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Testing for and Estimating Latency Effects for Poisson and Non-Poisson Spike Trains

vventura{at}stat.cmu.edu, Department of Statistics and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A.

Determining the variations in response latency of one or several neurons to a stimulus is of interest in different contexts. Two common problems concern correlating latency with a particular behavior, for example, the reaction time to a stimulus, and adjusting tools for detecting synchronization between two neurons. We use two such problems to illustrate the latency testing and estimation methods developed in this article. Our test for latencies is a formal statistical test that produces a p-value. It is applicable for Poisson and non-Poisson spike trains via use of the bootstrap. Our estimation method is model free, it is fast and easy to implement, and its performance compares favorably to other methods currently available.

This article has been cited by other articles:

				V. Ventura, C. Cai, and R. E. Kass Trial-to-Trial Variability and Its Effect on Time-Varying Dependency Between Two Neurons J Neurophysiol, October 1, 2005; 94(4): 2928 - 2939. [Abstract] [Full Text] [PDF]

				R. E. Kass, V. Ventura, and E. N. Brown Statistical Issues in the Analysis of Neuronal Data J Neurophysiol, July 1, 2005; 94(1): 8 - 25. [Abstract] [Full Text] [PDF]