Computational Neuroscience : Mathematical and Statistical Perspectives

Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, new challenges are emerging. For maximal effectiveness, those working to advance computational neuroscience will need to appreciate and exploit the complementary strengths of mechanistic theory and the statistical paradigm

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Year of publication:	2018
Authors:	Kass, Robert E. ; Amari, Shun-Ichi ; Arai, Kensuke ; Brown, Emery ; Diekman, Casey O. ; Diesmann, Markus ; Doiron, Brent ; Eden, Uri ; Fairhall, Adrienne ; Fiddyment, Grant M. ; Fukai, Tomoki ; Grün, Sonja ; Harrison, Matthew T. ; Helias, Moritz ; Nakahara, Hiroyuki ; Teramae, Jun-nosuke ; Thomas, Peter J. ; Reimers, Mark ; Rodu, Jordan ; Rotstein, Horacio G. ; Shea-Brown, Eric ; Shimazaki, Hideaki ; Shinomoto, Shigeru ; Yu, Byron M. ; Kramer, Mark
Publisher:	[S.l.] : SSRN
Subject:	Mathematik \| Mathematics \| Neurowissenschaften \| Neuroscience \| Theorie \| Theory \| Finanzmathematik \| Mathematical finance \| Statistische Methode \| Statistical method
Description of contents:	Abstract [papers.ssrn.com]