Bayesian representation learning in the cortex regulated by acetylcholine

Neural Networks

Volumn 17, Issue 10, 2004, Pages 1391-1400

  Hirayama, Junichiro ^a   Yoshimoto, Junichiro ^a,b   Ishii, Shin ^a,c  

^a NARA INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

^b OKINAWA INSTITUTE OF SCIENCE AND TECHNOLOGY GRADUATE UNIVERSITY   (Japan)

^c JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

Author keywords

Acetylcholine; Cortical representation; Model selection; On line learning; Probabilistic principal component analysis; Variational Bayes method

Indexed keywords

ACETYLCHOLINE (ACH); BAYESIAN REPRESENTATION LEARNING;

COMPUTER SIMULATION; DATA ACQUISITION; HEURISTIC METHODS; MATHEMATICAL MODELS; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY;

NEURAL NETWORKS;

ACETYLCHOLINE;

ADAPTATION; ARTICLE; BAYES THEOREM; BRAIN CORTEX; COGNITION; ENVIRONMENTAL FACTOR; LEARNING; MATHEMATICAL MODEL; NERVE CELL NETWORK; NEUROTRANSMISSION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROBABILITY; RECOGNITION; SIMULATION; TECHNIQUE;

ACETYLCHOLINE; ANIMALS; BAYES THEOREM; CEREBRAL CORTEX; HUMANS; LEARNING; MODELS, NEUROLOGICAL; PATTERN RECOGNITION, VISUAL;

EID: 8444252961     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2004.06.006     Document Type: Article

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