Fast population coding (Huys et al. 2007)

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"Uncertainty coming from the noise in its neurons and the ill-posed nature of many tasks plagues neural computations. Maybe surprisingly, many studies show that the brain manipulates these forms of uncertainty in a probabilistically consistent and normative manner, and there is now a rich theoretical literature on the capabilities of populations of neurons to implement computations in the face of uncertainty. However, one major facet of uncertainty has received comparatively little attention: time. In a dynamic, rapidly changing world, data are only temporarily relevant. Here, we analyze the computational consequences of encoding stimulus trajectories in populations of neurons. ..."
1 . Huys QJ, Zemel RS, Natarajan R, Dayan P (2007) Fast population coding. Neural Comput 19:404-41 [PubMed]
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Model Type: Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Simulation Environment: MATLAB;
Model Concept(s): Methods;
% This code is released in conjunction with the paper 
%	Huys QJM, Zemel RS, Natarajan R and Dayan P (2006): Fast population
%	coding Neural Computation
% and can be downloaded from 
% This script is the main script. It generates a time-varying stimulus drawn
% from a Gaussian Process prior, produces a population spike train from it and
% infers the posterior over the stimulus given the spikes. It calls PARAM.M to
% set the parameters, and that should be the only script you should have to
% modify. It then calls SETUP.M to setup a few more things and GETSTIM.M to
% produce the time-varying stimuli. The iteration over these stimuli then
% begins, and for each stimulus a set of spikes is drawn by GETSPK.M, the
% true posterior distribution p(s_T|\xi) is inferred and plotted by PLOTS.M
% Copyright Quentin Huys 2006

clear all
param;		% get parameters
setup;		% setup a few more things
getstim;	% get the stimuli

for infsample = 1:infsamples
	getspk;		% get the spikes
	getinf;		% do the inference 
	plots;		% plot plots
	fprintf('infsample = %g\r',infsample)