Effects of Synaptic Noise and Filtering on the Frequency Response of Spiking Neurons

TLDR

Noise, especially from background synaptic activity, significantly alters the response dynamics of nonlinear neuronal systems. When synaptic noise is modeled as white, the firing‑rate modulation amplitude falls as 1/√ω with a 45° lag, but incorporating realistic synaptic filtering keeps a finite modulation at high frequencies and removes the lag, enabling unlagged neuronal responses to rapid inputs.

Abstract

Noise can have a significant impact on the response dynamics of a nonlinear system. For neurons, the primary source of noise comes from background synaptic input activity. If this is approximated as white noise, the amplitude of the modulation of the firing rate in response to an input current oscillating at frequency omega decreases as 1/square root[omega] and lags the input by 45 degrees in phase. However, if filtering due to realistic synaptic dynamics is included, the firing rate is modulated by a finite amount even in the limit omega-->infinity and the phase lag is eliminated. Thus, through its effect on noise inputs, realistic synaptic dynamics can ensure unlagged neuronal responses to high-frequency inputs.