Effects of focal brain damage on political behaviour across different political ideologies (Brain, 2025)

Shan Siddiqi

Political Intensity Map is available here://neurovault.org/collections/20530/

Leave-one-out cross-validation MATLAB code: https://zenodo.org/records/15319409

Leave-one-out cross-validation MATLAB code:

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function [r p LOOpredictor LOOmaps] = LOO(zmaps,measure,covariates)

%Leave one out analysis using an M x N matrix of zmaps and an N x 1 matrix

%of measurements to predict.


s = size(measure,1);


h = waitbar(0,’wait’);


if nargin==2

for i=1:s

waitbar(i/s);

tmp = zmaps;

tmp2 = measure;

tmp(:,i) = [];

tmp2(i) = [];

LOOmaps(:,i) = corr(tmp’,tmp2,’rows’,’complete’);

end


for i=1:s

tmp = zmaps(:,i);

LOOmap = LOOmaps(:,i);

% LOOmap(LOOmap>0)=0;

tmp2 = corr(tmp,LOOmap,’rows’,’complete’);

% tmp2 = corr(tmp,LOOmaps(:,i),’rows’,’complete’);

LOOpredictor(i) = atanh(tmp2);

end

[r p] = corr(LOOpredictor’,measure,’rows’,’complete’);


else

for i=1:s

waitbar(i/s);

tmp = zmaps;

tmp2 = measure;

tmp3 = covariates;

tmp(:,i) = [];

tmp2(i) = [];

tmp3(i,:)=[];

LOOmap = partialcorr(tmp’,tmp2,tmp3,’rows’,’complete’);

tmpmap = zmaps(:,i);

LOOpredictor(i) = atanh(corr(tmpmap,LOOmap,’rows’,’complete’));

end

[r p] = partialcorr(LOOpredictor’,measure,covariates);

end

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