Valerie Ventura Associate Research Professor, Statistics Carnegie Mellon University Phone: (412) 268-4249 Fax: (412) 268-7828 Email: vventura@stat.cmu.edu Lab Website: http://lib.stat.cmu.edu/~vventura/

Ph. D., University of Oxford, U. K. Research Interests Models for neuronal firing patterns. Algorithms for neural prosthetes. Spike sorting. Functional connectivity. Bootstrap methods. Recent Publications Ventura V: Spike train decoding without spike sorting. Neural Computation, (in press), 2007. Kass RE, Ventura V: Spike count correlation increases with length of time interval in the presence of trial-to-trial variation. Neural Computation,18: 2583-2591, 2006. Canty AJ, Davison AC, Hinkley DV, Ventura V: Bootstrap diagnostics and remedies. The Canadian Journal of Statistics, 34: 5-27, 2006. (2006 CJS best paper award) Ventura V, Cai C, and Kass RE: Statistical assessment of time-varying dependence between two neurons. J. Neurophysiology, 94: 2940-2947, 2005. Ventura V, Cai C, and Kass RE: Trial-to-trial variability and its effect on time-varying dependence between two neurons. J. Neurophysiology, 94: 2928-2939, 2005. Kass RE, Ventura V, and Brown EN: Statistical issues in the analysis of neuronal data. J. Neurophysiology, 94: 8-25, 2005. Ventura V: Testing for, and estimating latency effects for Poisson and non-Poisson spike trains. Neural Computation, 16(11): 2323-2350, 2004. Ventura V, Paciorek CJ, and Risbey JS: Controlling the proportion of falsely-rejected hypotheses when conducting multiple tests with climatological data. Journal of Climate, 17(22): 4343-4356, 2004.