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

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.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2015-01-01

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

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

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

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,…

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

PubMed Central

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

2010-01-01

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

Functions of the human frontoparietal attention network: Evidence from neuroimaging

PubMed Central

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

2016-01-01

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

Functional 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.

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

PubMed

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

2015-01-01

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

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

PubMed

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

2014-01-01

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

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.

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.

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

Functional neuroimaging in epileptic encephalopathies.

PubMed

Siniatchkin, Michael; Capovilla, Giuseppe

2013-11-01

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

[Conversion disorder : functional neuroimaging and neurobiological mechanisms].

PubMed

Lejeune, J; Piette, C; Salmon, E; Scantamburlo, G

2017-04-01

Conversion disorder is a psychiatric disorder often encountered in neurology services. This condition without organic lesions was and still is sometimes referred as an imaginary illness or feigning. However, the absence of organic lesions does not exclude the possibility of cerebral dysfunction. The etiologic mechanisms underlying this disorder remain uncertain even today.The advent of cognitive and functional imaging opens up a field of exploration for psychiatry in understanding the neurobiological mechanisms underlying mental disorders and especially the conversion disorder. This article reports several neuroimaging studies of conversion disorder and attempts to generate hypotheses about neurobiological mechanisms.

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

PubMed Central

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

2017-01-01

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

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

PubMed Central

Morita, Tomoyo; Asada, Minoru; Naito, Eiichi

2016-01-01

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

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

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

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

PubMed Central

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

1999-01-01

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

Cholinergic modulation of cognition: Insights from human pharmacological functional neuroimaging

PubMed Central

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

2011-01-01

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

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

PubMed

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

2017-08-01

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

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance.

PubMed

Schlund, Michael W; Cataldo, Michael F; Siegle, Greg J; Ladouceur, Cecile D; Silk, Jennifer S; Forbes, Erika E; McFarland, Ashley; Iyengar, Satish; Dahl, Ronald E; Ryan, Neal D

2011-05-06

Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N=120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks. The proposed approach contributes to the pediatric neuroimaging literature by

Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies

PubMed Central

Kober, Hedy; Barrett, Lisa Feldman; Joseph, Josh; Bliss-Moreau, Eliza; Lindquist, Kristen; Wager, Tor D.

2009-01-01

We performed an updated quantitative meta-analysis of 162 neuroimaging studies of emotion using a novel multi-level kernel-based approach, focusing on locating brain regions consistently activated in emotional tasks and their functional organization into distributed functional groups, independent of semantically defined emotion category labels (e.g., “anger,” “fear”). Such brain-based analyses are critical if our ways of labeling emotions are to be evaluated and revised based on consistency with brain data. Consistent activations were limited to specific cortical sub-regions, including multiple functional areas within medial, orbital, and inferior lateral frontal cortices. Consistent with a wealth of animal literature, multiple subcortical activations were identified, including amygdala, ventral striatum, thalamus, hypothalamus, and periaqueductal gray. We used multivariate parcellation and clustering techniques to identify groups of co-activated brain regions across studies. These analyses identified six distributed functional groups, including medial and lateral frontal groups, two posterior cortical groups, and paralimbic and core limbic/brainstem groups. These functional groups provide information on potential organization of brain regions into large-scale networks. Specific follow-up analyses focused on amygdala, periaqueductal gray (PAG), and hypothalamic (Hy) activations, and identified frontal cortical areas co-activated with these core limbic structures. While multiple areas of frontal cortex co-activated with amygdala sub-regions, a specific region of dorsomedial prefrontal cortex (dmPFC, Brodmann’s Area 9/32) was the only area co-activated with both PAG and Hy. Subsequent mediation analyses were consistent with a pathway from dmPFC through PAG to Hy. These results suggest that medial frontal areas are more closely associated with core limbic activation than their lateral counterparts, and that dmPFC may play a particularly important role in the

The anatomy of language: contributions from functional neuroimaging

PubMed Central

PRICE, CATHY J.

2000-01-01

This article illustrates how functional neuroimaging can be used to test the validity of neurological and cognitive models of language. Three models of language are described: the 19th Century neurological model which describes both the anatomy and cognitive components of auditory and visual word processing, and 2 20th Century cognitive models that are not constrained by anatomy but emphasise 2 different routes to reading that are not present in the neurological model. A series of functional imaging studies are then presented which show that, as predicted by the 19th Century neurologists, auditory and visual word repetition engage the left posterior superior temporal and posterior inferior frontal cortices. More specifically, the roles Wernicke and Broca assigned to these regions lie respectively in the posterior superior temporal sulcus and the anterior insula. In addition, a region in the left posterior inferior temporal cortex is activated for word retrieval, thereby providing a second route to reading, as predicted by the 20th Century cognitive models. This region and its function may have been missed by the 19th Century neurologists because selective damage is rare. The angular gyrus, previously linked to the visual word form system, is shown to be part of a distributed semantic system that can be accessed by objects and faces as well as speech. Other components of the semantic system include several regions in the inferior and middle temporal lobes. From these functional imaging results, a new anatomically constrained model of word processing is proposed which reconciles the anatomical ambitions of the 19th Century neurologists and the cognitive finesse of the 20th Century cognitive models. The review focuses on single word processing and does not attempt to discuss how words are combined to generate sentences or how several languages are learned and interchanged. Progress in unravelling these and other related issues will depend on the integration of

Integrating Functional Brain Neuroimaging and Developmental Cognitive Neuroscience in Child Psychiatry Research

ERIC Educational Resources Information Center

Pavuluri, Mani N.; Sweeney, John A.

2008-01-01

The use of cognitive neuroscience and functional brain neuroimaging to understand brain dysfunction in pediatric psychiatric disorders is discussed. Results show that bipolar youths demonstrate impairment in affective and cognitive neural systems and in these two circuits' interface. Implications for the diagnosis and treatment of psychiatric…

Hypnosis and pain perception: An Activation Likelihood Estimation (ALE) meta-analysis of functional neuroimaging studies.

PubMed

Del Casale, Antonio; Ferracuti, Stefano; Rapinesi, Chiara; De Rossi, Pietro; Angeletti, Gloria; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo

2015-12-01

Several studies reported that hypnosis can modulate pain perception and tolerance by affecting cortical and subcortical activity in brain regions involved in these processes. We conducted an Activation Likelihood Estimation (ALE) meta-analysis on functional neuroimaging studies of pain perception under hypnosis to identify brain activation-deactivation patterns occurring during hypnotic suggestions aiming at pain reduction, including hypnotic analgesic, pleasant, or depersonalization suggestions (HASs). We searched the PubMed, Embase and PsycInfo databases; we included papers published in peer-reviewed journals dealing with functional neuroimaging and hypnosis-modulated pain perception. The ALE meta-analysis encompassed data from 75 healthy volunteers reported in 8 functional neuroimaging studies. HASs during experimentally-induced pain compared to control conditions correlated with significant activations of the right anterior cingulate cortex (Brodmann's Area [BA] 32), left superior frontal gyrus (BA 6), and right insula, and deactivation of right midline nuclei of the thalamus. HASs during experimental pain impact both cortical and subcortical brain activity. The anterior cingulate, left superior frontal, and right insular cortices activation increases could induce a thalamic deactivation (top-down inhibition), which may correlate with reductions in pain intensity. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-05-01

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

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

PubMed Central

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

2014-01-01

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

Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.

PubMed

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

2017-10-01

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

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.

Feasibility of functional neuroimaging to understand adolescent women's sexual decision making.

PubMed

Hensel, Devon J; Hummer, Tom A; Acrurio, Lindsay R; James, Thomas W; Fortenberry, J Dennis

2015-04-01

For young women, new sexual experiences normatively increase after puberty and coincide with extensive changes to brain regions governing self-regulation of risk behavior. These neurodevelopmental changes could leave some young women vulnerable for negative sexual outcomes, including sexually transmitted infection and unintended pregnancy. We evaluated the feasibility of using functional neuroimaging to understand the sexual decision making of adolescent women. Adolescent women (N = 14; 14-15 years) completed enrollment interviews, a neuroimaging task gauging neural activation to appetitive stimuli, and 30 days of prospective diaries following the scan characterizing daily affect and sexual behaviors. Descriptive and inferential statistics assessed the association between imaging and behavioral data. Young women were highly compliant with neuroimaging and diary protocol. Neural activity in a cognitive-affective network, including prefrontal and anterior cingulate regions, was significantly greater during low-risk decisions. Compared with other decisions, high-risk sexual decisions elicited greater activity in the anterior cingulate, and low-risk sexual decision elicited greater activity in regions of the visual cortex. Young women's sexual decision ratings were linked to their sexual history characteristics and daily self-reports of sexual emotions and behaviors. It is feasible to recruit and retain a cohort of female participants to perform a functional magnetic resonance imaging task focused on making decisions about sex, on the basis of varying levels of hypothetical sexual risk, and to complete longitudinal prospective diaries following this task. Preliminary evidence suggests that risk level differentially impacts brain activity related to sexual decision making in these women, which may be related to past and future sexual behaviors. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Energy landscape analysis of neuroimaging data

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

[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.

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.

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

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.

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

A Review on the Bioinformatics Tools for Neuroimaging

PubMed Central

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

2015-01-01

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

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance

PubMed Central

2011-01-01

Background Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. Method In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N = 120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Results Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. Discussion We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks Conclusion The proposed approach

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

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.

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

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging.

PubMed

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging

PubMed Central

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research. PMID:29033866

Functional Neuroimaging Insights into the Physiology of Human Sleep

PubMed Central

Dang-Vu, Thien Thanh; Schabus, Manuel; Desseilles, Martin; Sterpenich, Virginie; Bonjean, Maxime; Maquet, Pierre

2010-01-01

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep. Citation: Dang

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

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…

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.

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

PubMed

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

2018-03-01

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

Functional neuroimaging of conversion disorder: the role of ancillary activation.

PubMed

Burke, Matthew J; Ghaffar, Omar; Staines, W Richard; Downar, Jonathan; Feinstein, Anthony

2014-01-01

Previous functional neuroimaging studies investigating the neuroanatomy of conversion disorder have yielded inconsistent results that may be attributed to small sample sizes and disparate methodologies. The objective of this study was to better define the functional neuroanatomical correlates of conversion disorder. Ten subjects meeting clinical criteria for unilateral sensory conversion disorder underwent fMRI during which a vibrotactile stimulus was applied to anesthetic and sensate areas. A block design was used with 4 s of stimulation followed by 26 s of rest, the pattern repeated 10 times. Event-related group averages of the BOLD response were compared between conditions. All subjects were right-handed females, with a mean age of 41. Group analyses revealed 10 areas that had significantly greater activation (p < .05) when stimulation was applied to the anesthetic body part compared to the contralateral sensate mirror region. They included right paralimbic cortices (anterior cingulate cortex and insula), right temporoparietal junction (angular gyrus and inferior parietal lobule), bilateral dorsolateral prefrontal cortex (middle frontal gyri), right orbital frontal cortex (superior frontal gyrus), right caudate, right ventral-anterior thalamus and left angular gyrus. There was a trend for activation of the somatosensory cortex contralateral to the anesthetic region to be decreased relative to the sensate side. Sensory conversion symptoms are associated with a pattern of abnormal cerebral activation comprising neural networks implicated in emotional processing and sensory integration. Further study of the roles and potential interplay of these networks may provide a basis for an underlying psychobiological mechanism of conversion disorder.

Functional neuroimaging studies in addiction: multisensory drug stimuli and neural cue reactivity.

PubMed

Yalachkov, Yavor; Kaiser, Jochen; Naumer, Marcus J

2012-02-01

Neuroimaging studies on cue reactivity have substantially contributed to the understanding of addiction. In the majority of studies drug cues were presented in the visual modality. However, exposure to conditioned cues in real life occurs often simultaneously in more than one sensory modality. Therefore, multisensory cues should elicit cue reactivity more consistently than unisensory stimuli and increase the ecological validity and the reliability of brain activation measurements. This review includes the data from 44 whole-brain functional neuroimaging studies with a total of 1168 subjects (812 patients and 356 controls). Correlations between neural cue reactivity and clinical covariates such as craving have been reported significantly more often for multisensory than unisensory cues in the motor cortex, insula and posterior cingulate cortex. Thus, multisensory drug cues are particularly effective in revealing brain-behavior relationships in neurocircuits of addiction responsible for motivation, craving awareness and self-related processing. Copyright © 2011 Elsevier Ltd. All rights reserved.

[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.

[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.

Neuroimaging of the Periaqueductal Gray: State of the Field

PubMed Central

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

2011-01-01

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

Neuroimaging in 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

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…

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.

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

PubMed

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

2017-07-01

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

Machine learning for neuroimaging with scikit-learn.

PubMed

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

2014-01-01

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

Machine learning for neuroimaging with scikit-learn

PubMed Central

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

2014-01-01

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

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

The role of sexual abuse on functional neuroimaging markers associated with major depressive disorder.

PubMed

Skokauskas, Norbert; Carballedo, Angela; Fagan, Andrew; Frodl, Thomas

2015-10-01

Victims of child sexual abuse can develop depression and other mental health conditions that follow them well into adulthood. This study aimed to clarify the role of sexual abuse (SA) on functional imaging markers associated with MDD. Thirty-seven patients with MDD only; and 13 patients with both MDD and SA and 43 healthy controls performed emotional attention shifting tasks during fMRI session. Clinical diagnoses were made by consultant psychiatrists based on the DSM-IV-TR criteria and diagnoses were confirmed using SCID-I. Magnetic resonance images were obtained with a Philips Achieva 3 Tesla MRI scanner. Short form childhood trauma questionnaire, Hamilton Rating Scale for Depression and Beck's Depression Inventory were also employed. Data were analysed with Statistical Parametric Mapping 8 (SPM8). Using the contrast judgment of emotion minus judgment of geometry following emotional neutral stimuli, patients with MDD showed significantly reduced activation in comparison to healthy controls in the area of the right fusiform gyrus. With the contrast judgment of emotion minus judgment of geometry following emotional negative stimuli, participants with MDD and SA showed significantly higher activation in the area of the left inferior parietal lobe in comparison to participants with MDD without SA. The history of sexual abuse affects functional neuroimaging markers associated with major depressive disorder.

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

PubMed

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

2009-03-01

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

Experimental Design and Interpretation of Functional Neuroimaging Studies of Cognitive Processes

PubMed Central

Caplan, David

2008-01-01

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

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

PubMed Central

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

2012-01-01

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

[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.

On the role of general system theory for functional neuroimaging.

PubMed

Stephan, Klaas Enno

2004-12-01

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

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

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

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.

Sharing brain mapping statistical results with the neuroimaging data model

PubMed Central

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

2016-01-01

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

Advanced Neuroimaging in Traumatic Brain Injury

PubMed Central

Edlow, Brian L.; Wu, Ona

2013-01-01

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

Neuroimaging in human MDMA (Ecstasy) users.

PubMed

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

2008-10-01

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

GPU Accelerated Browser for Neuroimaging Genomics.

PubMed

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

2018-04-25

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

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.

Neuroimaging in psychiatric pharmacogenetics research: the promise and pitfalls.

PubMed

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

2013-11-01

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

Neuroimaging 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

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

PubMed Central

Roussotte, Florence; Soderberg, Lindsay

2010-01-01

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

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

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

PubMed

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

2017-09-21

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

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

PubMed Central

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

2017-01-01

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

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

PubMed Central

Parasuraman, Raja; Jiang, Yang

2012-01-01

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

Neuroimaging 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.

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

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

PubMed Central

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

2018-01-01

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

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.

[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.

Neural correlates of attention and arousal: insights from electrophysiology, functional neuroimaging and psychopharmacology.

PubMed

Coull, J T

1998-07-01

Attention and arousal are multi-dimensional psychological processes, which interact closely with one another. The neural substrates of attention, as well as the interaction between arousal and attention, are discussed in this review. After a brief discussion of psychological and neuropsychological theories of attention, event-related potential correlates of attention are discussed. Essentially, attention acts to modulate stimulus-induced electrical potentials (N100/P100, P300, N400), rather than generating any unique potentials of its own. Functional neuroimaging studies of attentional orienting, selective attention, divided attention and sustained attention (and its inter-dependence on underlying levels of arousal) are then reviewed. A distinction is drawn between the brain areas which are crucially involved in the top-down modulation of attention (the 'sources' of attention) and those sensory-association areas whose activity is modulated by attention (the 'sites' of attentional expression). Frontal and parietal (usually right-lateralised) cortices and thalamus are most often associated with the source of attentional modulation. Also, the use of functional neuroimaging to test explicit hypotheses about psychological theories of attention is emphasised. These experimental paradigms form the basis for a 'new generation' of functional imaging studies which exploit the dynamic aspect of imaging and demonstrate how it can be used as more than just a 'brain mapping' device. Finally, a review of psychopharmacological studies in healthy human volunteers outlines the contributions of the noradrenergic, cholinergic and dopaminergic neurotransmitter systems to the neurochemical modulation of human attention and arousal. While, noradrenergic and cholinergic systems are involved in 'low-level' aspects of attention (e.g. attentional orienting), the dopaminergic system is associated with more 'executive' aspects of attention such as attentional set-shifting or working memory.

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

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

PubMed

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

2018-07-01

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

Functional neuroimaging for addiction medicine: From mechanisms to practical considerations.

PubMed

Ekhtiari, Hamed; Faghiri, Ashkan; Oghabian, Mohammad-Ali; Paulus, Martin P

2016-01-01

During last 20 years, neuroimaging with functional magnetic resonance imaging (fMRI) in people with drug addictions has introduced a wide range of quantitative biomarkers from brain's regional or network level activities during different cognitive functions. These quantitative biomarkers could be potentially used for assessment, planning, prediction, and monitoring for "addiction medicine" during screening, acute intoxication, admission to a program, completion of an acute program, admission to a long-term program, and postgraduation follow-up. In this chapter, we have briefly reviewed main neurocognitive targets for fMRI studies associated with addictive behaviors, main study types using fMRI among drug dependents, and potential applications for fMRI in addiction medicine. Main challenges and limitations for extending fMRI studies and evidences aiming at clinical applications in addiction medicine are also discussed. There is still a significant gap between available evidences from group-based fMRI studies and personalized decisions during daily practices in addiction medicine. It will be important to fill this gap with large-scale clinical trials and longitudinal studies using fMRI measures with a well-defined strategic plan for the future. © 2016 Elsevier B.V. All rights reserved.

The Co-evolution of Neuroimaging and Psychiatric Neurosurgery.

PubMed

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

2016-01-01

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

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

PubMed

Letzen, Janelle E; Robinson, Michael E

2017-01-01

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

25 years of neuroimaging in amyotrophic lateral sclerosis.

PubMed

Foerster, Bradley R; Welsh, Robert C; Feldman, Eva L

2013-09-01

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques--such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy--allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development.

25 years of neuroimaging in amyotrophic lateral sclerosis

PubMed Central

Foerster, Bradley R.; Welsh, Robert C.; Feldman, Eva L.

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques—such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy—allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development. PMID:23917850

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.

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

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

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

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

PubMed Central

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

2013-01-01

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

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

ERIC Educational Resources Information Center

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

2010-01-01

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

The neural basis of episodic memory: evidence from functional neuroimaging.

PubMed Central

Rugg, Michael D; Otten, Leun J; Henson, Richard N A

2002-01-01

We review some of our recent research using functional neuroimaging to investigate neural activity supporting the encoding and retrieval of episodic memories, that is, memories for unique events. Findings from studies of encoding indicate that, at the cortical level, the regions responsible for the effective encoding of a stimulus event as an episodic memory include some of the regions that are also engaged to process the event 'online'. Thus, it appears that there is no single cortical site or circuit responsible for episodic encoding. The results of retrieval studies indicate that successful recollection of episodic information is associated with activation of lateral parietal cortex, along with more variable patterns of activity in dorsolateral and anterior prefrontal cortex. Whereas parietal regions may play a part in the representation of retrieved information, prefrontal areas appear to support processes that act on the products of retrieval to align behaviour with the demands of the retrieval task. PMID:12217177

Neuroimaging the interaction of mind and metabolism in humans

PubMed Central

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

2012-01-01

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

Neuroimaging 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.

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.

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.

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

PubMed

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

2018-03-09

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

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.

Are numbers grounded in a general magnitude processing system? A functional neuroimaging meta-analysis.

PubMed

Sokolowski, H Moriah; Fias, Wim; Bosah Ononye, Chuka; Ansari, Daniel

2017-10-01

It is currently debated whether numbers are processed using a number-specific system or a general magnitude processing system, also used for non-numerical magnitudes such as physical size, duration, or luminance. Activation likelihood estimation (ALE) was used to conduct the first quantitative meta-analysis of 93 empirical neuroimaging papers examining neural activation during numerical and non-numerical magnitude processing. Foci were compiled to generate probabilistic maps of activation for non-numerical magnitudes (e.g. physical size), symbolic numerical magnitudes (e.g. Arabic digits), and nonsymbolic numerical magnitudes (e.g. dot arrays). Conjunction analyses revealed overlapping activation for symbolic, nonsymbolic and non-numerical magnitudes in frontal and parietal lobes. Contrast analyses revealed specific activation in the left superior parietal lobule for symbolic numerical magnitudes. In contrast, small regions in the bilateral precuneus were specifically activated for nonsymbolic numerical magnitudes. No regions in the parietal lobes were activated for non-numerical magnitudes that were not also activated for numerical magnitudes. Therefore, numbers are processed using both a generalized magnitude system and format specific number regions. Copyright © 2017 Elsevier Ltd. All rights reserved.

The neuroimaging of sacred values.

PubMed

Vilarroya, Oscar; Hilferty, Joseph

2013-09-01

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

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

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

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.

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.

Functional neuroimaging insights into the physiology of human sleep.

PubMed

Dang-Vu, Thien Thanh; Schabus, Manuel; Desseilles, Martin; Sterpenich, Virginie; Bonjean, Maxime; Maquet, Pierre

2010-12-01

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep.

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.

Prognostic Role of Functional Neuroimaging after Multilobar Resection in Patients with Localization-Related Epilepsy.

PubMed

Cho, Eun Bin; Joo, Eun Yeon; Seo, Dae-Won; Hong, Seung-Chyul; Hong, Seung Bong

2015-01-01

To investigate the usage of functional neuroimaging as a prognostic tool for seizure recurrence and long-term outcomes in patients with multilobar resection, we recruited 90 patients who received multilobar resections between 1995 and 2013 with at least 1-year follow-up (mean 8.0 years). All patients were monitored using intracranial electroencephalography (EEG) after pre-surgical evaluation. Clinical data (demographics, electrophysiology, and neuroimaging) were reviewed retrospectively. Surgical outcomes were evaluated at 1, 2, 5 years after surgery, and at the end of the study. After 1 year, 56 patients (62.2%) became Engel class I and at the last follow-up, 47 patients (52.2%) remained seizure-free. Furthermore, non-localized 18F-fluorodeoxyglucose positron emission tomography (PET), identifying hypometabolic areas not concordant with ictal onset zones, significantly correlated with seizure recurrence after 1 year. Non-lesional magnetic resonance imaging (MRI) and left-sided resection correlated with poor outcomes. In the last follow-up, non-localized PET and left-sided resection significantly correlated with seizure recurrence. Both localized PET and ictal-interictal SPECT subtraction co-registered to MR (SISCOM) predicted good surgical outcomes in the last follow-up (69.2%, Engel I). This study suggests that PET and SISCOM may predict postoperative outcomes for patients after multilobar epilepsy and shows comparable long-term surgical outcomes after multilobar resection.

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

PubMed

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

2013-06-04

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

Volumetric neuroimage analysis extensions for the MIPAV software package.

PubMed

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

2007-09-15

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

Functional neuroimaging of normal aging: Declining brain, adapting brain.

PubMed

Sugiura, Motoaki

2016-09-01

Early functional neuroimaging research on normal aging brain has been dominated by the interest in cognitive decline. In this framework the age-related compensatory recruitment of prefrontal cortex, in terms of executive system or reduced lateralization, has been established. Further details on these compensatory mechanisms and the findings reflecting cognitive decline, however, remain the matter of intensive investigations. Studies in another framework where age-related neural alteration is considered adaptation to the environmental change are recently burgeoning and appear largely categorized into three domains. The age-related increase in activation of the sensorimotor network may reflect the alteration of the peripheral sensorimotor systems. The increased susceptibility of the network for the mental-state inference to the socioemotional significance may be explained by the age-related motivational shift due to the altered social perception. The age-related change in activation of the self-referential network may be relevant to the focused positive self-concept of elderly driven by a similar motivational shift. Across the domains, the concept of the self and internal model may provide the theoretical bases of this adaptation framework. These two frameworks complement each other to provide a comprehensive view of the normal aging brain. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2009-01-01

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

Where Is the Semantic System? A Critical Review and Meta-Analysis of 120 Functional Neuroimaging Studies

PubMed Central

Desai, Rutvik H.; Graves, William W.; Conant, Lisa L.

2009-01-01

Semantic memory refers to knowledge about people, objects, actions, relations, self, and culture acquired through experience. The neural systems that store and retrieve this information have been studied for many years, but a consensus regarding their identity has not been reached. Using strict inclusion criteria, we analyzed 120 functional neuroimaging studies focusing on semantic processing. Reliable areas of activation in these studies were identified using the activation likelihood estimate (ALE) technique. These activations formed a distinct, left-lateralized network comprised of 7 regions: posterior inferior parietal lobe, middle temporal gyrus, fusiform and parahippocampal gyri, dorsomedial prefrontal cortex, inferior frontal gyrus, ventromedial prefrontal cortex, and posterior cingulate gyrus. Secondary analyses showed specific subregions of this network associated with knowledge of actions, manipulable artifacts, abstract concepts, and concrete concepts. The cortical regions involved in semantic processing can be grouped into 3 broad categories: posterior multimodal and heteromodal association cortex, heteromodal prefrontal cortex, and medial limbic regions. The expansion of these regions in the human relative to the nonhuman primate brain may explain uniquely human capacities to use language productively, plan, solve problems, and create cultural and technological artifacts, all of which depend on the fluid and efficient retrieval and manipulation of semantic knowledge. PMID:19329570

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

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.

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.

Neuroimaging essentials in essential tremor: A systematic review

PubMed Central

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

2014-01-01

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

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.

Neuroimaging studies of GABA in schizophrenia: a systematic review with meta-analysis.

PubMed

Egerton, A; Modinos, G; Ferrera, D; McGuire, P

2017-06-06

Data from animal models and from postmortem studies suggest that schizophrenia is associated with brain GABAergic dysfunction. The extent to which this is reflected in data from in vivo studies of GABA function in schizophrenia is unclear. The Medline database was searched to identify articles published until 21 October 2016. The search terms included GABA, proton magnetic resonance spectroscopy ( 1 H-MRS), positron emission tomography (PET), single photon emission computed tomography (SPECT), schizophrenia and psychosis. Sixteen GABA 1 H-MRS studies (538 controls, 526 patients) and seven PET/SPECT studies of GABA A /benzodiazepine receptor (GABA A /BZR) availability (118 controls, 113 patients) were identified. Meta-analyses of 1 H-MRS GABA in the medial prefrontal cortex (mPFC), parietal/occipital cortex (POC) and striatum did not show significant group differences (mFC: g=-0.3, 409 patients, 495 controls, 95% confidence interval (CI): -0.6 to 0.1; POC: g=-0.3, 139 patients, 111 controls, 95% CI: -0.9 to 0.3; striatum: g=-0.004, 123 patients, 95 controls, 95% CI: -0.7 to 0.7). Heterogeneity across studies was high (I 2 >50%), and this was not explained by subsequent moderator or meta-regression analyses. There were insufficient PET/SPECT receptor availability studies for meta-analyses, but a systematic review did not suggest replicable group differences in regional GABA A /BZR availability. The current literature does not reveal consistent alterations in in vivo GABA neuroimaging measures in schizophrenia, as might be hypothesized from animal models and postmortem data. The analysis highlights the need for further GABA neuroimaging studies with improved methodology and addressing potential sources of heterogeneity.

Neuroimaging studies of GABA in schizophrenia: a systematic review with meta-analysis

PubMed Central

Egerton, A; Modinos, G; Ferrera, D; McGuire, P

2017-01-01

Data from animal models and from postmortem studies suggest that schizophrenia is associated with brain GABAergic dysfunction. The extent to which this is reflected in data from in vivo studies of GABA function in schizophrenia is unclear. The Medline database was searched to identify articles published until 21 October 2016. The search terms included GABA, proton magnetic resonance spectroscopy (1H-MRS), positron emission tomography (PET), single photon emission computed tomography (SPECT), schizophrenia and psychosis. Sixteen GABA 1H-MRS studies (538 controls, 526 patients) and seven PET/SPECT studies of GABAA/benzodiazepine receptor (GABAA/BZR) availability (118 controls, 113 patients) were identified. Meta-analyses of 1H-MRS GABA in the medial prefrontal cortex (mPFC), parietal/occipital cortex (POC) and striatum did not show significant group differences (mFC: g=−0.3, 409 patients, 495 controls, 95% confidence interval (CI): −0.6 to 0.1; POC: g=−0.3, 139 patients, 111 controls, 95% CI: −0.9 to 0.3; striatum: g=−0.004, 123 patients, 95 controls, 95% CI: −0.7 to 0.7). Heterogeneity across studies was high (I2>50%), and this was not explained by subsequent moderator or meta-regression analyses. There were insufficient PET/SPECT receptor availability studies for meta-analyses, but a systematic review did not suggest replicable group differences in regional GABAA/BZR availability. The current literature does not reveal consistent alterations in in vivo GABA neuroimaging measures in schizophrenia, as might be hypothesized from animal models and postmortem data. The analysis highlights the need for further GABA neuroimaging studies with improved methodology and addressing potential sources of heterogeneity. PMID:28585933

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

PubMed Central

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

2014-01-01

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

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.

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond.

PubMed

Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco

2017-01-01

The existence of so-called 'basic emotions' and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond

PubMed Central

Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco

2017-01-01

The existence of so-called ‘basic emotions’ and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In

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.

Neuroimaging the Effectiveness of Substance Use Disorder Treatments.

PubMed

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

2016-09-01

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

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

PubMed

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

2017-02-24

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

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

PubMed

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

2017-01-01

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

Neuroimaging Craving: Urge Intensity Matters

PubMed Central

Wilson, Stephen J.; Sayette, Michael A.

2015-01-01

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

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.

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.

A cognitive neurobiological account of deception: evidence from functional neuroimaging.

PubMed Central

Spence, Sean A; Hunter, Mike D; Farrow, Tom F D; Green, Russell D; Leung, David H; Hughes, Catherine J; Ganesan, Venkatasubramanian

2004-01-01

An organism may use misinformation, knowingly (through deception) or unknowingly (as in the case of camouflage), to gain advantage in a competitive environment. From an evolutionary perspective, greater tactical deception occurs among primates closer to humans, with larger neocortices. In humans, the onset of deceptive behaviours in childhood exhibits a developmental trajectory, which may be regarded as 'normal' in the majority and deficient among a minority with certain neurodevelopmental disorders (e.g. autism). In the human adult, deception and lying exhibit features consistent with their use of 'higher' or 'executive' brain systems. Accurate detection of deception in humans may be of particular importance in forensic practice, while an understanding of its cognitive neurobiology may have implications for models of 'theory of mind' and social cognition, and societal notions of responsibility, guilt and mitigation. In recent years, functional neuroimaging techniques (especially functional magnetic resonance imaging) have been used to study deception. Though few in number, and using very different experimental protocols, studies published in the peer-reviewed literature exhibit certain consistencies. Attempted deception is associated with activation of executive brain regions (particularly prefrontal and anterior cingulate cortices), while truthful responding has not been shown to be associated with any areas of increased activation (relative to deception). Hence, truthful responding may comprise a relative 'baseline' in human cognition and communication. The subject who lies may necessarily engage 'higher' brain centres, consistent with a purpose or intention (to deceive). While the principle of executive control during deception remains plausible, its precise anatomy awaits elucidation. PMID:15590616

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.

Neuroimaging correlates of aggression in schizophrenia: an update.

PubMed

Hoptman, Matthew J; Antonius, Daniel

2011-03-01

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

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

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

PubMed Central

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

2017-01-01

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

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

PubMed Central

Sharma, Anup; Newberg, Andrew B

2016-01-01

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

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

PubMed

Sharma, Anup; Newberg, Andrew B

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

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.

Intrinsic functional component analysis via sparse representation on Alzheimer's disease neuroimaging initiative database.

PubMed

Jiang, Xi; Zhang, Xin; Zhu, Dajiang

2014-10-01

Alzheimer's disease (AD) is the most common type of dementia (accounting for 60% to 80%) and is the fifth leading cause of death for those people who are 65 or older. By 2050, one new case of AD in United States is expected to develop every 33 sec. Unfortunately, there is no available effective treatment that can stop or slow the death of neurons that causes AD symptoms. On the other hand, it is widely believed that AD starts before development of the associated symptoms, so its prestages, including mild cognitive impairment (MCI) or even significant memory concern (SMC), have received increasing attention, not only because of their potential as a precursor of AD, but also as a possible predictor of conversion to other neurodegenerative diseases. Although these prestages have been defined clinically, accurate/efficient diagnosis is still challenging. Moreover, brain functional abnormalities behind those alterations and conversions are still unclear. In this article, by developing novel sparse representations of whole-brain resting-state functional magnetic resonance imaging signals and by using the most updated Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we successfully identified multiple functional components simultaneously, and which potentially represent those intrinsic functional networks involved in the resting-state activities. Interestingly, these identified functional components contain all the resting-state networks obtained from traditional independent-component analysis. Moreover, by using the features derived from those functional components, it yields high classification accuracy for both AD (94%) and MCI (92%) versus normal controls. Even for SMC we can still have 92% accuracy.

Neuroimaging craving: urge intensity matters.

PubMed

Wilson, Stephen J; Sayette, Michael A

2015-02-01

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

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.

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.

Neuroimaging studies of cognitive remediation in schizophrenia: A systematic and critical review.

PubMed

Penadés, Rafael; González-Rodríguez, Alexandre; Catalán, Rosa; Segura, Bàrbara; Bernardo, Miquel; Junqué, Carme

2017-03-22

To examine the effects of cognitive remediation therapies on brain functioning through neuroimaging procedures in patients with schizophrenia. A systematic, computerised literature search was conducted in the PubMed/Medline and PsychInfo databases. The search was performed through February 2016 without any restrictions on language or publication date. The search was performed using the following search terms: [("cogniti*" and "remediation" or "training" or "enhancement") and ("fMRI" or "MRI" or "PET" or "SPECT") and (schizophrenia or schiz*)]. The search was accompanied by a manual online search and a review of the references from each of the papers selected, and those papers fulfilling our inclusion criteria were also included. A total of 101 studies were found, but only 18 of them fulfilled the inclusion criteria. These studies indicated that cognitive remediation improves brain activation in neuroimaging studies. The most commonly reported changes were those that involved the prefrontal and thalamic regions. Those findings are in agreement with the hypofrontality hypothesis, which proposes that frontal hypoactivation is the underlying mechanism of cognitive impairments in schizophrenia. Nonetheless, great heterogeneity among the studies was found. They presented different hypotheses, different results and different findings. The results of more recent studies interpreted cognitive recovery within broader frameworks, namely, as amelioration of the efficiency of different networks. Furthermore, advances in neuroimaging methodologies, such as the use of whole-brain analysis, tractography, graph analysis, and other sophisticated methodologies of data processing, might be conditioning the interpretation of results and generating new theoretical frameworks. Additionally, structural changes were described in both the grey and white matter, suggesting a neuroprotective effect of cognitive remediation. Cognitive, functional and structural improvements tended to be

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.

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

Chronic disorders of consciousness: role of neuroimaging

NASA Astrophysics Data System (ADS)

Kremneva, E.; Sergeev, D.; Zmeykina, E.; Legostaeva, L.; Piradov, M.

2017-08-01

Chronic disorders of consciousness are clinically challenging conditions, and advanced methods of imaging for better understanding of diagnosis and prognosis are needed. Recent functional neuroradiological studies utilizing PET and fMRI demonstrated that besides widespread neuronal loss disruption of interconnection between certain cortical networks after the injury may also play the leading role in the development of behaviourally assessed unresponsiveness. Functional and structural connectivity, evaluated by neuroimaging approaches, may correlate with clinical status and may also play prognostic role. Integration of data from various diagnostic modalities is needed for further progress in this area.

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

In Search of the Trauma Memory: A Meta-Analysis of Functional Neuroimaging Studies of Symptom Provocation in Posttraumatic Stress Disorder (PTSD)

PubMed Central

Sartory, Gudrun; Cwik, Jan; Knuppertz, Helge; Schürholt, Benjamin; Lebens, Morena; Seitz, Rüdiger J.; Schulze, Ralf

2013-01-01

Notwithstanding some discrepancy between results from neuroimaging studies of symptom provocation in posttraumatic stress disorder (PTSD), there is broad agreement as to the neural circuit underlying this disorder. It is thought to be characterized by an exaggerated amygdalar and decreased medial prefrontal activation to which the elevated anxiety state and concomitant inadequate emotional regulation are attributed. However, the proposed circuit falls short of accounting for the main symptom, unique among anxiety disorders to PTSD, namely, reexperiencing the precipitating event in the form of recurrent, distressing images and recollections. Owing to the technical demands, neuroimaging studies are usually carried out with small sample sizes. A meta-analysis of their findings is more likely to cast light on the involved cortical areas. Coordinate-based meta-analyses employing ES-SDM (Effect Size Signed Differential Mapping) were carried out on 19 studies with 274 PTSD patients. Thirteen of the studies included 145 trauma-exposed control participants. Comparisons between reactions to trauma-related stimuli and a control condition and group comparison of reactions to the trauma-related stimuli were submitted to meta-analysis. Compared to controls and the neutral condition, PTSD patients showed significant activation of the mid-line retrosplenial cortex and precuneus in response to trauma-related stimuli. These midline areas have been implicated in self-referential processing and salient autobiographical memory. PTSD patients also evidenced hyperactivation of the pregenual/anterior cingulate gyrus and bilateral amygdala to trauma-relevant, compared to neutral, stimuli. Patients showed significantly less activation than controls in sensory association areas such as the bilateral temporal gyri and extrastriate area which may indicate that the patients’ attention was diverted from the presented stimuli by being focused on the elicited trauma memory. Being involved in

Deep learning for neuroimaging: a validation study.

PubMed

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

2014-01-01

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

Neuroimaging of neurocutaneous diseases.

PubMed

Nandigam, Kaveer; Mechtler, Laszlo L; Smirniotopoulos, James G

2014-02-01

An in-depth knowledge of the imaging characteristics of the common neurocutaneous diseases (NCD) described in this article will help neurologists understand the screening imaging modalities in these patients. The future of neuroimaging is geared towards developing and refining magnetic resonance imaging (MRI) sequences. The detection of tumors in NCD has greatly improved with availability of high-field strength 3T MRI machines. Neuroimaging will remain at the heart and soul of the multidisciplinary care of such complex diagnoses to guide early detection and monitor treatment. Published by Elsevier Inc.

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

Ethical and Clinical Considerations at the Intersection of Functional Neuroimaging and Disorders of Consciousness.

PubMed

Byram, Adrian C; Lee, Grace; Owen, Adrian M; Ribary, Urs; Stoessl, A Jon; Townson, Andrea; Illes, Judy

2016-10-01

Recent neuroimaging research on disorders of consciousness provides direct evidence of covert consciousness otherwise not detected clinically in a subset of severely brain-injured patients. These findings have motivated strategic development of binary communication paradigms, from which researchers interpret voluntary modulations in brain activity to glean information about patients' residual cognitive functions and emotions. The discovery of such responsiveness raises ethical and legal issues concerning the exercise of autonomy and capacity for decisionmaking on matters such as healthcare, involvement in research, and end of life. These advances have generated demands for access to the technology against a complex background of continued scientific advancement, questions about just allocation of healthcare resources, and unresolved legal issues. Interviews with professionals whose work is relevant to patients with disorders of consciousness reveal priorities concerning further basic research, legal and policy issues, and clinical considerations.

Functional Analyses and Treatment of Precursor Behavior

PubMed Central

Najdowski, Adel C; Wallace, Michele D; Ellsworth, Carrie L; MacAleese, Alicia N; Cleveland, Jackie M

2008-01-01

Functional analysis has been demonstrated to be an effective method to identify environmental variables that maintain problem behavior. However, there are cases when conducting functional analyses of severe problem behavior may be contraindicated. The current study applied functional analysis procedures to a class of behavior that preceded severe problem behavior (precursor behavior) and evaluated treatments based on the outcomes of the functional analyses of precursor behavior. Responding for all participants was differentiated during the functional analyses, and individualized treatments eliminated precursor behavior. These results suggest that functional analysis of precursor behavior may offer an alternative, indirect method to assess the operant function of severe problem behavior. PMID:18468282

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

PubMed

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

2013-01-01

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

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

[Functional neuroimaging in the study of aggressive behaviour in patients with schizophrenia].

PubMed

Garciá-Martí, Gracián; Martí-Bonmatí, Luis; Aguilar, Eduardo J; Sanz-Requena, Roberto; Alberich-Bayarri, Ángel; Bonmatí, Ana; Sanjuán, Julio

2013-02-16

Although aggressive behaviours are not always very highly prevalent in schizophrenia, their occurrence does represent a significant problem for patients and those around them. Although neuroimaging studies have made it possible to further our knowledge of the biology of these behaviours, there is still a notable degree of clinical heterogeneity in the study samples that makes it difficult to obtain conclusive results that can be compared with each other. To determine whether there are variations in the brain activity, as measured with functional magnetic resonance imaging, of a homogenous group of patients with schizophrenia and aggressive behaviour. The sample consisted of 32 patients with refractory schizophrenia and auditory hallucinations selected for the study. The subjects were submitted to a functional magnetic resonance imaging examination using an auditory paradigm with emotional stimulation, while the degree of aggressiveness was measured by means of the Brief Psychiatric Rating Scale. Significant correlations were found between functional activation and the degree of aggressiveness, which show focal hyperactivations in patients with a greater association to violent behaviours. The areas identified were located in the left hippocampus (p < 0.003, corrected) and in the right medial frontal gyrus (p < 0.004, corrected). This study determines the association between the degree of aggressiveness and certain regions in the brain that are responsible for cognitive and emotional processing in a phenotypically very homogenous group of patients with chronic auditory hallucinations and schizophrenia. This alteration of the neuronal circuits can favour loss in the processes involved in empathy and sensitivity, thus favouring the appearance of aggressive behaviours.

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.

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.

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.

Perception of affective and linguistic prosody: an ALE meta-analysis of neuroimaging studies.

PubMed

Belyk, Michel; Brown, Steven

2014-09-01

Prosody refers to the melodic and rhythmic aspects of speech. Two forms of prosody are typically distinguished: 'affective prosody' refers to the expression of emotion in speech, whereas 'linguistic prosody' relates to the intonation of sentences, including the specification of focus within sentences and stress within polysyllabic words. While these two processes are united by their use of vocal pitch modulation, they are functionally distinct. In order to examine the localization and lateralization of speech prosody in the brain, we performed two voxel-based meta-analyses of neuroimaging studies of the perception of affective and linguistic prosody. There was substantial sharing of brain activations between analyses, particularly in right-hemisphere auditory areas. However, a major point of divergence was observed in the inferior frontal gyrus: affective prosody was more likely to activate Brodmann area 47, while linguistic prosody was more likely to activate the ventral part of area 44. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Perception of affective and linguistic prosody: an ALE meta-analysis of neuroimaging studies

PubMed Central

Brown, Steven

2014-01-01

Prosody refers to the melodic and rhythmic aspects of speech. Two forms of prosody are typically distinguished: ‘affective prosody’ refers to the expression of emotion in speech, whereas ‘linguistic prosody’ relates to the intonation of sentences, including the specification of focus within sentences and stress within polysyllabic words. While these two processes are united by their use of vocal pitch modulation, they are functionally distinct. In order to examine the localization and lateralization of speech prosody in the brain, we performed two voxel-based meta-analyses of neuroimaging studies of the perception of affective and linguistic prosody. There was substantial sharing of brain activations between analyses, particularly in right-hemisphere auditory areas. However, a major point of divergence was observed in the inferior frontal gyrus: affective prosody was more likely to activate Brodmann area 47, while linguistic prosody was more likely to activate the ventral part of area 44. PMID:23934416

Neural Networks Involved in Adolescent Reward Processing: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies

PubMed Central

Silverman, Merav H.; Jedd, Kelly; Luciana, Monica

2015-01-01

Behavioral responses to, and the neural processing of, rewards change dramatically during adolescence and may contribute to observed increases in risk-taking during this developmental period. Functional MRI (fMRI) studies suggest differences between adolescents and adults in neural activation during reward processing, but findings are contradictory, and effects have been found in non-predicted directions. The current study uses an activation likelihood estimation (ALE) approach for quantitative meta-analysis of functional neuroimaging studies to: 1) confirm the network of brain regions involved in adolescents’ reward processing, 2) identify regions involved in specific stages (anticipation, outcome) and valence (positive, negative) of reward processing, and 3) identify differences in activation likelihood between adolescent and adult reward-related brain activation. Results reveal a subcortical network of brain regions involved in adolescent reward processing similar to that found in adults with major hubs including the ventral and dorsal striatum, insula, and posterior cingulate cortex (PCC). Contrast analyses find that adolescents exhibit greater likelihood of activation in the insula while processing anticipation relative to outcome and greater likelihood of activation in the putamen and amygdala during outcome relative to anticipation. While processing positive compared to negative valence, adolescents show increased likelihood for activation in the posterior cingulate cortex (PCC) and ventral striatum. Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults. Unlike adolescents, adults also activate executive control regions of the frontal and parietal lobes. These findings support hypothesized elevations in motivated activity during adolescence. PMID:26254587

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.

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…

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.

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

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

PubMed

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

2016-06-01

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

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

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.

Neuroimaging studies of cognitive remediation in schizophrenia: A systematic and critical review

PubMed Central

Penadés, Rafael; González-Rodríguez, Alexandre; Catalán, Rosa; Segura, Bàrbara; Bernardo, Miquel; Junqué, Carme

2017-01-01

AIM To examine the effects of cognitive remediation therapies on brain functioning through neuroimaging procedures in patients with schizophrenia. METHODS A systematic, computerised literature search was conducted in the PubMed/Medline and PsychInfo databases. The search was performed through February 2016 without any restrictions on language or publication date. The search was performed using the following search terms: [(“cogniti*” and “remediation” or “training” or “enhancement”) and (“fMRI” or “MRI” or “PET” or “SPECT”) and (schizophrenia or schiz*)]. The search was accompanied by a manual online search and a review of the references from each of the papers selected, and those papers fulfilling our inclusion criteria were also included. RESULTS A total of 101 studies were found, but only 18 of them fulfilled the inclusion criteria. These studies indicated that cognitive remediation improves brain activation in neuroimaging studies. The most commonly reported changes were those that involved the prefrontal and thalamic regions. Those findings are in agreement with the hypofrontality hypothesis, which proposes that frontal hypoactivation is the underlying mechanism of cognitive impairments in schizophrenia. Nonetheless, great heterogeneity among the studies was found. They presented different hypotheses, different results and different findings. The results of more recent studies interpreted cognitive recovery within broader frameworks, namely, as amelioration of the efficiency of different networks. Furthermore, advances in neuroimaging methodologies, such as the use of whole-brain analysis, tractography, graph analysis, and other sophisticated methodologies of data processing, might be conditioning the interpretation of results and generating new theoretical frameworks. Additionally, structural changes were described in both the grey and white matter, suggesting a neuroprotective effect of cognitive remediation. Cognitive

Functional neuroimaging studies of prospective memory: what have we learnt so far?

PubMed

Burgess, Paul W; Gonen-Yaacovi, Gil; Volle, Emmanuelle

2011-07-01

The complexity of the behaviour described by the term "prospective memory" meant that it was not at all clear, when the earliest studies were conducted, that this would prove a fruitful area for neuroimaging study. However, a consistent relation rapidly emerged between activation in rostral prefrontal cortex (approximating Brodmann Area 10) and performance of prospective memory paradigms. This consistency has greatly increased the accumulation of findings, since each study has offered perspectives on the previous ones. Considerable help too has come from broad agreement between functional neuroimaging findings and those from other methods (e.g. human lesion studies, electrophysiology). The result has been a quite startling degree of advance given the relatively few studies that have been conducted. These findings are summarised, along with those from other brain regions, and new directions suggested. Key points are that there is a medial-lateral dissociation within rostral PFC. Some (but not all) regions of medial rostral PFC are typically more active during performance of the ongoing task only, and lateral aspects are relatively more active during conditions involving delayed intentions. Some of these rostral PFC activations seem remarkably insensitive to the form of stimulus material presented, the nature of the ongoing task, the specifics of the intention, how easy or hard the PM cue is to detect, or the intended action is to recall. However there are other regions within rostral PFC where haemodynamic changes vary with alterations in these, and other, aspects of prospective memory paradigms. It is concluded that rostral PFC most likely plays a super-ordinate role during many stages of creating, maintaining and enacting delayed intentions, which in some cases may be linked to recent evidence showing that this brain region is involved in the control of stimulus-oriented vs. stimulus-independent attending. Other key brain regions activated during prospective

Porcupine: A visual pipeline tool for neuroimaging analysis

PubMed Central

Snoek, Lukas; Knapen, Tomas

2018-01-01

The field of neuroimaging is rapidly adopting a more reproducible approach to data acquisition and analysis. Data structures and formats are being standardised and data analyses are getting more automated. However, as data analysis becomes more complicated, researchers often have to write longer analysis scripts, spanning different tools across multiple programming languages. This makes it more difficult to share or recreate code, reducing the reproducibility of the analysis. We present a tool, Porcupine, that constructs one’s analysis visually and automatically produces analysis code. The graphical representation improves understanding of the performed analysis, while retaining the flexibility of modifying the produced code manually to custom needs. Not only does Porcupine produce the analysis code, it also creates a shareable environment for running the code in the form of a Docker image. Together, this forms a reproducible way of constructing, visualising and sharing one’s analysis. Currently, Porcupine links to Nipype functionalities, which in turn accesses most standard neuroimaging analysis tools. Our goal is to release researchers from the constraints of specific implementation details, thereby freeing them to think about novel and creative ways to solve a given problem. Porcupine improves the overview researchers have of their processing pipelines, and facilitates both the development and communication of their work. This will reduce the threshold at which less expert users can generate reusable pipelines. With Porcupine, we bridge the gap between a conceptual and an implementational level of analysis and make it easier for researchers to create reproducible and shareable science. We provide a wide range of examples and documentation, as well as installer files for all platforms on our website: https://timvanmourik.github.io/Porcupine. Porcupine is free, open source, and released under the GNU General Public License v3.0. PMID:29746461

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2013-01-01

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

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

PubMed

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

2017-01-01

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

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

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.

Right hemispheric dysfunction in a case of pure progressive aphemia: fusion of multimodal neuroimaging.

PubMed

Vitali, Paolo; Nobili, Flavio; Raiteri, Umberto; Canfora, Michela; Rosa, Marco; Calvini, Piero; Girtler, Nicola; Regesta, Giovanni; Rodriguez, Guido

2004-01-15

This article describes the unusual case of a 60-year-old woman suffering from pure progressive aphemia. The fusion of multimodal neuroimaging (MRI, perfusion SPECT) implicated the right frontal lobe, especially the inferior frontal gyrus. This area also showed the greatest functional MRI activation during the performance of a covert phonemic fluency task. Results are discussed in terms of bihemispheric language representation. The fusion of three sets of neuroimages has aided in the interpretation of the patient's cognitive brain dysfunction.

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 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

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

[How to start a neuroimaging study].

PubMed

Narumoto, Jin

2012-06-01

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

Neuroimaging studies of aggressive and violent behavior: current findings and implications for criminology and criminal justice.

PubMed

Bufkin, Jana L; Luttrell, Vickie R

2005-04-01

With the availability of new functional and structural neuroimaging techniques, researchers have begun to localize brain areas that may be dysfunctional in offenders who are aggressive and violent. Our review of 17 neuroimaging studies reveals that the areas associated with aggressive and/or violent behavioral histories, particularly impulsive acts, are located in the prefrontal cortex and the medial temporal regions. These findings are explained in the context of negative emotion regulation, and suggestions are provided concerning how such findings may affect future theoretical frameworks in criminology, crime prevention efforts, and the functioning of the criminal justice system.

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.

Differentiating Emotional Processing and Attention in Psychopathy with Functional Neuroimaging

PubMed Central

Anderson, Nathaniel E.; Steele, Vaughn R.; Maurer, J. Michael; Rao, Vikram; Koenigs, Michael R.; Decety, Jean; Kosson, David; Calhoun, Vince; Kiehl, Kent A.

2017-01-01

Psychopathic individuals are often characterized by emotional processing deficits, and recent research has examined the specific contexts and cognitive mechanisms that underlie these abnormalities. Some evidence suggests that abnormal features of attention are fundamental to psychopaths’ emotional deficits, but few studies have demonstrated the neural underpinnings responsible for such effects. Here, we use functional neuroimaging to examine attention-emotion interactions among incarcerated individuals (n=120) evaluated for psychopathic traits using the Hare Psychopathy Checklist – Revised (PCL-R). Using a task designed to manipulate attention to emotional features of visual stimuli, we demonstrate effects representing implicit emotional processing, explicit emotional processing, attention-facilitated emotional processing, and vigilance for emotional content. Results confirm the importance of considering mechanisms of attention when evaluating emotional processing differences related to psychopathic traits. The affective-interpersonal features of psychopathy (PCL-R Factor 1) were associated with relatively lower emotion-dependent augmentation of activity in visual processing areas during implicit emotional processing while antisocial-lifestyle features (PCL-R Factor 2) were associated with elevated activity in the amygdala and related salience-network regions. During explicit emotional processing psychopathic traits were associated with upregulation in the medial prefrontal cortex, insula, and superior frontal regions. Isolating the impact of explicit attention to emotional content, only Factor 1 was related to upregulation of activity in the visual processing stream, which was accompanied by increased activity in the angular gyrus. These effects highlight some important mechanisms underlying abnormal features of attention and emotional processing that accompany psychopathic traits. PMID:28092055

Differentiating emotional processing and attention in psychopathy with functional neuroimaging.

PubMed

Anderson, Nathaniel E; Steele, Vaughn R; Maurer, J Michael; Rao, Vikram; Koenigs, Michael R; Decety, Jean; Kosson, David S; Calhoun, Vince D; Kiehl, Kent A

2017-06-01

Individuals with psychopathy are often characterized by emotional processing deficits, and recent research has examined the specific contexts and cognitive mechanisms that underlie these abnormalities. Some evidence suggests that abnormal features of attention are fundamental to emotional deficits in persons with psychopathy, but few studies have demonstrated the neural underpinnings responsible for such effects. Here, we use functional neuroimaging to examine attention-emotion interactions among incarcerated individuals (n = 120) evaluated for psychopathic traits using the Hare Psychopathy Checklist-Revised (PCL-R). Using a task designed to manipulate attention to emotional features of visual stimuli, we demonstrate effects representing implicit emotional processing, explicit emotional processing, attention-facilitated emotional processing, and vigilance for emotional content. Results confirm the importance of considering mechanisms of attention when evaluating emotional processing differences related to psychopathic traits. The affective-interpersonal features of psychopathy (PCL-R Factor 1) were associated with relatively lower emotion-dependent augmentation of activity in visual processing areas during implicit emotional processing, while antisocial-lifestyle features (PCL-R Factor 2) were associated with elevated activity in the amygdala and related salience network regions. During explicit emotional processing, psychopathic traits were associated with upregulation in the medial prefrontal cortex, insula, and superior frontal regions. Isolating the impact of explicit attention to emotional content, only Factor 1 was related to upregulation of activity in the visual processing stream, which was accompanied by increased activity in the angular gyrus. These effects highlight some important mechanisms underlying abnormal features of attention and emotional processing that accompany psychopathic traits.

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 of child abuse: a critical review

PubMed Central

Hart, Heledd; Rubia, Katya

2012-01-01

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

Neuroimaging and Research into Second Language Acquisition

ERIC Educational Resources Information Center

Sabourin, Laura

2009-01-01

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

Big Data and Neuroimaging.

PubMed

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

2017-12-01

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

The 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

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).

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 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

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

PubMed

Fu, Cynthia H Y; Costafreda, Sergi G

2013-09-01

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

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).

The role of neuroimaging in the discovery of processing stages. A review.

PubMed

Mulder, G; Wijers, A A; Lange, J J; Buijink, B M; Mulder, L J; Willemsen, A T; Paans, A M

1995-11-01

In this contribution we show how neuroimaging methods can augment behavioural methods to discover processing stages. Event Related Brain Potentials (ERPs), Brain Electrical Source Analysis (BESA) and regional changes in cerebral blood flow (rCBF) do not necessarily require behavioural responses. With the aid of rCBF we are able to discover several cortical and subcortical brain systems (processors) active in selective attention and memory search tasks. BESA describes cortical activity with high temporal resolution in terms of a limited number of neural generators within these brain systems. The combination of behavioural methods and neuroimaging provides a picture of the functional architecture of the brain. The review is organized around three processors: the Visual, Cognitive and Manual Motor Processors.

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

PubMed

Pfeifer, Jennifer H; Peake, Shannon J

2012-01-01

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

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

2015-12-01

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

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.

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

Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure

PubMed Central

Raschle, Nora M.; Lee, Michelle; Buechler, Roman; Christodoulou, Joanna A.; Chang, Maria; Vakil, Monica; Stering, Patrice L.; Gaab, Nadine

2009-01-01

Within the last decade there has been an increase in the use of structural and functional magnetic resonance imaging (fMRI) to investigate the neural basis of human perception, cognition and behavior 1, 2. Moreover, this non-invasive imaging method has grown into a tool for clinicians and researchers to explore typical and atypical brain development. Although advances in neuroimaging tools and techniques are apparent, (f)MRI in young pediatric populations remains relatively infrequent 2. Practical as well as technical challenges when imaging children present clinicians and research teams with a unique set of problems 3, 2. To name just a few, the child participants are challenged by a need for motivation, alertness and cooperation. Anxiety may be an additional factor to be addressed. Researchers or clinicians need to consider time constraints, movement restriction, scanner background noise and unfamiliarity with the MR scanner environment2,4-10. A progressive use of functional and structural neuroimaging in younger age groups, however, could further add to our understanding of brain development. As an example, several research groups are currently working towards early detection of developmental disorders, potentially even before children present associated behavioral characteristics e.g.11. Various strategies and techniques have been reported as a means to ensure comfort and cooperation of young children during neuroimaging sessions. Play therapy 12, behavioral approaches 13, 14,15, 16-18 and simulation 19, the use of mock scanner areas 20,21, basic relaxation 22 and a combination of these techniques 23 have all been shown to improve the participant's compliance and thus MRI data quality. Even more importantly, these strategies have proven to increase the comfort of families and children involved 12. One of the main advances of such techniques for the clinical practice is the possibility of avoiding sedation or general anesthesia (GA) as a way to manage children

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

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

PubMed

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

2017-03-01

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

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.

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

PubMed

Doan, Lisa; Choi, Daniel; Kline, Richard

2017-10-01

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

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

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.

“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

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

Coordinate based random effect size meta-analysis of neuroimaging studies.

PubMed

Tench, C R; Tanasescu, Radu; Constantinescu, C S; Auer, D P; Cottam, W J

2017-06-01

Low power in neuroimaging studies can make them difficult to interpret, and Coordinate based meta-analysis (CBMA) may go some way to mitigating this issue. CBMA has been used in many analyses to detect where published functional MRI or voxel-based morphometry studies testing similar hypotheses report significant summary results (coordinates) consistently. Only the reported coordinates and possibly t statistics are analysed, and statistical significance of clusters is determined by coordinate density. Here a method of performing coordinate based random effect size meta-analysis and meta-regression is introduced. The algorithm (ClusterZ) analyses both coordinates and reported t statistic or Z score, standardised by the number of subjects. Statistical significance is determined not by coordinate density, but by a random effects meta-analyses of reported effects performed cluster-wise using standard statistical methods and taking account of censoring inherent in the published summary results. Type 1 error control is achieved using the false cluster discovery rate (FCDR), which is based on the false discovery rate. This controls both the family wise error rate under the null hypothesis that coordinates are randomly drawn from a standard stereotaxic space, and the proportion of significant clusters that are expected under the null. Such control is necessary to avoid propagating and even amplifying the very issues motivating the meta-analysis in the first place. ClusterZ is demonstrated on both numerically simulated data and on real data from reports of grey matter loss in multiple sclerosis (MS) and syndromes suggestive of MS, and of painful stimulus in healthy controls. The software implementation is available to download and use freely. Copyright © 2017 Elsevier Inc. All rights reserved.

Abnormal brain activation during threatening face processing in schizophrenia: A meta-analysis of functional neuroimaging studies.

PubMed

Dong, Debo; Wang, Yulin; Jia, Xiaoyan; Li, Yingjia; Chang, Xuebin; Vandekerckhove, Marie; Luo, Cheng; Yao, Dezhong

2017-11-15

Impairment of face perception in schizophrenia is a core aspect of social cognitive dysfunction. This impairment is particularly marked in threatening face processing. Identifying reliable neural correlates of the impairment of threatening face processing is crucial for targeting more effective treatments. However, neuroimaging studies have not yet obtained robust conclusions. Through comprehensive literature search, twenty-one whole brain datasets were included in this meta-analysis. Using seed-based d-Mapping, in this voxel-based meta-analysis, we aimed to: 1) establish the most consistent brain dysfunctions related to threating face processing in schizophrenia; 2) address task-type heterogeneity in this impairment; 3) explore the effect of potential demographic or clinical moderator variables on this impairment. Main meta-analysis indicated that patients with chronic schizophrenia demonstrated attenuated activations in limbic emotional system along with compensatory over-activation in medial prefrontal cortex (MPFC) during threatening faces processing. Sub-task analyses revealed under-activations in right amygdala and left fusiform gyrus in both implicit and explicit tasks. The remaining clusters were found to be differently involved in different types of tasks. Moreover, meta-regression analyses showed brain abnormalities in schizophrenia were partly modulated by age, gender, medication and severity of symptoms. Our results highlighted breakdowns in limbic-MPFC circuit in schizophrenia, suggesting general inability to coordinate and contextualize salient threat stimuli. These findings provide potential targets for neurotherapeutic and pharmacological interventions for schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Applications of Optical Neuroimaging in Usability Research

PubMed Central

Hill, Audrey P.; Bohil, Corey J.

2016-01-01

FEATURE AT A GLANCE In this article we review recent and potential applications of optical neuroimaging to human factors and usability research. We focus specifically on functional near-infrared spectroscopy (fNIRS) because of its cost-effectiveness and ease of implementation. Researchers have used fNIRS to assess a range of psychological phenomena relevant to human factors, such as cognitive workload, attention, motor activity, and more. It offers the opportunity to measure hemodynamic correlates of mental activity during task completion in human factors and usability studies. We also consider some limitations and future research directions. PMID:28286404

Brain regions involved in subprocesses of small-space episodic object-location memory: a systematic review of lesion and functional neuroimaging studies.

PubMed

Zimmermann, Kathrin; Eschen, Anne

2017-04-01

Object-location memory (OLM) enables us to keep track of the locations of objects in our environment. The neurocognitive model of OLM (Postma, A., Kessels, R. P. C., & Van Asselen, M. (2004). The neuropsychology of object-location memory. In G. L. Allen (Ed.), Human spatial memory: Remembering where (pp. 143-160). Mahwah, NJ: Lawrence Erlbaum, Postma, A., Kessels, R. P. C., & Van Asselen, M. (2008). How the brain remembers and forgets where things are: The neurocognition of object-location memory. Neuroscience & Biobehavioral Reviews, 32, 1339-1345. doi: 10.1016/j.neubiorev.2008.05.001 ) proposes that distinct brain regions are specialised for different subprocesses of OLM (object processing, location processing, and object-location binding; categorical and coordinate OLM; egocentric and allocentric OLM). It was based mainly on findings from lesion studies. However, recent episodic memory studies point to a contribution of additional or different brain regions to object and location processing within episodic OLM. To evaluate and update the neurocognitive model of OLM, we therefore conducted a systematic literature search for lesion as well as functional neuroimaging studies contrasting small-space episodic OLM with object memory or location memory. We identified 10 relevant lesion studies and 8 relevant functional neuroimaging studies. We could confirm some of the proposals of the neurocognitive model of OLM, but also differing hypotheses from episodic memory research, about which brain regions are involved in the different subprocesses of small-space episodic OLM. In addition, we were able to identify new brain regions as well as important research gaps.

Functional neuroimaging of psychotherapeutic processes in anxiety and depression: from mechanisms to predictions.

PubMed

Lueken, Ulrike; Hahn, Tim

2016-01-01

The review provides an update of functional neuroimaging studies that identify neural processes underlying psychotherapy and predict outcomes following psychotherapeutic treatment in anxiety and depressive disorders. Following current developments in this field, studies were classified as 'mechanistic' or 'predictor' studies (i.e., informing neurobiological models about putative mechanisms versus aiming to provide predictive information). Mechanistic evidence points toward a dual-process model of psychotherapy in anxiety disorders with abnormally increased limbic activation being decreased, while prefrontal activity is increased. Partly overlapping findings are reported for depression, albeit with a stronger focus on prefrontal activation following treatment. No studies directly comparing neural pathways of psychotherapy between anxiety and depression were detected. Consensus is accumulating for an overarching role of the anterior cingulate cortex in modulating treatment response across disorders. When aiming to quantify clinical utility, the need for single-subject predictions is increasingly recognized and predictions based on machine learning approaches show high translational potential. Present findings encourage the search for predictors providing clinically meaningful information for single patients. However, independent validation as a crucial prerequisite for clinical use is still needed. Identifying nonresponders a priori creates the need for alternative treatment options that can be developed based on an improved understanding of those neural mechanisms underlying effective interventions.

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

PubMed Central

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

2013-01-01

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

Neuroimaging of Human Balance Control: A Systematic Review

PubMed Central

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

2017-01-01

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

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

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

PubMed Central

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

2017-01-01

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

Multiple brain atlas database and atlas-based neuroimaging system.

PubMed

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

1997-01-01

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

Common and distinct networks underlying reward valence and processing stages: A meta-analysis of functional neuroimaging studies

PubMed Central

Liu, Xun; Hairston, Jacqueline; Schrier, Madeleine; Fan, Jin

2011-01-01

To better understand the reward circuitry in human brain, we conducted activation likelihood estimation (ALE) and parametric voxel-based meta-analyses (PVM) on 142 neuroimaging studies that examined brain activation in reward-related tasks in healthy adults. We observed several core brain areas that participated in reward-related decision making, including the nucleus accumbens (NAcc), caudate, putamen, thalamus, orbitofrontal cortex (OFC), bilateral anterior insula, anterior (ACC) and posterior (PCC) cingulate cortex, as well as cognitive control regions in the inferior parietal lobule and prefrontal cortex (PFC). The NAcc was commonly activated by both positive and negative rewards across various stages of reward processing (e.g., anticipation, outcome, and evaluation). In addition, the medial OFC and PCC preferentially responded to positive rewards, whereas the ACC, bilateral anterior insula, and lateral PFC selectively responded to negative rewards. Reward anticipation activated the ACC, bilateral anterior insula, and brain stem, whereas reward outcome more significantly activated the NAcc, medial OFC, and amygdala. Neurobiological theories of reward-related decision making should therefore distributed and interrelated representations of reward valuation and valence assessment into account. PMID:21185861

Functional Analyses and Treatment of Precursor Behavior

ERIC Educational Resources Information Center

Najdowski, Adel C.; Wallace, Michele D.; Ellsworth, Carrie L.; MacAleese, Alicia N.; Cleveland, Jackie

2008-01-01

Functional analysis has been demonstrated to be an effective method to identify environmental variables that maintain problem behavior. However, there are cases when conducting functional analyses of severe problem behavior may be contraindicated. The current study applied functional analysis procedures to a class of behavior that preceded severe…

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

PubMed

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

2018-04-26

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

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

PubMed Central

2018-01-01

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

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.

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

PubMed

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

2017-05-18

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

The 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

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).

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.

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

PubMed Central

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

2018-01-01

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

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

PubMed

Dugré, Jules R; Dumais, Alexandre; Bitar, Nathalie; Potvin, Stéphane

2018-01-01

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

The teen brain: insights from neuroimaging.

PubMed

Giedd, Jay N

2008-04-01

Few parents of a teenager are surprised to hear that the brain of a 16-year-old is different from the brain of an 8-year-old. Yet to pin down these differences in a rigorous scientific way has been elusive. Magnetic resonance imaging, with the capacity to provide exquisitely accurate quantifications of brain anatomy and physiology without the use of ionizing radiation, has launched a new era of adolescent neuroscience. Longitudinal studies of subjects from ages 3-30 years demonstrate a general pattern of childhood peaks of gray matter followed by adolescent declines, functional and structural increases in connectivity and integrative processing, and a changing balance between limbic/subcortical and frontal lobe functions, extending well into young adulthood. Although overinterpretation and premature application of neuroimaging findings for diagnostic purposes remains a risk, converging data from multiple imaging modalities is beginning to elucidate the implications of these brain changes on cognition, emotion, and behavior.

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.

The coordinate-based meta-analysis of neuroimaging data.

PubMed

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

2017-01-01

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

The coordinate-based meta-analysis of neuroimaging data

PubMed Central

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

2017-01-01

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

Application of neuroanatomical ontologies for neuroimaging data annotation.

PubMed

Turner, Jessica A; Mejino, Jose L V; Brinkley, James F; Detwiler, Landon T; Lee, Hyo Jong; Martone, Maryann E; Rubin, Daniel L

2010-01-01

The annotation of functional neuroimaging results for data sharing and re-use is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA) to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus). This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are "part of" which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a subpart of the middle frontal gyrus) to more general (how many activations were found in areas connected via a known white matter tract?). In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuroanatomical ontology is publicly available as a view of FMA at the Bioportal website. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining.

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.

Contributions of episodic retrieval and mentalizing to autobiographical thought: evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses

PubMed Central

Andrews-Hanna, Jessica R.; Saxe, Rebecca; Yarkoni, Tal

2014-01-01

A growing number of studies suggest the brain’s “default network” becomes engaged when individuals recall their personal past or simulate their future. Recent reports of heterogeneity within the network raises the possibility that these autobiographical processes are comprised of multiple component processes, each supported by distinct functional-anatomic subsystems. We previously hypothesized that a medial temporal subsystem contributes to autobiographical memory and future thought by enabling individuals to retrieve prior information and bind this information into a mental scene. Conversely, a dorsal medial subsystem was proposed to support social-reflective aspects of autobiographical thought, allowing individuals to reflect on the mental states of one’s self and others (i.e. “mentalizing”). To test these hypotheses, we first examined activity in the default network subsystems as participants performed two commonly employed tasks of episodic retrieval and mentalizing. In a subset of participants, relationships among task-evoked regions were examined at rest, in the absence of an overt task. Finally, large-scale fMRI meta-analyses were conducted to identify brain regions that most strongly predicted the presence of episodic retrieval and mentalizing, and these results were compared to meta-analyses of autobiographical tasks. Across studies, laboratory-based episodic retrieval tasks were preferentially linked to the medial temporal subsystem, while mentalizing tasks were preferentially linked to the dorsal medial subsystem. In turn, autobiographical tasks engaged aspects of both subsystems. These results suggest the default network is a heterogeneous brain system whose subsystems support distinct component processes of autobiographical thought. PMID:24486981

Contributions of episodic retrieval and mentalizing to autobiographical thought: evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses.

PubMed

Andrews-Hanna, Jessica R; Saxe, Rebecca; Yarkoni, Tal

2014-05-01

A growing number of studies suggest the brain's "default network" becomes engaged when individuals recall their personal past or simulate their future. Recent reports of heterogeneity within the network raise the possibility that these autobiographical processes comprised of multiple component processes, each supported by distinct functional-anatomic subsystems. We previously hypothesized that a medial temporal subsystem contributes to autobiographical memory and future thought by enabling individuals to retrieve prior information and bind this information into a mental scene. Conversely, a dorsal medial subsystem was proposed to support social-reflective aspects of autobiographical thought, allowing individuals to reflect on the mental states of one's self and others (i.e. "mentalizing"). To test these hypotheses, we first examined activity in the default network subsystems as participants performed two commonly employed tasks of episodic retrieval and mentalizing. In a subset of participants, relationships among task-evoked regions were examined at rest, in the absence of an overt task. Finally, large-scale fMRI meta-analyses were conducted to identify brain regions that most strongly predicted the presence of episodic retrieval and mentalizing, and these results were compared to meta-analyses of autobiographical tasks. Across studies, laboratory-based episodic retrieval tasks were preferentially linked to the medial temporal subsystem, while mentalizing tasks were preferentially linked to the dorsal medial subsystem. In turn, autobiographical tasks engaged aspects of both subsystems. These results suggest the default network is a heterogeneous brain system whose subsystems support distinct component processes of autobiographical thought. Copyright © 2014 Elsevier Inc. All rights reserved.

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

PubMed

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

2014-11-01

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

Choosing Wisely: A Neurosurgical Perspective on Neuroimaging for Headaches

PubMed Central

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

2016-01-01

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

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.

The extended fronto-striatal model of obsessive compulsive disorder: convergence from event-related potentials, neuropsychology and neuroimaging

PubMed Central

Melloni, Margherita; Urbistondo, Claudia; Sedeño, Lucas; Gelormini, Carlos; Kichic, Rafael; Ibanez, Agustin

2012-01-01

In this work, we explored convergent evidence supporting the fronto-striatal model of obsessive-compulsive disorder (FSMOCD) and the contribution of event-related potential (ERP) studies to this model. First, we considered minor modifications to the FSMOCD model based on neuroimaging and neuropsychological data. We noted the brain areas most affected in this disorder -anterior cingulate cortex (ACC), basal ganglia (BG), and orbito-frontal cortex (OFC) and their related cognitive functions, such as monitoring and inhibition. Then, we assessed the ERPs that are directly related to the FSMOCD, including the error-related negativity (ERN), N200, and P600. Several OCD studies present enhanced ERN and N2 responses during conflict tasks as well as an enhanced P600 during working memory (WM) tasks. Evidence from ERP studies (especially regarding ERN and N200 amplitude enhancement), neuroimaging and neuropsychological findings suggests abnormal activity in the OFC, ACC, and BG in OCD patients. Moreover, additional findings from these analyses suggest dorsolateral prefrontal and parietal cortex involvement, which might be related to executive function (EF) deficits. Thus, these convergent results suggest the existence of a self-monitoring imbalance involving inhibitory deficits and executive dysfunctions. OCD patients present an impaired ability to monitor, control, and inhibit intrusive thoughts, urges, feelings, and behaviors. In the current model, this imbalance is triggered by an excitatory role of the BG (associated with cognitive or motor actions without volitional control) and inhibitory activity of the OFC as well as excessive monitoring of the ACC to block excitatory impulses. This imbalance would interact with the reduced activation of the parietal-DLPC network, leading to executive dysfunction. ERP research may provide further insight regarding the temporal dynamics of action monitoring and executive functioning in OCD. PMID:23015786

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

PubMed Central

Letzen, Janelle E.; Robinson, Michael E.

2016-01-01

The default mode network (DMN) has been proposed as a biomarker for several chronic pain conditions. DMN functional connectivity (fcMRI) is typically examined during resting-state fMRI, in which participants are instructed to let thoughts wander. However, factors at the time of data collection (e.g., negative mood) that might systematically impact pain perception and its brain activity, influencing the application of the DMN as a pain biomarker, are rarely reported. The present study measured whether positive and negative moods altered DMN fcMRI patterns in chronic low back pain (CLBP) patients, specifically focusing on negative mood due to its clinical-relevance. Thirty-three participants (CLBP = 17) underwent resting-state fMRI scanning before and after sad and happy mood inductions, and rated levels of mood and pain intensity at the time of scanning. Two-way repeated measures ANOVAs were conducted on resting-state functional connectivity data. Significant group (CLBP > HC) X condition (sadness > baseline) interaction effects were identified in clusters spanning parietal operculum/postcentral gyrus, insular cortices, anterior cingulate cortex, frontal pole, and a portion of the cerebellum (pFDR < .05). However, only one significant cluster covering a portion of the cerebellum was identified examining a two-way repeated measures ANOVA for happiness > baseline (pFDR < .05). Overall, these findings suggest that DMN fcMRI is affected by negative mood in individuals with and without CLBP. It is possible that DMN fcMRI seen in chronic pain patients is related to an affective dimension of pain, which is important to consider in future neuroimaging biomarker development and implementation. PMID:27583568

Immunological and neuroimaging biomarkers of complicated grief

PubMed Central

O'Connor, Mary-Frances

2012-01-01

Complicated grief (CG) is a disorder marked by intense and persistent yearning for the deceased, in addition to other criteria. The present article reviews what is known about the immunologic and neuroimaging biomarkers of both acute grief and CG, Attachment theory and cognitive stress theory are reviewed as they pertain to bereavement, as is the biopsychosocial model of CG. Reduced immune cell function has been replicated in a variety of bereaved populations. The regional brain activation to grief cues frequently includes the dorsal anterior cingulate cortex and insula, and also the posterior cingulate cortex. Using theory to point to future research directions, we may eventually learn which biomarkers are helpful in predicting CG, and its treatment. PMID:22754286

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

PubMed Central

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

2010-01-01

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

The Extended Language Network: A Meta-Analysis of Neuroimaging Studies on Text Comprehension

PubMed Central

Ferstl, Evelyn C.; Neumann, Jane; Bogler, Carsten; von Cramon, D. Yves

2010-01-01

Language processing in context requires more than merely comprehending words and sentences. Important subprocesses are inferences for bridging successive utterances, the use of background knowledge and discourse context, and pragmatic interpretations. The functional neuroanatomy of these text comprehension processes has only recently been investigated. Although there is evidence for right-hemisphere contributions, reviews have implicated the left lateral prefrontal cortex, left temporal regions beyond Wernicke’s area, and the left dorso-medial prefrontal cortex (dmPFC) for text comprehension. To objectively confirm this extended language network and to evaluate the respective contribution of right hemisphere regions, meta-analyses of 23 neuroimaging studies are reported here. The analyses used replicator dynamics based on activation likelihood estimates. Independent of the baseline, the anterior temporal lobes (aTL) were active bilaterally. In addition, processing of coherent compared with incoherent text engaged the dmPFC and the posterior cingulate cortex. Right hemisphere activations were seen most notably in the analysis of contrasts testing specific subprocesses, such as metaphor comprehension. These results suggest task dependent contributions for the lateral PFC and the right hemisphere. Most importantly, they confirm the role of the aTL and the fronto-medial cortex for language processing in context. PMID:17557297

Impact of ontology evolution on functional analyses.

PubMed

Groß, Anika; Hartung, Michael; Prüfer, Kay; Kelso, Janet; Rahm, Erhard

2012-10-15

Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes. Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.

Can Neuroimaging Markers of Vascular Pathology Explain Cognitive Performance in Adults with Sickle Cell Anemia? A Review of the Literature

PubMed Central

Jorgensen, Dana R.; Rosano, Caterina; Novelli, Enrico M.

2017-01-01

Adults with homozygous sickle cell anemia have, on average, lower cognitive function than unaffected controls. The mechanisms underlying cognitive deterioration in this population are poorly understood, but cerebral small vessel disease (CSVD) is likely to be implicated. We conducted a systematic review using the Prisma Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of articles that included both measures of cognitive function and magnetic resonance imaging (MRI) neuroimaging markers of small vessel disease. While all five studies identified small vessel disease by MRI, only two of them found a significant relationship between structural changes and cognitive performance. Differences in methodologies and small sample sizes likely accounted for the discrepancies between the studies. We conclude that while MRI is a valuable tool to identify markers of CSVD in this population, larger studies are needed to definitely establish a link between MRI-detectable abnormalities and cognitive function in sickle cell anemia. PMID:27689914

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

PubMed

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

2011-09-01

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

Training Residential Staff to Conduct Trial-Based Functional Analyses

ERIC Educational Resources Information Center

Lambert, Joseph M.; Bloom, Sarah E.; Kunnavatana, S. Shanun; Collins, Shawnee D.; Clay, Casey J.

2013-01-01

We taught 6 supervisors of a residential service provider for adults with developmental disabilities to train 9 house managers to conduct trial-based functional analyses. Effects of the training were evaluated with a nonconcurrent multiple baseline. Results suggest that house managers can be trained to conduct trial-based functional analyses with…

Role of Ongoing, Intrinsic Activity of Neuronal Populations for Quantitative Neuroimaging of Functional Magnetic Resonance Imaging–Based Networks

PubMed Central

Herman, Peter; Sanganahalli, Basavaraju G.; Coman, Daniel; Blumenfeld, Hal; Rothman, Douglas L.

2011-01-01

Abstract A primary objective in neuroscience is to determine how neuronal populations process information within networks. In humans and animal models, functional magnetic resonance imaging (fMRI) is gaining increasing popularity for network mapping. Although neuroimaging with fMRI—conducted with or without tasks—is actively discovering new brain networks, current fMRI data analysis schemes disregard the importance of the total neuronal activity in a region. In task fMRI experiments, the baseline is differenced away to disclose areas of small evoked changes in the blood oxygenation level-dependent (BOLD) signal. In resting-state fMRI experiments, the spotlight is on regions revealed by correlations of tiny fluctuations in the baseline (or spontaneous) BOLD signal. Interpretation of fMRI-based networks is obscured further, because the BOLD signal indirectly reflects neuronal activity, and difference/correlation maps are thresholded. Since the small changes of BOLD signal typically observed in cognitive fMRI experiments represent a minimal fraction of the total energy/activity in a given area, the relevance of fMRI-based networks is uncertain, because the majority of neuronal energy/activity is ignored. Thus, another alternative for quantitative neuroimaging of fMRI-based networks is a perspective in which the activity of a neuronal population is accounted for by the demanded oxidative energy (CMRO2). In this article, we argue that network mapping can be improved by including neuronal energy/activity of both the information about baseline and small differences/fluctuations of BOLD signal. Thus, total energy/activity information can be obtained through use of calibrated fMRI to quantify differences of ΔCMRO2 and through resting-state positron emission tomography/magnetic resonance spectroscopy measurements for average CMRO2. PMID:22433047

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,…

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

PubMed Central

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

2012-01-01

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

Functional Analysis in Public Schools: A Summary of 90 Functional Analyses

ERIC Educational Resources Information Center

Mueller, Michael M.; Nkosi, Ajamu; Hine, Jeffrey F.

2011-01-01

Several review and epidemiological studies have been conducted over recent years to inform behavior analysts of functional analysis outcomes. None to date have closely examined demographic and clinical data for functional analyses conducted exclusively in public school settings. The current paper presents a data-based summary of 90 functional…

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

PubMed Central

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

2010-01-01

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

Neuroimaging: beginning to appreciate its complexities.

PubMed

Parens, Erik; Johnston, Josephine

2014-01-01

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

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

PubMed

Manley, Andrew T; Maertens, Paul M

2015-01-01

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

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

PubMed

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

2018-03-01

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

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.

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

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2017-01-15

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

How Shakespeare tempests the brain: neuroimaging insights.

PubMed

Keidel, James L; Davis, Philip M; Gonzalez-Diaz, Victorina; Martin, Clara D; Thierry, Guillaume

2013-04-01

Shakespeare made extensive use of the functional shift (FS), a rhetorical device involving a change in the grammatical status of words, e.g., using nouns as verbs. Previous work using event-related brain potentials showed how FS triggers a surprise effect inviting mental re-evaluation, seemingly independent of semantic processing. Here, we used functional magnetic resonance imaging to investigate brain activation in participants making judgements on the semantic relationship between sentences -some containing a Shakespearean FS- and subsequently presented words. Behavioural performance in the semantic decision task was high and unaffected by sentence type. However, neuroimaging results showed that sentences featuring FS elicited significant activation beyond regions classically activated by typical language tasks, including the left caudate nucleus, the right inferior frontal gyrus and the right inferior temporal gyrus. These findings show how Shakespeare's grammatical exploration forces the listener to take a more active role in integrating the meaning of what is said. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

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

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.

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

PubMed

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

2016-12-01

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

Integrating Genetic, Psychopharmacological and Neuroimaging Studies: A Converging Methods Approach to Understanding the Neurobiology of ADHD

ERIC Educational Resources Information Center

Durston, Sarah; Konrad, Kerstin

2007-01-01

This paper aims to illustrate how combining multiple approaches can inform us about the neurobiology of ADHD. Converging evidence from genetic, psychopharmacological and functional neuroimaging studies has implicated dopaminergic fronto-striatal circuitry in ADHD. However, while the observation of converging evidence from multiple vantage points…

Test-specific control conditions for functional analyses.

PubMed

Fahmie, Tara A; Iwata, Brian A; Querim, Angie C; Harper, Jill M

2013-01-01

Most functional analyses of problem behavior include a common condition (play or noncontingent reinforcement) as a control for both positive and negative reinforcement. However, test-specific conditions that control for each potential source of reinforcement may be beneficial occasionally. We compared responding during alone, ignore, play, and differential reinforcement of other behavior (DRO) control conditions for individuals whose problem behavior was maintained by positive or negative reinforcement. Results showed that all of the conditions were effective controls for problem behavior maintained by positive reinforcement; however, the DRO condition was consistently ineffective as a control for problem behavior maintained by negative reinforcement. Implications for the design of functional analyses and future research are discussed. © Society for the Experimental Analysis of Behavior.

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

PubMed Central

2018-01-01

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

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

PubMed

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

2011-01-01

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

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2011-03-01

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

Translational Immunoimaging and Neuroimaging Demonstrate Corneal Neuroimmune Crosstalk.

PubMed

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

2016-11-01

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

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.

Correlation Functions Aid Analyses Of Spectra

NASA Technical Reports Server (NTRS)

Beer, Reinhard; Norton, Robert H., Jr.

1989-01-01

New uses found for correlation functions in analyses of spectra. In approach combining elements of both pattern-recognition and traditional spectral-analysis techniques, spectral lines identified in data appear useless at first glance because they are dominated by noise. New approach particularly useful in measurement of concentrations of rare species of molecules in atmosphere.

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.

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

PubMed Central

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

2014-01-01

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

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 Data Sharing on the Neuroinformatics Database Platform

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-12-01

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

Pretherapeutic functional neuroimaging predicts tremor arrest after thalamotomy.

PubMed

Tuleasca, C; Najdenovska, E; Régis, J; Witjas, T; Girard, N; Champoudry, J; Faouzi, M; Thiran, J-P; Bach Cuadra, M; Levivier, M; Van De Ville, D

2018-05-01

Essential tremor (ET) represents the most common movement disorder. Drug-resistant ET can benefit from standard stereotactic procedures (deep brain stimulation or radiofrequency thalamotomy) or alternatively minimally invasive high-focused ultrasound or radiosurgery. All aim at same target, thalamic ventro-intermediate nucleus (Vim). The study included a cohort of 17 consecutive patients, with ET, treated only with left unilateral stereotactic radiosurgical thalamotomy (SRS-T) between September 2014 and August 2015. The mean time to tremor improvement was 3.32 months (SD 2.7, 0.5-10). Neuroimaging data were collected at baseline (n = 17). Standard tremor scores, including activities of daily living (ADL) and tremor score on treated hand (TSTH), were completed pretherapeutically and 1 year later. We further correlate these scores with baseline inter-connectivity in twenty major large-scale brain networks. We report as predictive three networks, with the interconnected statistically significant clusters: primary motor cortex interconnected with inferior olivary nucleus, bilateral thalamus interconnected with motor cerebellum lobule V 2 (ADL), and anterior default-mode network interconnected with Brodmann area 10 3 (TSTH). For all, more positive pretherapeutic interconnectivity correlated with higher drop in points on the respective scores. Age, disease duration, or time-to-response after SRS-T were not statistically correlated with pretherapeutic brain connectivity measures (P > .05). The same applied to pretherapeutic tremor scores, after using the same methodology described above. Our findings have clinical implications for predicting clinical response after SRS-T. Here, using pretherapeutic magnetic resonance imaging and data processing without prior hypothesis, we show that pretherapeutic network(s) interconnectivity strength predicts tremor arrest in drug-naïve ET, following stereotactic radiosurgical thalamotomy. © 2018 John Wiley & Sons A/S. Published

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

PubMed

Sander, Tilmann H; Zhou, Bin

2016-09-01

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

Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis

PubMed Central

2011-01-01

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

Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis.

PubMed

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

2011-01-25

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

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.

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave.

PubMed

Oosterhof, Nikolaas N; Connolly, Andrew C; Haxby, James V

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. Co

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave

PubMed Central

Oosterhof, Nikolaas N.; Connolly, Andrew C.; Haxby, James V.

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. Co

Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

PubMed Central

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

2014-01-01

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

Brain basis of early parent–infant interactions: psychology, physiology, and in vivo functional neuroimaging studies

PubMed Central

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

2015-01-01

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 functional magnetic resonance imaging (fMRI) brain imaging experiments of parents. We begin with a discussion of background, perspectives and caveats for considering the neurobiology of parent–infant relationships. Then, we discuss aspects of the psychology of parenting that are significantly motivating some of the more basic neuroscience research. Following that, we discuss some of the neurohormones that are important for the regulation of social bonding, and the dysregulation of parenting with cocaine abuse. Then, we review the brain circuitry underlying parenting, proceeding from relevant rodent and nonhuman primate research to human work. Finally, we focus on a study-by-study review of functional neuroimaging studies in humans. Taken together, this research suggests that networks of highly conserved hypothalamic–midbrain–limbic–paralimbic–cortical circuits act in concert to support aspects of parent response to infants, including the emotion, attention, motivation, empathy, decision-making and other thinking that are required to navigate the complexities of parenting. Specifically, infant stimuli activate basal forebrain regions, which regulate brain circuits that handle specific nurturing and caregiving responses and activate the brain’s more general circuitry for handling emotions, motivation, attention, and empathy – all of which are crucial for effective parenting. We argue that an integrated understanding of the brain basis of parenting has profound implications for mental health. PMID:17355399

Neural correlates of the LSD experience revealed by multimodal neuroimaging.

PubMed

Carhart-Harris, Robin L; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T; Williams, Tim M; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I; Nichols, David; Hellyer, Peter J; Hobden, Peter; Evans, John; Singh, Krish D; Wise, Richard G; Curran, H Valerie; Feilding, Amanda; Nutt, David J

2016-04-26

Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD's marked effects on the visual cortex did not significantly correlate with the drug's other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of "ego-dissolution" and "altered meaning," implying the importance of this particular circuit for the maintenance of "self" or "ego" and its processing of "meaning." Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others.

Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data.

PubMed

Drakesmith, M; Caeyenberghs, K; Dutt, A; Lewis, G; David, A S; Jones, D K

2015-09-01

Graph theory (GT) is a powerful framework for quantifying topological features of neuroimaging-derived functional and structural networks. However, false positive (FP) connections arise frequently and influence the inferred topology of networks. Thresholding is often used to overcome this problem, but an appropriate threshold often relies on a priori assumptions, which will alter inferred network topologies. Four common network metrics (global efficiency, mean clustering coefficient, mean betweenness and smallworldness) were tested using a model tractography dataset. It was found that all four network metrics were significantly affected even by just one FP. Results also show that thresholding effectively dampens the impact of FPs, but at the expense of adding significant bias to network metrics. In a larger number (n=248) of tractography datasets, statistics were computed across random group permutations for a range of thresholds, revealing that statistics for network metrics varied significantly more than for non-network metrics (i.e., number of streamlines and number of edges). Varying degrees of network atrophy were introduced artificially to half the datasets, to test sensitivity to genuine group differences. For some network metrics, this atrophy was detected as significant (p<0.05, determined using permutation testing) only across a limited range of thresholds. We propose a multi-threshold permutation correction (MTPC) method, based on the cluster-enhanced permutation correction approach, to identify sustained significant effects across clusters of thresholds. This approach minimises requirements to determine a single threshold a priori. We demonstrate improved sensitivity of MTPC-corrected metrics to genuine group effects compared to an existing approach and demonstrate the use of MTPC on a previously published network analysis of tractography data derived from a clinical population. In conclusion, we show that there are large biases and instability induced

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

Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers

PubMed Central

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

2010-01-01

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

Neuroimaging classification of progression patterns in glioblastoma: a systematic review.

PubMed

Piper, Rory J; Senthil, Keerthi K; Yan, Jiun-Lin; Price, Stephen J

2018-03-30

Our primary objective was to report the current neuroimaging classification systems of spatial patterns of progression in glioblastoma. In addition, we aimed to report the terminology used to describe 'progression' and to assess the compliance with the Response Assessment in Neuro-Oncology (RANO) Criteria. We conducted a systematic review to identify all neuroimaging studies of glioblastoma that have employed a categorical classification system of spatial progression patterns. Our review was registered with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) registry. From the included 157 results, we identified 129 studies that used labels of spatial progression patterns that were not based on radiation volumes (Group 1) and 50 studies that used labels that were based on radiation volumes (Group 2). In Group 1, we found 113 individual labels and the most frequent were: local/localised (58%), distant/distal (51%), diffuse (20%), multifocal (15%) and subependymal/subventricular zone (15%). We identified 13 different labels used to refer to 'progression', of which the most frequent were 'recurrence' (99%) and 'progression' (92%). We identified that 37% (n = 33/90) of the studies published following the release of the RANO classification were adherent compliant with the RANO criteria. Our review reports significant heterogeneity in the published systems used to classify glioblastoma spatial progression patterns. Standardization of terminology and classification systems used in studying progression would increase the efficiency of our research in our attempts to more successfully treat glioblastoma.

Robust regression for large-scale neuroimaging studies.

PubMed

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

2015-05-01

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

Testosterone in the brain: neuroimaging findings and the potential role for neuropsychopharmacology.

PubMed

Höfer, Peter; Lanzenberger, Rupert; Kasper, Siegfried

2013-02-01

Testosterone plays a substantial role in a number of physiological processes in the brain. It is able to modulate the expression of certain genes by binding to androgen receptors. Acting via neurotransmitter receptors, testosterone shows the potential to mediate a non-genomic so-called "neuroactive effect". Various neurotransmitter systems are also influenced by the aromatized form of testosterone, estradiol. The following article summarizes the findings of preclinical and clinical neuroimaging studies including structural and functional magnetic resonance imaging (MRI/fMRI), voxel based morphometry (VBM), as well as pharmacological fMRI (phfMRI) and positron emission tomography (PET) regarding the effects of testosterone on the human brain. The impact of testosterone on the pathogenesis of psychiatric disorders and on sex-related prevalence differences have been supported by a wide range of clinical studies. An antidepressant effect of testosterone can be implicitly explained by its effects on the limbic system--especially amygdala, a major target in the treatment of depression--solidly demonstrated by a large body of neuroimaging findings. Copyright © 2012 Elsevier B.V. and ECNP. 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

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

PubMed

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

2007-01-01

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

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

PubMed Central

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

2011-01-01

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

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

Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms

PubMed Central

Joshi, Alark; Scheinost, Dustin; Okuda, Hirohito; Belhachemi, Dominique; Murphy, Isabella; Staib, Lawrence H.; Papademetris, Xenophon

2011-01-01

Developing both graphical and command-line user interfaces for neuroimaging algorithms requires considerable effort. Neuroimaging algorithms can meet their potential only if they can be easily and frequently used by their intended users. Deployment of a large suite of such algorithms on multiple platforms requires consistency of user interface controls, consistent results across various platforms and thorough testing. We present the design and implementation of a novel object-oriented framework that allows for rapid development of complex image analysis algorithms with many reusable components and the ability to easily add graphical user interface controls. Our framework also allows for simplified yet robust nightly testing of the algorithms to ensure stability and cross platform interoperability. All of the functionality is encapsulated into a software object requiring no separate source code for user interfaces, testing or deployment. This formulation makes our framework ideal for developing novel, stable and easy-to-use algorithms for medical image analysis and computer assisted interventions. The framework has been both deployed at Yale and released for public use in the open source multi-platform image analysis software—BioImage Suite (bioimagesuite.org). PMID:21249532

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.

A simple tool for neuroimaging data sharing

PubMed Central

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

2014-01-01

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

A multimodal neuroimaging study of a case of crossed nonfluent/agrammatic primary progressive aphasia.

PubMed

Spinelli, Edoardo G; Caso, Francesca; Agosta, Federica; Gambina, Giuseppe; Magnani, Giuseppe; Canu, Elisa; Blasi, Valeria; Perani, Daniela; Comi, Giancarlo; Falini, Andrea; Gorno-Tempini, Maria Luisa; Filippi, Massimo

2015-10-01

Crossed aphasia has been reported mainly as post-stroke aphasia resulting from brain damage ipsilateral to the dominant right hand. Here, we described a case of a crossed nonfluent/agrammatic primary progressive aphasia (nfvPPA), who developed a corticobasal syndrome (CBS). We collected clinical, cognitive, and neuroimaging data for four consecutive years from a 55-year-old right-handed lady (JV) presenting with speech disturbances. 18-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) and DaT-scan with (123)I-Ioflupane were obtained. Functional MRI (fMRI) during a verb naming task was acquired to characterize patterns of language lateralization. Diffusion tensor MRI was used to evaluate white matter damage within the language network. At onset, JV presented with prominent speech output impairment and right frontal atrophy. After 3 years, language deficits worsened, with the occurrence of a mild agrammatism. The patient also developed a left-sided mild extrapyramidal bradykinetic-rigid syndrome. The clinical picture was suggestive of nfvPPA with mild left-sided extrapyramidal syndrome. At this time, voxel-wise SPM analyses of (18)F-FDG PET and structural MRI showed right greater than left frontal hypometabolism and damage, which included the Broca's area. DaT-scan showed a reduced uptake in the right striatum. FMRI during naming task demonstrated bilateral language activations, and tractography showed right superior longitudinal fasciculus (SLF) involvement. Over the following year, JV became mute and developed frank left-sided motor signs and symptoms, evolving into a CBS clinical picture. Brain atrophy worsened in frontal areas bilaterally, and extended to temporo-parietal regions, still with a right-sided asymmetry. Tractography showed an extension of damage to the left SLF and right inferior longitudinal fasciculus. We report a case of crossed nfvPPA followed longitudinally and studied with advanced neuroimaging techniques. The results highlight a

Computational principles of syntax in the regions specialized for language: integrating theoretical linguistics and functional neuroimaging

PubMed Central

Ohta, Shinri; Fukui, Naoki; Sakai, Kuniyoshi L.

2013-01-01

The nature of computational principles of syntax remains to be elucidated. One promising approach to this problem would be to construct formal and abstract linguistic models that parametrically predict the activation modulations in the regions specialized for linguistic processes. In this article, we review recent advances in theoretical linguistics and functional neuroimaging in the following respects. First, we introduce the two fundamental linguistic operations: Merge (which combines two words or phrases to form a larger structure) and Search (which searches and establishes a syntactic relation of two words or phrases). We also illustrate certain universal properties of human language, and present hypotheses regarding how sentence structures are processed in the brain. Hypothesis I is that the Degree of Merger (DoM), i.e., the maximum depth of merged subtrees within a given domain, is a key computational concept to properly measure the complexity of tree structures. Hypothesis II is that the basic frame of the syntactic structure of a given linguistic expression is determined essentially by functional elements, which trigger Merge and Search. We then present our recent functional magnetic resonance imaging experiment, demonstrating that the DoM is indeed a key syntactic factor that accounts for syntax-selective activations in the left inferior frontal gyrus and supramarginal gyrus. Hypothesis III is that the DoM domain changes dynamically in accordance with iterative Merge applications, the Search distances, and/or task requirements. We confirm that the DoM accounts for activations in various sentence types. Hypothesis III successfully explains activation differences between object- and subject-relative clauses, as well as activations during explicit syntactic judgment tasks. A future research on the computational principles of syntax will further deepen our understanding of uniquely human mental faculties. PMID:24385957

Computational principles of syntax in the regions specialized for language: integrating theoretical linguistics and functional neuroimaging.

PubMed

Ohta, Shinri; Fukui, Naoki; Sakai, Kuniyoshi L

2013-01-01

The nature of computational principles of syntax remains to be elucidated. One promising approach to this problem would be to construct formal and abstract linguistic models that parametrically predict the activation modulations in the regions specialized for linguistic processes. In this article, we review recent advances in theoretical linguistics and functional neuroimaging in the following respects. First, we introduce the two fundamental linguistic operations: Merge (which combines two words or phrases to form a larger structure) and Search (which searches and establishes a syntactic relation of two words or phrases). We also illustrate certain universal properties of human language, and present hypotheses regarding how sentence structures are processed in the brain. Hypothesis I is that the Degree of Merger (DoM), i.e., the maximum depth of merged subtrees within a given domain, is a key computational concept to properly measure the complexity of tree structures. Hypothesis II is that the basic frame of the syntactic structure of a given linguistic expression is determined essentially by functional elements, which trigger Merge and Search. We then present our recent functional magnetic resonance imaging experiment, demonstrating that the DoM is indeed a key syntactic factor that accounts for syntax-selective activations in the left inferior frontal gyrus and supramarginal gyrus. Hypothesis III is that the DoM domain changes dynamically in accordance with iterative Merge applications, the Search distances, and/or task requirements. We confirm that the DoM accounts for activations in various sentence types. Hypothesis III successfully explains activation differences between object- and subject-relative clauses, as well as activations during explicit syntactic judgment tasks. A future research on the computational principles of syntax will further deepen our understanding of uniquely human mental faculties.

Neuroimaging and Fetal Alcohol Spectrum Disorders

ERIC Educational Resources Information Center

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

2009-01-01

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

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

Alterations in emotion generation and regulation neurocircuitry in depression and eating disorders: A comparative review of structural and functional neuroimaging studies.

PubMed

Donofry, Shannon D; Roecklein, Kathryn A; Wildes, Jennifer E; Miller, Megan A; Erickson, Kirk I

2016-09-01

Major depression and eating disorders (EDs) are highly co-morbid and may share liability. Impaired emotion regulation may represent a common etiological or maintaining mechanism. Research has demonstrated that depressed individuals and individuals with EDs exhibit impaired emotion regulation, with these impairments being associated with changes in brain structure and function. The goal of this review was to evaluate findings from neuroimaging studies of depression and EDs to determine whether there are overlapping alterations in the brain regions known to be involved in emotion regulation, evidence of which would aid in the diagnosis and treatment of these conditions. Our review of the literature suggests that depression and EDs exhibit common structural and functional alterations in brain regions involved in emotion regulation, including the amygdala, ventral striatum and nucleus accumbens, anterior cingulate cortex, insula, and dorsolateral prefrontal cortex. We present preliminary support for a shared etiological mechanism. Future studies should consider manipulating emotion regulation in a sample of individuals with depression and EDs to better characterize abnormalities in these brain circuits. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-02-01

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

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

PubMed Central

Wiłkość, Monika; Izdebski, Paweł; Żurawski, Bogdan

2017-01-01

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

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

PubMed

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

2012-09-01

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

Incidental Findings in Neuroimaging: Ethical and Medicolegal Considerations

PubMed Central

Leung, Lawrence

2013-01-01

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

Incidental Findings in Neuroimaging: Ethical and Medicolegal Considerations.

PubMed

Leung, Lawrence

2013-01-01

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

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-12-27

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

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

PubMed

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

2015-08-15

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

An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex

PubMed Central

Van Essen, David C.; Drury, Heather A.; Dickson, James; Harwell, John; Hanlon, Donna; Anderson, Charles H.

2001-01-01

The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database. PMID:11522765

An integrated software suite for surface-based analyses of cerebral cortex.

PubMed

Van Essen, D C; Drury, H A; Dickson, J; Harwell, J; Hanlon, D; Anderson, C H

2001-01-01

The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.

An integrated software suite for surface-based analyses of cerebral cortex

NASA Technical Reports Server (NTRS)

Van Essen, D. C.; Drury, H. A.; Dickson, J.; Harwell, J.; Hanlon, D.; Anderson, C. H.

2001-01-01

The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.

Neural correlates of the LSD experience revealed by multimodal neuroimaging

PubMed Central

Carhart-Harris, Robin L.; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E.; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T.; Williams, Tim M.; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I.; Nichols, David; Hobden, Peter; Evans, John; Singh, Krish D.; Wise, Richard G.; Curran, H. Valerie; Feilding, Amanda; Nutt, David J.

2016-01-01

Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD’s marked effects on the visual cortex did not significantly correlate with the drug’s other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of “ego-dissolution” and “altered meaning,” implying the importance of this particular circuit for the maintenance of “self” or “ego” and its processing of “meaning.” Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others. PMID:27071089

Progressing From Initially Ambiguous Functional Analyses: Three Case Examples

PubMed Central

Tiger, Jeffrey H.; Fisher, Wayne W.; Toussaint, Karen A.; Kodak, Tiffany

2009-01-01

Most often functional analyses are initiated using a standard set of test conditions, similar to those described by Iwata, Dorsey, Slifer, Bauman, and Richman (1982/1994). These test conditions involve the careful manipulation of motivating operations, discriminative stimuli, and reinforcement contingencies to determine the events related to the occurrence and maintenance of problem behavior. Some individuals display problem behavior that is occasioned and reinforced by idiosyncratic or otherwise unique combinations of environmental antecedents and consequences of behavior, which are unlikely to be detected using these standard assessment conditions. For these individuals, modifications to the standard test conditions or the inclusion of novel test conditions may result in clearer assessment outcomes. The current study provides three case examples of individuals whose functional analyses were initially undifferentiated; however, modifications to the standard conditions resulted in the identification of behavioral functions and the implementation of effective function-based treatments. PMID:19233611

Neuroimaging Studies Illustrate the Commonalities Between Ageing and Brain Diseases.

PubMed

Cole, James H

2018-07-01

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

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

PubMed

Goldstein, Rita Z; Volkow, Nora D

2011-10-20

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

High-throughput neuroimaging-genetics computational infrastructure

PubMed Central

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

2014-01-01

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

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.

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

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.

Dreaming as mind wandering: evidence from functional neuroimaging and first-person content reports.

PubMed

Fox, Kieran C R; Nijeboer, Savannah; Solomonova, Elizaveta; Domhoff, G William; Christoff, Kalina

2013-01-01

Isolated reports have long suggested a similarity in content and thought processes across mind wandering (MW) during waking, and dream mentation during sleep. This overlap has encouraged speculation that both "daydreaming" and dreaming may engage similar brain mechanisms. To explore this possibility, we systematically examined published first-person experiential reports of MW and dreaming and found many similarities: in both states, content is largely audiovisual and emotional, follows loose narratives tinged with fantasy, is strongly related to current concerns, draws on long-term memory, and simulates social interactions. Both states are also characterized by a relative lack of meta-awareness. To relate first-person reports to neural evidence, we compared meta-analytic data from numerous functional neuroimaging (PET, fMRI) studies of the default mode network (DMN, with high chances of MW) and rapid eye movement (REM) sleep (with high chances of dreaming). Our findings show large overlaps in activation patterns of cortical regions: similar to MW/DMN activity, dreaming and REM sleep activate regions implicated in self-referential thought and memory, including medial prefrontal cortex (PFC), medial temporal lobe structures, and posterior cingulate. Conversely, in REM sleep numerous PFC executive regions are deactivated, even beyond levels seen during waking MW. We argue that dreaming can be understood as an "intensified" version of waking MW: though the two share many similarities, dreams tend to be longer, more visual and immersive, and to more strongly recruit numerous key hubs of the DMN. Further, whereas MW recruits fewer PFC regions than goal-directed thought, dreaming appears to be characterized by an even deeper quiescence of PFC regions involved in cognitive control and metacognition, with a corresponding lack of insight and meta-awareness. We suggest, then, that dreaming amplifies the same features that distinguish MW from goal-directed waking thought.

Dreaming as mind wandering: evidence from functional neuroimaging and first-person content reports

PubMed Central

Fox, Kieran C. R.; Nijeboer, Savannah; Solomonova, Elizaveta; Domhoff, G. William; Christoff, Kalina

2013-01-01

Isolated reports have long suggested a similarity in content and thought processes across mind wandering (MW) during waking, and dream mentation during sleep. This overlap has encouraged speculation that both “daydreaming” and dreaming may engage similar brain mechanisms. To explore this possibility, we systematically examined published first-person experiential reports of MW and dreaming and found many similarities: in both states, content is largely audiovisual and emotional, follows loose narratives tinged with fantasy, is strongly related to current concerns, draws on long-term memory, and simulates social interactions. Both states are also characterized by a relative lack of meta-awareness. To relate first-person reports to neural evidence, we compared meta-analytic data from numerous functional neuroimaging (PET, fMRI) studies of the default mode network (DMN, with high chances of MW) and rapid eye movement (REM) sleep (with high chances of dreaming). Our findings show large overlaps in activation patterns of cortical regions: similar to MW/DMN activity, dreaming and REM sleep activate regions implicated in self-referential thought and memory, including medial prefrontal cortex (PFC), medial temporal lobe structures, and posterior cingulate. Conversely, in REM sleep numerous PFC executive regions are deactivated, even beyond levels seen during waking MW. We argue that dreaming can be understood as an “intensified” version of waking MW: though the two share many similarities, dreams tend to be longer, more visual and immersive, and to more strongly recruit numerous key hubs of the DMN. Further, whereas MW recruits fewer PFC regions than goal-directed thought, dreaming appears to be characterized by an even deeper quiescence of PFC regions involved in cognitive control and metacognition, with a corresponding lack of insight and meta-awareness. We suggest, then, that dreaming amplifies the same features that distinguish MW from goal-directed waking

Long-term cognitive function, neuroimaging, and quality of life in primary CNS lymphoma.

PubMed

Doolittle, Nancy D; Korfel, Agnieszka; Lubow, Meredith A; Schorb, Elisabeth; Schlegel, Uwe; Rogowski, Sabine; Fu, Rongwei; Dósa, Edit; Illerhaus, Gerald; Kraemer, Dale F; Muldoon, Leslie L; Calabrese, Pasquale; Hedrick, Nancy; Tyson, Rose Marie; Jahnke, Kristoph; Maron, Leeza M; Butler, Robert W; Neuwelt, Edward A

2013-07-02

To describe and correlate neurotoxicity indicators in long-term primary CNS lymphoma (PCNSL) survivors who were treated with high-dose methotrexate-based regimens with or without whole-brain radiotherapy (WBRT). Eighty PCNSL survivors from 4 treatment groups (1 with WBRT and 3 without WBRT) who were a minimum of 2 years after diagnosis and in complete remission underwent prospective neuropsychological, quality-of-life (QOL), and brain MRI evaluation. Clinical characteristics were compared among treatments by using the χ(2) test and analysis of variance. The association among neuroimaging, neuropsychological, and QOL outcomes was assessed by using the Pearson correlation coefficient. The median interval from diagnosis to evaluation was 5.5 years (minimum, 2 years; maximum, 26 years). Survivors treated with WBRT had lower mean scores in attention/executive function (p = 0.0011), motor skills (p = 0.0023), and neuropsychological composite score (p = 0.0051) compared with those treated without WBRT. Verbal memory was better in survivors with longer intervals from diagnosis to evaluation (p = 0.0045). On brain imaging, mean areas of total T2 abnormalities were different among treatments (p = 0.0006). Total T2 abnormalities after WBRT were more than twice the mean of any non-WBRT group and were associated with poorer neuropsychological and QOL outcomes. Our results suggest that in patients treated for PCNSL achieving complete remission and surviving at least 2 years, the addition of WBRT to methotrexate-based chemotherapy increases the risk of treatment-related neurotoxicity. Verbal memory may improve over time. This study provides Class III evidence that in patients treated for PCNSL achieving complete remission and surviving at least 2 years, the addition of WBRT to methotrexate-based chemotherapy increases the risk of treatment-related neurotoxicity.

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.

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

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

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

PubMed Central

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

2015-01-01

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

Cross-validation and hypothesis testing in neuroimaging: An irenic comment on the exchange between Friston and Lindquist et al.

PubMed

Reiss, Philip T

2015-08-01

The "ten ironic rules for statistical reviewers" presented by Friston (2012) prompted a rebuttal by Lindquist et al. (2013), which was followed by a rejoinder by Friston (2013). A key issue left unresolved in this discussion is the use of cross-validation to test the significance of predictive analyses. This note discusses the role that cross-validation-based and related hypothesis tests have come to play in modern data analyses, in neuroimaging and other fields. It is shown that such tests need not be suboptimal and can fill otherwise-unmet inferential needs. Copyright © 2015 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Minati, Ludovico

2006-06-01

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

Statistical Challenges in "Big Data" Human Neuroimaging.

PubMed

Smith, Stephen M; Nichols, Thomas E

2018-01-17

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

Progressing from initially ambiguous functional analyses: three case examples.

PubMed

Tiger, Jeffrey H; Fisher, Wayne W; Toussaint, Karen A; Kodak, Tiffany

2009-01-01

Most often functional analyses are initiated using a standard set of test conditions, similar to those described by Iwata, Dorsey, Slifer, Bauman, and Richman [Iwata, B. A., Dorsey, M. F., Slifer, K. J., Bauman, K. E., & Richman, G. S. (1994). Toward a functional analysis of self-injury. Journal of Applied Behavior Analysis, 27, 197-209 (Reprinted from Analysis and Intervention in Developmental Disabilities, 2, 3-20, 1982)]. These test conditions involve the careful manipulation of motivating operations, discriminative stimuli, and reinforcement contingencies to determine the events related to the occurrence and maintenance of problem behavior. Some individuals display problem behavior that is occasioned and reinforced by idiosyncratic or otherwise unique combinations of environmental antecedents and consequences of behavior, which are unlikely to be detected using these standard assessment conditions. For these individuals, modifications to the standard test conditions or the inclusion of novel test conditions may result in clearer assessment outcomes. The current study provides three case examples of individuals whose functional analyses were initially undifferentiated; however, modifications to the standard conditions resulted in the identification of behavioral functions and the implementation of effective function-based treatments.

The experience of art: insights from neuroimaging.

PubMed

Nadal, Marcos

2013-01-01

The experience of art is a complex one. It emerges from the interaction of multiple cognitive and affective processes. Neuropsychological and neuroimaging studies are revealing the broadly distributed network of brain regions upon which it relies. This network can be divided into three functional components: (i) prefrontal, parietal, and temporal cortical regions support evaluative judgment, attentional processing, and memory retrieval; (ii) the reward circuit, including cortical, subcortical regions, and some of its regulators, is involved in the generation of pleasurable feelings and emotions, and the valuation and anticipation of reward; and (iii) attentional modulation of activity in low-, mid-, and high-level cortical sensory regions enhances the perceptual processing of certain features, relations, locations, or objects. Understanding how these regions act in concert to produce unique and moving art experiences and determining the impact of personal and cultural meaning and context on this network the biological foundation of the experience of art--remain future challenges. © 2013 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2017-01-01

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

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

PubMed Central

Goldstein, Rita Z.; Volkow, Nora D.

2012-01-01

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

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

PubMed

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

2017-03-01

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

Connectivity and functional profiling of abnormal brain structures in pedophilia

PubMed Central

Poeppl, Timm B.; Eickhoff, Simon B.; Fox, Peter T.; Laird, Angela R.; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

2015-01-01

Despite its 0.5–1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multi-modal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. PMID:25733379

Connectivity and functional profiling of abnormal brain structures in pedophilia.

PubMed

Poeppl, Timm B; Eickhoff, Simon B; Fox, Peter T; Laird, Angela R; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

2015-06-01

Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. © 2015 Wiley Periodicals, Inc.

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

PubMed

Nakao, Tomohiro; Okada, Kayo; Kanba, Shigenobu

2014-08-01

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

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

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

PubMed

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

2017-01-01

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

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

PubMed

Nowinski, Wieslaw L; Belov, Dmitry

2003-09-01

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

Effects of computerized cognitive training on neuroimaging outcomes in older adults: a systematic review.

PubMed

Ten Brinke, Lisanne F; Davis, Jennifer C; Barha, Cindy K; Liu-Ambrose, Teresa

2017-07-10

Worldwide, the population is aging and the number of individuals diagnosed with dementia is rising rapidly. Currently, there are no effective pharmaceutical cures. Hence, identifying lifestyle approaches that may prevent, delay, or treat cognitive impairment and dementia in older adults is becoming increasingly important. Computerized Cognitive Training (CCT) is a promising strategy to combat cognitive decline. Yet, the underlying mechanisms of the effect of CCT on cognition remain poorly understood. Hence, the primary objective of this systematic review was to examine peer-reviewed literature ascertaining the effect of CCT on both structural and functional neuroimaging measures among older adults to gain insight into the underlying mechanisms by which CCT may benefit cognitive function. In accordance with PRISMA guidelines, we used the following databases: MEDLINE, EMBASE, and CINAHL. Two independent reviewers abstracted data using pre-defined terms. These included: main study characteristics such as the type of training (i.e., single- versus multi-domain), participant demographics (age ≥ 50 years; no psychiatric conditions), and the inclusion of neuroimaging outcomes. The Physiotherapy Evidence Database (PEDro) scale was used to assess quality of all studies included in this systematic review. Nine studies were included in this systematic review, with four studies including multiple MRI sequences. Results of this systematic review are mixed: CCT was found to increase and decrease both brain structure and function in older adults. In addition, depending on region of interest, both increases and decreases in structure and function were associated with behavioural performance. Of all studies included in this systematic review, results from the highest quality studies, which were two randomized controlled trials, demonstrated that multi-domain CCT could lead to increases in hippocampal functional connectivity. Further high quality studies that include an active

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

PubMed

Zarzeczny, Amy; Caulfield, Timothy

2012-01-01

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

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.

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

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

Culture-sensitive neural substrates of human cognition: a transcultural neuroimaging approach.

PubMed

Han, Shihui; Northoff, Georg

2008-08-01

Our brains and minds are shaped by our experiences, which mainly occur in the context of the culture in which we develop and live. Although psychologists have provided abundant evidence for diversity of human cognition and behaviour across cultures, the question of whether the neural correlates of human cognition are also culture-dependent is often not considered by neuroscientists. However, recent transcultural neuroimaging studies have demonstrated that one's cultural background can influence the neural activity that underlies both high- and low-level cognitive functions. The findings provide a novel approach by which to distinguish culture-sensitive from culture-invariant neural mechanisms of human cognition.

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

PubMed

Toga, Arthur W

2012-02-01

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

Validating Trial-Based Functional Analyses in Mainstream Primary School Classrooms

ERIC Educational Resources Information Center

Austin, Jennifer L.; Groves, Emily A.; Reynish, Lisa C.; Francis, Laura L.

2015-01-01

There is growing evidence to support the use of trial-based functional analyses, particularly in classroom settings. However, there currently are no evaluations of this procedure with typically developing children. Furthermore, it is possible that refinements may be needed to adapt trial-based analyses to mainstream classrooms. This study was…

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

PubMed

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

2014-02-15

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

Cognitive Impairment Precedes and Predicts Functional Impairment in Mild Alzheimer's Disease.

PubMed

Liu-Seifert, Hong; Siemers, Eric; Price, Karen; Han, Baoguang; Selzler, Katherine J; Henley, David; Sundell, Karen; Aisen, Paul; Cummings, Jeffrey; Raskin, Joel; Mohs, Richard

2015-01-01

The temporal relationship of cognitive deficit and functional impairment in Alzheimer's disease (AD) is not well characterized. Recent analyses suggest cognitive decline predicts subsequent functional decline throughout AD progression. To better understand the relationship between cognitive and functional decline in mild AD using autoregressive cross-lagged (ARCL) panel analyses in several clinical trials. Data included placebo patients with mild AD pooled from two multicenter, double-blind, Phase 3 solanezumab (EXPEDITION/2) or semagacestat (IDENTITY/2) studies, and from AD patients participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cognitive and functional outcomes were assessed using AD Assessment Scale-Cognitive subscale (ADAS-Cog), AD Cooperative Study-Activities of Daily Living instrumental subscale (ADCS-iADL), or Functional Activities Questionnaire (FAQ), respectively. ARCL panel analyses evaluated relationships between cognitive and functional impairment over time. In EXPEDITION, ARCL panel analyses demonstrated cognitive scores significantly predicted future functional impairment at 5 of 6 time points, while functional scores predicted subsequent cognitive scores in only 1 of 6 time points. Data from IDENTITY and ADNI programs yielded consistent results whereby cognition predicted subsequent function, but not vice-versa. Analyses from three databases indicated cognitive decline precedes and predicts subsequent functional decline in mild AD dementia, consistent with previously proposed hypotheses, and corroborate recent publications using similar methodologies. Cognitive impairment may be used as a predictor of future functional impairment in mild AD dementia and can be considered a critical target for prevention strategies to limit future functional decline in the dementia process.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2017-05-24

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

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

PubMed

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

2010-05-01

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

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.

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.

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

PubMed

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

2017-07-01

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

A Comparison of Descriptive and Functional Analyses of Inappropriate Mealtime Behavior.

PubMed

Borrero, Carrie S W; England, Jennie D; Sarcia, Ben; Woods, Julia N

2016-12-01

In recent years, rather than being used to assess the potential function of a response, descriptive assessment methods have been applied to evaluate potential consequences or contingencies for problem behavior (Borrero, Woods, Borrero, Masler, & Lesser in Journal of Applied Behavior Analysis, 43 , 71-88. doi: 10.1901/jaba.2010.43-71, 2010) or to assist with designing baseline conditions to approximate caregiver behavior (Casey et al. in Behavior Modification, 33 , 537-558. doi: 10.1177/0145445509341457, 2009). It has been shown that descriptive assessments of some forms of problem behavior (e.g., self-injury, aggression) are not good indicators of behavioral function and should not be used exclusively when conducting functional behavior assessments (Thompson & Iwata in Journal of Applied Behavior Analysis, 40 , 333-338. doi: 10.1901/jaba.2007.56.06/epdf, 2007). However, the extent to which descriptive assessments of inappropriate mealtime behavior can predict behavioral function is not yet clear. We conducted descriptive assessments of inappropriate mealtime behavior and compared the results to functional analyses for ten children with severe food refusal. Results showed that, for 71 % of participants, the descriptive and functional analyses matched. These results suggest that the correspondence between descriptive and functional analyses, at least for inappropriate mealtime behavior, may be higher than that for other forms of problem behavior.

An expanded role for neuroimaging in the evaluation of memory impairment

PubMed Central

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

2014-01-01

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

The posttraumatic stress disorder project in Brazil: neuropsychological, structural and molecular neuroimaging studies in victims of urban violence.

PubMed

Bressan, Rodrigo A; Quarantini, Lucas C; Andreoli, Sérgio B; Araújo, Celia; Breen, Gerome; Guindalini, Camila; Hoexter, Marcelo; Jackowski, Andrea P; Jorge, Miguel R; Lacerda, Acioly L T; Lara, Diogo R; Malta, Stella; Moriyama, Tais S; Quintana, Maria I; Ribeiro, Wagner S; Ruiz, Juliana; Schoedl, Aline F; Shih, Ming C; Figueira, Ivan; Koenen, Karestan C; Mello, Marcelo F; Mari, Jair J

2009-06-01

Life trauma is highly prevalent in the general population and posttraumatic stress disorder is among the most prevalent psychiatric consequences of trauma exposure. Brazil has a unique environment to conduct translational research about psychological trauma and posttraumatic stress disorder, since urban violence became a Brazilian phenomenon, being particularly related to the rapid population growth of its cities. This research involves three case-control studies: a neuropsychological, a structural neuroimaging and a molecular neuroimaging study, each focusing on different objectives but providing complementary information. First, it aims to examine cognitive functioning of PTSD subjects and its relationships with symptomatology. The second objective is to evaluate neurostructural integrity of orbitofrontal cortex and hippocampus in PTSD subjects. The third aim is to evaluate if patients with PTSD have decreased dopamine transporter density in the basal ganglia as compared to resilient controls subjects. This paper shows the research rationale and design for these three case-control studies. Cases and controls will be identified through an epidemiologic survey conducted in the city of São Paulo. Subjects exposed to traumatic life experiences resulting in posttraumatic stress disorder (cases) will be compared to resilient victims of traumatic life experiences without PTSD (controls) aiming to identify biological variables that might protect or predispose to PTSD. In the neuropsychological case-control study, 100 patients with PTSD, will be compared with 100 victims of trauma without posttraumatic stress disorder, age- and sex-matched controls. Similarly, 50 cases and 50 controls will be enrolled for the structural study and 25 cases and 25 controls in the functional neuroimaging study. All individuals from the three studies will complete psychometrics and a structured clinical interview (the Structured Clinical Interview for DSM-IV and the Clinician

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

PubMed Central

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

2012-01-01

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

Chronic Methamphetamine Abuse and Corticostriatal Deficits Revealed by Neuroimaging

PubMed Central

London, Edythe D.; Kohno, Milky; Morales, Angelica; Ballard, Michael E.

2014-01-01

Despite aggressive efforts to contain it, methamphetamine use disorder continues to be major public health problem; and with generic behavioral therapies still the mainstay of treatment for methamphetamine abuse, rates of attrition and relapse remain high. This review summarizes the findings of structural, molecular, and functional neuroimaging studies of methamphetamine abusers, focusing on cortical and striatal abnormalities and their potential contributions to cognitive and behavioral phenotypes that can serve to promote compulsive drug use. These studies indicate that individuals with a history of chronic methamphetamine abuse often display several signs of corticostriatal dysfunction, including abnormal gray- and white-matter integrity, monoamine neurotransmitter system deficiencies, neuroinflammation, poor neuronal integrity, and aberrant patterns of brain connectivity and function, both when engaged in cognitive tasks and at rest. More importantly, many of these neural abnormalities were found to be linked with certain addiction-related phenotypes that may influence treatment response (e.g., poor self-control, cognitive inflexibility, maladaptive decision-making), raising the possibility that they may represent novel therapeutic targets. PMID:25451127

Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age

PubMed Central

Emerson, Robert W.; Adams, Chloe; Nishino, Tomoyuki; Hazlett, Heather Cody; Wolff, Jason J.; Zwaigenbaum, Lonnie; Constantino, John N.; Shen, Mark D.; Swanson, Meghan R.; Elison, Jed T.; Kandala, Sridhar; Estes, Annette M.; Botteron, Kelly N.; Collins, Louis; Dager, Stephen R.; Evans, Alan C.; Gerig, Guido; Gu, Hongbin; McKinstry, Robert C.; Paterson, Sarah; Schultz, Robert T.; Styner, Martin; Network, IBIS; Schlaggar, Bradley L.; Pruett, John R.; Piven, Joseph

2018-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social deficits and repetitive behaviors that typically emerge by 24 months of age. To develop effective early interventions that can potentially ameliorate the defining deficits of ASD and improve long-term outcomes, early detection is essential. Using prospective neuroimaging of 59 6-month-old infants with a high familial risk for ASD, we show that functional connectivity magnetic resonance imaging correctly identified which individual children would receive a research clinical best-estimate diagnosis of ASD at 24 months of age. Functional brain connections were defined in 6-month-old infants that correlated with 24-month scores on measures of social behavior, language, motor development, and repetitive behavior, which are all features common to the diagnosis of ASD. A fully cross-validated machine learning algorithm applied at age 6 months had a positive predictive value of 100% [95% confidence interval (CI), 62.9 to 100], correctly predicting 9 of 11 infants who received a diagnosis of ASD at 24 months (sensitivity, 81.8%; 95% CI, 47.8 to 96.8). All 48 6-month-old infants who were not diagnosed with ASD were correctly classified [specificity, 100% (95% CI, 90.8 to 100); negative predictive value, 96.0% (95% CI, 85.1 to 99.3)]. These findings have clinical implications for early risk assessment and the feasibility of developing early preventative interventions for ASD. PMID:28592562

Graphical Neuroimaging Informatics: Application to Alzheimer’s Disease

PubMed Central

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

2013-01-01

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

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

PubMed

Bilenko, Natalia Y; Gallant, Jack L

2016-01-01

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

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

PubMed

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

2014-01-01

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

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

Prefrontal Control and Internet Addiction: A Theoretical Model and Review of Neuropsychological and Neuroimaging Findings

PubMed Central

Brand, Matthias; Young, Kimberly S.; Laier, Christian

2014-01-01

Most people use the Internet as a functional tool to perform their personal goals in everyday-life such as making airline or hotel reservations. However, some individuals suffer from a loss of control over their Internet use resulting in personal distress, symptoms of psychological dependence, and diverse negative consequences. This phenomenon is often referred to as Internet addiction. Only Internet Gaming Disorder has been included in the appendix of the DSM-5, but it has already been argued that Internet addiction could also comprise problematic use of other applications with cybersex, online relations, shopping, and information search being Internet facets at risk for developing an addictive behavior. Neuropsychological investigations have pointed out that certain prefrontal functions in particular executive control functions are related to symptoms of Internet addiction, which is in line with recent theoretical models on the development and maintenance of the addictive use of the Internet. Control processes are particularly reduced when individuals with Internet addiction are confronted with Internet-related cues representing their first choice use. For example, processing Internet-related cues interferes with working memory performance and decision making. Consistent with this, results from functional neuroimaging and other neuropsychological studies demonstrate that cue-reactivity, craving, and decision making are important concepts for understanding Internet addiction. The findings on reductions in executive control are consistent with other behavioral addictions, such as pathological gambling. They also emphasize the classification of the phenomenon as an addiction, because there are also several similarities with findings in substance dependency. The neuropsychological and neuroimaging results have important clinical impact, as one therapy goal should enhance control over the Internet use by modifying specific cognitions and Internet use expectancies

Prefrontal control and internet addiction: a theoretical model and review of neuropsychological and neuroimaging findings.

PubMed

Brand, Matthias; Young, Kimberly S; Laier, Christian

2014-01-01

Most people use the Internet as a functional tool to perform their personal goals in everyday-life such as making airline or hotel reservations. However, some individuals suffer from a loss of control over their Internet use resulting in personal distress, symptoms of psychological dependence, and diverse negative consequences. This phenomenon is often referred to as Internet addiction. Only Internet Gaming Disorder has been included in the appendix of the DSM-5, but it has already been argued that Internet addiction could also comprise problematic use of other applications with cybersex, online relations, shopping, and information search being Internet facets at risk for developing an addictive behavior. Neuropsychological investigations have pointed out that certain prefrontal functions in particular executive control functions are related to symptoms of Internet addiction, which is in line with recent theoretical models on the development and maintenance of the addictive use of the Internet. Control processes are particularly reduced when individuals with Internet addiction are confronted with Internet-related cues representing their first choice use. For example, processing Internet-related cues interferes with working memory performance and decision making. Consistent with this, results from functional neuroimaging and other neuropsychological studies demonstrate that cue-reactivity, craving, and decision making are important concepts for understanding Internet addiction. The findings on reductions in executive control are consistent with other behavioral addictions, such as pathological gambling. They also emphasize the classification of the phenomenon as an addiction, because there are also several similarities with findings in substance dependency. The neuropsychological and neuroimaging results have important clinical impact, as one therapy goal should enhance control over the Internet use by modifying specific cognitions and Internet use expectancies.

PENN Biomarker Core of the Alzheimer’s Disease Neuroimaging Initiative

PubMed Central

Shaw, Leslie M.

2009-01-01

There is a pressing need to develop effective prevention and disease-modifying treatments for Alzheimer’s disease (AD), a dreaded affliction whose incidence increases almost logarithmically with age starting at about 65 years. A key need in the field of AD research is the validation of imaging and biochemical biomarkers. Biomarker tests that are shown to reliably predict the disease before it is clinically expressed would permit testing of new therapeutics at the earliest time point possible in order to give the best chance for delaying the onset of dementia in these patients. In this review the current state of AD biochemical biomarker research is discussed. A new set of guidelines for the diagnosis of AD in the research setting places emphasis on the inclusion of selected imaging and biochemical biomarkers, in addition to neuropsychological behavioral testing. Importantly, the revised guidelines were developed to identify patients at the earliest stages prior to full-blown dementia as well as patients with the full spectrum of the disease. The Alzheimer’s Disease Neuroimaging Initiative is a multicenter consortium study that includes as one of its primary goals the development of standardized neuroimaging and biochemical biomarker methods for AD clinical trials, as well as using these to measure changes over time in mildly cognitively impaired patients who convert to AD as compared to the natural variability of these in control subjects and their further change over time in AD patients. Validation of the biomarker results by correlation analyses with neuropsychological and neurobehavioral test data is one of the primary outcomes of this study. This validation data will hopefully provide biomarker test performance needed for effective measurement of the efficacy of new treatment and prevention therapeutic agents. PMID:18097156

Sustained effects of ecstasy on the human brain: a prospective neuroimaging study in novel users.

PubMed

de Win, Maartje M L; Jager, Gerry; Booij, Jan; Reneman, Liesbeth; Schilt, Thelma; Lavini, Cristina; Olabarriaga, Sílvia D; den Heeten, Gerard J; van den Brink, Wim

2008-11-01

Previous studies have suggested toxic effects of recreational ecstasy use on the serotonin system of the brain. However, it cannot be excluded that observed differences between users and non-users are the cause rather than the consequence of ecstasy use. As part of the Netherlands XTC Toxicity (NeXT) study, we prospectively assessed sustained effects of ecstasy use on the brain in novel ecstasy users using repeated measurements with a combination of different neuroimaging parameters of neurotoxicity. At baseline, 188 ecstasy-naive volunteers with high probability of first ecstasy use were examined. After a mean period of 17 months follow-up, neuroimaging was repeated in 59 incident ecstasy users and 56 matched persistent ecstasy-naives and their outcomes were compared. Neuroimaging included [(123)I]beta-carbomethoxy-3beta-(4-iodophenyl)tropane (CIT) SPECT to measure serotonin transporter densities as indicators of serotonergic function; (1)H-MR spectroscopy ((1)H-MRS) to measure brain metabolites as indicators of neuronal damage; diffusion tensor imaging (DTI) to measure the apparent diffusion coefficient and fractional anisotropy (FA) of the diffusional motion of water molecules in the brain as indicators of axonal integrity; and perfusion weighted imaging (PWI) to measure regional relative cerebral blood volume (rrCBV) which indicates brain perfusion. With this approach, both structural ((1)H-MRS and DTI) and functional ([(123)I]beta-CIT SPECT and PWI) aspects of neurotoxicity were combined. Compared to persistent ecstasy-naives, novel low-dose ecstasy users (mean 6.0, median 2.0 tablets) showed decreased rrCBV in the globus pallidus and putamen; decreased FA in thalamus and frontoparietal white matter; increased FA in globus pallidus; and increased apparent diffusion coefficient in the thalamus. No changes in serotonin transporter densities and brain metabolites were observed. These findings suggest sustained effects of ecstasy on brain microvasculature, white

Effects of delaying binge drinking on adolescent brain development: a longitudinal neuroimaging study.

PubMed

Bourque, Josiane; Baker, Travis E; Dagher, Alain; Evans, Alan C; Garavan, Hugh; Leyton, Marco; Séguin, Jean R; Pihl, Robert; Conrod, Patricia J

2016-12-13

Onset of alcohol use by 14 relative to 21 years of age strongly predicts elevated risk for severe alcohol use problems, with 27% versus 4% of individuals exhibiting alcohol dependence within 10 years of onset. What remains unclear is whether this early alcohol use (i) is a marker for later problems, reflected as a pre-existing developmental predisposition, (ii) causes global neural atrophy or (iii) specifically disturbs neuro-maturational processes implicated in addiction, such as executive functions or reward processing. Since our group has demonstrated that a novel intervention program targeting personality traits associated with adolescent alcohol use can prevent the uptake of drinking and binge drinking by 40 to 60%, a crucial question is whether prevention of early onset alcohol misuse will protect adolescent neurodevelopment and which domains of neurodevelopment can be protected. A subsample of 120 youth at high risk for substance misuse and 30 low-risk youth will be recruited from the Co-Venture trial (Montreal, Canada) to take part in this 5-year follow-up neuroimaging study. The Co-Venture trial is a community-based cluster-randomised trial evaluating the effectiveness of school-based personality-targeted interventions on substance use and cognitive outcomes involving approximately 3800 Grade 7 youths. Half of the 120 high-risk participants will have received the preventative intervention program. Cognitive tasks and structural and functional neuroimaging scans will be conducted at baseline, and at 24- and 48-month follow-up. Two functional paradigms will be used: the Stop-Signal Task to measure motor inhibitory control and a modified version of the Monetary Incentive Delay Task to evaluate reward processing. The expected results should help identify biological vulnerability factors, and quantify the consequences of early alcohol abuse as well as the benefits of early intervention using brain metrics.

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.

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses – The case of behavioral variant frontotemporal dementia

PubMed Central

Schroeter, Matthias L.; Laird, Angela R.; Chwiesko, Caroline; Deuschl, Christine; Schneider, Else; Bzdok, Danilo; Eickhoff, Simon B.; Neumann, Jane

2014-01-01

Introduction Uniform coordinate systems in neuroimaging research have enabled comprehensive systematic and quantitative meta-analyses. Such approaches are particularly relevant for neuropsychiatric diseases, the understanding of their symptoms, prediction and treatment. Behavioral variant frontotemporal dementia (bvFTD), a common neurodegenerative syndrome, is characterized by deep alterations in behavior and personality. Investigating this ‘nexopathy’ elucidates the healthy social and emotional brain. Methods Here, we combine three multimodal meta-analyses approaches – anatomical & activation likelihood estimates and behavioral domain profiles – to identify neural correlates of bvFTD in 417 patients and 406 control subjects and to extract mental functions associated with this disease by meta-analyzing functional activation studies in the comprehensive probabilistic functional brain atlas of the BrainMap database. Results The analyses identify the frontomedian cortex, basal ganglia, anterior insulae and thalamus as most relevant hubs, with a regional dissociation between atrophy and hypometabolism. Neural networks affected by bvFTD were associated with emotion and reward processing, empathy and executive functions (mainly inhibition), suggesting these functions as core domains affected by the disease and finally leading to its clinical symptoms. In contrast, changes in theory of mind or mentalizing abilities seem to be secondary phenomena of executive dysfunctions. Conclusions The study creates a novel conceptual framework to understand neuropsychiatric diseases by powerful data-driven meta-analytic approaches that shall be extended to the whole neuropsychiatric spectrum in the future. PMID:24763126

Neuroimaging studies in people with gender incongruence.

PubMed

Kreukels, Baudewijntje P C; Guillamon, Antonio

2016-01-01

The current review gives an overview of brain studies in transgender people. First, we describe studies into the aetiology of feelings of gender incongruence, primarily addressing the sexual differentiation hypothesis: does the brain of transgender individuals resemble that of their natal sex, or that of their experienced gender? Findings from neuroimaging studies focusing on brain structure suggest that the brain phenotypes of trans women (MtF) and trans men (FtM) differ in various ways from control men and women with feminine, masculine, demasculinized and defeminized features. The brain phenotypes of people with feelings of gender incongruence may help us to figure out whether sex differentiation of the brain is atypical in these individuals, and shed light on gender identity development. Task-related imaging studies may show whether brain activation and task performance in transgender people is sex-atypical. Second, we review studies that evaluate the effects of cross-sex hormone treatment on the brain. This type of research provides knowledge on how changes in sex hormone levels may affect brain structure and function.

Neuroimaging of love: fMRI meta-analysis evidence toward new perspectives in sexual medicine.

PubMed

Ortigue, Stephanie; Bianchi-Demicheli, Francesco; Patel, Nisa; Frum, Chris; Lewis, James W

2010-11-01

Brain imaging is becoming a powerful tool in the study of human cerebral functions related to close personal relationships. Outside of subcortical structures traditionally thought to be involved in reward-related systems, a wide range of neuroimaging studies in relationship science indicate a prominent role for different cortical networks and cognitive factors. Thus, the field needs a better anatomical/network/whole-brain model to help translate scientific knowledge from lab bench to clinical models and ultimately to the patients suffering from disorders associated with love and couple relationships. The aim of the present review is to provide a review across wide range of functional magnetic resonance imaging (fMRI) studies to critically identify the cortical networks associated with passionate love, and to compare and contrast it with other types of love (such as maternal love and unconditional love for persons with intellectual disabilities). Retrospective review of pertinent neuroimaging literature. Review of published literature on fMRI studies of love illustrating brain regions associated with different forms of love. Although all fMRI studies of love point to the subcortical dopaminergic reward-related brain systems (involving dopamine and oxytocin receptors) for motivating individuals in pair-bonding, the present meta-analysis newly demonstrated that different types of love involve distinct cerebral networks, including those for higher cognitive functions such as social cognition and bodily self-representation. These metaresults provide the first stages of a global neuroanatomical model of cortical networks involved in emotions related to different aspects of love. Developing this model in future studies should be helpful for advancing clinical approaches helpful in sexual medicine and couple therapy. © 2010 International Society for Sexual Medicine.

Disclosing neuroimaging incidental findings: a qualitative thematic analysis of health literacy challenges.

PubMed

Rancher, Caitlin E; Shoemaker, Jody M; Petree, Linda E; Holdsworth, Mark; Phillips, John P; Helitzer, Deborah L

2016-10-11

Returning neuroimaging incidental findings (IF) may create a challenge to research participants' health literacy skills as they must interpret and make appropriate healthcare decisions based on complex radiology jargon. Disclosing IF can therefore present difficulties for participants, research institutions and the healthcare system. The purpose of this study was to identify the extent of the health literacy challenges encountered when returning neuroimaging IF. We report on findings from a retrospective survey and focus group sessions with major stakeholders involved in disclosing IF. We surveyed participants who had received a radiology report from a research study and conducted focus groups with participants, parents of child participants, Institutional Review Board (IRB) members, investigators and physicians. Qualitative thematic analyses were conducted using standard group-coding procedures and descriptive summaries of health literacy scores and radiology report outcomes are examined. Although participants reported high health literacy skills (m = 87.3 on a scale of 1-100), 67 % did not seek medical care when recommended to do so; and many participants in the focus groups disclosed they could not understand the findings described in their report. Despite their lack of understanding, participants desire to have information about their radiology results, and the investigators feel ethically inclined to return findings. The language in clinically useful radiology reports can create a challenge for participants' health literacy skills and has the potential to negatively impact the healthcare system and investigators conducting imaging research. Radiology reports need accompanying resources that explain findings in lay language, which can help reduce the challenge caused by the need to communicate incidental findings.

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

PubMed

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

2017-10-28

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

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.

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

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 and Neurodevelopmental Outcome in Extremely Preterm Infants

PubMed Central

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

2015-01-01

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

Neural dichotomy of word concreteness: a view from functional neuroimaging.

PubMed

Kumar, Uttam

2016-02-01

Our perception about the representation and processing of concrete and abstract concepts is based on the fact that concrete words are highly imagined and remembered faster than abstract words. In order to explain the processing differences between abstract and concrete concepts, various theories have been proposed, yet there is no unanimous consensus about its neural implication. The present study investigated the processing of concrete and abstract words during an orthography judgment task (implicit semantic processing) using functional magnetic resonance imaging to validate the involvement of the neural regions. Relative to non-words, both abstract and concrete words show activation in the regions of bilateral hemisphere previously associated with semantic processing. The common areas (conjunction analyses) observed for abstract and concrete words are bilateral inferior frontal gyrus (BA 44/45), left superior parietal (BA 7), left fusiform gyrus and bilateral middle occipital. The additional areas for abstract words were noticed in bilateral superior temporal and bilateral middle temporal region, whereas no distinct region was noticed for concrete words. This suggests that words with abstract concepts recruit additional language regions in the brain.

Kidney function changes with aging in adults: comparison between cross-sectional and longitudinal data analyses in renal function assessment.

PubMed

Chung, Sang M; Lee, David J; Hand, Austin; Young, Philip; Vaidyanathan, Jayabharathi; Sahajwalla, Chandrahas

2015-12-01

The study evaluated whether the renal function decline rate per year with age in adults varies based on two primary statistical analyses: cross-section (CS), using one observation per subject, and longitudinal (LT), using multiple observations per subject over time. A total of 16628 records (3946 subjects; age range 30-92 years) of creatinine clearance and relevant demographic data were used. On average, four samples per subject were collected for up to 2364 days (mean: 793 days). A simple linear regression and random coefficient models were selected for CS and LT analyses, respectively. The renal function decline rates per year were 1.33 and 0.95 ml/min/year for CS and LT analyses, respectively, and were slower when the repeated individual measurements were considered. The study confirms that rates are different based on statistical analyses, and that a statistically robust longitudinal model with a proper sampling design provides reliable individual as well as population estimates of the renal function decline rates per year with age in adults. In conclusion, our findings indicated that one should be cautious in interpreting the renal function decline rate with aging information because its estimation was highly dependent on the statistical analyses. From our analyses, a population longitudinal analysis (e.g. random coefficient model) is recommended if individualization is critical, such as a dose adjustment based on renal function during a chronic therapy. Copyright © 2015 John Wiley & Sons, Ltd.

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

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

PubMed Central

Bilenko, Natalia Y.; Gallant, Jack L.

2016-01-01

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

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

PubMed

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

2014-01-01

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

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

PubMed

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

2015-01-01

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

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…

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

PubMed

Habas, Christophe

2012-06-01

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

Multimodal Neuroimaging Differences in Nicotine Abstinent vs. Satiated Smokers.

PubMed

Chaarani, Bader; Spechler, Philip A; Ivanciu, Alexandra; Snowe, Mitchell; Nickerson, Joshua P; Higgins, Stephen T; Garavan, Hugh

2018-04-06

Research on cigarette smokers suggests cognitive and behavioral impairments. However, much remains unclear how the functional neurobiology of smokers is influenced by nicotine state. Therefore, we sought to determine which state, be it acute nicotine abstinence or satiety, would yield the most robust differences compared to non-smokers when assessing neurobiological markers of nicotine dependence. Smokers(N=15) and sociodemographically matched non-smokers(N=15) were scanned twice using a repeated-measures design. Smokers were scanned after a 24-hour nicotine abstinence, and immediately after smoking their usual brand cigarette. The neuroimaging battery included a stop-signal task of response inhibition and pseudo-continuous arterial spin labeling to measure cerebral blood flow (CBF). Whole brain voxel-wise ANCOVAs were carried out on stop success and stop fail SST contrasts and CBF maps to assess differences among non-, abstinent and satiated smokers. Cluster-correction was performed using AFNI's 3dClustSim to achieve a significance of p<0.05. Smokers exhibited higher brain activation in bilateral inferior frontal gyrus (IFG), a brain region known to be involved in inhibitory control, during successful response inhibitions relative to non-smokers. This effect was significantly higher during nicotine abstinence relative to satiety. Smokers also exhibited lower CBF in the bilateral IFG than non-smokers. These hypo-perfusions were not different between abstinence and satiety. These findings converge on alterations in smokers in prefrontal circuits known to be critical for inhibitory control. These effects are present, even when smokers are satiated, but the neural activity required to achieve performance equal to controls is increased when smokers are in acute abstinence. Our multi-modal neuroimaging study gives neurobiological insights into the cognitive demands of maintaining abstinence and suggest targets for assessing the efficacy of therapeutic interventions.

Neuroimaging biomarkers and impaired olfaction in cognitively normal individuals.

PubMed

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

2017-06-01

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

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

PubMed

Pustilnik, Amanda C

2012-05-01

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

A Developmental Neuroimaging Investigation of the Change Paradigm

ERIC Educational Resources Information Center

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

2011-01-01

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

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

PubMed Central

Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.

2013-01-01

Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172

Nervous System Injury and Neuroimaging of Zika Virus Infection.

PubMed

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

2018-01-01

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

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

PubMed

Chein, Jason M; Schneider, Walter

2005-12-01

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

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

PubMed

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

2010-01-01

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

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

PubMed Central

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

2017-01-01

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

The effects of alcohol on the nonhuman primate brain: a network science approach to neuroimaging.

PubMed

Telesford, Qawi K; Laurienti, Paul J; Friedman, David P; Kraft, Robert A; Daunais, James B

2013-11-01

Animal studies have long been an important tool for basic research as they offer a degree of control often lacking in clinical studies. Of particular value is the use of nonhuman primates (NHPs) for neuroimaging studies. Currently, studies have been published using functional magnetic resonance imaging (fMRI) to understand the default-mode network in the NHP brain. Network science provides an alternative approach to neuroimaging allowing for evaluation of whole-brain connectivity. In this study, we used network science to build NHP brain networks from fMRI data to understand the basic functional organization of the NHP brain. We also explored how the brain network is affected following an acute ethanol (EtOH) pharmacological challenge. Baseline resting-state fMRI was acquired in an adult male rhesus macaque (n = 1) and a cohort of vervet monkeys (n = 10). A follow-up scan was conducted in the rhesus macaque to assess network variability and to assess the effects of an acute EtOH challenge on the brain network. The most connected regions in the resting-state networks were similar across species and matched regions identified as the default-mode network in previous NHP fMRI studies. Under an acute EtOH challenge, the functional organization of the brain was significantly impacted. Network science offers a great opportunity to understand the brain as a complex system and how pharmacological conditions can affect the system globally. These models are sensitive to changes in the brain and may prove to be a valuable tool in long-term studies on alcohol exposure. Copyright © 2013 by the Research Society on Alcoholism.

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

PubMed Central

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

2015-01-01

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

Imaging of autoimmune encephalitis--Relevance for clinical practice and hippocampal function.

PubMed

Heine, J; Prüss, H; Bartsch, T; Ploner, C J; Paul, F; Finke, C

2015-11-19

The field of autoimmune encephalitides associated with antibodies targeting cell-surface antigens is rapidly expanding and new antibodies are discovered frequently. Typical clinical presentations include cognitive deficits, psychiatric symptoms, movement disorders and seizures and the majority of patients respond well to immunotherapy. Pathophysiological mechanisms and clinical features are increasingly recognized and indicate hippocampal dysfunction in most of these syndromes. Here, we review the neuroimaging characteristics of autoimmune encephalitides, including N-methyl-d-aspartate (NMDA) receptor, leucine-rich glioma inactivated 1 (LGI1), contactin-associated protein-like 2 (CASPR2) encephalitis as well as more recently discovered and less frequent forms such as dipeptidyl-peptidase-like protein 6 (DPPX) or glycine receptor encephalitis. We summarize findings of routine magnetic resonance imaging (MRI) investigations as well as (18)F-fluoro-2-deoxy-d-glucose (FDG)-positron emission tomography (PET) and single photon emission tomography (SPECT) imaging and relate these observations to clinical features and disease outcome. We furthermore review results of advanced imaging analyses such as diffusion tensor imaging, volumetric analyses and resting-state functional MRI. Finally, we discuss contributions of these neuroimaging observations to the understanding of the pathophysiology of autoimmune encephalitides. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Functional brain imaging and the induction of traumatic recall: a cross-correlational review between neuroimaging and hypnosis.

PubMed

Vermetten, Eric; Douglas Bremner, J

2004-07-01

The behavioral and psychophysiological alterations during recall in patients with trauma disorders often resemble phenomena that are seen in hypnosis. In studies of emotional recall as well as in neuroimaging studies of hypnotic processes similar brain structures are involved: thalamus, hippocampus, amygdala, medial prefrontal cortex, anterior cingulate cortex. This paper focuses on cross-correlations in traumatic recall and hypnotic responses and reviews correlations between the involvement of brain structures in traumatic recall and processes that are involved in hypnotic responsiveness. To further improve uniformity of results of brain imaging specifically for traumatic recall studies, attention is needed for standardization of hypnotic variables, isolation of the emotional process of interest (state),and assessment of trait-related differences.

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

PubMed Central

Hulvershorn, Leslie; Cullen, Kathryn; Anand, Amit

2011-01-01

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

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

PubMed Central

2012-01-01

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

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

PubMed

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

2018-01-01

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

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.

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

PubMed Central

Kuss, Daria J.; Griffiths, Mark D.

2012-01-01

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

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

PubMed

Kuss, Daria J; Griffiths, Mark D

2012-09-05

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

Neuroimaging Research with Children: Ethical Issues and Case Scenarios