Neural manifold under plasticity in a goal driven learning behaviour
File(s)
Author(s)
Feulner, Barbara
Clopath, Claudia
Type
Journal Article
Abstract
Neural activity is often low dimensional and dominated by only a few prominent neural covariation patterns. It has been hypothesised that these covariation patterns could form the building blocks used for fast and flexible motor control. Supporting this idea, recent experiments have shown that monkeys can learn to adapt their neural activity in motor cortex on a timescale of minutes, given that the change lies within the original low-dimensional subspace, also called neural manifold. However, the neural mechanism underlying this within-manifold adaptation remains unknown. Here, we show in a computational model that modification of recurrent weights, driven by a learned feedback signal, can account for the observed behavioural difference between within- and outside-manifold learning. Our findings give a new perspective, showing that recurrent weight changes do not necessarily lead to change in the neural manifold. On the contrary, successful learning is naturally constrained to a common subspace.
Date Issued
2021-02-01
Date Acceptance
2020-12-08
Citation
PLoS Computational Biology, 2021, 17 (2), pp.1-27
ISSN
1553-734X
Publisher
Public Library of Science (PLoS)
Start Page
1
End Page
27
Journal / Book Title
PLoS Computational Biology
Volume
17
Issue
2
Copyright Statement
© 2021 Feulner, Clopath. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License URL
Sponsor
Wellcome Trust
Biotechnology and Biological Sciences Research Council (BBSRC)
Biotechnology and Biological Sciences Research Cou
Simons Foundation
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000617972500003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
200790/Z/16/Z
BB/P018785/1
ORCA 64155 (BB/N013956/1)
Award ID:564408
Subjects
Science & Technology
Life Sciences & Biomedicine
Biochemical Research Methods
Mathematical & Computational Biology
Biochemistry & Molecular Biology
DIMENSIONALITY REDUCTION
DYNAMICS
NETWORKS
PATTERNS
Publication Status
Published
Article Number
ARTN e1008621
Date Publish Online
2021-02-05