The accuracy of membrane potential reconstruction based on spiking receptive fields

A common technique used to study the response selectivity of neurons is to measure the relationship between sensory stimulation and action potential responses. Action potentials, however, are only indirectly related to the synaptic inputs that determine the underlying, subthreshold, response selectivity. We present a method to predict membrane potential, the measurable result of the convergence of synaptic inputs, based on spike rate alone and then test its utility by comparing predictions to actual membrane potential recordings from simple cells in primary visual cortex. Using a noise stimulus, we found that spike rate receptive fields were in precise correspondence with membrane potential receptive fields (R(2) = 0.74). On average, spike rate alone could predict 44% of membrane potential fluctuations to dynamic noise stimuli, demonstrating the utility of this method to extract estimates of subthreshold responses. We also found that the nonlinear relationship between membrane potential and spike rate could also be extracted from spike rate data alone by comparing predictions from the noise stimulus with the actual spike rate. Our analysis reveals that linear receptive field models extracted from noise stimuli accurately reflect the underlying membrane potential selectivity and thus represent a method to generate estimates of the underlying average membrane potential from spike rate data alone.