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contributor authorJeff Moehlis
contributor authorEric Shea-Brown
contributor authorHerschel Rabitz
date accessioned2017-05-09T00:19:05Z
date available2017-05-09T00:19:05Z
date copyrightOctober, 2006
date issued2006
identifier issn1555-1415
identifier otherJCNDDM-25552#358_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/133262
description abstractVariational methods are used to determine the optimal currents that elicit spikes in various phase reductions of neural oscillator models. We show that, for a given reduced neuron model and target spike time, there is a unique current that minimizes a square-integral measure of its amplitude. For intrinsically oscillatory models, we further demonstrate that the form and scaling of this current is determined by the model’s phase response curve. These results reflect the role of intrinsic neural dynamics in determining the time course of synaptic inputs to which a neuron is optimally tuned to respond, and are illustrated using phase reductions of neural models valid near typical bifurcations to periodic firing, as well as the Hodgkin-Huxley equations.
publisherThe American Society of Mechanical Engineers (ASME)
titleOptimal Inputs for Phase Models of Spiking Neurons
typeJournal Paper
journal volume1
journal issue4
journal titleJournal of Computational and Nonlinear Dynamics
identifier doi10.1115/1.2338654
journal fristpage358
journal lastpage367
identifier eissn1555-1423
keywordsFire
keywordsBifurcation
keywordsCurrent
keywordsEquations
keywordsFiring (materials)
keywordsDynamics (Mechanics)
keywordsPhase space AND Trajectories (Physics)
treeJournal of Computational and Nonlinear Dynamics:;2006:;volume( 001 ):;issue: 004
contenttypeFulltext


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