Experience-Induced Neural Circuits That Achieve High Capacity

Neural Computation

Volumn 21, Issue 10, 2009, Pages 2715-2754

  Feldman, Vitaly ^a   Valiant, Leslie G ^b  

^a IBM ALMADEN RESEARCH CENTER   (United States)

^b HARVARD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; LEARNING SYSTEMS;

CIRCUIT MODIFICATION; COGNITIVE ACTIONS; CORTEXES; HIERARCHICAL MEMORY; HIGH CAPACITY; HIGH-CAPACITY; LOWER AVERAGE; NEURAL CIRCUITS; RESOURCE CONSTRAINT; SYNAPTIC STRENGTHS;

TIMING CIRCUITS;

ACTION POTENTIAL; ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; BRAIN CORTEX; COGNITION; COMPUTER SIMULATION; HUMAN; LEARNING; MEMORY; NERVE CELL; NERVE CELL NETWORK; NERVE TRACT; PHYSIOLOGY; SYNAPTIC TRANSMISSION;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; CEREBRAL CORTEX; COGNITION; COMPUTER SIMULATION; HUMANS; LEARNING; MEMORY; MODELS, NEUROLOGICAL; NERVE NET; NEURAL NETWORKS (COMPUTER); NEURAL PATHWAYS; NEURONS; SYNAPTIC TRANSMISSION;

EID: 67650271709     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/neco.2009.08-08-851     Document Type: Article

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