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Efficient inference of synaptic plasticity rule with Gaussian process regression.

Shirui Chen1,2, Qixin Yang3,2, Sukbin Lim2,4

  • 1Department of Applied Mathematics, University of Washington, Lewis Hall 201, Box 353925, Seattle, WA 98195-3925, USA.

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|March 7, 2023
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Summary
This summary is machine-generated.

Gaussian process regression (GPR) efficiently infers synaptic plasticity rules from sparse, noisy data. This method is flexible and robust, aiding understanding of learning and memory mechanisms.

Keywords:
Cognitive neuroscienceNeuroscienceSystems neuroscience

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Machine Learning

Background:

  • Understanding synaptic plasticity is crucial for elucidating learning and memory.
  • Current methods for inferring plasticity rules face challenges with sparse and noisy experimental data.

Purpose of the Study:

  • To develop and evaluate an efficient method for inferring synaptic plasticity rules across diverse experimental conditions.
  • To assess the performance of Gaussian process regression (GPR) in recovering firing-rate dependence of plasticity.

Main Methods:

  • Investigated biologically plausible models of synaptic plasticity.
  • Applied Gaussian process regression (GPR), a nonparametric Bayesian approach, to infer plasticity rules.
  • Evaluated GPR's performance on simulated sparse and noisy data, considering direct synaptic weight changes and indirect neural activity measures.

Main Results:

  • GPR demonstrated superior performance compared to other methods assuming low-rankness or smoothness.
  • GPR effectively recovered firing-rate dependence even with sparse and noisy data.
  • The method showed robustness across various plasticity rules and noise levels, and could simultaneously infer multiple rules.

Conclusions:

  • Gaussian process regression (GPR) offers a flexible and efficient approach for inferring synaptic plasticity.
  • Its effectiveness in low-sampling regimes makes it suitable for contemporary experimental techniques.
  • GPR facilitates the inference of a broader range of synaptic plasticity models, advancing neuroscience research.