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Article overview
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Steady State of an Inhibitory Neural Network | | P. L. Krapivsky
; S. Redner
; | | Date: |
24 May 2001 | | Journal: | Phys. Rev. E 64, 041906 (2001) | | Subject: | Adaptation and Self-Organizing Systems; Disordered Systems and Neural Networks; Quantitative Methods | nlin.AO cond-mat.dis-nn q-bio.QM | | Abstract: | We investigate the dynamics of a neural network where each neuron evolves according to the combined effects of deterministic integrate-and-fire dynamics and purely inhibitory coupling with K randomly-chosen "neighbors". The inhibition reduces the voltage of a given neuron by an amount Delta when one of its neighbors fires. The interplay between the integration and inhibition leads to a steady state which is determined by solving the rate equations for the neuronal voltage distribution. We also study the evolution of a single neuron and find that the mean lifetime between firing events equals 1+K*Delta and that the probability that a neuron has not yet fired decays exponentially with time. | | Source: | arXiv, nlin.AO/0105058 | | Other source: | [GID 357689] pmid11690051 | | Services: | Forum | Review | PDF | Favorites | |
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