Robert E. Kass, Ph.D.
Adjunct Professor, Neuroscience- Ph.D. University of Chicago (1980)
- Office: 229H Baker Hall
- Telephone:412-268-8723
- Fax:412-268-7828
- E-mail: kass@stat.cmu.edu
- Website: http://www.stat.cmu.edu/~kass/
Statistical analysis of neural data.
Research Summary:
For many years, Professor Kass worked on Bayesian statistical theory and methodology, which is now among the fastest-growing areas in the field of Statistics. Currently his group focuses on the statistical analysis of neural data, specializing in spike train analysis using single and multiple electrodes, in vivo and in vitro.
Kass and colleagues have developed methods for estimation and analysis of instantaneous firing rate of individual neurons; analysis of regularity and variability in firing rate functions across conditions and across neurons; analysis of non-Poisson spike trains; description of trial-to-trial variability; analysis of time-varying correlation across pairs of neurons; and real-time decoding of motor cortical signals for neural prostheses.
Selected Publications:
Brockwell, A.E., Rojas, A.L., and Kass, R.E. Recursive Bayesian decoding of motor cortical signals by particle filtering, Journal of Neurophysiology, 91: 1899--1907, 2004.
Brown, E.N., Kass, R.E., and Mitra, P.N. Multiple neural spike trains
analysis: state-of-the-art and future challenges. Nature Neuroscience, 7, 456--461, 2004.
Kass, R.E., Ventura, V., and Brown, E.N. Statistical issues in the analysis of neuronal data, Journal of Neurophysiology, 94: 8-25, 2005.
Ventura, V. Cai, C., and Kass, R.E. Trial-to-trial variability and its effect on time-varying dependence between two neurons, Journal of Neurophysiology, 94: 2928-2939, 2005.