Welcome to


Applications for Spike-Train Correlational Analysis

Recurrence-Time History Matching (RTHM) is a method for graphically and statistically evaluating relationships between neurons in a local network, based on their temporal firing patterns.  The central algorithm is derived from similarity measures, specifically the Hausdorff metric.  RTHM enhances the resolution and sensitivity of the traditional cross-correlogram.  Software currently implemented includes RTHM analysis and graphical display, statistical analysis of correlational strength, spike-train manipulation, and a purely stochastic model for generating artificial spike trains for testing analytical methods.