estimates a set of linear filters (or "receptive fields") that best capture a neuron's input-output properties, using an information-theoretic objective that optimally combines spike-triggered average and spike-triggered covariance information. The filters can be considered as the first stage in a linear-nonlinear-Poisson (LNP) model of the neuron's response. They are sorted by informativeness, providing an estimate of the mutual information gained by the inclusion of each filter. Adapted from: http://pillowlab.cps.utexas.edu/code_iSTAC.html