Published August 2022
| public
Journal Article
Learning, fast and slow
- Creators
-
Meister, Markus
Abstract
Animals can learn efficiently from a single experience and change their future behavior in response. However, in other instances, animals learn very slowly, requiring thousands of experiences. Here, I survey tasks involving fast and slow learning and consider some hypotheses for what differentiates the underlying neural mechanisms. It has been proposed that fast learning relies on neural representations that favor efficient Hebbian modification of synapses. These efficient representations may be encoded in the genome, resulting in a repertoire of fast learning that differs across species. Alternatively, the required neural representations may be acquired from experience through a slow process of unsupervised learning from the environment.
Additional Information
© 2022 Elsevier. Available online 23 May 2022, Version of Record 23 May 2022. This review comes from a themed issue on Neurobiology of Behavior; Edited by Tiago Branco and Mala Murthy. MM acknowledges support from NIH (R01 NS111477), the Simons Collaboration on the Global Brain (543015) and the Tianqiao and Chrissy Chen Institute for Neuroscience. Thanks to Ralph Adolphs, Pietro Perona, Ueli Rutishauser, Doris Tsao, and Tony Zador for helpful comments and critiques. Code and data. Code and data supporting this article can be found at https://github.com/markusmeister/Learning_Fast_And_Slow. Conflict of interest statement: Nothing declared.Additional details
- Eprint ID
- 115059
- Resolver ID
- CaltechAUTHORS:20220607-425325000
- R01 NS111477
- NIH
- 543015
- Simons Foundation
- Tianqiao and Chrissy Chen Institute for Neuroscience
- Created
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2022-06-07Created from EPrint's datestamp field
- Updated
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2022-06-07Created from EPrint's last_modified field
- Caltech groups
- Tianqiao and Chrissy Chen Institute for Neuroscience, Division of Biology and Biological Engineering