Universal Statistical Behavior of Neural Spike Trains

Abstract

The statistical properties of spike trains generated by a sensory neuron are studied. It is shown that the spike trains exhibit universal statistical behavior over short times, modulated by a strongly stimulus-dependent behavior over long times. This decomposition is accounted for by a “frequency integrator” model, under conditions of time scale separation. We provide explicit formulas for the statistical properties in both the universal and the stimulus-dependent regimes, which are in very good agreement with the data. The universal regime is characterized by a dimensionless free parameter, which is observed experimentally to remain constant under different external stimuli.