Estimating Functional Connectivity and Topology in Large-Scale Neuronal Assemblies

Statistical and Computational Methods

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Éditeur :

Springer


Collection :

Springer Theses

Paru le : 2020-11-06



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Description
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.

  
Pages
87 pages
Collection
Springer Theses
Parution
2020-11-06
Marque
Springer
EAN papier
9783030590413
EAN PDF
9783030590420

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
8
Taille du fichier
4792 Ko
Prix
147,69 €
EAN EPUB
9783030590420

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
8
Taille du fichier
25569 Ko
Prix
147,69 €