Dynamic Functional Connectivity In Neuropsychiatric Disorders Methods And Applications
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Dynamic Functional Connectivity in Neuropsychiatric Disorders: Methods and Applications
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Dynamic Functional Connectivity in Neuropsychiatric Disorders: Methods and Applications, volume II
Neuropsychiatric disorders have a huge impact on individuals, families and societies. However, the neuropathology underlying cognitive deficits in neuropsychiatric disorders remains unclear. Resting-state functional connectivity provides a powerful way to investigate functional alterations underlying cognitive deficits in neuropsychiatric disorders. Traditional FC analysis measures the correlations of signals with an assumption that functional connectivity remains constant during the observation period. In recent years, several studies have demonstrated the feasibility of dynamic methods in characterization of functional brain changes, such as dynamic functional connectivity investigated by a sliding window method. However, selection of window size, window stepsize and window type are open areas of research and an important parameter to capture the resting-state FC dynamics.
Brain Network Dysfunction in Neuropsychiatric Illness
Author: Vaibhav A. Diwadkar
language: en
Publisher: Springer Nature
Release Date: 2021-05-11
Brain network function and dysfunction is the dominant model for understanding how the brain gives rise to normal and abnormal behavior. Moreover, neuropsychiatric illnesses continue to resist attempts to reveal an understanding of their bases. Thus, this timely volume provides a synthesis of the uses of multiple analytic methods as they are applied to neuroimaging data, to seek understanding of the neurobiological bases of psychiatric illnesses, understanding that can subsequently aid in their management and treatment. A principle focus is on the analyses and application of methods to functional magnetic resonance imaging (fMRI) data. fMRI remains the most widely used neuroimaging technique for estimating brain network function, and several of the methods covered can estimate brain network dysfunction in resting and task-active states. Additional chapters provide details on how these methods are (and can be) applied in the understanding of several neuropsychiatric disorders, including schizophrenia, mood disorders, autism, borderline personality disorder, and attention deficit hyperactivity disorder (ADHD). A final complement of chapters provides a collective overview of how this framework continues to provoke theoretical advances in our conception of the brain in psychiatry. This unique volume is designed to be a comprehensive resource for imaging researchers interested in psychiatry, and for psychiatrists interested in advanced imaging applications.