What is it about?

Neurons in the brain exchange information through a junction called synapse and a change in synaptic efficacy (synaptic plasticity) is considered to be an elementary process constituting our learning and memory. Although we know a rule under which every single synapse changes its efficacy, we need to know a macroscopic efficacy change of ten thousands of synapses because a single synapse contributes only negligibly. Here we demonstrate that a statistical theory based on so-called Fokker-Planck equation provides a perfect tool to predict a macroscopic efficacy change of a population of synapses, which corresponds to a visible change in information transmission in the networks of neurons in the brain.

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Why is it important?

A previous study calculated a macroscopic efficacy change of a population of synapses only numerically, meaning that the macroscopic outcome corresponding to each different single-synapse rule is known only after each run of numerical calculation. Our semi-analytic method based on the Fokker-Planck equation gives a clear insight into how a macroscopic behavior changes upon a change in a single-synapse plasticity rule. Our analysis, therefore, deepens our understanding of the meaning of each feature of a single-synapse plasticity rule which varies depending on a kind of neurons and an animal species to which a neuron belongs to.

Perspectives

The proposed method provides a way of calculating how an information processing changes in a system consisting of a single neuron innervated by tens of thousands of neurons. This study paves a way to understand a more realistic neural system in which a large number of neurons innervating mutually.

Dr Hideyuki Cateau
Tokyo Institute of Technology

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This page is a summary of: A Stochastic Method to Predict the Consequence of Arbitrary Forms of Spike-Timing-Dependent Plasticity, Neural Computation, March 2003, The MIT Press,
DOI: 10.1162/089976603321192095.
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