Titlebook: Brain Network Dysfunction in Neuropsychiatric Illness; Methods, Application Vaibhav A. Diwadkar,Simon B. Eickhoff Book 2021 Springer Nature

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https://doi.org/10.1007/978-1-4302-6766-9py and intervention can be tested. With a focus on major depressive disorder (MDD), we highlight the rationale for using this computational approach in psychiatric disorders to characterize disease mechanisms and map these characterizations to treatment predictions.

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Vaibhav A. Diwadkar,Simon B. EickhoffCombines and synthesizes expertise from neuroimaging and psychiatry.Discusses applications of neuroimaging to reveal dysfunctional brain networks interactions in specific neuropsychiatric disorders.Ex

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Intelligent Systems Reference Libraryends of neurodevelopment and neurodegeneration, thus implying that they cannot be “cured.” Though psychiatric nosology is relatively tractable and characterized by high reliability, the etiology of neuropsychiatric conditions is considered anything but. Unlike some other medical conditions, their ge

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https://doi.org/10.1007/978-3-030-13743-4gh-resolution, and high-speed assessment of human brain activation and connectivity. Because clinical MRI scanners equipped with fMRI capability are ubiquitous throughout the world – with at least one in most hospitals – its use has grown rapidly since its inception in the early 1990s. Over the year

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Maria Virvou,Efthimios Alepis,Lakhmi C. Jainstinct regions whose interactions are both functionally segregated and integrated across the whole brain. Functional connections integrate multiple brain systems to produce unique networks attending to the different cognitive and sensory demands of the body. Detection and quantification of functiona

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Rania Saidi,Waad Bouaguel,Nadia Essoussiehavior of brain networks is revealed by the relative timing of coordinated brain areas during cognitive task performance (Bressler and Kelso 2016). Coordination of brain areas has been demonstrated by function-related phase synchrony of the EEG, MEG, iEEG, ECoG, or LFP at a fast timescale in the 1–

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Studies in Computational Intelligence diffusion-weighted MR signal has sensitivity to micrometer-scale tissue properties averaged over the imaging voxel size, for example, intra-cellular and extra-cellular volumes and the 3D orientations of axonal bundles. It derives its contrast from sensitivity to the bulk displacement of water throu