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(Neural Computation. 2002;14:2057-2110.)
© 2002 The MIT Press


Letter

Dynamics of the Firing Probability of Noisy Integrate-and-Fire Neurons

Nicolas Fourcaud

fourcaud{at}biomedicale.univ-paris5.fr, Laboratoire de Physique Statistique, École Normale Supérieure, 75231 Paris Cedex 05, France, and Neurophysique et Physiologie du Système Moteur, UFR biomédicale, Université Paris 5 René Descartes 45, 75006 Paris, France

Nicolas Brunel

brunel{at}biomedicale.univ-paris5.fr, Laboratoire de Physique Statistique, École Normale Supérieure, 75231 Paris Cedex 05, France, and Neurophysique et Physiologie du Système Moteur, UFR biomédicale, Université Paris 5 René Descartes 45, 75006 Paris, France

Cortical neurons in vivo undergo a continuous bombardment due to synaptic activity, which acts as a major source of noise. Here, we investigate the effects of the noise filtering by synapses with various levels of realism on integrate-and-fire neuron dynamics. The noise input is modeled by white (for instantaneous synapses) or colored (for synapses with a finite relaxation time) noise. Analytical results for the modulation of firing probability in response to an oscillatory input current are obtained by expanding a Fokker-Planck equation for small parameters of the problem—when both the amplitude of the modulation is small compared to the background firing rate and the synaptic time constant is small compared to the membrane time constant. We report here the detailed calculations showing that if a synaptic decay time constant is included in the synaptic current model, the firing-rate modulation of the neuron due to an oscillatory input remains finite in the high-frequency limit with no phase lag. In addition, we characterize the low-frequency behavior and the behavior of the high-frequency limit for intermediate decay times. We also characterize the effects of introducing a rise time to the synaptic currents and the presence of several synaptic receptors with different kinetics. In both cases, we determine, using numerical simulations, an effective decay time constant that describes the neuronal response completely.




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