| 书目名称 | Characterization of Neural Activity Using Complex Network Theory | | 副标题 | An Application to th | | 编辑 | Javier Gomez-Pilar | | 视频video | | | 概述 | Nominated as an outstanding PhD thesis by the Bioengineering Group of Comité Español de Automática (CEA).Describes novel methods for investigating the dynamics of neuronal interactions.Proposes a dyna | | 丛书名称 | Springer Theses | | 图书封面 |  | | 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 | | 关键词 | Neural Dynamics in Schizophrenia; Neural Network Modeling; Neural Coupling; Neural Synchronization; Neur | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-49900-6 | | isbn_softcover | 978-3-030-49902-0 | | isbn_ebook | 978-3-030-49900-6Series ISSN 2190-5053 Series E-ISSN 2190-5061 | | issn_series | 2190-5053 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 18:42:20
