Jittering spike trains carefully

Presented in lab meeting by Alex Ramirez on July 14th, 2010.

A Rate and History-Preserving Resampling Algorithm for Neural Spike Trains

by Matthew Harrison and Stuart Geman

In it the authors describe an algorithm that takes a spike train and jitters the spike times to create a new spike train which is maximally random while preserving the firing rate and recent spike-history of the original train.

Alex Ramirez : July 14

I'll be presenting a paper from Matt Harrsion.  In it the authors describe an algorithm that takes a spike train and jitters the spike times to create a new spike train which is maximally random while preserving the firing rate and recent spike-history of the original train.