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Efficient estimation of detailed single-neuron models (Huys et al. 2006)
infercell [15649]
"Biophysically accurate multicompartmental models of individual neurons ... depend on a large number of parameters that are difficult to estimate. ... We propose a statistical approach to the automatic estimation of various biologically relevant parameters, including 1) the distribution of channel densities, 2) the spatiotemporal pattern of synaptic input, and 3) axial resistances across extended dendrites. ... We demonstrate that the method leads to accurate estimations on a wide variety of challenging model data sets that include up to about 10,000 parameters (roughly two orders of magnitude more than previously feasible) and describe how the method gives insights into the functional interaction of groups of channels."
  • Neuron or other electrically excitable cell Show Other
  • Huys QJ, Ahrens MB, Paninski L (2006) Show Other
tom.morse@yale.edu
  • local backup copy of Huys et al. 2006 Show Other
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Revisions: 4
Last Time: 9/26/2017 4:07:11 PM
Reviewer: Tom Morse - MoldelDB admin
Owner: Tom Morse - MoldelDB admin