Bayesian inference with efficient neural population codes

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7552 LNCS, Issue PART 1, 2012, Pages 523-530

  Wei, Xue Xin ^a   Stocker, Alan A ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Neural encoding; Optimal decoding; Population vector

Indexed keywords

BAYESIAN INFERENCE; ESTIMATION BIAS; FIRING RATES; INTEGRATION TIME; NEURAL ENCODING; NEURAL INFORMATION PROCESSING; NEURAL MECHANISMS; NEURAL POPULATIONS; OPTIMAL DECODING; PHYSIOLOGICAL PARAMETERS; SENSORY NEURONS; TUNING CURVE;

BAYESIAN NETWORKS; DATA PROCESSING; DECODING; INFERENCE ENGINES; NEURAL NETWORKS; NEURONS; OPTIMIZATION; PHYSIOLOGICAL MODELS;

ENCODING (SYMBOLS);

EID: 84867680146     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33269-2_66     Document Type: Conference Paper

References (13)

1. Burgess, A.: Visual signal detection. III. On Bayesian use of prior knowledge and cross correlation. Journal of Optical Society of America A 2(9), 1498 (1985)
2. Stocker, A.A., Simoncelli, E.P.: Noise characteristics and prior expectations in human visual speed perception. Nature Neuroscience 9(4), 578-585 (2006)
3. Girshick, A.R., Landy,M.S., Simoncelli, E.P.: Cardinal rules: visual orientation perception reflects knowledge of environmental statistics. Nature Neuroscience 14(7), 926-932 (2011)
4. Sanborn, A.N., Dayan, P.: Optimal decisions for contrast discrimination. Journal of Vision 11(14) (2011)
5. Knill, D.: Robust cue integration: A Bayesian model and evidence from cue-conflict studies with stereoscopic and figure cues to slant. Journal of Vision 7(7), 1-24 (2007)
6. Jazayeri, M., Movshon, J.A.: Optimal representation of sensory information by neural populations. Nature Neuroscience 9, 690 (2006)
7. Ma, W.J., Beck, J.M., Latham, P.E., Pouget, A.: Bayesian inference with probabilistic population codes. Nature Neuroscience 9, 1432 (2006)
8. Simoncelli, E.P.: Optimal Estimation in Sensory Systems. In: The New Cognitive Neuroscience, 4th edn. MIT Press (2009)
9. Barlow, H.B.: Possible principles underlying the transformation of sensory messages. In: Rosenblith,W.A. (ed.) Sensory Communication, pp. 217-234. MIT Press, Cambridge (1961)
10. Ganguli, D., Simoncelli, E.P.: Implicit encoding of prior probabilities in optimal neural populations. In: Adv. Neural Information Processing Systems NIPS, vol. 23, pp. 658-666 (2011)
11. Fischer, B.J.: Bayesian estimates from heterogeneous population codes. In: Proc. IEEE Int'l. Joint Conf. on Neural Networks. IEEE (2010)
12. Georgopoulos, A.P., Schwartz, A.B., Kettner, R.E.: Neuronal population coding of movement direction. Science 233(4771), 1416 (1986)
13. Miller, K.D., Troyer, T.W.: Neural noise can explain expansive, power-law nonlinearities in neural response functions. J. Neurophysiol. 7(2), 653-659 (2002)