Journal
JOURNAL OF COMPUTATIONAL NEUROSCIENCE
Volume 36, Issue 3, Pages 469-481Publisher
SPRINGER
DOI: 10.1007/s10827-013-0481-5
Keywords
Recurrent network; Synchronization; Quadratic integrate and fire neuron; Theta neuron; Random networks; Mean field theory
Funding
- Gatsby Charitable Foundation
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We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.
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