Population coupling predicts the plasticity of stimulus responses in cortical circuits

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Abstract

Some neurons have stimulus responses that are stable over days, whereas other neurons have highly plastic stimulus responses. Using a recurrent network model, we explore whether this could be due to an underlying diversity in their synaptic plasticity. We find that, in a network with diverse learning rates, neurons with fast rates are more coupled to population activity than neurons with slow rates. This plasticity-coupling link predicts that neurons with high population coupling exhibit more long-term stimulus response variability than neurons with low population coupling. We substantiate this prediction using recordings from the Allen Brain Observatory, finding that a neuron's population coupling is correlated with the plasticity of its orientation preference. Simulations of a simple perceptual learning task suggest a particular functional architecture: a stable 'backbone' of stimulus representation formed by neurons with low population coupling, on top of which lies a flexible substrate of neurons with high population coupling.

Data availability

All calcium imaging data came from the Allen Institute for Brain Science, Allen Brain Observatory. Available from: http://observatory.brain-map.org/visualcoding/A list of experiment IDs can be found on FigShare, under the doi 10.6084/m9.figshare.11837406Code has been made available at https://github.com/yannaodh/sweeney_clopath_2020 and is under the doi:10.5281/zenodo.3757305.Previously Published Datasets: Allen Brain Observatory: Allen Institute, 2016, http://observatory.brain-map.org/visualcoding/, http://observatory.brain-map.org/visualcoding/

Article and author information

Author details

Yann Sweeney

Department of Bioengineering, Imperial College London, London, United Kingdom

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-2164-2438
Claudia Clopath

Department of Bioengineering, Imperial College London, London, United Kingdom

For correspondence
c.clopath@imperial.ac.uk

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-4507-8648

Funding

Biotechnology and Biological Sciences Research Council (BB/N013956/1,BB/N019008/1)

Claudia Clopath

Wellcome (200790/Z/16/Z)

Claudia Clopath

Engineering and Physical Sciences Research Council (EP/R035806/1)

Claudia Clopath

Simons Foundation (564408)

Claudia Clopath

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.