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Titlebook: Characterization of Neural Activity Using Complex Network Theory; An Application to th Javier Gomez-Pilar Book 2021 The Editor(s) (if appli

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發(fā)表于 2025-3-21 18:42:20 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Characterization of Neural Activity Using Complex Network Theory
副標(biāo)題An Application to th
編輯Javier Gomez-Pilar
視頻videohttp://file.papertrans.cn/225/224007/224007.mp4
概述Nominated as an outstanding PhD thesis by the Bioengineering Group of Comité Espa?ol de Automática (CEA).Describes novel methods for investigating the dynamics of neuronal interactions.Proposes a dyna
叢書(shū)名稱Springer Theses
圖書(shū)封面Titlebook: Characterization of Neural Activity Using Complex Network Theory; An Application to th Javier Gomez-Pilar Book 2021 The Editor(s) (if appli
描述.This book reports on the development and assessment of a novel framework for studying neural interactions (the connectome) and their dynamics (the chronnectome). Using EEG recordings taken during an auditory oddball task performed by 48 patients with schizophrenia and 87 healthy controls, and applying local and network measures, changes in brain activation from pre-stimulus to cognitive response were assessed, and significant differences were observed between the patients and controls. This book investigates the source of the network abnormalities and presents new evidence for the disconnection hypothesis and the aberrant salience hypothesis with regard to schizophrenia. Moreover, it puts forward a novel approach to combining local regularity measures and graph measures in order to characterize schizophrenia brain dynamics, and presents interesting findings on the regularity of brain patterns in healthy control subjects versus patients with schizophrenia. Besides providing new evidence for the disconnection hypothesis, it offers a source of inspiration for future research directions in the field..
出版日期Book 2021
關(guān)鍵詞Neural Dynamics in Schizophrenia; Neural Network Modeling; Neural Coupling; Neural Synchronization; Neur
版次1
doihttps://doi.org/10.1007/978-3-030-49900-6
isbn_softcover978-3-030-49902-0
isbn_ebook978-3-030-49900-6Series ISSN 2190-5053 Series E-ISSN 2190-5061
issn_series 2190-5053
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 20:18:26 | 只看該作者
,Die H?ufigkeit des Augenzitterns,nse during cognition in schizophrenia. Thirdly, a novel graph measure of network complexity was developed. SCG provides an estimation of the ratio between the order of the network and the amount of information stored in it. The measure is insensitive to changes in connectivity strength and network s
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發(fā)表于 2025-3-22 01:31:41 | 只看該作者
Introduction, included in the Thesis is justified in this introductory chapter (Sect.?1.1). The general context of Biomedical Engineering and neural signal processing is briefly described in Sect.?1.2. Section 1.3 is devoted to schizophrenia disorder. Section 1.4 is oriented to explain physiological underpinning
地板
發(fā)表于 2025-3-22 06:45:50 | 只看該作者
Discussion,nse during cognition in schizophrenia. Thirdly, a novel graph measure of network complexity was developed. SCG provides an estimation of the ratio between the order of the network and the amount of information stored in it. The measure is insensitive to changes in connectivity strength and network s
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Characterization of Neural Activity Using Complex Network TheoryAn Application to th
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Characterization of Neural Activity Using Complex Network Theory978-3-030-49900-6Series ISSN 2190-5053 Series E-ISSN 2190-5061
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