Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Korcsak-Gorzo, Agnes, Linssen, Charl, Albers, Jasper, Dasbach, Stefan, Duarte, Renato, Kunkel, Susanne, Morrison, Abigail, Senk, Johanna, Stapmanns, Jonas, Tetzlaff, Tom, Diesmann, Markus, van Albada, Sacha J.
Natura: Preprint
Pubblicazione: 2022
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866909302710599680
author Korcsak-Gorzo, Agnes
Linssen, Charl
Albers, Jasper
Dasbach, Stefan
Duarte, Renato
Kunkel, Susanne
Morrison, Abigail
Senk, Johanna
Stapmanns, Jonas
Tetzlaff, Tom
Diesmann, Markus
van Albada, Sacha J.
author_facet Korcsak-Gorzo, Agnes
Linssen, Charl
Albers, Jasper
Dasbach, Stefan
Duarte, Renato
Kunkel, Susanne
Morrison, Abigail
Senk, Johanna
Stapmanns, Jonas
Tetzlaff, Tom
Diesmann, Markus
van Albada, Sacha J.
contents This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience. It provides an introductory overview on how to account for empirical data in mathematical models, implement such models in software, and perform simulations reflecting experiments. This path is demonstrated with respect to four key aspects of synaptic signaling: the connectivity of brain networks, synaptic transmission, synaptic plasticity, and the heterogeneity across synapses. Each step and aspect of the modeling and simulation workflow comes with its own challenges and pitfalls, which are highlighted and addressed.
format Preprint
id arxiv_https___arxiv_org_abs_2212_05354
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
Korcsak-Gorzo, Agnes
Linssen, Charl
Albers, Jasper
Dasbach, Stefan
Duarte, Renato
Kunkel, Susanne
Morrison, Abigail
Senk, Johanna
Stapmanns, Jonas
Tetzlaff, Tom
Diesmann, Markus
van Albada, Sacha J.
Neurons and Cognition
Neural and Evolutionary Computing
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience. It provides an introductory overview on how to account for empirical data in mathematical models, implement such models in software, and perform simulations reflecting experiments. This path is demonstrated with respect to four key aspects of synaptic signaling: the connectivity of brain networks, synaptic transmission, synaptic plasticity, and the heterogeneity across synapses. Each step and aspect of the modeling and simulation workflow comes with its own challenges and pitfalls, which are highlighted and addressed.
title Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
topic Neurons and Cognition
Neural and Evolutionary Computing
url https://arxiv.org/abs/2212.05354