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Merge pull request #37 from nguyen-td/feature
Add PAC
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| Original file line number | Diff line number | Diff line change |
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| % Outputs: | ||
| % b_orig - ROI x ROI bispectrum | ||
| % b_anti - ROI x ROI antisymmetrized bispectrum | ||
| % b_orig_norm - ROI x ROI normalized bispectrum | ||
| % b_anti_norm - ROI x ROI normalized antisymmetrized bispectrum | ||
| % b_orig_norm - ROI x ROI bicoherence (normalized by threenorm) | ||
| % b_anti_norm - ROI x ROI antisymmetrized bicoherence (normalized by threenorm) | ||
| % | ||
| % Copyright (C) Franziska Pellegrini, [email protected] | ||
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| segleng = params.segleng; | ||
| segshift = params.segshift; | ||
| epleng = params.epleng; | ||
| filt = params.filt; | ||
| fcomb = params.fcomb; | ||
| fs = params.fs; | ||
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| fres = fs; | ||
| frqs = sfreqs(fres, fs); | ||
| freqinds_low = [find(frqs==filt.low) find(frqs==filt.high-filt.low)]; | ||
| freqinds_up = [find(frqs==filt.low) find(frqs==filt.high)]; | ||
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| for proi = 1:nroi | ||
| % extract all frequencies in the selected bands | ||
| size_low = size(fcomb.low, 2); | ||
| size_high = size(fcomb.high, 2); | ||
| inds_low = frqs >= fcomb.low(1) & frqs <= fcomb.low(size_low); | ||
| inds_high = frqs >= fcomb.high(1) & frqs <= fcomb.high(size_high); | ||
| frqs_low = frqs(inds_low); | ||
| frqs_high = frqs(inds_high); | ||
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| % determine all frequency combinations | ||
| [m, n] = ndgrid(frqs_low, frqs_high); | ||
| frqs_combs = [m(:),n(:)]; | ||
| n_combs = size(frqs_combs, 1); | ||
| warning('PAC is going to be estimated on %d frequency pair(s).', n_combs); | ||
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| freqinds_low = zeros(n_combs, 2); | ||
| freqinds_up = zeros(n_combs, 2); | ||
| for i = 1:n_combs | ||
| low = frqs_combs(i,1); | ||
| high = frqs_combs(i,2); | ||
| freqinds_low(i,:) = [find(frqs == low) find(frqs == high - low)]; | ||
| freqinds_up(i,:) = [find(frqs == low) find(frqs == high)]; | ||
| end | ||
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| for proi = 1:nroi | ||
| for aroi = proi:nroi | ||
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| % upper freqs | ||
| X = data([proi aroi],:,:); | ||
| [bs_up,~] = data2bs_event(X(:,:)', segleng, segshift, epleng, freqinds_up); | ||
| biv_orig_up = ([abs(bs_up(1, 2, 2)) abs(bs_up(2, 1, 1))]); | ||
| xx = bs_up - permute(bs_up, [2 1 3]); %Bkmm - Bmkm | ||
| biv_anti_up = ([abs(xx(1, 2, 2)) abs(xx(2, 1, 1))]); | ||
| [bs_up,~] = data2bs_event(X(:,:)', segleng, segshift, epleng, freqinds_up); | ||
| biv_orig_up = ([abs(bs_up(1, 2, 2, :)) abs(bs_up(2, 1, 1, :))]); | ||
| xx = bs_up - permute(bs_up, [2 1 3 4]); %Bkmm - Bmkm | ||
| biv_anti_up = ([abs(xx(1, 2, 2, :)) abs(xx(2, 1, 1, :))]); | ||
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| % normalized by threenorm | ||
| [RTP_up,~]=data2bs_threenorm(X(:,:)',segleng,segshift,epleng,freqinds_up); | ||
| bicoh_up=bs_up./sqrt(RTP_up); | ||
| [RTP_up,~] = data2bs_threenorm(X(:,:)', segleng, segshift, epleng, freqinds_up); | ||
| bicoh_up = bs_up ./ RTP_up; | ||
| bicoh_up = mean(bicoh_up, 4); | ||
| biv_orig_up_norm = ([abs(bicoh_up(1, 2, 2)) abs(bicoh_up(2, 1, 1))]); | ||
| xx=bicoh_up-permute(bicoh_up, [2 1 3]); | ||
| xx = bicoh_up-permute(bicoh_up, [2 1 3]); | ||
| biv_anti_up_norm = ([abs(xx(1, 2, 2)) abs(xx(2, 1, 1))]); | ||
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| % lower freqs | ||
| [bs_low,~] = data2bs_event(X(:,:)', segleng, segshift, epleng, freqinds_low); | ||
| biv_orig_low = ([abs(bs_low(1, 2, 2)) abs(bs_low(2, 1, 1))]); | ||
| xx = bs_low - permute(bs_low, [2 1 3]); | ||
| biv_anti_low =([abs(xx(1, 2, 2)) abs(xx(2, 1, 1))]); | ||
| biv_orig_low = ([abs(bs_low(1, 2, 2, :)) abs(bs_low(2, 1, 1, :))]); | ||
| xx = bs_low - permute(bs_low, [2 1 3, 4]); | ||
| biv_anti_low =([abs(xx(1, 2, 2, :)) abs(xx(2, 1, 1, :))]); | ||
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| % normalized by threenorm | ||
| [RTP_low,~]=data2bs_threenorm(X(:,:)',segleng,segshift,epleng,freqinds_low); | ||
| bicoh_low=bs_low./sqrt(RTP_low); | ||
| [RTP_low,~] = data2bs_threenorm(X(:,:)', segleng, segshift, epleng, freqinds_low); | ||
| bicoh_low = bs_low ./ RTP_low; | ||
| bicoh_low = mean(bicoh_low, 4); | ||
| biv_orig_low_norm = ([abs(bicoh_low(1, 2, 2)) abs(bicoh_low(2, 1, 1))]); | ||
| xx=bicoh_low-permute(bicoh_low, [2 1 3]); | ||
| xx = bicoh_low-permute(bicoh_low, [2 1 3]); | ||
| biv_anti_low_norm = ([abs(xx(1, 2, 2)) abs(xx(2, 1, 1))]); | ||
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| b_orig(aroi,proi) = mean([biv_orig_up(1) biv_orig_low(1)]); % mean across the two possible bispec combinations | ||
| b_orig(aroi,proi) = mean([biv_orig_up(1) biv_orig_low(1)]); | ||
| b_orig(proi,aroi) = mean([biv_orig_up(2) biv_orig_low(2)]); | ||
| b_anti(aroi,proi) = mean([biv_anti_up(1) biv_anti_low(1)]); | ||
| b_anti(proi,aroi) = mean([biv_anti_up(2) biv_anti_low(2)]); | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,61 @@ | ||
| % Test PAC implementation for different inputs: single frequencies and frequency bands. | ||
| %% Run pipeline | ||
| clear | ||
| eeglab | ||
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| eeglabp = fileparts(which('eeglab.m')); | ||
| EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/')); | ||
| EEG = pop_resample( EEG, 100); | ||
| EEG = pop_epoch( EEG, { }, [-0.5 1.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes'); | ||
| EEG = pop_select( EEG, 'trial',1:30); | ||
| [ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG); | ||
| eeglab redraw; | ||
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| EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ... | ||
| 'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),... | ||
| 'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),... | ||
| 'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] ); | ||
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| EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'functions','supportfiles','head_modelColin27_5003_Standard-10-5-Cap339.mat'), ... | ||
| 'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1); | ||
| EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','LORETA-Talairach-BAs','nPCA',3); | ||
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| %% Test bispectrum for single frequency inputs | ||
| low = 10; | ||
| high = 50; | ||
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| fcomb.low = low; | ||
| fcomb.high = high; | ||
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| EEG1 = pop_roi_connect(EEG, 'methods', {'PAC', 'MIM', 'COH'}, 'fcomb', fcomb); % test all 3 connectivity functions (data2spwctrgc, data2strgcmim, roi_pac) | ||
| EEG2 = pop_roi_connect(EEG, 'methods', {'PAC'}, 'fcomb', fcomb, 'bs_outopts', 4); % compute only b_orig, b_orig_norm | ||
| EEG3 = pop_roi_connect(EEG, 'methods', {'PAC'}, 'fcomb', fcomb, 'bs_outopts', 5); % compute only b_anti, b_anti_norm | ||
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| %% Test bispectrum for frequency band inputs | ||
| low = [4 8]; | ||
| high = [48 50]; | ||
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| fcomb.low = low; | ||
| fcomb.high = high; | ||
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| tic | ||
| EEG4 = pop_roi_connect(EEG, 'methods', {'PAC', 'MIM', 'COH'}, 'fcomb', fcomb); % test all 3 connectivity functions (data2spwctrgc, data2strgcmim, roi_pac)toc | ||
| toc | ||
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| %% Test PAC plotting | ||
| % Test for single frequency inputs | ||
| pop_roi_connectplot(EEG1, 'measure', 'pac', 'plotmatrix', 'on'); | ||
| pop_roi_connectplot(EEG1, 'measure', 'pac_anti', 'plotmatrix', 'on'); | ||
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| % Provoke errors by plotting bispectral tensors that do not exist | ||
| pop_roi_connectplot(EEG2, 'measure', 'pac_anti', 'plotmatrix', 'on'); % bs_outopts 4 means only original bispectra are computed, so cannot plot anti | ||
| pop_roi_connectplot(EEG3, 'measure', 'pac', 'plotmatrix', 'on'); % bs_outopts 5 means only antisymm. bispectra are computed, so cannot plot normal bispectrum | ||
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| % Test for frequency bands | ||
| pop_roi_connectplot(EEG4, 'measure', 'pac', 'plotmatrix', 'on'); | ||
| pop_roi_connectplot(EEG4, 'measure', 'pac_anti', 'plotmatrix', 'on'); | ||
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| % plot MIM and COH as a sanity check | ||
| pop_roi_connectplot(EEG1, 'measure', 'mim', 'plotmatrix', 'on'); | ||
| pop_roi_connectplot(EEG1, 'measure', 'coh', 'plotmatrix', 'on'); | ||
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