Supplementary Figure 2: Post-spike filter corrects for non-Poisson interval statistics.
From: Encoding and decoding in parietal cortex during sensorimotor decision-making
We use the time-rescaling theorem to transform the observed spike trains and check if the transformed interval statistics resulting from post-spike filter are consistent with the Poisson assumption. (a) Quantile-quantile plot of time-rescaled interval distribution. Diagonal represents Poisson process model assumptions. (b) Subsamples of adjacent time-rescaled inter-spike intervals. Note the uniformity of the intervals resulting from the model with the post-spike filter. The post-spike filter decorrelates the consecutive intervals, which is consistent with the Poisson assumption, indicated by the reduction of correlation coefficient (R) values.
