Optimal stimulus shapes for neuronal excitation

PLoS Computational Biology

Volumn 7, Issue 7, 2011, Pages

  Forger, Daniel B ^a,b   Paydarfar, David ^b,c,d   Clay, John R ^b,e  

^a UNIVERSITY OF MICHIGAN   (United States)

^b MARINE BIOLOGICAL LABORATORY   (United States)

^c HARVARD UNIVERSITY   (United States)

^d UNIVERSITY OF MASSACHUSETTS MEDICAL SCHOOL   (United States)

^e NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALCULATIONS; CELL SIGNALING; ELECTROPHYSIOLOGY; NEURAL NETWORKS; STOCHASTIC SYSTEMS;

'CURRENT; ACTION-POTENTIALS; APPLIED CURRENT; CALCULUS OF VARIATIONS; HODGKIN-HUXLEY MODELS; LEAST ENERGY COST; SPIKE GENERATION; SQUID GIANT AXON; STOCHASTIC SEARCH; TIME COURSE;

NEURONS;

ACTION POTENTIAL; ARTICLE; CONTROLLED STUDY; DISCRIMINATIVE STIMULUS; HODGKIN HUXLEY EQUATION; INTRACELLULAR SIGNALING; NERVE CELL NETWORK; NERVE CELL STIMULATION; NOISE; POLARIZATION; POSTSYNAPTIC POTENTIAL; PROCESS OPTIMIZATION; SINGLE CELL ANALYSIS; SPIKE WAVE; STIMULUS RESPONSE; STOCHASTIC MODEL; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; CEPHALOPOD; ELECTROSTIMULATION; METHODOLOGY; NERVE FIBER; PH; PHYSIOLOGY; STATISTICS;

CEPHALOPODA;

ACTION POTENTIALS; ANIMALS; AXONS; COMPUTATIONAL BIOLOGY; DECAPODIFORMES; ELECTRIC STIMULATION; HYDROGEN-ION CONCENTRATION; MODELS, NEUROLOGICAL; STOCHASTIC PROCESSES;

EID: 79960966675     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002089     Document Type: Article

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