| 書目名稱 | Estimating Functional Connectivity and Topology in Large-Scale Neuronal Assemblies |
| 副標(biāo)題 | Statistical and Comp |
| 編輯 | Vito Paolo Pastore |
| 視頻video | http://file.papertrans.cn/316/315760/315760.mp4 |
| 概述 | Nominated as an outstanding Ph.D. thesis by the University of Genoa, Italy.Describes statistical methods to infer functional connectivity in in vitro neuronal assemblies.Explains the computation of th |
| 叢書名稱 | Springer Theses |
| 圖書封面 |  |
| 描述 | This book describes a set of novel statistical algorithms designed to infer functional connectivity of large-scale neural assemblies. The algorithms are developed with the aim of maximizing computational accuracy and efficiency, while faithfully reconstructing both the inhibitory and excitatory functional links. The book reports on statistical methods to compute the most significant functional connectivity graph, and shows how to use graph theory to extract the topological features of the computed network. A particular feature is that the methods used and extended at the purpose of this work are reported in a fairly completed, yet concise manner, together with the necessary mathematical fundamentals and explanations to understand their application. Furthermore, all these methods have been embedded in the user-friendly open source software named SpiCoDyn, which is also introduced here. All in all, this book provides researchers and graduate students in bioengineering, neurophysiology and computer science, with a set of simplified and reduced models for studying functional connectivity in in silico biological neuronal networks, thus overcoming the complexity of brain circuits...??. |
| 出版日期 | Book 2021 |
| 關(guān)鍵詞 | Functional Connectivity Analysis; Correlation-based Connectivity Methods; Cross-correlation Histogram; |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-59042-0 |
| isbn_softcover | 978-3-030-59044-4 |
| isbn_ebook | 978-3-030-59042-0Series 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 |
|Archiver|手機(jī)版|小黑屋|
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