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dc.contributor.authorForger, Daniel B.  Concept link
dc.contributor.authorPaydarfar, David  Concept link
dc.contributor.authorClay, John R.  Concept link
dc.identifier.citationPLoS Computational Biology 7 (2011): e1002089en_US
dc.descriptionThe work is made available under the Creative Commons CC0 public domain dedication. The definitive version was published in PLoS Computational Biology 7 (2011): e1002089, doi:10.1371/journal.pcbi.1002089.en_US
dc.description.abstractAn important problem in neuronal computation is to discern how features of stimuli control the timing of action potentials. One aspect of this problem is to determine how an action potential, or spike, can be elicited with the least energy cost, e.g., a minimal amount of applied current. Here we show in the Hodgkin & Huxley model of the action potential and in experiments on squid giant axons that: 1) spike generation in a neuron can be highly discriminatory for stimulus shape and 2) the optimal stimulus shape is dependent upon inputs to the neuron. We show how polarity and time course of post-synaptic currents determine which of these optimal stimulus shapes best excites the neuron. These results are obtained mathematically using the calculus of variations and experimentally using a stochastic search methodology. Our findings reveal a surprising complexity of computation at the single cell level that may be relevant for understanding optimization of signaling in neurons and neuronal networks.en_US
dc.description.sponsorshipThis work was supported by the Intramural Research Program of the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892 and NIH grant R01 HL718884 to DP. DBF is an AFOSR Young Investigator (FA 9550-08-01-0076).en_US
dc.publisherPublic Library of Scienceen_US
dc.rightsPublic Domain Dedication*
dc.titleOptimal stimulus shapes for neuronal excitationen_US

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