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Stable continual learning through structured multiscale plasticity manifolds

Mishra, P and Narayanan, R (2021) Stable continual learning through structured multiscale plasticity manifolds. In: Current Opinion in Neurobiology, 70 . pp. 51-63.

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Official URL: https://doi.org/10.1016/j.conb.2021.07.009


Biological plasticity is ubiquitous. How does the brain navigate this complex plasticity space, where any component can seemingly change, in adapting to an ever-changing environment? We build a systematic case that stable continuous learning is achieved by structured rules that enforce multiple, but not all, components to change together in specific directions. This rule-based low-dimensional plasticity manifold of permitted plasticity combinations emerges from cell type�specific molecular signaling and triggers cascading impacts that span multiple scales. These multiscale plasticity manifolds form the basis for behavioral learning and are dynamic entities that are altered by neuromodulation, metaplasticity, and pathology. We explore the strong links between heterogeneities, degeneracy, and plasticity manifolds and emphasize the need to incorporate plasticity manifolds into learning-theoretical frameworks and experimental designs. © 2021 The Author(s)

Item Type: Journal Article
Publication: Current Opinion in Neurobiology
Publisher: Elsevier Ltd
Additional Information: The copyright for this article belongs to Authors
Keywords: conceptual framework; experimental design; learning; neuromodulation; review; signal transduction
Department/Centre: Division of Biological Sciences > Molecular Biophysics Unit
Date Deposited: 24 Sep 2021 07:57
Last Modified: 24 Sep 2021 07:57
URI: http://eprints.iisc.ac.in/id/eprint/69748

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