Fast population coding (Huys et al. 2007)

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Accession:93394
"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. ..."
Reference:
1 . Huys QJ, Zemel RS, Natarajan R, Dayan P (2007) Fast population coding. Neural Comput 19:404-41 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Methods;
Implementer(s):
% PARAM.M
%
% 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 
%
%	http://www.gatsby.ucl.ac.uk/~qhuys/code.html
%
% This script sets the parameters. It is called by MAIN.M. You shold not have to
% modify anything but this script. The main variable to set is RW. 
%
% Copyright Quentin Huys 2006


rw = 1;			% set rw=1 for OU prior, and rw=0 for smooth prior

%==============================================================================
%			PARAMETERS SPECIFIC TO OU AND SMOOTH STIMULI
%==============================================================================

%.......................................Smooth prior
if rw==0;	tau = .05;		% tau is the main (temporal) parameter
		lambda = .2;		% lambda scales the prior
		maxrate = 144;		% max firing rate (scaled by delta later)
%.......................................OU prior
elseif rw==1;	tau = .35;		% tau scales the prior here 
		lambda = 2e-4;		% lambda is the main (temporal) parameter
		maxrate = 108;		% max firing rate (scaled by delta later)
end

%==============================================================================
%			GENERAL PARAMETERS 
%==============================================================================
n = 100;		% number of neurones
ds = n;			% resolution of the distribution to be plotted. 
infsamples = 1;		% how many different trajectories

lim = 1;		% size of the stimulus space to be plotted.
sigma=.1;		% width of (normalised) tuning functions

Tmax = .3;		% Total length of time [s]
delta = .001;		% Timestep [s];