Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
Fuente:
arXiv
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| Autori principali: | , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2022
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| _version_ | 1866909302710599680 |
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| 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 |