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LICENSE | ||
README.md | ||
V1_reverse_correl.m | ||
V1_reverse_correl_m_seq.m | ||
binned_param.m | ||
calc_resp_complex.m | ||
dim_activation_conv.m | ||
filter_definitions_LGN.m | ||
filter_definitions_V1_simple.m | ||
gabor2D.m | ||
gauss2D.m | ||
image_circular_grating.m | ||
image_m_sequence.m | ||
image_square_grating.m | ||
images_dense_noise.m | ||
images_hartley_subspace.m | ||
images_m_sequence.m | ||
images_sparse_noise.m | ||
m_sequence.m | ||
maxsubplot.m | ||
odd.m | ||
plot_multi_unit_average_activity.m | ||
plot_orientation_tuning_shift.m | ||
plot_reverse_correl_freq.m | ||
plot_reverse_correl_freq_logprob.m | ||
plot_reverse_correl_image.m | ||
plot_reverse_correl_joint_orient.m | ||
plot_reverse_correl_orient.m | ||
plot_reverse_correl_orient_gaussfit.m | ||
plot_reverse_correl_orient_logprob.m | ||
plot_reverse_correl_param_surf.m | ||
plot_reverse_correl_tuning_width.m | ||
preprocess_V1_input.m | ||
reconstruct_V1RF.m |
README.md
This code implements the simulation results reported in:
Please cite this paper if this code is used in, or to motivate, any publications.
USAGE
This code was tested with MATLAB Version 7.10 (R2010a).
To use this software:
run matlab
cd to the directory containing this code
Some functions make use of the nansuite toolbox by Jan Glaescher, available at http://www.mathworks.com/matlabcentral/fileexchange/6837 and/or the fitgauss function by James R. Blake, available at http://www.mathworks. co.uk/matlabcentral/fileexchange/7489-fitgauss. These functions should thus be installed somewhere on your matlab path.
To perform any reverse correlation experiment edit the "imageType" parameter in V1_reverse_correl.m to the appropriate value, then execute:
>> [w,rcImage,rcFreq,rcOrient,rcBlank,rcJointOrient,fcStim]=V1_reverse_correl;
To analyse the results from an experiment Mapping Spatial RFs (ones with imageType='sparse', 'hartley', or 'dense') use:
>> plot_reverse_correl_image(w,rcImage,13,[1:8:32],[-2:6]);%Fig 2, Tables 1 and 2
Adjust the values in the 1st set of square brackets to select the nodes, and the values in the 2nd set of square brackets to select the time-lags, at which the recontructed RFs will be plotted.
To analyse the results from an experiment Measuring Orientation Tuning (ones with imageType='CDL2005', 'RHS1997', or 'RHS2003') use:
>> plot_reverse_correl_orient_logprob(w,rcOrient,rcBlank,[],[1:32],[-2:6],1,1);%Figs 3 and 4
or:
>> plot_reverse_correl_orient(w,rcOrient,[],[29],[-1:6]);%Fig 5
In both cases, adjust the values in the 2nd set of square brackets to select the nodes whose response is to be plotted, and the values in the 3rd set of square brackets to select the time-lags at which the tuning curves will be plotted.
To analyse the results from an experiment measuring the shift in preferred orientation as a function of the orientation of the preceding stimulus (i.e. one with imageType='Felsen02') use:
>> plot_orientation_tuning_shift(w,rcJointOrient,[1:32],[3]);%Fig 6
Adjust the values in the 1st set of square brackets to select the nodes, and the value in the 2nd set of square brackets to select the time-lag, for which the mean shift will be calculated.