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Estimating functional connectivity and topology in large-scale neuronal assemblies : statistical and computational methods / / Vito Paolo Pastore



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Autore: Pastore Vito Paolo Visualizza persona
Titolo: Estimating functional connectivity and topology in large-scale neuronal assemblies : statistical and computational methods / / Vito Paolo Pastore Visualizza cluster
Pubblicazione: Cham, Switzerland : , : Springer, , [2021]
©2021
Edizione: 1st ed. 2021.
Descrizione fisica: 1 online resource (XV, 87 p. 43 illus., 39 illus. in color.)
Disciplina: 153
Soggetto topico: Neural networks (Neurobiology) - Mathematical models
Nota di contenuto: Introduction -- Materials and Methods -- Results -- Conclusion.
Sommario/riassunto: 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. .
Titolo autorizzato: Estimating functional connectivity and topology in large-scale neuronal assemblies  Visualizza cluster
ISBN: 3-030-59042-9
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484069103321
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Serie: Springer theses.