Homeostatic scaling of excitability in recurrent neural networks

PLoS Computational Biology

Volumn 8, Issue 5, 2012, Pages

  Remme, Michiel W H ^a,b   Wadman, Wytse J ^a  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b HUMBOLDT UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

RECURRENT NEURAL NETWORKS;

A-STABLE; ACTIVITY-DEPENDENT; EXCITATORY NEURONS; INHIBITORY NEURONS; NETWORK STABILITY; NEURAL ACTIVITY; QUIESCENT STATE; RECURRENT NETWORKS; SATURATED STATE; SCALINGS;

NEURONS;

ADAPTATION; ARTICLE; CELL FUNCTION; CELL POPULATION; HOMEOSTATIC SCALING OF INTRINSIC EXCITABILITY; NEGATIVE FEEDBACK; NERVE CELL CHARACTERISTICS AND FUNCTIONS; NERVE CELL EXCITABILITY; NERVE CELL INHIBITION; NERVE CELL NETWORK; NERVE CELL PLASTICITY; NERVE CONDUCTION; ACTION POTENTIAL; ANIMAL; BIOLOGICAL MODEL; BIOLOGICAL RHYTHM; COMPUTER SIMULATION; EXCITATORY POSTSYNAPTIC POTENTIAL; FEEDBACK SYSTEM; HOMEOSTASIS; HUMAN; NERVE CELL; PHYSIOLOGY; SYNAPTIC TRANSMISSION;

ACTION POTENTIALS; ANIMALS; BIOLOGICAL CLOCKS; COMPUTER SIMULATION; EXCITATORY POSTSYNAPTIC POTENTIALS; FEEDBACK, PHYSIOLOGICAL; HOMEOSTASIS; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NEURONS; SYNAPTIC TRANSMISSION;

EID: 84863690891     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002494     Document Type: Article

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