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Smoothing of, and parameter estimation from, noisy biophysical recordings (Huys & Paninski 2009)
Tom Morse - MoldelDB admin
publiccode [12317]
" ... Sequential Monte Carlo (“particle filtering”) methods, in combination with a detailed biophysical description of a cell, are used for principled, model-based smoothing of noisy recording data. We also provide an alternative formulation of smoothing where the neural nonlinearities are estimated in a non-parametric manner. Biophysically important parameters of detailed models (such as channel densities, intercompartmental conductances, input resistances, and observation noise) are inferred automatically from noisy data via expectation-maximisation. ..."
tom.morse@yale.edu
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Revisions: 5
Last Time: 9/26/2017 4:19:09 PM
Reviewer: Tom Morse - MoldelDB admin
Owner: Tom Morse - MoldelDB admin