Abstract
We study the dynamics of sparsely connected recurrent networks composed of excitatory and inhibitory integrate-and-fire (IF) neurons firing at low rates, and in particular cross-Correlations (CC) between spike times of pairs of neurons using both numerical simulations and a recent theory. CCs exhibit damped oscillations with a frequency which depends on synaptic time constants. Individual CCs are shown to depend weakly on synaptic connectivity. They depend more strongly on the firing rates of individual neurons.
Associated with CNRS, Paris 6 and Paris 7 universities.
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Brunel, N. (1997). Cross-correlations in sparsely connected recurrent networks of spiking neurons. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020128
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DOI: https://doi.org/10.1007/BFb0020128
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