Literature DB >> 35082444

Cortical preparatory activity indexes learned motor memories.

Xulu Sun1,2, Daniel J O'Shea3,4, Matthew D Golub3,4, Eric M Trautmann3,4, Saurabh Vyas3,5, Stephen I Ryu4,6,7, Krishna V Shenoy8,9,10,11,12,13.   

Abstract

The brain's remarkable ability to learn and execute various motor behaviours harnesses the capacity of neural populations to generate a variety of activity patterns. Here we explore systematic changes in preparatory activity in motor cortex that accompany motor learning. We trained rhesus monkeys to learn an arm-reaching task1 in a curl force field that elicited new muscle forces for some, but not all, movement directions2,3. We found that in a neural subspace predictive of hand forces, changes in preparatory activity tracked the learned behavioural modifications and reassociated4 existing activity patterns with updated movements. Along a neural population dimension orthogonal to the force-predictive subspace, we discovered that preparatory activity shifted uniformly for all movement directions, including those unaltered by learning. During a washout period when the curl field was removed, preparatory activity gradually reverted in the force-predictive subspace, but the uniform shift persisted. These persistent preparatory activity patterns may retain a motor memory of the learned field5,6 and support accelerated relearning of the same curl field. When a set of distinct curl fields was learned in sequence, we observed a corresponding set of field-specific uniform shifts which separated the associated motor memories in the neural state space7-9. The precise geometry of these uniform shifts in preparatory activity could serve to index motor memories, facilitating the acquisition, retention and retrieval of a broad motor repertoire.
© 2022. The Author(s), under exclusive licence to Springer Nature Limited.

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Year:  2022        PMID: 35082444     DOI: 10.1038/s41586-021-04329-x

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   69.504


  3 in total

1.  Understanding implicit and explicit sensorimotor learning through neural dynamics.

Authors:  Xueqian Deng; Mengzhan Liufu; Jingyue Xu; Chen Yang; Zina Li; Juan Chen
Journal:  Front Comput Neurosci       Date:  2022-08-03       Impact factor: 3.387

2.  What is the nature of motor adaptation to dynamic perturbations?

Authors:  Etienne Moullet; Agnès Roby-Brami; Emmanuel Guigon
Journal:  PLoS Comput Biol       Date:  2022-08-30       Impact factor: 4.779

3.  Selective modulation of cortical population dynamics during neuroprosthetic skill learning.

Authors:  Ellen L Zippi; Albert K You; Karunesh Ganguly; Jose M Carmena
Journal:  Sci Rep       Date:  2022-09-24       Impact factor: 4.996

  3 in total

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