Title: Conditional inference for assessing the statistical significance of neural spiking patterns

Speaker: Matt Harrison, Carnegie Mellon University

Date/Time: Tuesday, February 24, 2009, 9:00 – 10:00am

Location: CSRI Building/Room 90 (Sandia NM)

Brief Abstract: Conditional inference has proven useful for exploratory analysis of neurophysiological point process data.  I will illustrate this approach and then focus on a specific sub-problem: random generation of binary matrices with margin constraints.  Sequential importance sampling (SIS) is an effective technique for approximate uniform sampling of binary matrices with specified margins.  I will describe how to simplify and improve existing SIS procedures using improved asymptotic enumeration and dynamic programming (DP).  The DP approach is interesting because it facilitates generalizations.

CSRI POC: Suzanne Rountree, (505) 844-4379