Weight dependence in BCM leads to adjustable synaptic competition

Albesa-González, Albert; Froc, Maxime; Williamson, Oliver; van Rossum, Mark C.W.

Abstract

Models of synaptic plasticity have been used to better understand neural development as well as learning and memory. One prominent classic model is the Bienenstock-Cooper-Munro (BCM) model that has been particularly successful in explaining plasticity of the visual cortex. Here, in an effort to include more biophysical detail in the BCM model, we incorporate 1) feedforward inhibition, and 2) the experimental observation that large synapses are relatively harder to potentiate than weak ones, while synaptic depression is proportional to the synaptic strength. These modifications change the outcome of unsupervised plasticity under the BCM model. The amount of feed-forward inhibition adds a parameter to BCM that turns out to determine the strength of competition. In the limit of strong inhibition the learning outcome is identical to standard BCM and the neuron becomes selective to one stimulus only (winner-take-all). For smaller values of inhibition, competition is weaker and the receptive fields are less selective. However, both BCM variants can yield realistic receptive fields.

Citation

Albesa-González, A., Froc, M., Williamson, O., & van Rossum, M. C. (2022). Weight dependence in BCM leads to adjustable synaptic competition. Journal of Computational Neuroscience, 50(4), 431-444. https://doi.org/10.1007/s10827-022-00824-w

• Journal Article Type: Article
• Acceptance Date: Jun 8, 2022
• Online Publication Date: Jun 29, 2022
• Publication Date: 2022-11
• Deposit Date: Jun 29, 2022
• Publicly Available Date: Jun 29, 2022
• Journal: Journal of Computational Neuroscience
• Print ISSN: 0929-5313
• Electronic ISSN: 1573-6873
• Publisher: Springer Science and Business Media LLC
• Peer Reviewed: Peer Reviewed
• Volume: 50
• Issue: 4
• Pages: 431-444
• DOI: https://doi.org/10.1007/s10827-022-00824-w
• Keywords: Cellular and Molecular Neuroscience; Cognitive Neuroscience; Sensory Systems
• Public URL: https://nottingham-repository.worktribe.com/output/8765883
• Publisher URL: https://link.springer.com/article/10.1007/s10827-022-00824-w