Effects of stimulus transformations on estimated functional properties of mechanosensory neurons

Abstract

The functional properties of a neural sensory cell or small ensembles are often characterized by analyzing response-conditioned stimulus ensembles. Many widely used analytical methods, like STA, Wiener kernels or STRF, rely on simple statistics of those ensembles. They also tend to rely on simple noise models for the residuals of the conditional ensemble. However, in many cases the response-conditioned stimulus set has a more complex structure than any simple noise model. If not taken explicitly into account, this difference can bias the estimates of many simple statistics, and distort the estimated functionality of a neural sensory system. Here we present analysis of two transformation-based noise sources in the rat vibrissal system: temporal jitter and temporal dilation invariance. We analyze the perturbations for several cells and correct their effect on the spike-triggered average.