A spiking neuron model: Applications and learning

Neural Networks

Volumn 15, Issue 7, 2002, Pages 891-908

  Christodoulou, Chris ^a,b   Bugmann, Guido ^c   Clarkson, Trevor G ^b,d  

^a UNIVERSITY OF LONDON   (United Kingdom)

^b KING'S COLLEGE LONDON   (United Kingdom)

^c UNIVERSITY OF PLYMOUTH   (United Kingdom)

^d Radiocommunications Agency   (United Kingdom)

Author keywords

Directional selectivity; High firing variability; Inhibition; Motion detection; Postsynaptic delay learning; Spiking neuron model; Temporal Noisy Leaky Integrator; Temporal pattern detection

Indexed keywords

ALGORITHMS; BIOSENSORS; COMPUTER VISION; NEUROLOGY; ROBOTICS;

NEUROTRANSMITTERS;

NEURAL NETWORKS;

ACTION POTENTIAL; ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BIOLOGY; BRAIN CELL; DENDRITIC CELL; DYNAMICS; INHIBITION KINETICS; LEARNING; MEMBRANE POTENTIAL; MODEL; NERVE CELL; NERVE EXCITABILITY; NONHUMAN; PAPER; PRIORITY JOURNAL; REFRACTORY PERIOD; REPOLARIZATION; SOMATIC CELL; SPIKE; SYNAPSE; TEMPORAL NOISY LEAKY INTEGRATOR; TEMPORAL SUMMATION; TIME; TRAINING; VELOCITY; VISION;

ANALOG-DIGITAL CONVERSION; ANIMALS; ARTIFICIAL INTELLIGENCE; EXCITATORY POSTSYNAPTIC POTENTIALS; HUMANS; INHIBITION (PSYCHOLOGY); LEARNING; MEMBRANE POTENTIALS; MODELS, NEUROLOGICAL; MOTION; NEURAL NETWORKS (COMPUTER); NEURONS; STOCHASTIC PROCESSES; SYNAPSES; TIME FACTORS;

EID: 0036755131     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(02)00034-5     Document Type: Article

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