Statistical Physics approach to dendritic computation: The excitable-wave mean-field approximation
Neurons and Cognition
2012-01-18 v2 Statistical Mechanics
Cellular Automata and Lattice Gases
Biological Physics
Subcellular Processes
Abstract
We analytically study the input-output properties of a neuron whose active dendritic tree, modeled as a Cayley tree of excitable elements, is subjected to Poisson stimulus. Both single-site and two-site mean-field approximations incorrectly predict a non-equilibrium phase transition which is not allowed in the model. We propose an excitable-wave mean-field approximation which shows good agreement with previously published simulation results [Gollo et al., PLoS Comput. Biol. 5(6) e1000402 (2009)] and accounts for finite-size effects. We also discuss the relevance of our results to experiments in neuroscience, emphasizing the role of active dendrites in the enhancement of dynamic range and in gain control modulation.
Cite
@article{arxiv.1109.2036,
title = {Statistical Physics approach to dendritic computation: The excitable-wave mean-field approximation},
author = {Leonardo L. Gollo and Osame Kinouchi and Mauro Copelli},
journal= {arXiv preprint arXiv:1109.2036},
year = {2012}
}
Comments
30 pages, 8 figures