Efficient estimation of detailed single-neuron models (Huys et al. 2006)

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"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."
1 . Huys QJ, Ahrens MB, Paninski L (2006) Efficient estimation of detailed single-neuron models. J Neurophysiol 96:872-90 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Simulation Environment: MATLAB;
Model Concept(s): Methods;

Infer full compartmental model given only access to the voltage in the
compartments. This code is released in conjunction with the paper 

      Huys QJM, Ahrens M and Paninski L (2006): Efficient estimation of
      detailed single-neurone models

and can be downloaded from 


The paper can be downloaded from


Copyright Quentin Huys 2006


To use the code, unzip it, eg on a linux machine type
	gunzip hap06_code.gz

Which will create a directory with all the files. 

From within Matlab, change to that directory by typing eg
	cd hap06_code

Edit the file PARAM.M to change any parameters you want, like the number of
compartments in the cell, the size of each compartment, the amount of noise etc.
You should not have to edit any of the other files. 

To run the inference, simply type

and hit ENTER. Enjoy. 


I don't know of any bugs at the moment, but please do let me know if you find
any (qhuys@gatsby.ucl.ac.uk)