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Estimating Functional Connectivity And Topology In Largescale Neuronal Assemblies Statistical And Computational Methods 1st Ed Vito Paolo Pastore

  • SKU: BELL-22497190
Estimating Functional Connectivity And Topology In Largescale Neuronal Assemblies Statistical And Computational Methods 1st Ed Vito Paolo Pastore
$ 31.00 $ 45.00 (-31%)

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Estimating Functional Connectivity And Topology In Largescale Neuronal Assemblies Statistical And Computational Methods 1st Ed Vito Paolo Pastore instant download after payment.

Publisher: Springer International Publishing;Springer
File Extension: PDF
File size: 4.64 MB
Author: Vito Paolo Pastore
ISBN: 9783030590413, 9783030590420, 3030590410, 3030590429
Language: English
Year: 2021
Edition: 1st ed.

Product desciption

Estimating Functional Connectivity And Topology In Largescale Neuronal Assemblies Statistical And Computational Methods 1st Ed Vito Paolo Pastore by Vito Paolo Pastore 9783030590413, 9783030590420, 3030590410, 3030590429 instant download after payment.

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.

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