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The Triple Network Model Of Mental Disorders Disease Specific Characterization Of Cognitive Large Scale Brain Networks Via Functional Magnetic Resonance Imaging Fmri
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Book Synopsis The Triple Network Model of Mental Disorders: Disease-specific Characterization of Cognitive Large-scale Brain Networks Via Functional Magnetic Resonance Imaging (fMRI) by : Ioan-Andrei Manoliu
Download or read book The Triple Network Model of Mental Disorders: Disease-specific Characterization of Cognitive Large-scale Brain Networks Via Functional Magnetic Resonance Imaging (fMRI) written by Ioan-Andrei Manoliu and published by . This book was released on 2013 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Magnetic resonance imaging of disturbed brain connectivity in psychiatric illness by : Alex Fornito
Download or read book Magnetic resonance imaging of disturbed brain connectivity in psychiatric illness written by Alex Fornito and published by Frontiers E-books. This book was released on with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: The widespread application of brain imaging to the study of psychiatric disorders has led to a revolution in our understanding of the neural basis of psychiatric illness. In particular, the advent of magnetic resonance imaging (MRI) has provided an unprecedented capacity for quantifying diverse aspects of brain structure and function in vivo, and has been used to identify brain changes associated with the full spectrum of psychopathology. With respect to major psychiatric disorders, it is now abundantly clear from this literature that focal brain dysfunction is rare. Rather, most disorders are associated with abnormalities in large-scale networks of spatially distributed and interconnected brain regions; i.e., they are disorders of brain connectivity. Such considerations highlight the need to understand brain dysfunction in psychiatric illness from a network-based perspective. This goal is starting to be realized through recent advances in the use of MRI to map the brain’s complex connectivity architecture. In this special edition, we invite contributions that address brain network dysfunction in psychiatric illnesses. Specifically, the work must be concerned with understanding interactions between brain regions, and how their alterations are affected by psychiatric disease. These interactions can be studied at the level of anatomy using diffusion-MRI or function using functional MRI (fMRI), with the full range of methods available (e.g., tractography, seed-based correlations, independent component analysis, graph analysis, dynamic causal modeling, etc.). Contributions can be either reviews of recent, relevant literature addressing brain network dysfunction in psychiatric disease, or experimental papers describing novel insights into brain network disturbances in such illnesses. Contributions will be invited covering a broad spectrum of psychiatric disease, including mood and anxiety disorders, schizophrenia, autism, attention-deficit hyperactivity disorder and neurodegenerative conditions. It is intended that this volume will provide important insights into how brain networks are perturbed by psychiatric disease, and allow identification of commonalities and differences across diagnostic categories.
Book Synopsis Mapping Psychopathology with fMRI and Effective Connectivity Analysis by : Baojuan Li
Download or read book Mapping Psychopathology with fMRI and Effective Connectivity Analysis written by Baojuan Li and published by Frontiers Media SA. This book was released on 2017-06-22 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a growing appreciation that many psychiatric (and neurological) conditions can be understood as functional disconnection syndromes – as reflected in aberrant functional integration and synaptic connectivity. This Research Topic considers recent advances in understanding psychopathology in terms of aberrant effective connectivity – as measured noninvasively using functional magnetic resonance imaging (fMRI). Recently, there has been increasing interest in inferring directed connectivity (effective connectivity) from fMRI data. Effective connectivity refers to the influence that one neural system exerts over another and quantifies the directed coupling among brain regions – and how they change with pathophysiology. Compared to functional connectivity, effective connectivity allows one to understand how brain regions interact with each other in terms of context sensitive changes and directed coupling – and therefore may provide mechanistic insights into the neural basis of psychopathology. Established models of effective connectivity include psychophysiological interaction (PPI), structural equation modeling (SEM) and dynamic causal modelling (DCM). DCM is unique because it explicitly models the interaction among brain regions in terms of latent neuronal activity. Moreover, recent advances in DCM such as stochastic and spectral DCM, make it possible to characterize the interaction between different brain regions both at rest and during a cognitive task.
Book Synopsis The Dynamics of Emotional and Cognitive Networks by :
Download or read book The Dynamics of Emotional and Cognitive Networks written by and published by . This book was released on 2015 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is composed of two complementary projects. One focuses on the study of the dynamics between emotional and cognitive networks in healthy subjects using functional magnetic resonance imaging (fMRI). The second project builds on the results obtained in healthy subjects to formulate a computational model of the physiopathology and treatment mechanisms in major depression disorder (M31). 1.Graph-based analysis on the emotional-cognitive demands The regulation of cognitive and emotional processes is critical for diverse functions such as attention, problem solving, error detection, motivation, decision making and social behavior. Dysregulation of these processes is at the core of Major Depressive Disorder (M31). Currently neuroimaging and anatomical methods applied to emotional and cognitive processes present two views of brain organization: one view presents a considerable degree of functional specialization and the other view proposes that cognition and emotion are integrated in the brain. Here, we address this issue by studying the network topology underlying the competitive interactions between emotional and cognitive networks in healthy subjects. To this end, we designed a task that contrasted periods with very high emotional and cognitive demands. We concatenated two tasks: A Sadness Provocation (SP) followed by a Spatial Working Memory (WM) task. We hypothesized that this behavioral paradigm would enhance the modularity of emotional and cognitive brain networks and would reveal the cortical areas that act as network hubs, which are critical for regulating the flow and integration of information between regions. We collected fMRI data from 22 healthy subjects performing this task. We analyzed their brain activity with a general linear model, looking for activation patterns linked to the various phases of the tasks, which we then used to extract 20 regions of interest (ROI) on a subject-by-subject basis. We computed the correlations between fMRI time series in pairs of ROIs, obtaining a matrix of correlations for each subject, and we then applied network measures from graph theory. Subjects that scored highest their sadness intensity showed a more marked decrease in their cognitive performance after SP, and presented stronger activity in subgenual anterior cingulate cortex (sACC) and weaker activity in dorsolateral prefrontal cortex (dlPFC). The network analysis identified two main modules, one cognitive and one emotional. Analysis of connectivity degree and participation coefficient identified the areas that acted as hubs and their modulation: the left dlPFC degree decreased after sadness provocation and the left medial frontal pole (mFP) degree was modulated by sadness intensity. Functional connectivity analyses revealed that these hub areas modulated their connectivity following sadness experience: dlPFC and sACC showed stronger anticorrelation, and mFP and sACC strengthened their correlation. Our results identify the hubs that mediate the interaction between emotional and cognitive networks in a context of high emotional and cognitive demands, and they suggest possible targets to develop new therapeutic strategies for mood disorders. 2.A computational model of Major Depression Several lines of evidence associate major depressive disorder (M31) with a dysfunction of cingulo-frontal network dynamics following glutamate metabolism dysfunction in the ventral anterior cingulate cortex (vACC). However, we still lack a mechanistic framework to understand how these alterations underlie M31 and how treatments improve depression symptoms. We built a biophysical computational model of two cortical areas (vACC, and dorso-lateral prefrontal cortex, dlPFC) that acts as a switch between emotional and cognitive processing: the two areas cannot be co-active due to effective mutual inhibition. We simulated M31 by slowing down glutamate decay in vACC, serotonergic treatments (SSRI) by activating serotonin 1A receptors in vACC, and deep brain stimulation by periodic stimulation of vACC interneurons at 130 Hz. We analyzed network dynamics mathematically in a simpler firing rate network model, and we derived the conditions for the emergence of cortical oscillations. M31 networks differed from healthy networks in that vACC presented constant activation in the absence of emotional inputs, which was not suppressed by dlPFC activation. In turn, vACC hyper-activation prevented dlPFC from responding to cognitive signals, mimicking cognitive dysfunction in M31. SSRI counteracted aberrant vACC activity but it also abolished its normal response to emotional stimuli. In treatment-resistant models, DBS treatment restored the switch function. Activity oscillations in the theta and beta/gamma bands correlated with network function, representing a marker of switch-like operation in the network. The model articulates mechanistically how glutamate deficits generate aberrant vACC dynamics, and how this underlies emotional and cognitive symptoms in M31. The model accounts for the progression of depression, dose-dependent SSRI treatment, DBS treatment of treatment-resistant models and EEG rhythmic biomarkers in a biophysical model of the pathophysiology of M31.
Book Synopsis Multiscale Models of Brain Disorders by : Vassilis Cutsuridis
Download or read book Multiscale Models of Brain Disorders written by Vassilis Cutsuridis and published by Springer Nature. This book was released on 2019-10-11 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on our current understanding of brain dynamics in various brain disorders (e.g. epilepsy, Alzheimer’s and Parkinson’s disease) and how the multi-scale, multi-level tools of computational neuroscience can enhance this understanding. In recent years, there have been significant advances in the study of the dynamics of the disordered brain at both the microscopic and the macroscopic levels. This understanding can be furthered by the application of multi-scale computational models as integrative principles that may link single neuron dynamics and the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI. Focusing on the computational models that are used to study movement, memory and cognitive disorders as well as epilepsy and consciousness related diseases, the book brings together physiologists and anatomists investigating cortical circuits; cognitive neuroscientists studying brain dynamics and behavior by means of EEG and functional magnetic resonance imaging (fMRI); and computational neuroscientists using neural modeling techniques to explore local and large-scale disordered brain dynamics. Covering topics that have a significant impact on the field of medicine, neuroscience and computer science, the book appeals to a diverse group of investigators.
Book Synopsis Detecting and Characterizing Large-scale Human Brain Networks by : Kaustubh Satyendra Supekar
Download or read book Detecting and Characterizing Large-scale Human Brain Networks written by Kaustubh Satyendra Supekar and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding human brain function is one of the most important endeavors in modern science. There is growing evidence that cognitive functions are executed by large-scale networks, comprising multiple interacting anatomically-connected brain areas. Although considerable progress has been made in understanding which specific brain areas are involved in particular cognitive functions, very little is known about the integrative functioning of large-scale brain networks. This is due in part to the lack of methods to pursue this line of research. This dissertation describes computational methods for detecting and characterizing large-scale human brain networks, combining data from task-free functional magnetic resonance imaging (fMRI) and structural diffusion tensor imaging (DTI), two complementary brain imaging modalities. Application of our methods to task-free fMRI and DTI data obtained from a wide range of subject populations provided new insights into how large-scale human brain networks develop, mature, and get disrupted in psychiatric and neurological disorders. More generally, this work demonstrates the power of our multimodal network-analytic approach to obtain a system-level understanding of brain function across the human lifespan.
Download or read book Placebo written by Fabrizio Benedetti and published by Springer. This book was released on 2014-10-10 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the recent explosion of placebo research at many levels the Editors believe that a volume on Placebo would be a good addition to the Handbook of Experimental Pharmacology series. In particular, this volume will be built up on a meeting on Placebo which will be held in Tuebingen (Germany) in January 2013, and where the most prominent researchers in this field will present and exchange their ideas. The authors who will be invited to write chapters for this volume will be the very same speakers at this meeting, thus guaranteeing high standard and excellence in the topic that will be treated. The approach of the book is mainly pharmacological, including basic research and clinical trials, and the contents range from different medical conditions and systems, such as pain and the immune system, to different experimental approaches, like in vivo receptor binding and pharmacological/behavioral conditioning. Overall, the volume will give an idea of modern placebo research, of timely concepts in both experimental and clinical pharmacology, as well as of modern methods and tools in neuroscience.
Book Synopsis Magnetic Resonance Imaging of Healthy and Diseased Brain Networks by : Yong He
Download or read book Magnetic Resonance Imaging of Healthy and Diseased Brain Networks written by Yong He and published by Frontiers Media SA. This book was released on 2015-03-05 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI and functional MRI) with sophisticated analytic strategies such as graph theory, it is possible to noninvasively map the patterns of structural and functional connectivity of human whole-brain networks. With these novel approaches, many studies have shown that human brain networks have nonrandom properties such as modularity, small-worldness and highly connected hubs. Importantly, these quantifiable network properties change with age, learning and disease. Moreover, there is growing evidence for behavioral and genetic correlates. Network analysis of neuroimaging data is opening up a new avenue of research into the understanding of the organizational principles of the brain that will be of interest for all basic scientists and clinical researchers. Such approaches are powerful but there are a number of challenging issues when extracting reliable brain networks from various imaging modalities and analyzing the topological properties, e.g., definitions of network nodes and edges and reproducibility of network analysis. We assembled contributions related to the state-of-the-art methodologies of brain connectivity and the applications involving development, aging and neuropsychiatric disorders such as Alzheimer’s disease, schizophrenia, attention deficit hyperactivity disorder and mood and anxiety disorders. It is anticipated that the articles in this Research Topic will provide a greater range and depth of provision for the field of imaging connectomics.
Book Synopsis Introduction to Resting State fMRI Functional Connectivity by : Janine Bijsterbosch
Download or read book Introduction to Resting State fMRI Functional Connectivity written by Janine Bijsterbosch and published by Oxford University Press. This book was released on 2017-06-15 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spontaneous 'resting-state' fluctuations in neuronal activity offer insights into the inherent organisation of the human brain, and may provide markers for diagnosis and treatment of mental disorders. Resting state functional magnetic resonance imaging (fMRI) can be used to investigate intrinsic functional connectivity networks, which are identified based on similarities in the signal measured from different regions. From data acquisition to results interpretation, An Introduction to Resting State fMRI Functional Connectivity discusses a wide range of approaches without expecting previous knowledge of the reader, making it truly accessible to readers from a broad range of backgrounds. Supplemented with online examples to enable the reader to obtain hands-on experience working with data, the text also provides details to enhance learning for those already experienced in the field. The Oxford Neuroimaging Primers are written for new researchers or advanced undergraduates in neuroimaging to provide a thorough understanding of the ways in which neuroimaging data can be analysed and interpreted. Aimed at students without a background in mathematics or physics, this book is also important reading for those familiar with task fMRI but new to the field of resting state fMRI.
Book Synopsis Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging by : Catherine Elizabeth Chang
Download or read book Toward Improved Characterization of Brain Network Temporal Properties with Functional Magnetic Resonance Imaging written by Catherine Elizabeth Chang and published by Stanford University. This book was released on 2011 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast is a powerful technique for non-invasive measurement of brain activity. Recent fMRI studies have revealed that the spontaneous BOLD fluctuations of the human brain organize into distributed, temporally-coherent networks ("resting-state networks"; RSNs). Examination of RSNs has yielded valuable insight into neural organization and development, and demonstrates potential as a biomarker for conditions such as Alzheimer's disease and depression. However, the accuracy by which the spatio-temporal properties of RSNs can be delineated using fMRI is compromised by the presence of physiological (cardiac and respiratory) noise and vascular hemodynamic variability. Further, our present understanding of how RSNs may interact and support cognitive function has been limited by the fact that the vast majority of studies to-date analyze RSNs in a manner that assumes temporal stationarity. Here, we describe efforts to correct for non-neural physiological influences on the BOLD signal, as well as investigations into the dynamic character of resting-state network connectivity. It is found that low-frequency variations in cardiac and respiratory processes account for significant noise across widespread gray matter regions, and that a constrained deconvolution approach may prove effective for modeling and reducing their effects. Application of the proposed noise-reduction procedure is observed to yield negative correlations between the spontaneous fluctuations of two major RSNs. The relationship between respiratory volume changes and the BOLD signal is further examined by simultaneously monitoring and comparing chest expansion data, end-tidal gas concentrations, and spontaneous BOLD fluctuations. The use of a breath-holding task is proposed for quantifying regional differences in BOLD signal timing that arise from local vasomotor response delays; such non-neural timing delays are found to impact inferences of resting-state connectivity and causality. Finally, a preliminary analysis of non-stationary connectivity between RSNs is performed using wavelet and sliding-window approaches, and it is observed that interactions between networks may reconfigure on time-scales of seconds to minutes.
Book Synopsis Handbook of Neuroengineering by : Nitish V. Thakor
Download or read book Handbook of Neuroengineering written by Nitish V. Thakor and published by Springer Nature. This book was released on 2023-02-02 with total page 3686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook serves as an authoritative reference book in the field of Neuroengineering. Neuroengineering is a very exciting field that is rapidly getting established as core subject matter for research and education. The Neuroengineering field has also produced an impressive array of industry products and clinical applications. It also serves as a reference book for graduate students, research scholars and teachers. Selected sections or a compendium of chapters may be used as “reference book” for a one or two semester graduate course in Biomedical Engineering. Some academicians will construct a “textbook” out of selected sections or chapters. The Handbook is also meant as a state-of-the-art volume for researchers. Due to its comprehensive coverage, researchers in one field covered by a certain section of the Handbook would find other sections valuable sources of cross-reference for information and fertilization of interdisciplinary ideas. Industry researchers as well as clinicians using neurotechnologies will find the Handbook a single source for foundation and state-of-the-art applications in the field of Neuroengineering. Regulatory agencies, entrepreneurs, investors and legal experts can use the Handbook as a reference for their professional work as well.
Book Synopsis Brain Connectivity Analysis: Investigating Brain Disorders by : Barry Horwitz
Download or read book Brain Connectivity Analysis: Investigating Brain Disorders written by Barry Horwitz and published by Frontiers E-books. This book was released on with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, advances in human structural and functional neuroimaging (fMRI, PET, EEG/MEG) have resulted in an explosion of studies investigating the anatomical and functional connectivity between different regions of the brain. More and more studies have employed resting and task-related connectivity analyses to assess functional interactions, and diffusion-weighted tractography to study white matter organization. Many of these studies have addressed normal human function, but recently, a number of investigators have turned their attention to examining brain disorders. The study of brain disorders is a complex endeavor; not only does it require understanding the normal brain, and the regions involved in a particular function, but also it needs a deeper understanding of brain networks and their dynamics. This Research Topic will provide the scientific community with an overview of how to apply connectivity methods to study brain disease, and with perspectives on what are the strength and limitations of each modality. For this Research Topic, we solicit both reviews and original research articles on the use of brain connectivity analysis, with non-human or human models, to explore neurological, psychiatric, developmental and neurodegenerative disorders from a system perspective. Connectivity studies that have focused on one or more of the following will be of particular interest: (1) detection of abnormal functional/structural connectivity; (2) neural plasticity, assessed by changes in connectivity, in patients with brain disorders; (3) assessment of therapy using connectivity measures; (4) relation of connectivity changes to behavioral changes.
Book Synopsis Directed Network Recovery from Large Systems with Applications in Functional Magnetic Resonance Imaging (fMRI) by : Adora Melissa Dsouza
Download or read book Directed Network Recovery from Large Systems with Applications in Functional Magnetic Resonance Imaging (fMRI) written by Adora Melissa Dsouza and published by . This book was released on 2019 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The existence of networks is ubiquitous in natural as well as man-made systems. Identifying the underlying network structure of components of a complex system, especially from simultaneously observed signals, is an actively growing area of research. One of the biggest challenges encountered with network modeling from time-series data is that we rarely know the underlying network structure governing interactions amongst the signals. Thus, the task to be accomplished for such problems is that the network modeling technique should be well-equipped to characterize different types of interactions. Interactions (i) may be casual in nature, (ii) may have nonlinear dependencies, (iii) may take place with different components interacting directly or indirectly with others (iv) may be part of a large or small system. Hence, network modeling approaches should be formulated keeping these different characteristics of interaction in mind. To this end, this work presents three approaches that can detect causal relationships, in systems regardless of size. These approaches are first tested and validated on various simulations with a known underlying network structure of interactions. Subsequently, they are evaluated on real brain activity data recorded using functional magnetic resonance imaging (fMRI). Studies on how the brain is connected and how different regions communicate is a growing and evolving field, as improvements in fMRI technology call for improved analysis techniques. One of the three investigated approaches that is nonlinear uses local models to extract the underlying network structure from fMRI data for both simulated and real data. Such an approach uses state space reconstruction to estimate causality. We also develop two extensions to Granger causality analysis that can determine network graphs for large systems. These approaches are not susceptible to falsely capturing indirect connections since they are multivariate. We first develop a linear multivariate Granger causality analysis approach called large-scale Granger causality (lsGC). Subsequently, we develop large-scale nonlinear Granger causality (lsNGC), which is an extension of lsGC as it accounts for nonlinear dependencies. Methods currently adopted in fMRI literature are either too simplistic and unable to capture the various types of interactions or are too complex and cannot be extended to large systems. With the aforementioned approaches, we demonstrate that the three investigated network modeling techniques can characterize complex interactions without being severely impacted by network size and limited observations. These methods can potentially replace traditional correlation-based approaches used to estimate the network structure in fMRI. Additionally, they can also be used to aid model-driven approaches that require a pre-specified network structure. Furthermore, the promising results on experimental fMRI data suggest that these approaches may aid in identifying imaging-derived biomarkers that can assist clinicians in monitoring disease progression and response to therapeutic intervention for patients with a wide range of neurological and psychiatric disorders"--Pages xii-xiii.
Book Synopsis Brain Connectivity in Autism by : Rajesh K. Kana
Download or read book Brain Connectivity in Autism written by Rajesh K. Kana and published by Frontiers E-books. This book was released on 2014-09-23 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: The brain's ability to process information crucially relies on connectivity. Understanding how the brain processes complex information and how such abilities are disrupted in individuals with neuropsychological disorders will require an improved understanding of brain connectivity. Autism is an intriguingly complex neurodevelopmental disorder with multidimensional symptoms and cognitive characteristics. A biological origin for autism spectrum disorders (ASD) had been proposed even in the earliest published accounts (Kanner, 1943; Asperger, 1944). Despite decades of research, a focal neurobiological marker for autism has been elusive. Nevertheless, disruptions in interregional and functional and anatomical connectivity have been a hallmark of neural functioning in ASD. Theoretical accounts of connectivity perceive ASD as a cognitive and neurobiological disorder associated with altered functioning of integrative circuitry. Neuroimaging studies have reported disruptions in functional connectivity (synchronization of activated brain areas) during cognitive tasks and during task-free resting states. While these insights are valuable, they do not address the time-lagged causality and directionality of such correlations. Despite the general promise of the connectivity account of ASD, inconsistencies and methodological differences among studies call for more thorough investigations. A comprehensive neurological account of ASD should incorporate functional, effective, and anatomical connectivity measures and test the diagnostic utility of such measures. In addition, questions pertaining to how cognitive and behavioral intervention can target connection abnormalities in ASD should be addressed. This research topic of the Frontiers in Human Neuroscience addresses “Brain Connectivity in Autism” primarily from cognitive neuroscience and neuroimaging perspectives.
Book Synopsis Pattern Analysis of the Human Connectome by : Dewen Hu
Download or read book Pattern Analysis of the Human Connectome written by Dewen Hu and published by Springer. This book was released on 2020-11-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :030948202X Total Pages :391 pages Book Rating :4.3/5 (94 download)
Book Synopsis Fostering Healthy Mental, Emotional, and Behavioral Development in Children and Youth by : National Academies of Sciences, Engineering, and Medicine
Download or read book Fostering Healthy Mental, Emotional, and Behavioral Development in Children and Youth written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-01-18 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthy mental, emotional, and behavioral (MEB) development is a critical foundation for a productive adulthood. Much is known about strategies to support families and communities in strengthening the MEB development of children and youth, by promoting healthy development and also by preventing and mitigating disorder, so that young people reach adulthood ready to thrive and contribute to society. Over the last decade, a growing body of research has significantly strengthened understanding of healthy MEB development and the factors that influence it, as well as how it can be fostered. Yet, the United States has not taken full advantage of this growing knowledge base. Ten years later, the nation still is not effectively mitigating risks for poor MEB health outcomes; these risks remain prevalent, and available data show no significant reductions in their prevalence. Fostering Healthy Mental, Emotional, and Behavioral Development in Children and Youth: A National Agenda examines the gap between current research and achievable national goals for the next ten years. This report identifies the complexities of childhood influences and highlights the need for a tailored approach when implementing new policies and practices. This report provides a framework for a cohesive, multidisciplinary national approach to improving MEB health.
Book Synopsis Computational Psychiatry by : Alan Anticevic
Download or read book Computational Psychiatry written by Alan Anticevic and published by Academic Press. This book was released on 2017-09-19 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Psychiatry: Mathematical Modeling of Mental Illness is the first systematic effort to bring together leading scholars in the fields of psychiatry and computational neuroscience who have conducted the most impactful research and scholarship in this area. It includes an introduction outlining the challenges and opportunities facing the field of psychiatry that is followed by a detailed treatment of computational methods used in the service of understanding neuropsychiatric symptoms, improving diagnosis and guiding treatments. This book provides a vital resource for the clinical neuroscience community with an in-depth treatment of various computational neuroscience approaches geared towards understanding psychiatric phenomena. Its most valuable feature is a comprehensive survey of work from leaders in this field. Offers an in-depth overview of the rapidly evolving field of computational psychiatry Written for academics, researchers, advanced students and clinicians in the fields of computational neuroscience, clinical neuroscience, psychiatry, clinical psychology, neurology and cognitive neuroscience Provides a comprehensive survey of work from leaders in this field and a presentation of a range of computational psychiatry methods and approaches geared towards a broad array of psychiatric problems
