| % function call_subs_processing | |
| % executes the entire signal processing, etc for each motor subject | |
| %% add path | |
| addpath dc_files | |
| warning('off','signal:psd:PSDisObsolete'); %annoying | |
| %% define subject and rhythm frequency range ("bands") | |
| subjects=[ | |
| 'bp';... | |
| 'cc';... | |
| 'zt';... | |
| 'jp';... | |
| 'ht';... | |
| 'mv';... | |
| 'wc';... | |
| 'wm';... | |
| 'jc';... | |
| ]; | |
| %% | |
| bands=[[4 8];[8 12];[12 20]]; | |
| % bands=[12 20]; | |
| % bands=[4 8]; | |
| % bands=[8 12]; | |
| disp('subject, coh-Zm0, k, coh-Zmd, k, coh-rhy, k, rhy-zmd, k, rhy-zm0, k, zm0-zmd, k ') % this is the key for stats given at the end | |
| %% cycle through subjects | |
| for q=1:size(subjects,1) | |
| subject=subjects(q,:); | |
| % disp(subject) | |
| %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
| % % Checklist for each dataset: | |
| % % Steps 1-3 done ahead of time, all variables in file 'data/#subject#_fingerflex.mat | |
| % % 1 - reject bad channels - "data" variable has this already removed | |
| % % 2 - get rendering and locations - brain rendering structure is in "brain" variable | |
| % % 3 - assign electrodes to anatomic clusters - positions are in "locs" variable (channel number x 3), with labels in "elec_regions" | |
| % % translation code for "elec_labels": | |
| % 1 ? dorsal M1 | |
| % 2 - rolandic | |
| % 3 ? dorsal S1 | |
| % 4 ? ventral sensorimotor (M1+ S1) | |
| % 6 ? frontal (non-rolandic) | |
| % 7 ? parietal (non-rolandic) | |
| % 8 ? temporal | |
| % 9 ? occipital | |
| %% % 4 - identify events | |
| pts = gen_inv_pts(subject); %note, in paper, these were checked / cleaned manually as well - this is first pass. check if you use | |
| %% % 5 - decoupling to get broadband (lnA), then timecourse | |
| load(['data/' subject '/' subject '_fingerflex'],'data'), data=car(data); | |
| [spectra]=calc_dg_spectra(data,pts); | |
| [nspectra]=calc_nspectra(spectra); | |
| [pc_weights, pc_vecs, pc_vals, f]=dg_pca_step(subject,nspectra); | |
| save(['data/' subject '/' subject '_decoupled'],'*spectra','pts','pc_*','f'), | |
| clear data *spectra pts pc_* | |
| % get timeseries of lnA | |
| gen_pc_all(subject) | |
| %% % 6 - generate all pac palettes | |
| gen_pac_matrix_all(subject) | |
| %% % 7 - generate broadband amplitude correlations | |
| get_lnAcorr_tot(subject) | |
| %% analyses for each band | |
| for k=1:size(bands,1) | |
| band=bands(k,:); | |
| disp(num2str(band)) | |
| %% 8 - rhythm extraction and trial by trial rhythm amplitude, broadband amplitude, and pac amplitudes, Zmod corrected | |
| % note that trial-by-trial data calls "stim" | |
| get_rhythm_dist(subject, band) | |
| %% 9 - Generate whole run coherence | |
| get_coh_tot(subject,band) | |
| %% 10 - Generate whole run amplitude correlations for each rhythm | |
| get_rhy_ampcorr_tot(subject,band) | |
| %% 11 - Generate trial-by-trial coherence and amplitude cross-correlation (as well as broadband cross-correlation) for most significant thumb and forefinger electrodes | |
| for dtype=1:2 | |
| task_cohere_corr(subject, band, dtype) | |
| end | |
| %% 12 statistics in individual channels for | |
| for dtype=1:2 | |
| % get stats to find dg_chan - primary electrode to use | |
| load(['data/' subject '/' subject '_fband_' num2str(band(1)) '_' num2str(band(2))],'pts','*block*','*type*','dz_*','tr_sc'), % load rhythm - which band is irrelevant - only need lnA | |
| [lnA_r, lnA_p, lnA_m, lnA_s, rhy_r, rhy_p, rhy_m, rhy_s, Zmd_r, Zmd_p, Zmd_m, Zmd_s]=dg_block_stats(lnA_blocks, rhythm_blocks, dz_dist, tr_sc, beh_types, baseline_type); | |
| [tmp dg_chan]=max(abs(lnA_r(:,dtype))); clear *_s *_m *_r *_p tmp *_blocks *_type* tr_sc dz_dist | |
| gen_chan_triggered(subject,dg_chan,dtype,band) | |
| end | |
| end | |
| %% 13 coherence - overlap statistics. Calculate then display. | |
| coh_overlap_work(subject) | |
| load(['data/' subject '/' subject '_coh_OL'], 'OL_*','OLM_*','p_val_*', 'rs_kurt_*') | |
| disp([subject ', ' num2str(OL_pct_coh_Zm0) ', ' num2str(p_val_coh_Zm0) ', ' num2str(OL_pct_coh_zmd) ', ' num2str(p_val_coh_zmd) ', ' num2str(OL_pct_coh_rhy) ', ' num2str(p_val_coh_rhy) ', ' num2str(OL_pct_rhy_zmd) ', ' num2str(p_val_rhy_zmd) ', ' num2str(OL_pct_Zm0_rhy) ', ' num2str(p_val_Zm0_rhy) ', ' num2str(OL_pct_Zm0_zmd) ', ' num2str(p_val_Zm0_zmd)]) | |
| end | |