A microcircuit model of the frontal eye fields (Heinzle et al. 2007)

 Download zip file 
Help downloading and running models
Accession:110022
" ... we show that the canonical circuit (Douglas et al. 1989, Douglas and Martin 1991) can, with a few modifications, model the primate FEF. The spike-based network of integrate-and-fire neurons was tested in tasks that were used in electrophysiological experiments in behaving macaque monkeys. The dynamics of the model matched those of neurons observed in the FEF, and the behavioral results matched those observed in psychophysical experiments. The close relationship between the model and the cortical architecture allows a detailed comparison of the simulation results with physiological data and predicts details of the anatomical circuit of the FEF."
Reference:
1 . Heinzle J, Hepp K, Martin KA (2007) A microcircuit model of the frontal eye fields. J Neurosci 27:9341-53 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Spatio-temporal Activity Patterns; Action Selection/Decision Making; Vision;
Implementer(s):
% makeall_inputs defines all the inputs for the simulation of the FEF.
% These inputs are: Dorsal visual input and Fixation input to FEF; 
% Ventral feature specific input to Recognition Module.
%
% created: Jakob Heinzle 01/07


clear inputs
inputs.ninputs=0;

% Add the visual input to layer 4
name='VisualInput';type='exc';to='E4';inarray=inarray1;retinotopic=1;
MeanInp=0.056;NoiseLevel=1;t_on=tvisual_on;t_trans_off=tvisual_transoff;t_off=tvisual_off;sustained_level=0.5;
add_input;

% Add the fixation input to fixation neurons
name='FixationInput';type='exc';to='IFIX';inarray=1;retinotopic=0;
MeanInp=0.2;NoiseLevel=1;t_on=tfix_on;t_trans_off=tmax;t_off=tfix_off;sustained_level=1;
add_input;

% Pro-Saccade feature detectors.
name='ProFeature';type='exc';to='EFp';inarray=(featarray==1);retinotopic=1;
MeanInp=0.178;NoiseLevel=0;t_on=tvisual_on;t_trans_off=tvisual_off;t_off=tvisual_off;sustained_level=1;
add_input;

% Fixation feature detectors.
name='FixFeature';type='exc';to='EFf';inarray=(featarray==2);retinotopic=1;
MeanInp=0.178;NoiseLevel=0;t_on=tvisual_on;t_trans_off=tvisual_off;t_off=tvisual_off;sustained_level=1;
add_input;

% Anti-Saccade feature detectors.
name='AntiFeature';type='exc';to='EFa';inarray=(featarray==3);retinotopic=1;
MeanInp=0.178;NoiseLevel=0;t_on=tvisual_on;t_trans_off=tvisual_off;t_off=tvisual_off;sustained_level=1;
add_input;

% Space feature detectors. Used to recognize spaces at the fovea.
name='SpaceFeature';type='exc';to='EFspace';inarray=(inarray1(11)==0);retinotopic=0;
MeanInp=0.178;NoiseLevel=0;t_on=tvisual_on;t_trans_off=tvisual_off;t_off=tvisual_off;sustained_level=1;
add_input;


if select_task==7
% Anti-Saccade feature during delay
name='AntiDuringDelay';type='exc';to='EFa';inarray=inputs.external{3}.inarray;retinotopic=1;
MeanInp=0.178;NoiseLevel=0;t_on=tvisual_on+stimdelay;t_trans_off=tvisual_off+stimdelay;t_off=tvisual_off+stimdelay;sustained_level=1;
add_input;

% Visual Input during delay. This input is not really needed and could be 
% left away, if the anti-saccade input is consiedered to be not directly
% visual, or as salient as the first visual input.
name='VisualDuringDelay';type='exc';to='E4';inarray=inarray1;retinotopic=1;
MeanInp=0.056;NoiseLevel=1;t_on=tvisual_on+stimdelay;t_trans_off=tvisual_off+stimdelay;t_off=tvisual_off+stimdelay;sustained_level=0.5;
add_input;
end