Emerging Bayesian priors in a self-organizing recurrent network

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

Volumn 6792 LNCS, Issue PART 2, 2011, Pages 127-134

  Lazar, Andreea ^a   Pipa, Gordon ^b   Triesch, Jochen ^c  

^a MAX PLANCK INSTITUTE FOR BRAIN RESEARCH   (Germany)

^b UNIVERSITY OF OSNABRÜCK   (Germany)

^c FRANKFURT INSTITUTE FOR ADVANCED STUDIES   (Germany)

Author keywords

Bayesian inference; intrinsic plasticity; recurrent networks; Spontaneous activity; statistical priors; STDP

Indexed keywords

BAYESIAN INFERENCE; INTRINSIC PLASTICITY; RECURRENT NETWORKS; SPONTANEOUS ACTIVITY; STATISTICAL PRIORS; STDP;

BAYESIAN NETWORKS; INFERENCE ENGINES; NETWORK PERFORMANCE; RECURRENT NEURAL NETWORKS;

PROBABILITY DISTRIBUTIONS;

EID: 79959353033     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21738-8_17     Document Type: Conference Paper

References (8)

1. Fiser, J., Berkes, P., Orban, G., Lengyel, M.: Statistically optimal perception and learning: from behavior to neural representations. Trends Cogn. Sci. 14(3), 119-130 (2010)
2. Kver, H., Bao, S.: Cortical plasticity as a mechanism for storing bayesian priors in sensory perception. PLoS One 5(5), e10497 (2010)
3. Ringach, D.L.: Spontaneous and driven cortical activity: implications for computation. Curr. Opin. Neurobiol. 19(4), 439-444 (2009)
4. Han, F., Caporale, N., Dan, Y.: Reverberation of recent visual experience in spontaneous cortical waves. Neuron 60(2), 321-327 (2008)
5. Berkes, P., Orban, G.: Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment. Science 331(6013), 83-87 (2011)
6. Lazar, A., Pipa, G., Triesch, J.: SORN: a self-organizing recurrent neural network. Front Comput. Neurosci. 3, 23 (2009)
7. Jaeger, H.: The "echo state" approach to analysing and training recurrent neural networks. GMD Report 148, GMD - German National Research Institute for Computer Science (2001)
8. Maass, W., Natschläger, T., Markram, H.: Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation 14, 2531-2560 (2002)