From the Statistical Physics of Disordered Systems to Neuroscience

Nicolas Brunel, Rémi Monasson, Haim Sompolinsky, J. Leo van Hemmen

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This chapter studies the bridges and differences between the statistical physics of disordered systems, as developed notably in the context of spin glass theory, and problems in neuroscience. In a first contribution (Sec. 25.1), Nicolas Brunel, Rémi Monasson and Haim Sompolinsky first recall the main lines of the statistical physics approach to neural networks models as developed in the 1980s and 1990s. They then survey more recent developments at the interface between statistical physics and neuroscience, including the inference of synaptic plasticity rules and the statistics of synaptic connectivity. Finally they present the Tempotron model for learning temporal patterns. In a second contribution (Sec. 25.2), Leo van Hemmen discusses the difference between real spin glasses, neuronal networks (of real biological neurons) and neural networks (of artificial neurons); with illustrations ranging from site-disorder models of spin glasses to temporal coding in neuronal networks and unlearning.

Original languageEnglish
Title of host publicationSpin Glass Theory and Far Beyond
Subtitle of host publicationReplica Symmetry Breaking after 40 Years
PublisherWorld Scientific Publishing Co.
Pages499-521
Number of pages23
ISBN (Electronic)9789811273926
ISBN (Print)9789811273919
DOIs
StatePublished - 1 Jan 2023

Bibliographical note

Publisher Copyright:
© 2023 World Scientific Publishing.

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