A spike-train probability model

Neural Computation

Volumn 13, Issue 8, 2001, Pages 1713-1720

  Kass, Robert E ^a   Ventura, Valérie ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; COMPUTER PROGRAM; COMPUTER SIMULATION; HUMAN; NERVE CELL; PHYSIOLOGY; POISSON DISTRIBUTION; PROBABILITY; STATISTICAL MODEL; TIME;

ANIMALS; COMPUTER SIMULATION; HUMANS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); NEURONS; POISSON DISTRIBUTION; PROBABILITY; SOFTWARE; TIME FACTORS;

EID: 0035432526     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/08997660152469314     Document Type: Article

References (17)

1. Barbieri, R., Quirk, M. C., Frank, L. M., Wilson, M. A., & Brown, E. N. (in press). Non-Poisson stimulus-response models of neural spike train activity. Neuroscience Methods.
2. Berry, M. J. and Meister, M. (1998). Refractoriness and neural precision. J. Neuroscience, 18, 2200-2211.
3. Brillinger, D. R. (1988). Maximum likelihood analysis of spike trains of interacting nerve cells. Biol. Cyber., 59, 189-200.
4. Brown, E. N., Frank, L. M., Tang, D., Quirk, M. C., & Wilson, M. A. (1998). A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells. J. Neurosci., 18, 7411-7425.
5. Cox, D. R., & Lewis, P. A. W. (1972). Multivariate point processes. In Proc. 6th Berkeley Symp. Math. Statist. Prob. 3, (pp. 401-448). Berkeley: University of California Press.
6. Daley, D. J., & Vere-Jones, D. (1988). Introduction to the theory of point processes. New York: Springer-Verlag.
7. DiMatteo, I., Genovese, C. R., & Kass, R. E. (2000). Bayesian curve fitting with free-knot splines. In press.
8. McCullagh, P., & Nelder, J. A. (1989). Generalized linear models (2d ed.). New York: Chapman and Hall.
9. Miller, M. I. and Mark, K. E. (1992). A statistical study of cochlear nerve discharge patterns in response to complex speech stimuli. J. Acoust. Soc. Am., 92, 202-209.
10. Olson, C. R., Gettner, S. N., Ventura, V., Carta, R., & Kass, R. E. (2000). Neuronal activity in macaque supplementary eye field during planning of saccades in response to pattern and spatial cues. J. Neurophys., 84, 1369-1384.
11. Optican, L. M., & Richmond, B. J. (1987). Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. III. Information theoretic analysis. J. Neurophysiol., 57, 162-178.
12. Oram, M. W., Wiener, M. C., Lestienne, R., & Richmond, B. J. (1999). Stochastic nature of precisely timed spike patterns in visual system neuronal responses. J. Neurophysiol., 81, 3021-3033.
13. Riehle, A., Grün, S., Diesmann, M., & Aertsen, A. (1997). Spike synchronization and rate modulation differentially involved in motor cortical function. Science, 278, 1950-1953.
14. Sanger, T. D. (1996). Probability density estimation for the interpretation of neural population codes. J. Neurophysiol., 76, 2790-2793.
15. Venables, W. N., & Ripley, B. D. (2000). Modern applied statistics with S-PLUS (3rd ed.). New York: Springer-Verlag.
16. Ventura, V., Carta, R., Kass, R. E., Gettner, S. N. & Olson, C. R. (in press). Statistical analysis of temporal evolution in single-neuron firing rates. Biostatistics.
17. Zhang, K., Ginzburg, I., McNaughton, B. L. & Sejnowski, T. J. (1998). Interpreting neuronal population activity by reconstruction: Unified framework with application to hippocampal place cells. J. Neurophysiol., 79, 1017-1044.