Integrate-and-Fire Neurons Driven by Correlated Stochastic Input

  title={Integrate-and-Fire Neurons Driven by Correlated Stochastic Input},
  author={Emilio Salinas and Terrence J. Sejnowski},
  journal={Neural Computation},
Neurons are sensitive to correlations among synaptic inputs. However, analytical models that explicitly include correlations are hard to solve analytically, so their influence on a neuron's response has been difficult to ascertain. To gain some intuition on this problem, we studied the firing times of two simple integrate-and-fire model neurons driven by a correlated binary variable that represents the total input current. Analytic expressions were obtained for the average firing rate and… CONTINUE READING


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