Characterizing spike trains with LempelZiv complexity
We review several applications of LempelZiv complexity to the characterization of neural responses. In particular, LempelZiv complexity allows to estimate the entropy of binned spike trains in an alternative way to the usual method based on the relative frequencies of words, with the definitive advantage of no requiring very long registers. We also use complexity to discriminate neural responses to different kinds of stimuli and to evaluate the number of states of neuronal sources.
spike trains lempelziv complexity entropy neuronal sources