Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule

Neural Networks

Volumn 48, Issue , 2013, Pages 109-124

  Beyeler, Michael ^a   Dutt, Nikil D ^a   Krichmar, Jeffrey L ^a,b  

^a Irvine   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Decision making; Object recognition; Spiking neural network; STDP; Supervised learning; Synaptic dynamics

Indexed keywords

DECISION MAKING PROCESS; GRAPHICS PROCESSING UNIT; PSYCHOPHYSICAL EXPERIMENTS; SPIKE-TIMING-DEPENDENT PLASTICITY; SPIKING NEURAL NETWORK(SNN); SPIKING NEURAL NETWORKS; STDP; SYNAPTIC DYNAMICS;

COMPUTER GRAPHICS; COMPUTER GRAPHICS EQUIPMENT; DECISION MAKING; DYNAMICS; ENCODING (SYMBOLS); NEURONS; OBJECT RECOGNITION; PROGRAM PROCESSORS; SUPERVISED LEARNING;

NEURAL NETWORKS;

ARTICLE; BRAIN FUNCTION; CATEGORIZATION; CLASSIFICATION; COMPUTER GRAPHICS; DECISION MAKING; LEARNING; MEMORY CONSOLIDATION; MODEL; NERVE CELL NETWORK; NERVE CELL PLASTICITY; NERVOUS SYSTEM CONDUCTANCE; NEUROBIOLOGY; PATTERN RECOGNITION; PRIORITY JOURNAL; PSYCHOMOTOR ACTIVITY; RESPONSE TIME; SIMULATOR; SPIKE TIMING DEPENDENT PLASTICITY; SPIKE WAVE; SPIKING NEURAL NETWORK; SYNAPSE; VISUAL DISCRIMINATION;

DECISION-MAKING; OBJECT RECOGNITION; SPIKING NEURAL NETWORK; STDP; SUPERVISED LEARNING; SYNAPTIC DYNAMICS;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; BRAIN; CALCIUM SIGNALING; COMPUTER SIMULATION; COMPUTER SYSTEMS; DATABASES, FACTUAL; DECISION THEORY; HAPLORHINI; HUMANS; MEMORY; MICROCOMPUTERS; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); NEURONAL PLASTICITY; NEURONS; REPRODUCIBILITY OF RESULTS; STOCHASTIC PROCESSES; SYNAPSES; VISUAL PERCEPTION;

EID: 84883397026     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2013.07.012     Document Type: Article

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