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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Abstract
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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