Imperial College London
Alternate

Professor Claudia Clopath

Faculty of Engineering, Department of Bioengineering

Professor of Computational Neuroscience
 
 
 
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Contact

 

+44 (0)20 7594 1435c.clopath Website

 
 
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Location

 

Royal School of Mines 4.09Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Feulner:2022:10.1038/s41467-022-32646-w,
author = {Feulner, B and Perich, MG and Chowdhury, RH and Miller, LE and Gallego, JA and Clopath, C},
doi = {10.1038/s41467-022-32646-w},
journal = {Nature Communications},
title = {Small, correlated changes in synaptic connectivity may facilitate rapid motor learning},
url = {http://dx.doi.org/10.1038/s41467-022-32646-w},
volume = {13},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Animals can rapidly adapt their movements to external perturbations. This adaptation is paralleled by changes in single neuron activity in the motor cortices. Behavioural and neural recording studies suggest that when animals learn to counteract a visuomotor perturbation, these changes originate from altered inputs to the motor cortices rather than from changes in local connectivity, as neural covariance is largely preserved during adaptation. Since measuring synaptic changes in vivo remains very challenging, weused a modular recurrent network model to compare the expected neural activity changes following learning through altered inputs (Hinput) and learning through local connectivity changes (Hlocal). Learning under Hinput produced small changes in neural activity and largely preserved the neural covariance, in good agreement with neural recordings in monkeys. Surprisingly given the presumed dependence of stable neural covariance onpreserved circuit connectivity, Hlocal led to only slightly larger changes in neural activity and covariance compared to Hinput. This similarity is due to Hlocal only requiring small, correlated connectivity changes to counteract the perturbation, which provided the network with significant robustness against simulated synaptic noise. Simulations of tasks that impose increasingly larger behavioural changes revealed a growing difference betweenHinput and Hlocal, which could be exploited when designing future experiments.
AU  - Feulner,B
AU  - Perich,MG
AU  - Chowdhury,RH
AU  - Miller,LE
AU  - Gallego,JA
AU  - Clopath,C
DO  - 10.1038/s41467-022-32646-w
PY  - 2022///
SN  - 2041-1723
TI  - Small, correlated changes in synaptic connectivity may facilitate rapid motor learning
T2  - Nature Communications
UR  - http://dx.doi.org/10.1038/s41467-022-32646-w
UR  - https://www.nature.com/articles/s41467-022-32646-w
UR  - http://hdl.handle.net/10044/1/98598
VL  - 13
ER  -
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