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Connecting neural dynamics and computation across spatial and temporal scales. In: The Cerebral Cortex and Thalamus, M. Sherman and M. Usrey, Eds., Oxford Univ. Press 2023.

Mease, Rebecca A; Shea-Brown, Eric T; Fairhall, Adrienne L (November 2023, Oxford University Press)
Sherman, M; Usrey, M (Ed.)
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The Mind of a Mouse

https://doi.org/10.1016/j.cell.2020.08.010

Abbott, Larry F.; Bock, Davi D.; Callaway, Edward M.; Denk, Winfried; Dulac, Catherine; Fairhall, Adrienne L.; Fiete, Ila; Harris, Kristen M.; Helmstaedter, Moritz; Jain, Viren; et al (September 2020, Cell)
null (Ed.)
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Computational Neuroscience: Mathematical and Statistical Perspectives

https://doi.org/10.1146/annurev-statistics-041715-033733

Kass, Robert E; Amari, Shun-Ichi; Arai, Kensuke; Brown, Emery N; Diekman, Casey O; Diesmann, Markus; Doiron, Brent; Eden, Uri T; Fairhall, Adrienne L; Fiddyment, Grant M; et al (March 2018, Annual Review of Statistics and Its Application)

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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