Statistics of spikes trains, synaptic plasticity and Gibbs distributions
B. Cessac, H. Rostro, J.C. Vasquez, T. Vi\'eville
TL;DR
This paper introduces a mathematical framework for analyzing the statistical properties of spike trains generated by neural networks with synaptic plasticity, providing insights into their complex dynamics.
Contribution
It presents a novel mathematical approach to study spike train statistics in neural networks with synaptic plasticity, bridging neural dynamics and statistical analysis.
Findings
Framework enables detailed statistical analysis of spike trains.
Provides new insights into the role of synaptic plasticity.
Lays groundwork for future theoretical and computational studies.
Abstract
We introduce a mathematical framework where the statistics of spikes trains, produced by neural networks evolving under synaptic plasticity, can be analysed.
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Neural dynamics and brain function · Neural Networks and Applications