Bayesian estimation of stimulus responses in Poisson spike trains

Neural Computation

Volumn 16, Issue 7, 2004, Pages 1325-1343

  Lehky, Sidney R ^a,b  

^a RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

^b NATIONAL INSTITUTE OF MENTAL HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ANIMAL; ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; COMPARATIVE STUDY; DRUG EFFECT; ELECTROSTIMULATION; NERVE CELL; PHYSIOLOGY; POISSON DISTRIBUTION; RADIATION EXPOSURE; STATISTICAL MODEL; TIME;

ACTION POTENTIALS; ANIMALS; BAYES THEOREM; ELECTRIC STIMULATION; LIKELIHOOD FUNCTIONS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NEURONS; POISSON DISTRIBUTION; TIME FACTORS;

EID: 2942618189     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976604323057407     Document Type: Article

References (5)

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2. Kay, S. M. (1993). Fundamentals of statistical signal processing: Estimation theory. Upper Saddle River, NJ: Prentice Hall.
3. Martignon, L., Deco, G., Laskey, K., Diamond, M., Freiwald, W., & Vaadia, E. (2000). Neural coding: Higher order temporal patterns in the neurostatistics of cell assemblies. Neural Comput., 12, 2621-2653.
4. Sanger, T. D. (1996). Probability density estimation for the interpretation of neural population codes. J. Neurophysiol., 76, 2790-2793.
5. 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.