroscopy metabolite concentration and diffusion tensor metrics is essential to interpret pathological cases. Perfusion MR and functional MR can provide additional physiological information. Both MR spectroscopy and diffusion tensor imaging can provide additional information in the differential of neonatal encephalopathy, including perinatal white matter injury, hypoxic-ischemic brain injury, metabolic disease, infection, and birth injury.

A View of the Neural Representation of Second Language Syntax through Artificial Language Learning under Implicit Contexts of Exposure

ERIC Educational Resources Information Center

Morgan-Short, Kara; Deng, ZhiZhou; Brill-Schuetz, Katherine A.; Faretta- Stutenberg, Mandy; Wong, Patrick C. M.; Wong, Francis C. K.

2015-01-01

The current study aims to make an initial neuroimaging contribution to central implicit-explicit issues in second language (L2) acquisition by considering how implicit and explicit contexts mediate the neural representation of L2. Focusing on implicit contexts, the study employs a longitudinal design to examine the neural representation of L2…

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

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

PubMed

Mansu Kim; Seong-Jin Son; Hyunjin Park

2017-07-01

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

Dopaminergic Neurotransmission in the Human Brain: New Lessons from Perturbation and Imaging

PubMed Central

Ko, Ji Hyun; Strafella, Antonio P.

2012-01-01

Dopamine plays an important role in several brain functions and is involved in the pathogenesis of several psychiatric and neurological disorders. Neuroimaging techniques such as positron emission tomography allow us to quantify dopaminergic activity in the living human brain. Combining these with brain stimulation techniques offers us the unique opportunity to tackle questions regarding region-specific neurochemical activity. Such studies may aid clinicians and scientists to disentangle neural circuitries within the human brain and thereby help them to understand the underlying mechanisms of a given function in relation to brain diseases. Furthermore, it may also aid the development of alternative treatment approaches for various neurological and psychiatric conditions. PMID:21536838

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

PubMed

Taylor, James M; Whalen, Paul J

2015-06-01

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

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.

[Awake craniotomy].

PubMed

Kobyakov, G L; Lubnin, A Yu; Kulikov, A S; Gavrilov, A G; Goryaynov, S A; Poddubskiy, A A; Lodygina, K S

2016-01-01

Awake craniotomy is a neurosurgical intervention aimed at identifying and preserving the eloquent functional brain areas during resection of tumors located near the cortical and subcortical language centers. This article provides a review of the modern literature devoted to the issue. The anatomical rationale and data of preoperative functional neuroimaging, intraoperative electrophysiological monitoring, and neuropsychological tests as well as the strategy of active surgical intervention are presented. Awake craniotomy is a rapidly developing technique aimed at both preserving speech and motor functions and improving our knowledge in the field of speech psychophysiology.

Tools of the trade: theory and method in mindfulness neuroscience.

PubMed

Tang, Yi-Yuan; Posner, Michael I

2013-01-01

Mindfulness neuroscience is an emerging research field that investigates the underlying mechanisms of different mindfulness practices, different stages and different states of practice as well as different effects of practice over the lifespan. Mindfulness neuroscience research integrates theory and methods from eastern contemplative traditions, western psychology and neuroscience, and from neuroimaging techniques, physiological measures and behavioral tests. We here review several key theoretical and methodological challenges in the empirical study of mindfulness neuroscience and provide suggestions for overcoming these challenges.

Advanced and Conventional Magnetic Resonance Imaging in Neuropsychiatric Lupus

PubMed Central

Sarbu, Nicolae; Bargalló, Núria; Cervera, Ricard

2015-01-01

Neuropsychiatric lupus is a major diagnostic challenge, and a main cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). Magnetic resonance imaging (MRI) is, by far, the main tool for assessing the brain in this disease. Conventional and advanced MRI techniques are used to help establishing the diagnosis, to rule out alternative diagnoses, and recently, to monitor the evolution of the disease. This review explores the neuroimaging findings in SLE, including the recent advances in new MRI methods. PMID:26236469

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

ERIC Educational Resources Information Center

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

2017-01-01

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

Quantification of functional near infrared spectroscopy to assess cortical reorganization in children with cerebral palsy

PubMed Central

Tian, Fenghua; Delgado, Mauricio R.; Dhamne, Sameer C.; Khan, Bilal; Alexandrakis, George; Romero, Mario I.; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J.; Liu, Hanli

2013-01-01

Cerebral palsy (CP) is the most common motor disorder in children. Currently available neuroimaging techniques require complete body confinement and steadiness and thus are extremely difficult for pediatric patients. Here, we report the use and quantification of functional near infrared spectroscopy (fNIRS) to investigate the functional reorganization of the sensorimotor cortex in children with hemiparetic CP. Ten of sixteen children with congenital hemiparesis were measured during finger tapping tasks and compared with eight of sixteen age-matched healthy children, with an overall measurement success rate of 60%. Spatiotemporal analysis was introduced to quantify the motor activation and brain laterality. Such a quantitative approach reveals a consistent, contralateral motor activation in healthy children at 7 years of age or older. In sharp contrast, children with congenital hemiparesis exhibit all three of contralateral, bilateral and ipsilateral motor activations, depending on specific ages of the pediatric subjects. This study clearly demonstrates the feasibility of fNIRS to be utilized for investigating cortical reorganization in children with CP or other cortical disorders. PMID:21164944

Cerebral versus Ocular Visual Impairment: The Impact on Developmental Neuroplasticity.

PubMed

Martín, Maria B C; Santos-Lozano, Alejandro; Martín-Hernández, Juan; López-Miguel, Alberto; Maldonado, Miguel; Baladrón, Carlos; Bauer, Corinna M; Merabet, Lotfi B

2016-01-01

Cortical/cerebral visual impairment (CVI) is clinically defined as significant visual dysfunction caused by injury to visual pathways and structures occurring during early perinatal development. Depending on the location and extent of damage, children with CVI often present with a myriad of visual deficits including decreased visual acuity and impaired visual field function. Most striking, however, are impairments in visual processing and attention which have a significant impact on learning, development, and independence. Within the educational arena, current evidence suggests that strategies designed for individuals with ocular visual impairment are not effective in the case of CVI. We propose that this variance may be related to differences in compensatory neuroplasticity related to the type of visual impairment, as well as underlying alterations in brain structural connectivity. We discuss the etiology and nature of visual impairments related to CVI, and how advanced neuroimaging techniques (i.e., diffusion-based imaging) may help uncover differences between ocular and cerebral causes of visual dysfunction. Revealing these differences may help in developing future strategies for the education and rehabilitation of individuals living with visual impairment.

Learning to remember: The early ontogeny of episodic memory☆

PubMed Central

Mullally, Sinéad L.; Maguire, Eleanor A.

2014-01-01

Over the past 60 years the neural correlates of human episodic memory have been the focus of intense neuroscientific scrutiny. By contrast, neuroscience has paid substantially less attention to understanding the emergence of this neurocognitive system. In this review we consider how the study of memory development has evolved. In doing so, we concentrate primarily on the first postnatal year because it is within this time window that the most dramatic shifts in scientific opinion have occurred. Moreover, this time frame includes the critical age (∼9 months) at which human infants purportedly first begin to demonstrate rudimentary hippocampal-dependent memory. We review the evidence for and against this assertion, note the lack of direct neurocognitive data speaking to this issue, and question how demonstrations of exuberant relational learning and memory in infants as young as 3-months old can be accommodated within extant models. Finally, we discuss whether current impasses in the infant memory literature could be leveraged by making greater use of neuroimaging techniques, such as magnetic resonance imaging (MRI), which have been deployed so successfully in adults. PMID:24480487

[German research institute/Max-Planck Institute for psychiatry].

PubMed

Ploog, D

1999-12-01

The Deutsche Forschungsanstalt für Psychiatrie (DFA, German Institute for Psychiatric Research) in Munich was founded in 1917 bel Emil Kraepelin. For a long time it was the only institution in Germany entirely devoted to psychiatric research. Because of its strictly science-oriented and multidisciplinary approach it also became a model for institutions elsewhere. Kraepelin's ideas have certainly had a strong influence on psychiatry in the twentieth century. The fascinating and instructive history of the DFA reflects the central issues and determinants of psychiatric research. First, talented individuals are needed to conduct such research, and there was no lack in this regard. Second, the various topics chosen are dependent on the available methods and resources. And finally, the issues addressed and the ethical standards of the researchers are heavily dependent on the zeitgeist, as is evident in the three epochs of research at the DFA, from 1917 to 1933, from 1933 to 1945, and from the postwar period to the present. With the introduction of molecular biology and neuroimaging techniques into psychiatric research a change in paradigm took place and a new phase of the current epoch began.

Endoscopic monoportal removal of a choroid plexus papilloma in the posterior third ventricle in a child.

PubMed

Sufianov, Albert A; Gaibov, Saidi S K; Sufianov, Rinat A

2015-07-01

Currently, only a few reports describe the minimally invasive removal of choroid plexus papillomas (CPPs) and, to the best of the authors' knowledge, no reports detail the resection of such a papilloma through an endoscopic approach in infants. The authors here describe the endoscopic removal of a third ventricle CPP in a child. A 5-month-old male infant presented with progressive macrocephaly, vomiting, and convulsions. A lesion in the posterior third ventricle was detected on brain MRI. Because of the patient's very young age, neuroendoscopy was used as the least invasive technique. The tumor was completely resected through a monoportal neuroendoscopic approach. Histologically, the tumor was classified as a WHO Grade I CPP. After surgery, the patient's condition improved, with no complications during his recovery. Ten-month follow-up neuroimaging revealed no evidence of tumor recurrence or progressive hydrocephaly. In view of the successful neuroendoscopic excision of this posterior third ventricle CPP, the authors believe that this method seems promising in the treatment of young children with intraventricular lesions.

Cerebral versus Ocular Visual Impairment: The Impact on Developmental Neuroplasticity

PubMed Central

Martín, Maria B. C.; Santos-Lozano, Alejandro; Martín-Hernández, Juan; López-Miguel, Alberto; Maldonado, Miguel; Baladrón, Carlos; Bauer, Corinna M.; Merabet, Lotfi B.

2016-01-01

Cortical/cerebral visual impairment (CVI) is clinically defined as significant visual dysfunction caused by injury to visual pathways and structures occurring during early perinatal development. Depending on the location and extent of damage, children with CVI often present with a myriad of visual deficits including decreased visual acuity and impaired visual field function. Most striking, however, are impairments in visual processing and attention which have a significant impact on learning, development, and independence. Within the educational arena, current evidence suggests that strategies designed for individuals with ocular visual impairment are not effective in the case of CVI. We propose that this variance may be related to differences in compensatory neuroplasticity related to the type of visual impairment, as well as underlying alterations in brain structural connectivity. We discuss the etiology and nature of visual impairments related to CVI, and how advanced neuroimaging techniques (i.e., diffusion-based imaging) may help uncover differences between ocular and cerebral causes of visual dysfunction. Revealing these differences may help in developing future strategies for the education and rehabilitation of individuals living with visual impairment. PMID:28082927

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).

Mindfulness and Fear Extinction: A Brief Review of Its Current Neuropsychological Literature and Possible Implications for Posttraumatic Stress Disorder.

PubMed

Kummar, Auretta S

2017-01-01

Research in the neuroscience of mindfulness has grown rapidly in recent years. This includes empirical investigations into structural and functional changes in several brain regions-particularly, the hippocampus, the prefrontal cortex, and the amygdala-in association with the practice of mindfulness. Of interest to the current paper is that such brain regions are also implicated in empirical research focusing on fear extinction. While fear extinction has, therefore, been suggested as one of the possible mechanisms to underlie the positive effects of mindfulness, the conceptual links and research implications have lacked specific focus and detailed discussion in the literature. The purpose of this paper is, therefore, two-fold. First, this paper briefly reviews the extant literature on the neuropsychological mechanisms underlying mindfulness-particularly that, which has been found to be similarly implied in fear extinction-and hence, suggests future research directions based on its current state in the literature. Second, this paper explores the implications of this for fear-based psychopathologies, specifically for posttraumatic stress disorder (PTSD). Discussion from this paper suggests the idea of fear extinction as an underlying mechanism of mindfulness to be one that is still preliminary, yet promising; in turn, elucidating the need for further methodologically rigorous study to specifically determine fear extinction as a result of mindfulness, as well as to incorporate neuroimaging techniques in supporting the existing literature that have found preliminary support of mindfulness for PTSD.

Mechanisms and Effects of Transcranial Direct Current Stimulation

PubMed Central

Giordano, James; Bikson, Marom; Kappenman, Emily S.; Clark, Vincent P.; Coslett, H. Branch; Hamblin, Michael R.; Hamilton, Roy; Jankord, Ryan; Kozumbo, Walter J.; McKinley, R. Andrew; Nitsche, Michael A.; Reilly, J. Patrick; Richardson, Jessica; Wurzman, Rachel

2017-01-01

The US Air Force Office of Scientific Research convened a meeting of researchers in the fields of neuroscience, psychology, engineering, and medicine to discuss most pressing issues facing ongoing research in the field of transcranial direct current stimulation (tDCS) and related techniques. In this study, we present opinions prepared by participants of the meeting, focusing on the most promising areas of research, immediate and future goals for the field, and the potential for hormesis theory to inform tDCS research. Scientific, medical, and ethical considerations support the ongoing testing of tDCS in healthy and clinical populations, provided best protocols are used to maximize safety. Notwithstanding the need for ongoing research, promising applications include enhancing vigilance/attention in healthy volunteers, which can accelerate training and support learning. Commonly, tDCS is used as an adjunct to training/rehabilitation tasks with the goal of leftward shift in the learning/treatment effect curves. Although trials are encouraging, elucidating the basic mechanisms of tDCS will accelerate validation and adoption. To this end, biomarkers (eg, clinical neuroimaging and findings from animal models) can support hypotheses linking neurobiological mechanisms and behavioral effects. Dosage can be optimized using computational models of current flow and understanding dose–response. Both biomarkers and dosimetry should guide individualized interventions with the goal of reducing variability. Insights from other applied energy domains, including ionizing radiation, transcranial magnetic stimulation, and low-level laser (light) therapy, can be prudently leveraged. PMID:28210202

Hypnosis and imaging of the living human brain.

PubMed

Landry, Mathieu; Raz, Amir

2015-01-01

Over more than two decades, studies using imaging techniques of the living human brain have begun to explore the neural correlates of hypnosis. The collective findings provide a gripping, albeit preliminary, account of the underlying neurobiological mechanisms involved in hypnotic phenomena. While substantial advances lend support to different hypotheses pertaining to hypnotic modulation of attention, control, and monitoring processes, the complex interactions among the many mediating variables largely hinder our ability to isolate robust commonalities across studies. The present account presents a critical integrative synthesis of neuroimaging studies targeting hypnosis as a function of suggestion. Specifically, hypnotic induction without task-specific suggestion is examined, as well as suggestions concerning sensation and perception, memory, and ideomotor response. The importance of carefully designed experiments is highlighted to better tease apart the neural correlates that subserve hypnotic phenomena. Moreover, converging findings intimate that hypnotic suggestions seem to induce specific neural patterns. These observations propose that suggestions may have the ability to target focal brain networks. Drawing on evidence spanning several technological modalities, neuroimaging studies of hypnosis pave the road to a more scientific understanding of a dramatic, yet largely evasive, domain of human behavior.

The Alzheimer's Disease Neuroimaging Initiative 2 PET Core: 2015.

PubMed

Jagust, William J; Landau, Susan M; Koeppe, Robert A; Reiman, Eric M; Chen, Kewei; Mathis, Chester A; Price, Julie C; Foster, Norman L; Wang, Angela Y

2015-07-01

This article reviews the work done in the Alzheimer's Disease Neuroimaging Initiative positron emission tomography (ADNI PET) core over the past 5 years, largely concerning techniques, methods, and results related to amyloid imaging in ADNI. The PET Core has used [(18)F]florbetapir routinely on ADNI participants, with over 1600 scans available for download. Four different laboratories are involved in data analysis, and have examined factors such as longitudinal florbetapir analysis, use of [(18)F]fluorodeoxyglucose (FDG)-PET in clinical trials, and relationships between different biomarkers and cognition. Converging evidence from the PET Core has indicated that cross-sectional and longitudinal florbetapir analyses require different reference regions. Studies have also examined the relationship between florbetapir data obtained immediately after injection, which reflects perfusion, and FDG-PET results. Finally, standardization has included the translation of florbetapir PET data to a centiloid scale. The PET Core has demonstrated a variety of methods for the standardization of biomarkers such as florbetapir PET in a multicenter setting. Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Neuroimaging of Fear-Associated Learning

PubMed Central

Greco, John A; Liberzon, Israel

2016-01-01

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

Functional neuroimaging studies of sexual arousal and orgasm in healthy men and women: a review and meta-analysis.

PubMed

Stoléru, Serge; Fonteille, Véronique; Cornélis, Christel; Joyal, Christian; Moulier, Virginie

2012-07-01

In the last fifteen years, functional neuroimaging techniques have been used to investigate the neuroanatomical correlates of sexual arousal in healthy human subjects. In most studies, subjects have been requested to watch visual sexual stimuli and control stimuli. Our review and meta-analysis found that in heterosexual men, sites of cortical activation consistently reported across studies are the lateral occipitotemporal, inferotemporal, parietal, orbitofrontal, medial prefrontal, insular, anterior cingulate, and frontal premotor cortices as well as, for subcortical regions, the amygdalas, claustrum, hypothalamus, caudate nucleus, thalami, cerebellum, and substantia nigra. Heterosexual and gay men show a similar pattern of activation. Visual sexual stimuli activate the amygdalas and thalami more in men than in women. Ejaculation is associated with decreased activation throughout the prefrontal cortex. We present a neurophenomenological model to understand how these multiple regional brain responses could account for the varied facets of the subjective experience of sexual arousal. Further research should shift from passive to active paradigms, focus on functional connectivity and use subliminal presentation of stimuli. Copyright © 2012 Elsevier Ltd. All rights reserved.

Only time will tell - why temporal information is essential for our neuroscientific understanding of semantics.

PubMed

Hauk, Olaf

2016-08-01

Theoretical developments about the nature of semantic representations and processes should be accompanied by a discussion of how these theories can be validated on the basis of empirical data. Here, I elaborate on the link between theory and empirical research, highlighting the need for temporal information in order to distinguish fundamental aspects of semantics. The generic point that fast cognitive processes demand fast measurement techniques has been made many times before, although arguably more often in the psychophysiological community than in the metabolic neuroimaging community. Many reviews on the neuroscience of semantics mostly or even exclusively focus on metabolic neuroimaging data. Following an analysis of semantics in terms of the representations and processes involved, I argue that fundamental theoretical debates about the neuroscience of semantics can only be concluded on the basis of data with sufficient temporal resolution. Any "semantic effect" may result from a conflation of long-term memory representations, retrieval and working memory processes, mental imagery, and episodic memory. This poses challenges for all neuroimaging modalities, but especially for those with low temporal resolution. It also throws doubt on the usefulness of contrasts between meaningful and meaningless stimuli, which may differ on a number of semantic and non-semantic dimensions. I will discuss the consequences of this analysis for research on the role of convergence zones or hubs and distributed modal brain networks, top-down modulation of task and context as well as interactivity between levels of the processing hierarchy, for example in the framework of predictive coding.

Individual classification of ADHD patients by integrating multiscale neuroimaging markers and advanced pattern recognition techniques

PubMed Central

Cheng, Wei; Ji, Xiaoxi; Zhang, Jie; Feng, Jianfeng

2012-01-01

Accurate classification or prediction of the brain state across individual subject, i.e., healthy, or with brain disorders, is generally a more difficult task than merely finding group differences. The former must be approached with highly informative and sensitive biomarkers as well as effective pattern classification/feature selection approaches. In this paper, we propose a systematic methodology to discriminate attention deficit hyperactivity disorder (ADHD) patients from healthy controls on the individual level. Multiple neuroimaging markers that are proved to be sensitive features are identified, which include multiscale characteristics extracted from blood oxygenation level dependent (BOLD) signals, such as regional homogeneity (ReHo) and amplitude of low-frequency fluctuations. Functional connectivity derived from Pearson, partial, and spatial correlation is also utilized to reflect the abnormal patterns of functional integration, or, dysconnectivity syndromes in the brain. These neuroimaging markers are calculated on either voxel or regional level. Advanced feature selection approach is then designed, including a brain-wise association study (BWAS). Using identified features and proper feature integration, a support vector machine (SVM) classifier can achieve a cross-validated classification accuracy of 76.15% across individuals from a large dataset consisting of 141 healthy controls and 98 ADHD patients, with the sensitivity being 63.27% and the specificity being 85.11%. Our results show that the most discriminative features for classification are primarily associated with the frontal and cerebellar regions. The proposed methodology is expected to improve clinical diagnosis and evaluation of treatment for ADHD patient, and to have wider applications in diagnosis of general neuropsychiatric disorders. PMID:22888314