Tutorial 28: Scripting

1 function tutorial_introduction(tutorial_dir, reports_dir) 2 % TUTORIAL_INTRODUCTION: Script that runs all the Brainstorm introduction tutorials. 3 % 4 % INPUTS: 5 % - tutorial_dir : Directory where the sample_introduction.zip file has been unzipped 6 % - reports_dir : Directory where to save the execution report (instead of displaying it) 7 8 % @============================================================================= 9 % This function is part of the Brainstorm software: 10 % https://neuroimage.usc.edu/brainstorm 11 % 12 % Copyright (c) University of Southern California & McGill University 13 % This software is distributed under the terms of the GNU General Public License 14 % as published by the Free Software Foundation. Further details on the GPLv3 15 % license can be found at http://www.gnu.org/copyleft/gpl.html. 16 % 17 % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE 18 % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY 19 % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF 20 % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY 21 % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. 22 % 23 % For more information type "brainstorm license" at command prompt. 24 % =============================================================================@ 25 % 26 % Author: Francois Tadel, 2016-2017 27 28 29 % ===== FILES TO IMPORT ===== 30 % Output folder for reports 31 if (nargin < 2) || isempty(reports_dir) || ~isdir(reports_dir) 32 reports_dir = []; 33 end 34 % You have to specify the folder in which the tutorial dataset is unzipped 35 if (nargin == 0) || isempty(tutorial_dir) || ~file_exist(tutorial_dir) 36 error('The first argument must be the full path to the dataset folder.'); 37 end 38 % Subject name 39 SubjectName = 'Subject01'; 40 % Build the path of the files to import 41 AnatDir = fullfile(tutorial_dir, 'sample_introduction', 'anatomy'); 42 Run1File = fullfile(tutorial_dir, 'sample_introduction', 'data', 'S01_AEF_20131218_01_600Hz.ds'); 43 Run2File = fullfile(tutorial_dir, 'sample_introduction', 'data', 'S01_AEF_20131218_02_600Hz.ds'); 44 NoiseFile = fullfile(tutorial_dir, 'sample_introduction', 'data', 'S01_Noise_20131218_02_600Hz.ds'); 45 % Check if the folder contains the required files 46 if ~file_exist(Run1File) 47 error(['The folder ' tutorial_dir ' does not contain the folder from the file sample_introduction.zip.']); 48 end 49 % Re-inialize random number generator 50 if (bst_get('MatlabVersion') >= 712) 51 rng('default'); 52 end 53 54 55 %% ===== TUTORIAL #1: CREATE PROTOCOL ================================================ 56 % =================================================================================== 57 disp([10 'DEMO> Tutorial #1: Create protocol' 10]); 58 % The protocol name has to be a valid folder name (no spaces, no weird characters...) 59 ProtocolName = 'TutorialIntroduction'; 60 % Start brainstorm without the GUI 61 if ~brainstorm('status') 62 brainstorm nogui 63 end 64 % Delete existing protocol 65 gui_brainstorm('DeleteProtocol', ProtocolName); 66 % Create new protocol 67 gui_brainstorm('CreateProtocol', ProtocolName, 0, 0); 68 % Start a new report 69 bst_report('Start'); 70 % Reset colormaps 71 bst_colormaps('RestoreDefaults', 'meg'); 72 % Set the current display mode to 'butterfly' 73 bst_set('TSDisplayMode', 'butterfly'); 74 75 76 %% ===== TUTORIAL #2: IMPORT ANATOMY ================================================= 77 % =================================================================================== 78 disp([10 'DEMO> Tutorial #2: Import anatomy' 10]); 79 % Process: Import FreeSurfer folder 80 bst_process('CallProcess', 'process_import_anatomy', [], [], ... 81 'subjectname', SubjectName, ... 82 'mrifile', {AnatDir, 'FreeSurfer'}, ... 83 'nvertices', 15000, ... 84 'nas', [127, 213, 139], ... 85 'lpa', [ 52, 113, 96], ... 86 'rpa', [202, 113, 91]); 87 % This automatically calls the SPM registration procedure because the AC/PC/IH points are not defined 88 89 90 91 %% ===== TUTORIAL #3: EXPLORE ANATOMY ================================================ 92 % =================================================================================== 93 disp([10 'DEMO> Tutorial #3: Explore anatomy' 10]); 94 % Get subject definition 95 sSubject = bst_get('Subject', SubjectName); 96 % Get MRI file and surface files 97 MriFile = sSubject.Anatomy(sSubject.iAnatomy).FileName; 98 CortexFile = sSubject.Surface(sSubject.iCortex).FileName; 99 HeadFile = sSubject.Surface(sSubject.iScalp).FileName; 100 % Display MRI 101 hFigMri1 = view_mri(MriFile); 102 hFigMri3 = view_mri_3d(MriFile, [], [], 'NewFigure'); 103 hFigMri2 = view_mri_slices(MriFile, 'x', 20); 104 pause(0.5); 105 % Close figures 106 close([hFigMri1 hFigMri2 hFigMri3]); 107 % Display scalp and cortex 108 hFigSurf = view_surface(HeadFile); 109 hFigSurf = view_surface(CortexFile, [], [], hFigSurf); 110 hFigMriSurf = view_mri(MriFile, CortexFile); 111 % Figure configuration 112 iTess = 2; 113 panel_surface('SetShowSulci', hFigSurf, iTess, 1); 114 panel_surface('SetSurfaceColor', hFigSurf, iTess, [1 0 0]); 115 panel_surface('SetSurfaceSmooth', hFigSurf, iTess, 0.5, 0); 116 panel_surface('SetSurfaceTransparency', hFigSurf, iTess, 0.8); 117 figure_3d('SetStandardView', hFigSurf, 'left'); 118 pause(0.5); 119 % Close figures 120 close([hFigSurf hFigMriSurf]); 121 122 123 124 %% ===== TUTORIAL #4: CHANNEL FILE =================================================== 125 % =================================================================================== 126 disp([10 'DEMO> Tutorial #4: Channel file' 10]); 127 % Process: Create link to raw files 128 sFilesRun1 = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 129 'subjectname', SubjectName, ... 130 'datafile', {Run1File, 'CTF'}, ... 131 'channelalign', 1); 132 sFilesRun2 = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 133 'subjectname', SubjectName, ... 134 'datafile', {Run2File, 'CTF'}, ... 135 'channelalign', 1); 136 sFilesNoise = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 137 'subjectname', SubjectName, ... 138 'datafile', {NoiseFile, 'CTF'}, ... 139 'channelalign', 0); 140 sFilesRaw = [sFilesRun1, sFilesRun2, sFilesNoise]; 141 % Process: Snapshot: Sensors/MRI registration 142 bst_process('CallProcess', 'process_snapshot', [sFilesRun1, sFilesRun2], [], ... 143 'target', 1, ... % Sensors/MRI registration 144 'modality', 1, ... % MEG (All) 145 'orient', 1, ... % left 146 'Comment', 'MEG/MRI Registration'); 147 148 % View sensors 149 hFig = view_surface(HeadFile); 150 hFig = view_channels(sFilesRun1.ChannelFile, 'MEG', 1, 1, hFig); 151 % Hide sensors 152 pause(0.5); 153 hFig = view_channels(sFilesRun1.ChannelFile, 'MEG', 0, 0, hFig); 154 % View coils 155 hFig = view_channels(sFilesRun1.ChannelFile, 'CTF', 1, 1, hFig); 156 % View helmet 157 pause(0.5); 158 hFig = view_helmet(sFilesRun1.ChannelFile, hFig); 159 pause(0.5); 160 close(hFig); 161 % Edit good/bad channel for current file 162 gui_edit_channel(sFilesRun1.ChannelFile); 163 pause(0.5); 164 % Unload everything 165 bst_memory('UnloadAll', 'Forced'); 166 167 168 169 %% ===== TUTORIAL #5: REVIEW RAW ===================================================== 170 % =================================================================================== 171 disp([10 'DEMO> Tutorial #5: Review raw' 10]); 172 % Process: Convert to continuous (CTF): Continuous 173 bst_process('CallProcess', 'process_ctf_convert', sFilesRaw, [], ... 174 'rectype', 2); % Continuous 175 176 % View recordings 177 hFigMeg = view_timeseries(sFilesRun1.FileName, 'MEG'); 178 hFigEeg = view_timeseries(sFilesRun1.FileName, 'Misc'); 179 hFigSel = view_timeseries(sFilesRun1.FileName, 'MEG', {'MLT11','MLT12','MLT13'}); 180 % Figure configuration 181 pause(0.5); 182 panel_record('SetTimeLength', 3); 183 panel_record('SetStartTime', 100); 184 panel_record('SetDisplayMode', hFigMeg, 'column'); 185 panel_montage('SetCurrentMontage', hFigMeg, 'CTF LT'); 186 % Set filters: panel_filter('SetFilters', LowPassEnabled, LowPassValue, HighPassEnabled, HighPassValue, SinRemovalEnabled, SinRemovalValue, MirrorEnabled, FullSourcesEnabled) 187 panel_filter('SetFilters', 1, 100, 1, 1, 0, [], 0, 0); 188 pause(0.5); 189 panel_record('SetDisplayMode', hFigMeg, 'butterfly'); 190 panel_montage('SetCurrentMontage', hFigMeg, ''); 191 % Close figures 192 close([hFigMeg hFigEeg hFigSel]); 193 194 195 196 %% ===== TUTORIAL #8: STIM DELAYS ==================================================== 197 % =================================================================================== 198 disp([10 'DEMO> Tutorial #8: Stim delays' 10]); 199 % Process: Detect: standard_fix 200 bst_process('CallProcess', 'process_evt_detect_analog', [sFilesRun1, sFilesRun2], [], ... 201 'eventname', 'standard_fix', ... 202 'channelname', 'UADC001', ... 203 'timewindow', [], ... 204 'threshold', 1.2, ... 205 'blanking', 0.2, ... 206 'highpass', 0, ... 207 'lowpass', 0, ... 208 'refevent', 'standard', ... 209 'isfalling', 0, ... 210 'ispullup', 0, ... 211 'isclassify', 0); 212 % Process: Detect: deviant_fix 213 bst_process('CallProcess', 'process_evt_detect_analog', [sFilesRun1, sFilesRun2], [], ... 214 'eventname', 'deviant_fix', ... 215 'channelname', 'UADC001', ... 216 'timewindow', [], ... 217 'threshold', 1.2, ... 218 'blanking', 0.2, ... 219 'highpass', 0, ... 220 'lowpass', 0, ... 221 'refevent', 'deviant', ... 222 'isfalling', 0, ... 223 'ispullup', 0, ... 224 'isclassify', 0); 225 % Process: Read from channel 226 bst_process('CallProcess', 'process_evt_read', [sFilesRun1, sFilesRun2], [], ... 227 'stimchan', 'UDIO001', ... 228 'trackmode', 1, ... % Value: detect the changes of channel value 229 'zero', 0); 230 231 % Process: Delete events 232 bst_process('CallProcess', 'process_evt_delete', [sFilesRun1, sFilesRun2], [], ... 233 'eventname', 'standard, deviant, button'); 234 % Process: Rename event (standard_fix>standard) 235 bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 236 'src', 'standard_fix', ... 237 'dest', 'standard'); 238 % Process: Rename event (deviant_fix>deviant) 239 bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 240 'src', 'deviant_fix', ... 241 'dest', 'deviant'); 242 % Process: Rename event (64>button) 243 bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 244 'src', '64', ... 245 'dest', 'button'); 246 247 248 249 %% ===== TUTORIAL #10: FREQUENCY FILTERS ============================================= 250 % =================================================================================== 251 disp([10 'DEMO> Tutorial #10: Frequency filters' 10]); 252 % Process: Sinusoid removal: 60Hz 120Hz 180Hz 300Hz 253 sFilesNotch = bst_process('CallProcess', 'process_notch', sFilesRaw, [], ... 254 'freqlist', [60, 120, 180], ... 255 'sensortypes', 'MEG', ... 256 'read_all', 0); 257 % Process: Power spectrum density (Welch) 258 sFilesPsd = bst_process('CallProcess', 'process_psd', [sFilesRaw, sFilesNotch], [], ... 259 'timewindow', [], ... 260 'win_length', 4, ... 261 'win_overlap', 50, ... 262 'clusters', {}, ... 263 'sensortypes', 'MEG', ... 264 'edit', struct(... 265 'Comment', 'Power', ... 266 'TimeBands', [], ... 267 'Freqs', [], ... 268 'ClusterFuncTime', 'none', ... 269 'Measure', 'power', ... 270 'Output', 'all', ... 271 'SaveKernel', 0)); 272 % Process: Snapshot: Frequency spectrum 273 bst_process('CallProcess', 'process_snapshot', sFilesPsd, [], ... 274 'target', 10, ... % Frequency spectrum 275 'modality', 1, ... % MEG (All) 276 'Comment', 'Power spectrum density'); 277 % Process: Delete folders 278 bst_process('CallProcess', 'process_delete', sFilesRaw, [], ... 279 'target', 2); % Delete folders 280 % Separate the three outputs 281 sFilesRun1 = {sFilesNotch(1).FileName}; 282 sFilesRun2 = {sFilesNotch(2).FileName}; 283 sFilesNoise = {sFilesNotch(3).FileName}; 284 285 286 287 %% ===== TUTORIAL #11: BAD CHANNELS ================================================== 288 % =================================================================================== 289 % % Process: Set bad channels 290 % sFiles = bst_process('CallProcess', 'process_channel_setbad', sFilesRun2, [], ... 291 % 'sensortypes', 'MRT51, MLO52, MLO42, MLO43'); 292 293 294 295 %% ===== TUTORIAL #12: ARTIFACTS DETECTION =========================================== 296 % =================================================================================== 297 disp([10 'DEMO> Tutorial #12: Artifacts detection' 10]); 298 % Process: Detect heartbeats 299 bst_process('CallProcess', 'process_evt_detect_ecg', [sFilesRun1, sFilesRun2], [], ... 300 'channelname', 'ECG', ... 301 'timewindow', [], ... 302 'eventname', 'cardiac'); 303 % Process: Detect eye blinks 304 bst_process('CallProcess', 'process_evt_detect_eog', [sFilesRun1, sFilesRun2], [], ... 305 'channelname', 'VEOG', ... 306 'timewindow', [], ... 307 'eventname', 'blink'); 308 % Process: Remove simultaneous 309 bst_process('CallProcess', 'process_evt_remove_simult', [sFilesRun1, sFilesRun2], [], ... 310 'remove', 'cardiac', ... 311 'target', 'blink', ... 312 'dt', 0.25, ... 313 'rename', 0); 314 315 316 317 %% ===== TUTORIAL #13: SSP =========================================================== 318 % =================================================================================== 319 disp([10 'DEMO> Tutorial #13: SSP' 10]); 320 % Process: SSP ECG: cardiac 321 bst_process('CallProcess', 'process_ssp_ecg', [sFilesRun1, sFilesRun2], [], ... 322 'eventname', 'cardiac', ... 323 'sensortypes', 'MEG', ... 324 'usessp', 0, ... 325 'select', 1); 326 % Process: SSP EOG: blink 327 bst_process('CallProcess', 'process_ssp_eog', sFilesRun1, [], ... 328 'eventname', 'blink', ... 329 'sensortypes', 'MEG', ... 330 'usessp', 0, ... 331 'select', [1 2]); 332 bst_process('CallProcess', 'process_ssp_eog', sFilesRun2, [], ... 333 'eventname', 'blink', ... 334 'sensortypes', 'MEG', ... 335 'usessp', 0, ... 336 'select', 1); 337 338 339 %% ===== TUTORIAL #14: BAD SEGMENTS ================================================== 340 % =================================================================================== 341 disp([10 'DEMO> Tutorial #14: Bad segments' 10]); 342 % Process: Detect other artifacts 343 bst_process('CallProcess', 'process_evt_detect_badsegment', [sFilesRun1, sFilesRun2], [], ... 344 'timewindow', [], ... 345 'sensortypes', 'MEG', ... 346 'threshold', 3, ... % 3 347 'isLowFreq', 1, ... 348 'isHighFreq', 1); 349 350 % Process: Rename event (1-7Hz > saccade) (Run02 only) 351 bst_process('CallProcess', 'process_evt_rename', sFilesRun2, [], ... 352 'src', '1-7Hz', ... 353 'dest', 'saccade'); 354 355 % Manual selection of saccades (cannot be done from the pipeline editor: manual edition of the structures) 356 sMatRun2 = in_bst_data(sFilesRun2{1}, 'F'); 357 iEvtSaccade = find(strcmpi({sMatRun2.F.events.label}, 'saccade')); 358 sMatRun2.F.events(iEvtSaccade).times = [30, 81.5, 104, 142.5, 167, 187.5, 246.5, 319; 31, 83, 105, 144, 168, 188.5, 248, 320]; 359 sMatRun2.F.events(iEvtSaccade).epochs = ones(1, size(sMatRun2.F.events(iEvtSaccade).times, 2)); 360 sMatRun2.F.events(iEvtSaccade).channels = []; 361 sMatRun2.F.events(iEvtSaccade).notes = []; 362 bst_save(file_fullpath(sFilesRun2{1}), sMatRun2, 'v6', 1); 363 364 % Process: SSP: saccade (Run02 only) 365 bst_process('CallProcess', 'process_ssp', sFilesRun2, [], ... 366 'timewindow', [], ... 367 'eventname', 'saccade', ... 368 'eventtime', [-0.2, 0.2], ... 369 'bandpass', [1.5, 7], ... 370 'sensortypes', 'MEG', ... 371 'usessp', 1, ... 372 'saveerp', 0, ... 373 'method', 1, ... 374 'select', 1); 375 % Process: Detect other artifacts (Run02 only) 376 bst_process('CallProcess', 'process_evt_detect_badsegment', sFilesRun2, [], ... 377 'timewindow', [], ... 378 'sensortypes', 'MEG', ... 379 'threshold', 3, ... % 3 380 'isLowFreq', 1, ... 381 'isHighFreq', 1); 382 383 % Process: Rename event (1-7Hz > bad_1-7Hz) 384 bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 385 'src', '1-7Hz', ... 386 'dest', 'bad_1-7Hz'); 387 % Process: Rename event (40-240Hz > bad_40-240Hz) 388 bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 389 'src', '40-240Hz', ... 390 'dest', 'bad_40-240Hz'); 391 % Process: Snapshot: SSP projectors 392 bst_process('CallProcess', 'process_snapshot', [sFilesRun1, sFilesRun2], [], ... 393 'target', 2, ... % SSP projectors 394 'Comment', 'SSP projectors'); 395 396 397 398 %% ===== TUTORIAL #15: IMPORT EVENTS ================================================= 399 % =================================================================================== 400 disp([10 'DEMO> Tutorial #15: Import events' 10]); 401 % Process: Import MEG/EEG: Events (Run01) 402 sFilesEpochs1 = bst_process('CallProcess', 'process_import_data_event', sFilesRun1, [], ... 403 'subjectname', SubjectName, ... 404 'condition', '', ... 405 'eventname', 'standard, deviant', ... 406 'timewindow', [], ... 407 'epochtime', [-0.100, 0.500], ... 408 'createcond', 0, ... 409 'ignoreshort', 1, ... 410 'usectfcomp', 1, ... 411 'usessp', 1, ... 412 'freq', [], ... 413 'baseline', [-0.1, -0.0017]); 414 % Process: Import MEG/EEG: Events (Run02) 415 sFilesEpochs2 = bst_process('CallProcess', 'process_import_data_event', sFilesRun2, [], ... 416 'subjectname', SubjectName, ... 417 'condition', '', ... 418 'eventname', 'standard, deviant', ... 419 'timewindow', [], ... 420 'epochtime', [-0.100, 0.500], ... 421 'createcond', 0, ... 422 'ignoreshort', 1, ... 423 'usectfcomp', 1, ... 424 'usessp', 1, ... 425 'freq', [], ... 426 'baseline', [-0.1, -0.0017]); 427 % Display raster plot 428 hFigRaster = view_erpimage({sFilesEpochs1.FileName}, 'erpimage', 'MEG'); 429 panel_display(); 430 bst_report('Snapshot', hFigRaster, sFilesEpochs1(1).FileName, 'ERP image'); 431 close(hFigRaster); 432 433 434 %% ===== TUTORIAL #16: AVERAGE ======================================================= 435 % =================================================================================== 436 disp([10 'DEMO> Tutorial #16: Average' 10]); 437 % Process: Average: By trial group (folder average) 438 sFilesAvg = bst_process('CallProcess', 'process_average', [sFilesEpochs1, sFilesEpochs2], [], ... 439 'avgtype', 5, ... % By trial groups (folder average) 440 'avg_func', 1, ... % Arithmetic average: mean(x) 441 'weighted', 0, ... 442 'keepevents', 1); 443 % Process: Delete events 'cardiac' 444 bst_process('CallProcess', 'process_evt_delete', sFilesAvg, [], ... 445 'eventname', 'cardiac'); 446 % Process: Snapshot: Recordings time series 447 bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 448 'target', 5, ... % Recordings time series 449 'modality', 1, ... % MEG (All) 450 'Comment', 'Evoked response'); 451 % Set colormap: global color scale 452 bst_colormaps('SetMaxMode', 'meg', 'global'); 453 % Process: Snapshot: Recordings topography (contact sheet) 454 bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 455 'target', 7, ... % Recordings topography (contact sheet) 456 'modality', 1, ... % MEG 457 'contact_time', [0, 0.350], ... 458 'contact_nimage', 15, ... 459 'Comment', 'Evoked response'); 460 461 % Process: Average+Stderr: By trial group (subject average) 462 sFilesAvgAll = bst_process('CallProcess', 'process_average', [sFilesEpochs1, sFilesEpochs2], [], ... 463 'avgtype', 6, ... % By trial group (subject average) 464 'avg_func', 7, ... % Arithmetic average + Standard error 465 'weighted', 0, ... 466 'keepevents', 1); 467 % Process: Delete events 'cardiac' 468 bst_process('CallProcess', 'process_evt_delete', sFilesAvgAll, [], ... 469 'eventname', 'cardiac'); 470 % Process: Delete events 'saccade' 471 bst_process('CallProcess', 'process_evt_delete', sFilesAvgAll, [], ... 472 'eventname', 'saccade'); 473 % Process: Snapshot: Recordings time series 474 bst_process('CallProcess', 'process_snapshot', sFilesAvgAll, [], ... 475 'target', 5, ... % Recordings time series 476 'modality', 1, ... % MEG (All) 477 'Comment', 'Evoked response'); 478 479 480 %% ===== TUTORIAL #17: EXPLORATION =================================================== 481 % =================================================================================== 482 disp([10 'DEMO> Tutorial #17: Bad segments' 10]); 483 % View averages 484 hFigMeg1 = view_timeseries(sFilesAvg(1).FileName, 'MEG'); 485 hFigMeg2 = view_timeseries(sFilesAvg(2).FileName, 'MEG'); 486 hFigEeg1 = view_timeseries(sFilesAvg(1).FileName, 'Misc'); 487 hFigEeg2 = view_timeseries(sFilesAvg(2).FileName, 'Misc'); 488 hFigTopo1 = view_topography(sFilesAvg(1).FileName, 'MEG', '2DSensorCap'); 489 hFigTopo2 = view_topography(sFilesAvg(2).FileName, 'MEG', '2DSensorCap'); 490 hFigTp2 = view_topography(sFilesAvg(3).FileName, 'MEG', '3DSensorCap'); 491 hFigTp3 = view_topography(sFilesAvg(3).FileName, 'MEG', '2DDisc'); 492 hFigTp4 = view_topography(sFilesAvg(3).FileName, 'MEG', '2DLayout'); 493 % Set time: 90ms 494 panel_time('SetCurrentTime', 0.090); 495 % Set filters: 40Hz low-pass, no high-pass 496 panel_filter('SetFilters', 1, 40, 0, [], 0, [], 0, 0); 497 % View selected sensors 498 SelectedChannels = {'MLC31', 'MLC32'}; 499 bst_figures('SetSelectedRows', SelectedChannels); 500 view_timeseries(sFilesAvg(4).FileName, [], SelectedChannels); 501 % Select time window 502 figure_timeseries('SetTimeSelectionManual', hFigMeg1, [0.070, 0.130]); 503 % Show sensors on 2DSensorCap topography 504 isMarkers = 1; 505 isLabels = 0; 506 figure_3d('ViewSensors', hFigTopo1, isMarkers, isLabels); 507 % Display time contact sheet for a figure 508 pause(0.5); 509 hContactFig = view_contactsheet( hFigTopo2, 'time', 'fig', [], 12, [0 0.120] ); 510 pause(0.5); 511 close(hContactFig); 512 513 514 515 %% ===== TUTORIAL #18: COLORMAPS ===================================================== 516 % =================================================================================== 517 disp([10 'DEMO> Tutorial #18: Colormaps' 10]); 518 % Set 'Meg' colormap to 'jet' 519 bst_colormaps('SetColormapName', 'meg', 'jet'); 520 pause(0.5); 521 % Set 'Meg' colormap to 'rwb' 522 bst_colormaps('SetColormapName', 'meg', 'cmap_rbw'); 523 % Set colormap to display absolute values 524 bst_colormaps('SetColormapAbsolute', 'meg', 1); 525 % Normalize colormap for each time frame 526 bst_colormaps('SetMaxMode', 'meg', 'local'); 527 % Hide colorbar 528 bst_colormaps('SetDisplayColorbar', 'meg', 0); 529 pause(0.5); 530 % Restore colormap to default values 531 bst_colormaps('RestoreDefaults', 'meg'); 532 % Edit good/bad channel for current file 533 gui_edit_channelflag(sFilesAvg(1).FileName); 534 % Close figures 535 pause(0.5); 536 bst_memory('UnloadAll', 'Forced'); 537 538 539 540 %% ===== TUTORIAL #20: HEAD MODEL ==================================================== 541 % =================================================================================== 542 disp([10 'DEMO> Tutorial #20: Head model' 10]); 543 % Process: Compute head model 544 bst_process('CallProcess', 'process_headmodel', sFilesAvg, [], ... 545 'comment', '', ... 546 'sourcespace', 1, ... 547 'meg', 3); % Overlapping spheres 548 % Get study structure 549 sStudy = bst_get('Study', sFilesAvg(1).iStudy); 550 % Show spheres 551 hFig = view_spheres(sStudy.HeadModel(sStudy.iHeadModel).FileName, sStudy.Channel.FileName, sSubject); 552 pause(0.5); 553 close(hFig); 554 555 556 557 %% ===== TUTORIAL #21: NOISE COVARIANCE ============================================== 558 % =================================================================================== 559 disp([10 'DEMO> Tutorial #21: Noise covariance' 10]); 560 % Process: Compute covariance (noise or data) 561 bst_process('CallProcess', 'process_noisecov', sFilesNoise, [], ... 562 'baseline', [], ... 563 'sensortypes', 'MEG, EEG, SEEG, ECOG', ... 564 'target', 1, ... % Noise covariance (covariance over baseline time window) 565 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 566 'identity', 0, ... 567 'copycond', 1, ... 568 'copysubj', 0, ... 569 'replacefile', 1); % Replace 570 % Process: Snapshot: Noise covariance 571 bst_process('CallProcess', 'process_snapshot', sFilesNoise, [], ... 572 'target', 3, ... % Noise covariance 573 'Comment', 'Noise covariance'); 574 575 % Process: Compute covariance (noise or data) [Run01] 576 bst_process('CallProcess', 'process_noisecov', sFilesEpochs1, [], ... 577 'baseline', [-0.1, -0.0017], ... 578 'datatimewindow', [0, 0.5], ... 579 'sensortypes', 'MEG, EEG, SEEG, ECOG', ... 580 'target', 2, ... % Data covariance (covariance over data time window) 581 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 582 'identity', 0, ... 583 'copycond', 0, ... 584 'copysubj', 0, ... 585 'replacefile', 1); % Replace 586 % Process: Compute covariance (noise or data) [Run02] 587 bst_process('CallProcess', 'process_noisecov', sFilesEpochs2, [], ... 588 'baseline', [-0.1, -0.0017], ... 589 'datatimewindow', [0, 0.5], ... 590 'sensortypes', 'MEG, EEG, SEEG, ECOG', ... 591 'target', 2, ... % Data covariance (covariance over data time window) 592 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 593 'identity', 0, ... 594 'copycond', 0, ... 595 'copysubj', 0, ... 596 'replacefile', 1); % Replace 597 % Process: Snapshot: Data covariance 598 bst_process('CallProcess', 'process_snapshot', [sFilesEpochs1(1), sFilesEpochs2(1)], [], ... 599 'target', 12, ... % Data covariance 600 'Comment', 'Data covariance'); 601 602 603 604 %% ===== TUTORIAL #22: SOURCE ESTIMATION ============================================= 605 % =================================================================================== 606 disp([10 'DEMO> Tutorial #22: Source estimation' 10]); 607 % === GET DEVIANT AVERAGE RUN01 === 608 % Process: Select recordings in: Subject01/S01_AEF_20131218_01_600Hz_notch 609 sFiles01 = bst_process('CallProcess', 'process_select_files_data', [], [], ... 610 'subjectname', SubjectName, ... 611 'condition', 'S01_AEF_20131218_01_600Hz_notch', ... 612 'includebad', 0); 613 % Process: Select file comments with tag: deviant 614 sFilesAvgDeviant01 = bst_process('CallProcess', 'process_select_tag', sFiles01, [], ... 615 'tag', 'Avg: deviant', ... 616 'search', 2, ... % Search the file comments 617 'select', 1); % Select only the files with the tag 618 619 % === CONSTRAINED EXAMPLE === 620 % Minimum norm options 621 InverseOptions = struct(... 622 'Comment', 'MN: MEG', ... 623 'InverseMethod', 'minnorm', ... 624 'InverseMeasure', 'amplitude', ... 625 'SourceOrient', {{'fixed'}}, ... 626 'Loose', 0.2, ... 627 'UseDepth', 1, ... 628 'WeightExp', 0.5, ... 629 'WeightLimit', 10, ... 630 'NoiseMethod', 'reg', ... 631 'NoiseReg', 0.1, ... 632 'SnrMethod', 'fixed', ... 633 'SnrRms', 0.001, ... 634 'SnrFixed', 3, ... 635 'ComputeKernel', 1, ... 636 'DataTypes', {{'MEG'}}); 637 % Process: Compute sources [2018] 638 sFilesSrcDeviant01 = bst_process('CallProcess', 'process_inverse_2018', sFilesAvgDeviant01, [], ... 639 'output', 2, ... % Kernel only: one per file 640 'inverse', InverseOptions); 641 642 % === DISPLAY SOURCES MANUALLY === 643 % View time series 644 hFigSrc1 = view_timeseries(sFilesAvgDeviant01(1).FileName, 'MEG'); 645 % View on the cortex surface 646 hFigSrc2 = script_view_sources(sFilesSrcDeviant01.FileName, 'cortex'); 647 % Set current time to 90ms 648 panel_time('SetCurrentTime', 0.090); 649 % Set orientation 650 figure_3d('SetStandardView', hFigSrc2, 'left'); 651 % Set surface threshold 652 iSurf = 1; 653 thresh = .30; 654 panel_surface('SetDataThreshold', hFigSrc2, iSurf, thresh); 655 % Set surface smoothing 656 panel_surface('SetSurfaceSmooth', hFigSrc2, iSurf, .6, 0); 657 % Show sulci 658 panel_surface('SetShowSulci', hFigSrc2, iSurf, 1); 659 660 % View sources on MRI (3D orthogonal slices) 661 hFigSrc3 = script_view_sources(sFilesSrcDeviant01.FileName, 'mri3d'); 662 panel_surface('SetDataThreshold', hFigSrc3, iSurf, thresh); 663 % Set the position of the cuts in the 3D figure 664 cutsPosVox = [74 93 159]; 665 panel_surface('PlotMri', hFigSrc3, cutsPosVox); 666 667 % View sources with MRI Viewer 668 hFigSrc4 = script_view_sources(sFilesSrcDeviant01.FileName, 'mriviewer'); 669 panel_surface('SetDataThreshold', hFigSrc4, iSurf, thresh); 670 % Set the position of the cuts in the MRI Viewer (values in millimeters) 671 figure_mri('SetLocation', 'voxel', hFigSrc4, [], cutsPosVox); 672 % Close figures 673 close([hFigSrc1 hFigSrc2 hFigSrc3 hFigSrc4]); 674 675 % === UNCONSTRAINED EXAMPLE === 676 % Unconstrained minnorm 677 InverseOptions.Comment = 'MN: MEG'; 678 InverseOptions.InverseMeasure = 'amplitude'; 679 InverseOptions.SourceOrient = {'free'}; 680 % Process: Compute sources [2018] 681 sFilesSrcUnconst = bst_process('CallProcess', 'process_inverse_2018', sFilesAvgDeviant01, [], ... 682 'output', 2, ... % Kernel only: one per file 683 'inverse', InverseOptions); 684 685 686 % === NORMALIZED SOURCES === 687 % dSPM 688 InverseOptions.Comment = 'dSPM: MEG'; 689 InverseOptions.InverseMeasure = 'dspm2018'; 690 InverseOptions.SourceOrient = {'fixed'}; 691 sFilesSrcDspm = bst_process('CallProcess', 'process_inverse_2018', sFilesAvgDeviant01, [], ... 692 'output', 2, ... % Kernel only: one per file 693 'inverse', InverseOptions); 694 % sLORETA (old function) 695 sFilesSrcSloreta = bst_process('CallProcess', 'process_inverse', sFilesAvgDeviant01, [], ... 696 'comment', '', ... 697 'method', 3, ... % sLORETA 698 'wmne', struct(... 699 'SourceOrient', {{'fixed'}}, ... 700 'loose', 0.2, ... 701 'SNR', 3, ... 702 'pca', 1, ... 703 'diagnoise', 0, ... 704 'regnoise', 1, ... 705 'magreg', 0.1, ... 706 'gradreg', 0.1, ... 707 'depth', 1, ... 708 'weightexp', 0.5, ... 709 'weightlimit', 10), ... 710 'sensortypes', 'MEG, MEG MAG, MEG GRAD, EEG', ... 711 'output', 2); % Kernel only: one per file 712 % Process: Z-score normalization: [-100ms,-2ms] 713 sFilesSrcZscore = bst_process('CallProcess', 'process_baseline_norm', sFilesSrcDeviant01, [], ... 714 'baseline', [-0.100, -0.002], ... 715 'source_abs', 0, ... 716 'method', 'zscore'); % Z-score transformation: x_std = (x - μ) / σ 717 718 % Process: Snapshot: Sources (one time) 719 bst_process('CallProcess', 'process_snapshot', sFilesSrcDeviant01, [], ... 720 'target', 8, ... % Sources (one time) 721 'orient', 1, ... % left 722 'time', 0.09, ... 723 'threshold', 30, ... 724 'Comment', 'Current density map (Constrained)'); 725 bst_process('CallProcess', 'process_snapshot', sFilesSrcDspm, [], ... 726 'target', 8, ... % Sources (one time) 727 'orient', 1, ... % left 728 'time', 0.09, ... 729 'threshold', 60, ... 730 'Comment', 'dSPM'); 731 bst_process('CallProcess', 'process_snapshot', sFilesSrcSloreta, [], ... 732 'target', 8, ... % Sources (one time) 733 'orient', 1, ... % left 734 'time', 0.09, ... 735 'threshold', 60, ... 736 'Comment', 'sLORETA'); 737 bst_process('CallProcess', 'process_snapshot', sFilesSrcZscore, [], ... 738 'target', 8, ... % Sources (one time) 739 'orient', 1, ... % left 740 'time', 0.09, ... 741 'threshold', 60, ... 742 'Comment', 'Z-score'); 743 bst_process('CallProcess', 'process_snapshot', sFilesSrcUnconst, [], ... 744 'target', 8, ... % Sources (one time) 745 'orient', 1, ... % left 746 'time', 0.0917, ... 747 'threshold', 0, ... 748 'Comment', 'Current density map (Unconstrained)'); 749 750 % === DELETE EXPERIMENTS === 751 % Process: Delete constrained example 752 bst_process('CallProcess', 'process_delete', [sFilesSrcDeviant01, sFilesSrcDspm, sFilesSrcSloreta, sFilesSrcZscore, sFilesSrcUnconst], [], ... 753 'target', 1); % Delete selected files 754 755 756 % === SHARED KERNEL === 757 % Constrained minnorm 758 InverseOptions.Comment = 'MN: MEG'; 759 InverseOptions.InverseMeasure = 'amplitude'; 760 InverseOptions.SourceOrient = {'fixed'}; 761 % Process: Compute sources [2018] 762 sFilesAvgSrc = bst_process('CallProcess', 'process_inverse_2018', sFilesAvg, [], ... 763 'output', 1, ... % Kernel only: shared 764 'inverse', InverseOptions); 765 766 767 % === AVERAGE SOURCES ACROSS RUNS === 768 % Process: Average: By trial group (subject average) 769 sFilesIntraSrc = bst_process('CallProcess', 'process_average', sFilesAvgSrc, [], ... 770 'avgtype', 6, ... % By trial group (subject average) 771 'avg_func', 1, ... % Arithmetic average: mean(x) 772 'weighted', 1, ... 773 'scalenormalized', 0); 774 % Process: Low-pass:40Hz 775 sFilesIntraSrcLow = bst_process('CallProcess', 'process_bandpass', sFilesIntraSrc, [], ... 776 'highpass', 0, ... 777 'lowpass', 40, ... 778 'attenuation', 'strict', ... % 60dB 779 'mirror', 0, ... 780 'overwrite', 0); 781 % Process: Z-score normalization: [-100ms,-2ms] 782 sFilesIntraZscore = bst_process('CallProcess', 'process_baseline_norm', sFilesIntraSrcLow, [], ... 783 'baseline', [-0.100, -0.0017], ... 784 'source_abs', 0, ... 785 'method', 'zscore'); % Z-score transformation: x_std = (x - μ) / σ 786 787 % Process: Delete intermediate results 788 bst_process('CallProcess', 'process_delete', sFilesIntraSrcLow, [], ... 789 'target', 1); % Delete selected files 790 % Screen captures 791 bst_process('CallProcess', 'process_snapshot', sFilesIntraZscore, [], ... 792 'target', 8, ... % Sources (one time) 793 'orient', 1, ... % left 794 'time', 0.09, ... 795 'threshold', 40, ... 796 'Comment', 'Average across runs (left)'); 797 bst_process('CallProcess', 'process_snapshot', sFilesIntraZscore, [], ... 798 'target', 8, ... % Sources (one time) 799 'orient', 2, ... % right 800 'time', 0.09, ... 801 'threshold', 40, ... 802 'Comment', 'Average across runs (right)'); 803 bst_process('CallProcess', 'process_snapshot', sFilesIntraZscore(1), [], ... 804 'target', 9, ... % Sources (contact sheet) 805 'orient', 1, ... % left 806 'contact_time', [0, 0.35], ... 807 'contact_nimage', 15, ... 808 'threshold', 20, ... 809 'Comment', 'Average across runs'); 810 811 812 %% ===== TUTORIAL #23: SCOUTS ======================================================== 813 % =================================================================================== 814 disp([10 'DEMO> Tutorial #23: Scouts' 10]); 815 % Load surface file 816 sCortex = in_tess_bst(CortexFile); 817 % Add new scouts in first atlas 818 sCortex.iAtlas = find(strcmpi({sCortex.Atlas.Name}, 'Destrieux')); 819 % Save file 820 bst_save(file_fullpath(CortexFile), sCortex, 'v7'); 821 % Unload everything 822 bst_memory('UnloadAll', 'Forced'); 823 % Find scouts indices to display: {'A1L', 'A1R', 'IFGL', 'M1L'} 824 [tmp,iScouts,tmp] = intersect({sCortex.Atlas(sCortex.iAtlas).Scouts.Label}, {'G_temp_sup-G_T_transv L', 'G_temp_sup-G_T_transv R', 'G_front_inf-Opercular L', 'G_precentral L'}); 825 826 % View cortex 827 hFigSurf1 = view_surface(CortexFile, [], [], 'NewFigure'); 828 hFigSurf2 = view_surface(CortexFile, [], [], 'NewFigure'); 829 figure_3d('SetStandardView', hFigSurf1, 'left'); 830 figure_3d('SetStandardView', hFigSurf2, 'right'); 831 panel_surface('SetSurfaceSmooth', hFigSurf1, 1, .6, 0); 832 panel_surface('SetSurfaceSmooth', hFigSurf2, 1, .6, 0); 833 panel_surface('SetShowSulci', hFigSurf1, 1, 1); 834 panel_surface('SetShowSulci', hFigSurf2, 1, 1); 835 % Configure scouts display 836 panel_scout('SetScoutsOptions', 0, 1, 1, 'all', 0.7, 1, 1, 0); 837 % View scouts 838 hFigScouts = view_scouts({sFilesIntraZscore.FileName}, iScouts); 839 hLegend = findobj(hFigScouts, 'Type', 'legend'); 840 if ~isempty(hLegend) && ishandle(hLegend(1)) 841 set(hLegend(1), 'Units', 'pixels'); 842 pos = get(hLegend(1), 'Position'); 843 set(hLegend(1), 'Position', [1, 1, pos(3), pos(4)]); 844 end 845 % Save figures 846 bst_report('Snapshot', hFigScouts, sFilesIntraZscore(1).FileName, 'Scouts', [100 100 670 250]); 847 % Close all 848 pause(1); 849 bst_memory('UnloadAll', 'Forced'); 850 851 852 853 %% ===== TUTORIAL #24: TIME-FREQUENCY ================================================ 854 % =================================================================================== 855 disp([10 'DEMO> Tutorial #24: Time-frequency' 10]); 856 % Process: Simulate generic signals 857 sSim = bst_process('CallProcess', 'process_simulate_matrix', [], [], ... 858 'subjectname', 'Test', ... 859 'condition', 'Simulation', ... 860 'samples', 6000, ... 861 'srate', 1000, ... 862 'matlab', ['f1 = 2; f2 = 20; f3 = 50;' 10 'i =2000:6000;' 10 'Data(1,i) = sin(f1*2*pi*t(i)) + 0.4 * cos(f2*2*pi*t(i));' 10 'Data = Data + 0.2 * sin(f3*2*pi*t) + 0.4 * rand(1,6000);']); 863 864 % Time-frequency options 865 TfOptions = struct(... 866 'Comment', 'Power,1-60Hz', ... 867 'TimeBands', [], ... 868 'Freqs', [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60], ... 869 'MorletFc', 1, ... 870 'MorletFwhmTc', 3, ... 871 'ClusterFuncTime', 'none', ... 872 'Measure', 'power', ... 873 'Output', 'average', ... 874 'SaveKernel', 0); 875 % Process: Time-frequency (Morlet wavelets) 876 sSimTf1 = bst_process('CallProcess', 'process_timefreq', sSim, [], ... 877 'edit', TfOptions, ... 878 'normalize', 'multiply'); % 1/f compensation: Multiply output values by frequency 879 880 % === NORMALIZATION === 881 % Process: Time-frequency (Morlet wavelets) 882 sSimTf2 = bst_process('CallProcess', 'process_timefreq', sSim, [], ... 883 'edit', TfOptions, ... 884 'normalize', 'none'); % None: Save non-standardized time-frequency maps 885 % Process: Spectral flattening 886 sSimTf2Multi = bst_process('CallProcess', 'process_tf_norm', sSimTf2, [], ... 887 'normalize', 'multiply', ... % 1/f compensation (multiple by frequency) 888 'overwrite', 0); 889 % Process: Event-related perturbation (ERS/ERD): [750ms,1250ms] 890 sSimTf2Ersd = bst_process('CallProcess', 'process_baseline_norm', sSimTf2, [], ... 891 'baseline', [0.75, 1.25], ... 892 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 893 'overwrite', 0); 894 895 % Process: Snapshot: Time-frequency maps 896 bst_process('CallProcess', 'process_snapshot', sSimTf2, [], ... 897 'target', 14, ... % Time-frequency maps 898 'Comment', 'Not normalized'); 899 % Process: Snapshot: Time-frequency maps 900 bst_process('CallProcess', 'process_snapshot', sSimTf2Multi, [], ... 901 'target', 14, ... % Time-frequency maps 902 'Comment', 'Spectral flattening: 1/f compensation'); 903 % Process: Snapshot: Time-frequency maps 904 bst_process('CallProcess', 'process_snapshot', sSimTf2Ersd, [], ... 905 'target', 14, ... % Time-frequency maps 906 'Comment', 'ERS/ERD'); 907 % Spectrum/Time series 908 hFigTf1 = view_spectrum(sSimTf2.FileName, 'Spectrum'); 909 hFigTf2 = view_spectrum(sSimTf2.FileName, 'TimeSeries'); 910 panel_time('SetCurrentTime', 0.5); 911 panel_freq('SetCurrentFreq', 2, 0); 912 bst_report('Snapshot', [hFigTf1 hFigTf2], sSimTf2.FileName, 'Not normalized: 2s/20Hz', [200, 200, 400, 250]); 913 panel_time('SetCurrentTime', 2.02); 914 panel_freq('SetCurrentFreq', 20, 0); 915 bst_report('Snapshot', [hFigTf1 hFigTf2], sSimTf2.FileName, 'Not normalized: 2s/20Hz', [200, 200, 400, 250]); 916 bst_memory('UnloadAll', 'Forced'); 917 918 919 % === HILBERT TRANSFORM === 920 % Process: Hilbert transform 921 sSimHilbert = bst_process('CallProcess', 'process_hilbert', sSim, [], ... 922 'edit', struct(... 923 'Comment', 'Power', ... 924 'TimeBands', [], ... 925 'Freqs', {{'delta', '2, 4', 'mean'; 'theta', '5, 7', 'mean'; 'alpha', '8, 12', 'mean'; 'beta', '15, 29', 'mean'; 'gamma1', '30, 59', 'mean'; 'gamma2', '60, 90', 'mean'}}, ... 926 'ClusterFuncTime', 'none', ... 927 'Measure', 'power', ... 928 'Output', 'all', ... 929 'SaveKernel', 0), ... 930 'normalize', 'none', ... % None: Save non-standardized time-frequency maps 931 'mirror', 0); 932 % Process: Spectral flattening 933 sSimHilbertMulti = bst_process('CallProcess', 'process_tf_norm', sSimHilbert, [], ... 934 'normalize', 'multiply', ... % 1/f compensation (multiple by frequency) 935 'overwrite', 0); 936 % Process: Event-related perturbation (ERS/ERD): [750ms,1250ms] 937 sSimHilbertErsd = bst_process('CallProcess', 'process_baseline_norm', sSimHilbert, [], ... 938 'baseline', [0.75, 1.25], ... 939 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 940 'overwrite', 0); 941 942 % Process: Snapshot: Time-frequency maps 943 bst_process('CallProcess', 'process_snapshot', sSimHilbert, [], ... 944 'target', 14, ... % Time-frequency maps 945 'Comment', 'Not normalized'); 946 % Process: Snapshot: Time-frequency maps 947 bst_process('CallProcess', 'process_snapshot', sSimHilbertMulti, [], ... 948 'target', 14, ... % Time-frequency maps 949 'Comment', 'Spectral flattening: 1/f compensation'); 950 % Process: Snapshot: Time-frequency maps 951 bst_process('CallProcess', 'process_snapshot', sSimHilbertErsd, [], ... 952 'target', 14, ... % Time-frequency maps 953 'Comment', 'ERS/ERD'); 954 955 % === SINGLE TRIALS === 956 TfOptions.Comment = 'Avg,Power,1-150Hz'; 957 TfOptions.Freqs = [1, 2, 3.1, 4.2, 5.4, 6.7, 8, 9.5, 11, 12.6, 14.3, 16.1, 18.1, 20.1, 22.3, 24.6, 27, 29.6, 32.4, 35.3, 38.4, 41.6, 45.1, 48.8, 52.7, 56.9, 61.3, 66, 70.9, 76.2, 81.8, 87.7, 94, 100.6, 107.7, 115.2, 123.1, 131.6, 140.5, 150]; 958 % Process: Time-frequency (Morlet wavelets) 959 sEpochsAvgTf = bst_process('CallProcess', 'process_timefreq', sFilesEpochs1, [], ... 960 'sensortypes', 'MEG, EEG', ... 961 'edit', TfOptions, ... 962 'normalize', 'none'); % None: Save non-standardized time-frequency maps 963 % Process: Event-related perturbation (ERS/ERD): [-75ms,0ms] 964 sEpochsAvgTfErsd = bst_process('CallProcess', 'process_baseline_norm', sEpochsAvgTf, [], ... 965 'baseline', [-0.075, 0], ... 966 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 967 'overwrite', 0); 968 969 % === DISPLAY === 970 % View time-frequency file 971 hFigTf1 = view_timefreq(sEpochsAvgTfErsd.FileName, 'SingleSensor'); 972 % Configure display 973 sOptions = panel_display('GetDisplayOptions'); 974 sOptions.HideEdgeEffects = 1; 975 sOptions.HighResolution = 1; 976 panel_display('SetDisplayOptions', sOptions); 977 % Other display modes 978 hFigTf2 = view_timefreq(sEpochsAvgTfErsd.FileName, 'AllSensors'); 979 hFigTf3 = view_timefreq(sEpochsAvgTfErsd.FileName, '2DLayout'); 980 hFigTf4 = view_timefreq(sEpochsAvgTfErsd.FileName, '2DLayoutOpt'); 981 bst_colormaps('SetColormapName', 'stat2', 'jet'); 982 bst_colormaps('SetColormapAbsolute', 'stat2', 1); 983 bst_report('Snapshot', hFigTf1, sEpochsAvgTfErsd.FileName, 'Time-frequency', [200, 200, 400, 250]); 984 bst_report('Snapshot', [hFigTf2 hFigTf3 hFigTf4], sEpochsAvgTfErsd.FileName, 'Time-frequency', [200, 200, 750, 400]); 985 close([hFigTf1 hFigTf2 hFigTf3 hFigTf4]); 986 % Image [channel x time] 987 hFigTf5 = view_erpimage(sEpochsAvgTfErsd.FileName, 'trialimage'); 988 % Topographies 989 hFigTf6 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '3DSensorCap'); 990 hFigTf7 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '2DDisc'); 991 hFigTf8 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '2DSensorCap'); 992 hFigTf9 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '2DLayout'); 993 panel_time('SetCurrentTime', 0.175); 994 panel_freq('SetCurrentFreq', 8, 0); 995 bst_report('Snapshot', [hFigTf5 hFigTf6 hFigTf7 hFigTf8 hFigTf9], sEpochsAvgTfErsd.FileName, 'Time-frequency: 8Hz', [200, 200, 400, 250]); 996 close([hFigTf5 hFigTf6 hFigTf7 hFigTf8 hFigTf9]); 997 998 999 % === AVERAGE FOR SCOUTS === 1000 % Select all sources for the single deviant epochs 1001 sFilesEpochDeviantSrc = bst_process('CallProcess', 'process_select_files_results', [], [], ... 1002 'subjectname', SubjectName, ... 1003 'condition', '', ... 1004 'includebad', 0); 1005 sFilesEpochDeviantSrc = bst_process('CallProcess', 'process_select_tag', sFilesEpochDeviantSrc, [], ... 1006 'tag', 'deviant', ... 1007 'search', 1, ... % Search the file names 1008 'select', 1); % Select only the files with the tag 1009 sFilesEpochDeviantSrc = bst_process('CallProcess', 'process_select_tag', sFilesEpochDeviantSrc, [], ... 1010 'tag', 'average', ... 1011 'search', 1, ... % Search the file names 1012 'select', 2); % Exclude the files with the tag 1013 1014 % Process: Time-frequency (Morlet wavelets) 1015 sFilesTfScout = bst_process('CallProcess', 'process_timefreq', sFilesEpochDeviantSrc, [], ... 1016 'clusters', {'Destrieux', {'G_temp_sup-G_T_transv L', 'G_temp_sup-G_T_transv R', 'G_front_inf-Opercular L', 'G_precentral L'}}, ... 1017 'scoutfunc', 1, ... % Mean 1018 'edit', struct(... 1019 'Comment', 'Deviant: Scouts,Avg,Power,1-150Hz', ... 1020 'TimeBands', [], ... 1021 'Freqs', [1, 2, 3.1, 4.2, 5.4, 6.7, 8, 9.5, 11, 12.6, 14.3, 16.1, 18.1, 20.1, 22.3, 24.6, 27, 29.6, 32.4, 35.3, 38.4, 41.6, 45.1, 48.8, 52.7, 56.9, 61.3, 66, 70.9, 76.2, 81.8, 87.7, 94, 100.6, 107.7, 115.2, 123.1, 131.6, 140.5, 150], ... 1022 'MorletFc', 1, ... 1023 'MorletFwhmTc', 3, ... 1024 'ClusterFuncTime', 'after', ... 1025 'Measure', 'power', ... 1026 'Output', 'average', ... 1027 'SaveKernel', 0), ... 1028 'normalize', 'none'); % None: Save non-standardized time-frequency maps) 1029 % Process: Event-related perturbation (ERS/ERD): [-75ms,0ms] 1030 sFilesTfScoutErsd = bst_process('CallProcess', 'process_baseline_norm', sFilesTfScout, [], ... 1031 'baseline', [-0.075, 0], ... 1032 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 1033 'overwrite', 0); 1034 % Process: Snapshot: Time-frequency maps 1035 bst_process('CallProcess', 'process_snapshot', sFilesTfScoutErsd, [], ... 1036 'target', 14, ... % Time-frequency maps 1037 'Comment', 'ERS/ERD'); 1038 1039 1040 % === FULL CORTEX / HILBERT === 1041 % Process: Hilbert transform 1042 sFilesHilbertCortex = bst_process('CallProcess', 'process_hilbert', sFilesEpochDeviantSrc, [], ... 1043 'clusters', {}, ... 1044 'scoutfunc', 1, ... % Mean 1045 'edit', struct(... 1046 'Comment', 'Deviant: Avg,Magnitude', ... 1047 'TimeBands', [], ... 1048 'Freqs', {{'delta', '2, 4', 'mean'; 'theta', '5, 7', 'mean'; 'alpha', '8, 12', 'mean'; 'beta', '15, 29', 'mean'; 'gamma1', '30, 59', 'mean'; 'gamma2', '60, 90', 'mean'}}, ... 1049 'ClusterFuncTime', 'none', ... 1050 'Measure', 'power', ... 1051 'Output', 'average', ... 1052 'RemoveEvoked', 0, ... 1053 'SaveKernel', 0), ... 1054 'normalize', 'none', ... % None: Save non-standardized time-frequency maps 1055 'mirror', 0); 1056 % Process: Event-related perturbation (ERS/ERD): [-75ms,0ms] 1057 sFilesHilbertCortexErsd = bst_process('CallProcess', 'process_baseline_norm', sFilesHilbertCortex, [], ... 1058 'baseline', [-0.075, 0], ... 1059 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 1060 'overwrite', 0); 1061 1062 % View results 1063 hFigTf1 = view_surface_data([], sFilesHilbertCortexErsd.FileName); 1064 hFigTf2 = view_timefreq(sFilesHilbertCortexErsd.FileName, 'SingleSensor', 362); 1065 figure_3d('SetStandardView', hFigTf1, 'left'); 1066 panel_surface('SetDataThreshold', hFigTf1, 1, 0.5); 1067 panel_time('SetCurrentTime', 0.175); 1068 panel_freq('SetCurrentFreq', 3); 1069 bst_colormaps('RestoreDefaults', 'stat2'); 1070 bst_report('Snapshot', [hFigTf1 hFigTf2], sFilesHilbertCortexErsd.FileName, 'Hilbert transform: Alpha band', [200, 200, 400, 250]); 1071 bst_memory('UnloadAll', 'Forced'); 1072 1073 1074 %% ===== TUTORIAL #25: DIFFRERENCE =================================================== 1075 % =================================================================================== 1076 disp([10 'DEMO> Tutorial #25: Difference' 10]); 1077 1078 % ===== SELECT TRIALS (DATA) ===== 1079 % Process: Select recordings in: Subject01/* 1080 sFilesAll = bst_process('CallProcess', 'process_select_files_data', [], [], ... 1081 'subjectname', SubjectName, ... 1082 'condition', '', ... 1083 'includebad', 0); 1084 % Process: Select file names with tag: deviant_trial 1085 sEpochDeviant = bst_process('CallProcess', 'process_select_tag', sFilesAll, [], ... 1086 'tag', 'deviant_trial', ... 1087 'search', 1, ... % Search the file names 1088 'select', 1); % Select only the files with the tag 1089 % Process: Select file names with tag: standard_trial 1090 sEpochStandard = bst_process('CallProcess', 'process_select_tag', sFilesAll, [], ... 1091 'tag', 'standard_trial', ... 1092 'search', 1, ... % Search the file names 1093 'select', 1); % Select only the files with the tag 1094 1095 % ===== SELECT TRIALS (SOURCE) ===== 1096 % Process: Select recordings in: Subject01/* 1097 sFilesAllSrc = bst_process('CallProcess', 'process_select_files_results', [], [], ... 1098 'subjectname', SubjectName, ... 1099 'condition', '', ... 1100 'includebad', 0); 1101 % Process: Select file names with tag: deviant_trial 1102 sEpochDeviantSrc = bst_process('CallProcess', 'process_select_tag', sFilesAllSrc, [], ... 1103 'tag', 'deviant_trial', ... 1104 'search', 1, ... % Search the file names 1105 'select', 1); % Select only the files with the tag 1106 % Process: Select file names with tag: standard_trial 1107 sEpochStandardSrc = bst_process('CallProcess', 'process_select_tag', sFilesAllSrc, [], ... 1108 'tag', 'standard_trial', ... 1109 'search', 1, ... % Search the file names 1110 'select', 1); % Select only the files with the tag 1111 1112 % ===== ABSOLUTE DIFFERENCE ====== 1113 % Process: Difference: A-B, abs 1114 sDiffSrc = bst_process('CallProcess', 'process_diff_ab', sFilesIntraSrc(1).FileName, sFilesIntraSrc(2).FileName, ... 1115 'source_abs', 1); 1116 % Process: Set comment: deviant|abs - standard|abs 1117 sDiffSrc = bst_process('CallProcess', 'process_set_comment', sDiffSrc, [], ... 1118 'tag', 'deviant|abs - standard|abs', ... 1119 'isindex', 1); 1120 % Process: Low-pass:40Hz 1121 sDiffSrcZscore = bst_process('CallProcess', 'process_bandpass', sDiffSrc, [], ... 1122 'highpass', 0, ... 1123 'lowpass', 40, ... 1124 'attenuation', 'strict', ... % 60dB 1125 'mirror', 0, ... 1126 'overwrite', 1); 1127 % Process: Z-score transformation: [-100ms,-2ms] 1128 sDiffSrcZscore = bst_process('CallProcess', 'process_baseline_norm', sDiffSrcZscore, [], ... 1129 'baseline', [-0.1, -0.002], ... 1130 'source_abs', 0, ... 1131 'method', 'zscore', ... % Z-score transformation: x_std = (x - μ) / σ 1132 'overwrite', 0); 1133 % Process: Snapshot: Sources (contact sheet) 1134 bst_process('CallProcess', 'process_snapshot', sDiffSrcZscore, [], ... 1135 'target', 9, ... % Sources (contact sheet) 1136 'modality', 1, ... % MEG (All) 1137 'orient', 1, ... % left 1138 'contact_time', [0, 0.35], ... 1139 'contact_nimage', 15, ... 1140 'threshold', 30, ... 1141 'Comment', 'Difference deviant - standard (absolute)'); 1142 1143 % ===== RELATIVE DIFFERENCE ===== 1144 % Process: Difference: A-B 1145 sDiffSrcRel = bst_process('CallProcess', 'process_diff_ab', sFilesIntraSrc(1).FileName, sFilesIntraSrc(2).FileName, ... 1146 'source_abs', 0); 1147 % Process: Set comment: deviant - standard 1148 sDiffSrcRel = bst_process('CallProcess', 'process_set_comment', sDiffSrcRel, [], ... 1149 'tag', 'deviant - standard', ... 1150 'isindex', 1); 1151 % Process: Low-pass:40Hz 1152 sDiffSrcRelZscore = bst_process('CallProcess', 'process_bandpass', sDiffSrcRel, [], ... 1153 'highpass', 0, ... 1154 'lowpass', 40, ... 1155 'attenuation', 'strict', ... % 60dB 1156 'mirror', 0, ... 1157 'overwrite', 1); 1158 % Process: Z-score transformation: [-100ms,-2ms] 1159 sDiffSrcRelZscore = bst_process('CallProcess', 'process_baseline_norm', sDiffSrcRelZscore, [], ... 1160 'baseline', [-0.1, -0.002], ... 1161 'source_abs', 0, ... 1162 'method', 'zscore', ... % Z-score transformation: x_std = (x - μ) / σ 1163 'overwrite', 0); 1164 % Configure colormap: hot/absolute 1165 bst_colormaps('SetColormapName', 'stat2', 'hot'); 1166 bst_colormaps('SetColormapAbsolute', 'stat2', 1); 1167 % Process: Snapshot: Sources (contact sheet) 1168 bst_process('CallProcess', 'process_snapshot', sDiffSrcRelZscore, [], ... 1169 'target', 9, ... % Sources (contact sheet) 1170 'modality', 1, ... % MEG (All) 1171 'orient', 1, ... % left 1172 'contact_time', [0, 0.35], ... 1173 'contact_nimage', 15, ... 1174 'threshold', 30, ... 1175 'Comment', 'Difference deviant - standard (relative)'); 1176 % Restore colormap: rwb/relative 1177 bst_colormaps('SetColormapName', 'stat2', 'cmap_rbw'); 1178 bst_colormaps('SetColormapAbsolute', 'stat2', 0); 1179 1180 % ===== DIFFERENCE OF MEANS ===== 1181 % Process: Select uniform number of files [uniform] 1182 [sEpochDeviantUni, sEpochStandardUni] = bst_process('CallProcess', 'process_select_uniform2', sEpochDeviant, sEpochStandard, ... 1183 'nfiles', 0, ... 1184 'method', 4); % Uniformly distributed 1185 % Process: Difference of means [mean] 1186 sDiffMean = bst_process('CallProcess', 'process_diff_mean', sEpochDeviantUni, sEpochStandardUni, ... 1187 'avg_func', 1, ... % Arithmetic average mean(A) - mean(B) 1188 'weighted', 0); 1189 % Process: Snapshot: Recordings time series 1190 bst_process('CallProcess', 'process_snapshot', sDiffMean, [], ... 1191 'target', 5, ... % Recordings time series 1192 'modality', 1, ... % MEG (All) 1193 'Comment', 'Difference of means'); 1194 1195 1196 1197 %% ===== TUTORIAL #26: STATISTICS ==================================================== 1198 % =================================================================================== 1199 disp([10 'DEMO> Tutorial #26: Statistics' 10]); 1200 % ===== HISTOGRAMS ===== 1201 % Process: Extract values: [160ms] MLP57 1202 sHistoDeviant = bst_process('CallProcess', 'process_extract_values', sEpochDeviant, [], ... 1203 'timewindow', [0.16, 0.16], ... 1204 'sensortypes', 'MLP57', ... 1205 'isabs', 0, ... 1206 'avgtime', 0, ... 1207 'avgrow', 0, ... 1208 'dim', 2, ... % Concatenate time (dimension 2) 1209 'Comment', ''); 1210 % Process: Extract values: [160ms] MLP57 1211 sHistoStandard = bst_process('CallProcess', 'process_extract_values', sEpochStandard, [], ... 1212 'timewindow', [0.16, 0.16], ... 1213 'sensortypes', 'MLP57', ... 1214 'isabs', 0, ... 1215 'avgtime', 0, ... 1216 'avgrow', 0, ... 1217 'dim', 2, ... % Concatenate time (dimension 2) 1218 'Comment', ''); 1219 % Display histograms 1220 hFigHisto = view_histogram({sHistoDeviant.FileName, sHistoStandard.FileName}); 1221 bst_report('Snapshot', hFigHisto, sHistoDeviant.FileName, 'Histograms for MLP57/160ms'); 1222 close(hFigHisto); 1223 1224 % ===== EXEMPLE #1: PARAMETRIC/DATA ===== 1225 % Process: t-test [equal] [-100ms,500ms] H0:(A-B = 0) 1226 sTestParamData = bst_process('CallProcess', 'process_test_parametric2', sEpochDeviant, sEpochStandard, ... 1227 'timewindow', [-0.1, 0.5], ... 1228 'sensortypes', '', ... 1229 'isabs', 0, ... 1230 'avgtime', 0, ... 1231 'avgrow', 0, ... 1232 'Comment', '', ... 1233 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) df = nA + nB - 2 1234 'tail', 'two'); % Two-tailed 1235 % Set display properties 1236 StatThreshOptions = bst_get('StatThreshOptions'); 1237 StatThreshOptions.pThreshold = 0.05; 1238 StatThreshOptions.Correction = 'fdr'; 1239 StatThreshOptions.Control = [1 2 3]; 1240 bst_set('StatThreshOptions', StatThreshOptions); 1241 % Process: Snapshot: Recordings time series 1242 bst_process('CallProcess', 'process_snapshot', sTestParamData, [], ... 1243 'target', 5, ... % Recordings time series 1244 'modality', 1, ... % MEG (All) 1245 'time', 0.16, ... 1246 'Comment', 'Parametric t-test (p<0.05, FDR)'); 1247 % Process: Snapshot: Recordings topography (one time) 1248 bst_process('CallProcess', 'process_snapshot', sTestParamData, [], ... 1249 'target', 6, ... % Recordings topography (one time) 1250 'modality', 1, ... % MEG (All) 1251 'time', 0.16, ... 1252 'Comment', 'Parametric t-test (p<0.05, FDR)'); 1253 1254 % ===== EXEMPLE #2: NON-PARAMETRIC/DATA ===== 1255 % Process: Perm t-test equal [-100ms,500ms MEG] H0:(A=B), H1:(A<>B) 1256 sTestPermData = bst_process('CallProcess', 'process_test_permutation2', sEpochDeviant, sEpochStandard, ... 1257 'timewindow', [-0.1, 0.5], ... 1258 'sensortypes', 'MEG', ... 1259 'isabs', 0, ... 1260 'avgtime', 0, ... 1261 'avgrow', 0, ... 1262 'iszerobad', 1, ... 1263 'Comment', '', ... 1264 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) 1265 'randomizations', 1000, ... 1266 'tail', 'two'); % Two-tailed 1267 % Process: Snapshot: Recordings time series 1268 bst_process('CallProcess', 'process_snapshot', sTestPermData, [], ... 1269 'target', 5, ... % Recordings time series 1270 'modality', 1, ... % MEG (All) 1271 'time', 0.16, ... 1272 'Comment', 'Non-parametric t-test (p<0.05, FDR)'); 1273 % Process: Snapshot: Recordings topography (one time) 1274 bst_process('CallProcess', 'process_snapshot', sTestPermData, [], ... 1275 'target', 6, ... % Recordings topography (one time) 1276 'modality', 1, ... % MEG (All) 1277 'time', 0.16, ... 1278 'Comment', 'Non-parametric t-test (p<0.05, FDR)'); 1279 1280 % ===== EXEMPLE #3: CLUSTER/DATA ===== 1281 % Process: FT t-test unequal cluster [-100ms,500ms MEG] H0:(A=B), H1:(A<>B) 1282 sTestClustData = bst_process('CallProcess', 'process_ft_timelockstatistics', sEpochDeviant, sEpochStandard, ... 1283 'sensortypes', 'MEG', ... 1284 'timewindow', [-0.1, 0.5], ... 1285 'isabs', 0, ... 1286 'avgtime', 0, ... 1287 'avgchan', 0, ... 1288 'randomizations', 1000, ... 1289 'statistictype', 1, ... % Independent t-test 1290 'tail', 'two', ... % Two-tailed 1291 'correctiontype', 2, ... % cluster 1292 'minnbchan', 0, ... 1293 'clusteralpha', 0.05); 1294 % Process: Snapshot: Recordings time series 1295 bst_process('CallProcess', 'process_snapshot', sTestClustData, [], ... 1296 'target', 5, ... % Recordings time series 1297 'time', 0.16, ... 1298 'modality', 1, ... % MEG (All) 1299 'Comment', 'Cluster-based permutation test'); 1300 % Process: Snapshot: Recordings topography (one time) 1301 bst_process('CallProcess', 'process_snapshot', sTestClustData, [], ... 1302 'target', 6, ... % Recordings topography (one time) 1303 'modality', 1, ... % MEG (All) 1304 'time', 0.16, ... 1305 'Comment', 'Cluster-based permutation test'); 1306 1307 % ===== EXAMPLE #4: PARAMETRIC/SOURCES ===== 1308 % Process: t-test [equal] [-100ms,500ms] H0:(A-B = 0) 1309 sTestParamSrc = bst_process('CallProcess', 'process_test_parametric2', sEpochDeviantSrc, sEpochStandardSrc, ... 1310 'timewindow', [-0.1, 0.5], ... 1311 'scoutsel', {}, ... 1312 'scoutfunc', 1, ... % Mean 1313 'isnorm', 0, ... 1314 'avgtime', 0, ... 1315 'Comment', '', ... 1316 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) df = nA + nB - 2 1317 'tail', 'two'); % Two-tailed 1318 % Process: Difference of means [abs(mean)] 1319 sDiffMeanSrc = bst_process('CallProcess', 'process_diff_mean', sEpochDeviantSrc, sEpochStandardSrc, ... 1320 'avg_func', 2, ... % Absolute value of average abs(mean(A)) - abs(mean(B)) 1321 'weighted', 0); 1322 % Process: Apply statistic threshold: p<0.05 (FDR:1,2,3) 1323 sDiffMeanSrcThresh = bst_process('CallProcess', 'process_extract_pthresh2', sTestParamSrc, sDiffMeanSrc, ... 1324 'pthresh', 0.05, ... 1325 'correction', 3, ... % False discovery rate (FDR) 1326 'control1', 1, ... 1327 'control2', 1, ... 1328 'control3', 1); 1329 % Process: Snapshot: Sources (one time) 1330 bst_process('CallProcess', 'process_snapshot', sTestParamSrc, [], ... 1331 'target', 8, ... % Sources (one time) 1332 'orient', 1, ... % left 1333 'time', 0.148, ... 1334 'threshold', 40, ... 1335 'Comment', 'Parametric t-test (p<0.05, FDR)'); 1336 % Process: Snapshot: Sources (one time) 1337 bst_process('CallProcess', 'process_snapshot', sDiffMeanSrc, [], ... 1338 'target', 8, ... % Sources (one time) 1339 'orient', 1, ... % left 1340 'time', 0.148, ... 1341 'threshold', 40, ... 1342 'Comment', 'abs(average(deviant)) - abs(average(standard))'); 1343 % Process: Snapshot: Sources (one time) 1344 bst_process('CallProcess', 'process_snapshot', sDiffMeanSrcThresh, [], ... 1345 'target', 8, ... % Sources (one time) 1346 'orient', 1, ... % left 1347 'time', 0.148, ... 1348 'threshold', 0, ... 1349 'Comment', 'Different of mean thresholded with t-test results'); 1350 1351 % ===== EXAMPLE #5: PARAMETRIC/SCOUTS ===== 1352 % Process: t-test equal [-100ms,500ms] H0:(A=B), H1:(A<>B) 1353 sTestParamScout = bst_process('CallProcess', 'process_test_parametric2', sEpochDeviantSrc, sEpochStandardSrc, ... 1354 'timewindow', [-0.1, 0.5], ... 1355 'scoutsel', {'Destrieux', {'G_front_inf-Opercular L', 'G_precentral L', 'G_temp_sup-G_T_transv L'}}, ... 1356 'scoutfunc', 1, ... % Mean 1357 'isnorm', 0, ... 1358 'avgtime', 0, ... 1359 'Comment', '', ... 1360 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) df = nA + nB - 2 1361 'tail', 'two'); % Two-tailed 1362 % Process: Apply statistic threshold: p<0.05 (FDR:1,2,3) 1363 sTestParamScoutThresh = bst_process('CallProcess', 'process_extract_pthresh', sTestParamScout, [], ... 1364 'pthresh', 0.05, ... 1365 'correction', 3, ... % False discovery rate (FDR) 1366 'control1', 1, ... 1367 'control2', 1, ... 1368 'control3', 1); 1369 % Process: Compute head model 1370 bst_process('CallProcess', 'process_headmodel', sTestParamScoutThresh, [], ... 1371 'sourcespace', 1, ... % Cortex surface 1372 'meg', 3); % Overlapping spheres 1373 % Process: Simulate recordings from scouts 1374 sSimulData = bst_process('CallProcess', 'process_simulate_recordings', sTestParamScoutThresh, [], ... 1375 'scouts', {'Destrieux', {'G_front_inf-Opercular L', 'G_precentral L', 'G_temp_sup-G_T_transv L'}}, ... 1376 'savesources', 1); 1377 1378 % Get corresponding source file 1379 [sStudy,iStudy,iRes] = bst_get('ResultsForDataFile', sSimulData.FileName); 1380 sSimulSrc = sStudy.Result(iRes).FileName; 1381 % Reset visualization filters 1382 panel_filter('SetFilters', 0, [], 0, [], 0, [], 0, 0); 1383 % Process: Snapshot: Recordings time series 1384 bst_process('CallProcess', 'process_snapshot', sTestParamScout, [], ... 1385 'target', 5, ... % Recordings time series 1386 'time', 0.148, ... 1387 'Comment', 'Parametric t-test (p<0.05, FDR)'); 1388 % Process: Snapshot: Sources (one time) 1389 bst_process('CallProcess', 'process_snapshot', sSimulSrc, [], ... 1390 'target', 8, ... % Sources (one time) 1391 'orient', 1, ... % left 1392 'time', 0.148, ... 1393 'threshold', 0, ... 1394 'Comment', 'Simulated sources'); 1395 % Process: Snapshot: Recordings time series 1396 bst_process('CallProcess', 'process_snapshot', sSimulData, [], ... 1397 'target', 5, ... % Recordings time series 1398 'modality', 1, ... % MEG (All) 1399 'time', 0.148, ... 1400 'Comment', 'Simulated MEG recordings'); 1401 1402 1403 % ===== EXAMPLE #6: NON-PARAMETRIC/TIMEFREQ ===== 1404 TfOptions.Output = 'all'; 1405 % Process: Time-frequency (Morlet wavelets) / DEVIANT 1406 sEpochDeviantTf = bst_process('CallProcess', 'process_timefreq', sEpochDeviant, [], ... 1407 'sensortypes', 'MLP57', ... 1408 'edit', TfOptions, ... 1409 'normalize', 'none'); % None: Save non-standardized time-frequency maps 1410 % Process: Time-frequency (Morlet wavelets) / STANDARD 1411 sEpochStandardTf = bst_process('CallProcess', 'process_timefreq', sEpochStandard, [], ... 1412 'sensortypes', 'MLP57', ... 1413 'edit', TfOptions, ... 1414 'normalize', 'none'); % None: Save non-standardized time-frequency maps 1415 % Process: Perm t-test equal [-100ms,500ms 1-150Hz] H0:(A=B), H1:(A<>B) 1416 sTestTf = bst_process('CallProcess', 'process_test_permutation2', sEpochDeviantTf, sEpochStandardTf, ... 1417 'timewindow', [-0.1, 0.5], ... 1418 'freqrange', [1, 150], ... 1419 'rows', '', ... 1420 'isabs', 0, ... 1421 'avgtime', 0, ... 1422 'avgrow', 0, ... 1423 'avgfreq', 0, ... 1424 'matchrows', 0, ... 1425 'iszerobad', 1, ... 1426 'Comment', '', ... 1427 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) 1428 'randomizations', 1000, ... 1429 'tail', 'two'); % Two-tailed 1430 % Set stat threshold 1431 StatThreshOptions.pThreshold = 0.05; 1432 StatThreshOptions.Correction = 'none'; 1433 bst_set('StatThreshOptions', StatThreshOptions); 1434 % Process: Snapshot: Time-frequency maps 1435 bst_process('CallProcess', 'process_snapshot', sTestTf, [], ... 1436 'target', 14, ... % Time-frequency maps 1437 'Comment', 'Non-parametric t-test (p<0.05, Uncorrected)'); 1438 % Process: Delete intermediate results 1439 bst_process('CallProcess', 'process_delete', [sEpochDeviantTf, sEpochStandardTf], [], ... 1440 'target', 1); % Delete selected files 1441 1442 1443 1444 %% ===== SAVE REPORT ===== 1445 % Save and display report 1446 ReportFile = bst_report('Save', []); 1447 if ~isempty(reports_dir) && ~isempty(ReportFile) 1448 bst_report('Export', ReportFile, reports_dir); 1449 else 1450 bst_report('Open', ReportFile); 1451 end 1452 1453 disp([10 'DEMO> Done.' 10]);

1 function tutorial_visual_single(bids_dir, reports_dir) 2 % TUTORIAL_VISUAL_SINGLE: Runs the Brainstorm/SPM group analysis pipeline (single subject, BIDS version). 3 % 4 % ONLINE TUTORIALS: https://neuroimage.usc.edu/brainstorm/Tutorials/VisualSingle 5 % 6 % INPUTS: 7 % - bids_dir: Path to folder ds000117 (https://openneuro.org/datasets/ds000117) 8 % |- derivatives/freesurfer/sub-XX : Segmentation folders generated with FreeSurfer 9 % |- derivatives/meg_derivatives/sub-XX/ses-meg/meg/*.fif : MEG+EEG recordings (processed with MaxFilter's SSS) 10 % |- derivatives/meg_derivatives/sub-emptyroom/ses-meg/meg/*.fif : Empty room measurements 11 % - reports_dir: If defined, exports all the reports as HTML to this folder 12 13 % @============================================================================= 14 % This function is part of the Brainstorm software: 15 % https://neuroimage.usc.edu/brainstorm 16 % 17 % Copyright (c) University of Southern California & McGill University 18 % This software is distributed under the terms of the GNU General Public License 19 % as published by the Free Software Foundation. Further details on the GPLv3 20 % license can be found at http://www.gnu.org/copyleft/gpl.html. 21 % 22 % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE 23 % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY 24 % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF 25 % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY 26 % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. 27 % 28 % For more information type "brainstorm license" at command prompt. 29 % =============================================================================@ 30 % 31 % Author: Francois Tadel, Elizabeth Bock, 2016-2018 32 33 34 %% ===== SCRIPT VARIABLES ===== 35 % Full list of subjects to process 36 SubjectNames = {'sub-01', 'sub-02', 'sub-03', 'sub-04', 'sub-05', 'sub-06', 'sub-07', 'sub-08', ... 37 'sub-09', 'sub-10', 'sub-11', 'sub-12', 'sub-13', 'sub-14', 'sub-15', 'sub-16'}; 38 % Empty-room dates for each subject (so that we can match automatically recordings with empty-room) 39 EmptyRoomSubj = 'sub-emptyroom'; 40 AcquisitionDates = {'09-Apr-2009', '06-May-2009', '11-May-2009', '18-May-2009', '15-May-2009', '15-May-2009', '15-May-2009', '15-May-2009', ... 41 '15-May-2009', '15-May-2009', '01-Jun-2009', '01-Jun-2009', '01-Jun-2009', '26-Nov-2009', '08-Dec-2009', '08-Dec-2009'}; 42 % Bad channels {iSubj} = {Run01, Run02, Run03, Run04, Run05, Run06} 43 BadChannels{1} = {'EEG016', 'EEG070', 'EEG050',{'EEG008','EEG050'}, [], []}; 44 BadChannels{2} = {{'EEG027', 'EEG030', 'EEG038'}, 'EEG010', 'EEG010', 'EEG010', 'EEG010', 'EEG010'}; 45 BadChannels{3} = {{'EEG008','EEG017'}, {'EEG008','EEG017'}, {'EEG008','EEG017'}, {'EEG008','EEG017'}, {'EEG008','EEG017','EEG001'}, {'EEG008','EEG017','EEG020'}}; 46 BadChannels{4} = {{'EEG038'}, {'EEG038','EEG001','EEG016'}, {'EEG038','EEG001','EEG016'}, {'EEG038','EEG001'}, {'EEG038','EEG001','EEG016'}, {'EEG038','EEG001','EEG016'}}; 47 BadChannels{5} = {'EEG001', 'EEG001', [], [], [], []}; 48 BadChannels{6} = {'EEG068', [], 'EEG004', [], [], []}; 49 BadChannels{7} = {[], [], {'EEG004','EEG008'}, {'EEG004','EEG008'},{'EEG004','EEG008','EEG043','EEG045','EEG047'}, {'EEG004','EEG008'}}; 50 BadChannels{8} = {[], [], [], [], [], []}; 51 BadChannels{9} = {[], 'EEG004', 'EEG004', [], 'EEG004', 'EEG004'}; 52 BadChannels{10} = {[], [], [], [], [], []}; 53 BadChannels{11} = {{'EEG010','EEG050'}, 'EEG050', 'EEG050', 'EEG050', 'EEG050', 'EEG050'}; 54 BadChannels{12} = {{'EEG024','EEG057'}, {'EEG024','EEG057'}, {'EEG024','EEG057'}, {'EEG024','EEG057','EEG070'}, {'EEG024','EEG057'}, {'EEG024','EEG057','EEG070'}}; 55 BadChannels{13} = {'EEG009', 'EEG009', {'EEG009','EEG057','EEG69'}, 'EEG009', {'EEG009','EEG044'}, {'EEG009','EEG044'}}; 56 BadChannels{14} = {'EEG029', 'EEG029', 'EEG029', {'EEG004','EEG008','EEG016','EEG029'}, {'EEG004','EEG008','EEG016','EEG029'}, {'EEG004','EEG008','EEG016','EEG029'}}; 57 BadChannels{15} = {'EEG038', 'EEG038', 'EEG038', 'EEG038', {'EEG054','EEG038'}, 'EEG038'}; 58 BadChannels{16} = {'EEG008', 'EEG008', 'EEG008', 'EEG008', 'EEG008', 'EEG008'}; 59 % SSP components to remove {iSubj} = {sRun01, sRun02, sRun03, sRun03, sRun04, sRun05, sRun06}, sRun0X={ECG_GRAD,ECG_MAG} 60 SspSelect{1} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; 61 SspSelect{2} = {{1,1}, {1,1}, {1,1}, {1,1}, {3,1}, {1,1}}; 62 SspSelect{3} = {{[],1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; 63 SspSelect{4} = {{[],1}, {[],1}, {[],1}, {[],1}, {[],1}, {[],1}}; 64 SspSelect{5} = {{2,1}, {1,1}, {1,1}, {[],1}, {1,1}, {1,1}}; 65 SspSelect{6} = {{2,1}, {2,1}, {1,1}, {2,1}, {1,1}, {2,1}}; 66 SspSelect{7} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; 67 SspSelect{8} = {{1,1}, {1,1}, {[],1}, {2,1}, {1,1}, {2,1}}; 68 SspSelect{9} = {{1,1}, {1,1}, {[],1}, {[],1}, {1,1}, {1,1}}; 69 SspSelect{10} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; 70 SspSelect{11} = {{[],1}, {[],1}, {[],1}, {[],1}, {[],[]}, {[],[]}}; 71 SspSelect{12} = {{[1,2],[1,2]}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; 72 SspSelect{13} = {{[],[]}, {[],[]}, {[],[]}, {[],[]}, {[],[]}, {[],[]}}; 73 SspSelect{14} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; 74 SspSelect{15} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; 75 SspSelect{16} = {{1,1}, {1,1}, {1,1}, {2,1}, {1,1}, {1,1}}; 76 77 78 %% ===== CREATE PROTOCOL ===== 79 % Start brainstorm without the GUI 80 if ~brainstorm('status') 81 brainstorm nogui 82 end 83 % Output folder for reports 84 if (nargin < 2) || isempty(reports_dir) || ~isdir(reports_dir) 85 reports_dir = []; 86 end 87 % You have to specify the folder in which the tutorial dataset is unzipped 88 if (nargin < 1) || isempty(bids_dir) || ~file_exist(bids_dir) || ~file_exist(bst_fullfile(bids_dir, 'derivatives')) || ~file_exist(bst_fullfile(bids_dir, 'dataset_description.json')) 89 error('The first argument must be the full path to the tutorial folder.'); 90 end 91 % The protocol name has to be a valid folder name (no spaces, no weird characters...) 92 ProtocolName = 'TutorialVisual'; 93 % Delete existing protocol 94 gui_brainstorm('DeleteProtocol', ProtocolName); 95 % Create new protocol 96 gui_brainstorm('CreateProtocol', ProtocolName, 0, 0); 97 % Set visualization filters: 40Hz low-pass, no high-pass 98 panel_filter('SetFilters', 1, 40, 0, [], 0, [], 0, 0); 99 % Set colormap: local color scale 100 bst_colormaps('SetMaxMode', 'meg', 'local'); 101 bst_colormaps('SetMaxMode', 'eeg', 'local'); 102 103 104 %% ===== PRE-PROCESS AND IMPORT ===== 105 for iSubj = 1:16 106 % Start a new report (one report per subject) 107 bst_report('Start'); 108 disp(sprintf('\n===== IMPORT: SUBJECT #%d =====\n', iSubj)); 109 110 % If subject already exists: delete it 111 [sSubject, iSubject] = bst_get('Subject', SubjectNames{iSubj}); 112 if ~isempty(sSubject) 113 db_delete_subjects(iSubject); 114 end 115 116 % ===== FILES TO IMPORT ===== 117 % Build the path of the files to import 118 AnatDir = fullfile(bids_dir, 'derivatives', 'freesurfer', SubjectNames{iSubj}, 'ses-mri', 'anat'); 119 DataDir = fullfile(bids_dir, 'derivatives', 'meg_derivatives', SubjectNames{iSubj}, 'ses-meg', 'meg'); 120 % Check if the folder contains the required files 121 if ~file_exist(AnatDir) 122 error(['The folder "' AnatDir '" does not exist.']); 123 end 124 if ~file_exist(DataDir) 125 error(['The folder "' DataDir '" does not exist.']); 126 end 127 128 % ===== ANATOMY ===== 129 % Process: Import anatomy folder 130 bst_process('CallProcess', 'process_import_anatomy', [], [], ... 131 'subjectname', SubjectNames{iSubj}, ... 132 'mrifile', {AnatDir, 'FreeSurfer'}, ... 133 'nvertices', 15000); 134 135 % ===== PROCESS EACH RUN ===== 136 for iRun = 1:6 137 % Files to import 138 FifFile = bst_fullfile(DataDir, sprintf('%s_ses-meg_task-facerecognition_run-%02d_proc-sss_meg.fif', SubjectNames{iSubj}, iRun)); 139 140 % ===== LINK CONTINUOUS FILE ===== 141 % Process: Create link to raw file 142 sFileRaw = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 143 'subjectname', SubjectNames{iSubj}, ... 144 'datafile', {FifFile, 'FIF'}, ... 145 'channelreplace', 1, ... 146 'channelalign', 0); 147 % Set acquisition date 148 panel_record('SetAcquisitionDate', sFileRaw.iStudy, AcquisitionDates{iSubj}); 149 150 % ===== PREPARE CHANNEL FILE ===== 151 % Process: Set channels type 152 bst_process('CallProcess', 'process_channel_settype', sFileRaw, [], ... 153 'sensortypes', 'EEG061, EEG064', ... 154 'newtype', 'NOSIG'); 155 bst_process('CallProcess', 'process_channel_settype', sFileRaw, [], ... 156 'sensortypes', 'EEG062', ... 157 'newtype', 'EOG'); 158 bst_process('CallProcess', 'process_channel_settype', sFileRaw, [], ... 159 'sensortypes', 'EEG063', ... 160 'newtype', 'ECG'); 161 162 % Process: Remove head points 163 sFileRaw = bst_process('CallProcess', 'process_headpoints_remove', sFileRaw, [], ... 164 'zlimit', 0); 165 % Process: Refine registration 166 sFileRaw = bst_process('CallProcess', 'process_headpoints_refine', sFileRaw, []); 167 % Process: Project electrodes on scalp 168 sFileRaw = bst_process('CallProcess', 'process_channel_project', sFileRaw, []); 169 170 % Process: Snapshot: Sensors/MRI registration 171 bst_process('CallProcess', 'process_snapshot', sFileRaw, [], ... 172 'target', 1, ... % Sensors/MRI registration 173 'modality', 1, ... % MEG (All) 174 'orient', 1, ... % left 175 'Comment', sprintf('MEG/MRI Registration: Subject #%d, Run #%d', iSubj, iRun)); 176 bst_process('CallProcess', 'process_snapshot', sFileRaw, [], ... 177 'target', 1, ... % Sensors/MRI registration 178 'modality', 4, ... % EEG 179 'orient', 1, ... % left 180 'Comment', sprintf('EEG/MRI Registration: Subject #%d, Run #%d', iSubj, iRun)); 181 182 % ===== IMPORT TRIGGERS ===== 183 % Process: Read from channel 184 bst_process('CallProcess', 'process_evt_read', sFileRaw, [], ... 185 'stimchan', 'STI101', ... 186 'trackmode', 2, ... % Bit: detect the changes for each bit independently 187 'zero', 0); 188 % Process: Group by name 189 bst_process('CallProcess', 'process_evt_groupname', sFileRaw, [], ... 190 'combine', 'Unfamiliar=3,4', ... 191 'dt', 0, ... 192 'delete', 1); 193 % Process: Rename event 194 bst_process('CallProcess', 'process_evt_rename', sFileRaw, [], ... 195 'src', '3', ... 196 'dest', 'Famous'); 197 % Process: Rename event 198 bst_process('CallProcess', 'process_evt_rename', sFileRaw, [], ... 199 'src', '5', ... 200 'dest', 'Scrambled'); 201 % Process: Add time offset 202 bst_process('CallProcess', 'process_evt_timeoffset', sFileRaw, [], ... 203 'info', [], ... 204 'eventname', 'Famous, Unfamiliar, Scrambled', ... 205 'offset', 0.0345); 206 % Process: Delete events 207 bst_process('CallProcess', 'process_evt_delete', sFileRaw, [], ... 208 'eventname', '1,2,6,7,8,9,10,11,12,13,14,15,16'); 209 % Process: Detect cHPI activity (Elekta):STI201 210 bst_process('CallProcess', 'process_evt_detect_chpi', sFileRaw, [], ... 211 'eventname', 'chpi_bad', ... 212 'channelname', 'STI201', ... 213 'method', 'off'); % Mark as bad when the HPI coils are OFF 214 215 % ===== FREQUENCY FILTERS ===== 216 % Process: Notch filter: 50Hz 100Hz 150Hz 200Hz 217 sFileClean = bst_process('CallProcess', 'process_notch', sFileRaw, [], ... 218 'freqlist', [50, 100, 150, 200], ... 219 'sensortypes', 'MEG, EEG', ... 220 'read_all', 0); 221 % Process: Power spectrum density (Welch) 222 sFilesPsd = bst_process('CallProcess', 'process_psd', [sFileRaw, sFileClean], [], ... 223 'timewindow', [], ... 224 'win_length', 4, ... 225 'win_overlap', 50, ... 226 'sensortypes', 'MEG, EEG', ... 227 'edit', struct(... 228 'Comment', 'Power', ... 229 'TimeBands', [], ... 230 'Freqs', [], ... 231 'ClusterFuncTime', 'none', ... 232 'Measure', 'power', ... 233 'Output', 'all', ... 234 'SaveKernel', 0)); 235 % Process: Snapshot: Frequency spectrum 236 bst_process('CallProcess', 'process_snapshot', sFilesPsd, [], ... 237 'target', 10, ... % Frequency spectrum 238 'Comment', sprintf('Power spctrum: Subject #%d, Run #%d', iSubj, iRun)); 239 240 % ===== BAD CHANNELS ===== 241 if ~isempty(BadChannels{iSubj}{iRun}) 242 % Process: Set bad channels 243 bst_process('CallProcess', 'process_channel_setbad', sFileClean, [], ... 244 'sensortypes', BadChannels{iSubj}{iRun}); 245 end 246 247 % ===== EEG REFERENCE ===== 248 % Process: Re-reference EEG 249 bst_process('CallProcess', 'process_eegref', sFileClean, [], ... 250 'eegref', 'AVERAGE', ... 251 'sensortypes', 'EEG'); 252 253 % ===== DETECT ARTIFACTS ====== 254 % Process: Detect heartbeats 255 bst_process('CallProcess', 'process_evt_detect_ecg', sFileClean, [], ... 256 'channelname', 'EEG063', ... 257 'timewindow', [], ... 258 'eventname', 'cardiac'); 259 % Different amplitude thresholds for different subjects 260 if strcmpi(SubjectNames{iSubj}, 'sub-05') 261 thresholdMAX = 50; 262 else 263 thresholdMAX = 100; 264 end 265 % Process: Detect: blink_BAD - Detects all events where the amplitude exceeds 100uV 266 bst_process('CallProcess', 'process_evt_detect_threshold', sFileClean, [], ... 267 'eventname', 'blink_BAD', ... 268 'channelname', 'EEG062', ... 269 'timewindow', [], ... 270 'thresholdMAX', thresholdMAX, ... 271 'units', 3, ... % uV (10^-6) 272 'bandpass', [0.3, 20], ... 273 'isAbsolute', 1, ... 274 'isDCremove', 0); 275 276 % ===== SSP COMPUTATION ===== 277 % Process: SSP ECG: cardiac 278 bst_process('CallProcess', 'process_ssp_ecg', sFileClean, [], ... 279 'eventname', 'cardiac', ... 280 'sensortypes', 'MEG GRAD', ... 281 'usessp', 1, ... 282 'select', SspSelect{iSubj}{iRun}{1}); 283 bst_process('CallProcess', 'process_ssp_ecg', sFileClean, [], ... 284 'eventname', 'cardiac', ... 285 'sensortypes', 'MEG MAG', ... 286 'usessp', 1, ... 287 'select', SspSelect{iSubj}{iRun}{2}); 288 % Process: Snapshot: SSP projectors 289 bst_process('CallProcess', 'process_snapshot', sFileClean, [], ... 290 'target', 2, ... 291 'Comment', sprintf('Subject #%d, Run #%d', iSubj, iRun)); % SSP projectors 292 293 % ===== IMPORT BAD EVENTS ===== 294 % Get bad segments: this is typically done manually, not from a script 295 BadSegments = GetBadSegments(iSubj, iRun); 296 % Process: Import from file 297 bst_process('CallProcess', 'process_evt_import', sFileClean, [], ... 298 'evtfile', {BadSegments, 'ARRAY-TIMES'}, ... 299 'evtname', 'BAD'); 300 301 % ===== IMPORT TRIALS ===== 302 % Process: Import MEG/EEG: Events 303 sFilesEpochs = bst_process('CallProcess', 'process_import_data_event', sFileClean, [], ... 304 'subjectname', SubjectNames{iSubj}, ... 305 'condition', '', ... 306 'eventname', 'Famous, Scrambled, Unfamiliar', ... 307 'timewindow', [], ... 308 'epochtime', [-0.5, 1.2], ... 309 'createcond', 0, ... 310 'ignoreshort', 1, ... 311 'usectfcomp', 1, ... 312 'usessp', 1, ... 313 'freq', [], ... 314 'baseline', [-0.5, -0.0009]); 315 316 % ===== AVERAGE: RUN ===== 317 % Process: Average: By trial group (folder average) 318 sFilesAvg = bst_process('CallProcess', 'process_average', sFilesEpochs, [], ... 319 'avgtype', 5, ... % By trial group (folder average) 320 'avg_func', 1, ... % Arithmetic average: mean(x) 321 'weighted', 0, ... 322 'keepevents', 0); 323 % Process: Snapshot: Recordings time series 324 bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 325 'target', 5, ... % Recordings time series 326 'modality', 4, ... % EEG 327 'time', 0.11, ... 328 'Comment', sprintf('Subject #%d, Run #%d', iSubj, iRun)); 329 % Process: Snapshot: Recordings topography 330 bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 331 'target', 6, ... % Recordings topography (one time) 332 'modality', 4, ... % EEG 333 'time', 0.11, ... 334 'Comment', sprintf('Subject #%d, Run #%d', iSubj, iRun)); 335 336 % ===== COMPUTE NOISECOV: EEG ===== 337 % Process: Compute covariance (noise or data) 338 bst_process('CallProcess', 'process_noisecov', sFilesEpochs, [], ... 339 'baseline', [-0.5, -0.0009], ... 340 'sensortypes', 'EEG', ... 341 'target', 1, ... % Noise covariance (covariance over baseline time window) 342 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 343 'identity', 0, ... 344 'copycond', 0, ... 345 'copysubj', 0, ... 346 'replacefile', 1); % Replace 347 end 348 349 % Save report 350 ReportFile = bst_report('Save', []); 351 if ~isempty(reports_dir) && ~isempty(ReportFile) 352 bst_report('Export', ReportFile, bst_fullfile(reports_dir, ['report_' ProtocolName '_' SubjectNames{iSubj} '.html'])); 353 end 354 end 355 356 357 %% ===== EMPTY ROOM RECORDINGS ===== 358 disp(sprintf('\n===== IMPORT: EMPTY-ROOM =====\n')); 359 % Loop on all the noise sessions 360 NoiseFiles = {}; 361 for ses = {'20090409', '20090506', '20090511', '20090515', '20090518', '20090601', '20091126', '20091208'} 362 NoiseFiles{end+1} = fullfile(bids_dir, 'derivatives', 'meg_derivatives', EmptyRoomSubj, ['ses-' ses{1}], 'meg', ['sub-emptyroom_ses-' ses{1} '_task-noise_proc-sss_meg.fif']); 363 end 364 % Process: Create link to raw file 365 sFilesNoise = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 366 'subjectname', EmptyRoomSubj, ... 367 'datafile', {NoiseFiles, 'FIF'}, ... 368 'channelreplace', 1, ... 369 'channelalign', 0); 370 % Process: Notch filter: 50Hz 100Hz 150Hz 200Hz 371 sFileNoiseClean = bst_process('CallProcess', 'process_notch', sFilesNoise, [], ... 372 'freqlist', [50, 100, 150, 200], ... 373 'sensortypes', 'MEG, EEG', ... 374 'read_all', 0); 375 % Process: Compute noise covariance 376 bst_process('CallProcess', 'process_noisecov', sFileNoiseClean, [], ... 377 'baseline', [], ... 378 'sensortypes', 'MEG', ... 379 'target', 1, ... % Noise covariance (covariance over baseline time window) 380 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 381 'identity', 0, ... 382 'copycond', 1, ... 383 'copysubj', 1, ... 384 'copymatch', 1, ... 385 'replacefile', 2); % Merge 386 387 388 %% ===== SOURCE ESTIMATION ===== 389 % Start a new report (one report for the source estimation of all the subjects) 390 bst_report('Start'); 391 % Loop on the subjects: This loop is separated from the previous one, because we should 392 % compute the BEM surfaces after importing all the runs, so that the registration is done 393 % using the high resolution head surface, instead of the smooth scalp BEM layer. 394 for iSubj = 1:length(SubjectNames) 395 disp(sprintf('\n===== SOURCES: SUBJECT #%d =====\n', iSubj)); 396 397 % ===== BEM SURFACES ===== 398 % Process: Generate BEM surfaces 399 bst_process('CallProcess', 'process_generate_bem', [], [], ... 400 'subjectname', SubjectNames{iSubj}, ... 401 'nscalp', 1082, ... 402 'nouter', 642, ... 403 'ninner', 642, ... 404 'thickness', 4, ... 405 'method', 'brainstorm'); 406 407 % ===== SELECT ALL AVERAGES ===== 408 % Process: Select data files in: */* 409 sFilesAvg = bst_process('CallProcess', 'process_select_files_data', [], [], ... 410 'subjectname', SubjectNames{iSubj}); 411 % Process: Select file comments with tag: Avg 412 sFilesAvg = bst_process('CallProcess', 'process_select_tag', sFilesAvg, [], ... 413 'tag', 'Avg'); % Select only the files with the tag 414 415 % ===== COMPUTE HEAD MODELS ===== 416 % Process: Compute head model (only for the first run of the subject) 417 bst_process('CallProcess', 'process_headmodel', sFilesAvg(1), [], ... 418 'sourcespace', 1, ... % Cortex surface 419 'meg', 3, ... % Overlapping spheres 420 'eeg', 3, ... % OpenMEEG BEM 421 'ecog', 1, ... % 422 'seeg', 1, ... % 423 'openmeeg', struct(... 424 'BemSelect', [1, 1, 1], ... 425 'BemCond', [1, 0.0125, 1], ... 426 'BemNames', {{'Scalp', 'Skull', 'Brain'}}, ... 427 'BemFiles', {{}}, ... 428 'isAdjoint', 0, ... 429 'isAdaptative', 1, ... 430 'isSplit', 0, ... 431 'SplitLength', 4000)); 432 % Get all the runs for this subject (ie the list of the study indices) 433 iStudyOther = setdiff(unique([sFilesAvg.iStudy]), sFilesAvg(1).iStudy); 434 % Copy the forward model file to the other runs 435 sHeadmodel = bst_get('HeadModelForStudy', sFilesAvg(1).iStudy); 436 for iStudy = iStudyOther 437 db_add(iStudy, sHeadmodel.FileName); 438 end 439 440 % ===== COMPUTE SOURCES: MEG ===== 441 % Process: Compute sources [2018] 442 sAvgSrcMeg = bst_process('CallProcess', 'process_inverse_2018', sFilesAvg, [], ... 443 'output', 1, ... % Kernel only: shared 444 'inverse', struct(... 445 'Comment', 'MN: MEG ALL', ... 446 'InverseMethod', 'minnorm', ... 447 'InverseMeasure', 'amplitude', ... 448 'SourceOrient', {{'fixed'}}, ... 449 'Loose', 0.2, ... 450 'UseDepth', 1, ... 451 'WeightExp', 0.5, ... 452 'WeightLimit', 10, ... 453 'NoiseMethod', 'reg', ... 454 'NoiseReg', 0.1, ... 455 'SnrMethod', 'fixed', ... 456 'SnrRms', 1e-06, ... 457 'SnrFixed', 3, ... 458 'ComputeKernel', 1, ... 459 'DataTypes', {{'MEG GRAD', 'MEG MAG'}})); 460 % Process: Snapshot: Sources (one time) - Loop only to get a correct comment for the report 461 for i = 1:length(sAvgSrcMeg) 462 bst_process('CallProcess', 'process_snapshot', sAvgSrcMeg(i), [], ... 463 'target', 8, ... % Sources (one time) 464 'orient', 4, ... % bottom 465 'time', 0.11, ... 466 'threshold', 20, ... 467 'Comment', ['MEG sources: ' sFilesAvg(i).FileName]); 468 end 469 470 % ===== COMPUTE SOURCES: EEG ===== 471 % Process: Compute sources [2018] 472 sAvgSrcEeg = bst_process('CallProcess', 'process_inverse_2018', sFilesAvg, [], ... 473 'output', 1, ... % Kernel only: shared 474 'inverse', struct(... 475 'Comment', 'MN: EEG', ... 476 'InverseMethod', 'minnorm', ... 477 'InverseMeasure', 'amplitude', ... 478 'SourceOrient', {{'fixed'}}, ... 479 'Loose', 0.2, ... 480 'UseDepth', 1, ... 481 'WeightExp', 0.5, ... 482 'WeightLimit', 10, ... 483 'NoiseMethod', 'reg', ... 484 'NoiseReg', 0.1, ... 485 'SnrMethod', 'fixed', ... 486 'SnrRms', 1e-06, ... 487 'SnrFixed', 3, ... 488 'ComputeKernel', 1, ... 489 'DataTypes', {{'EEG'}})); 490 % Process: Snapshot: Sources (one time) - Loop only to get a correct comment for the report 491 for i = 1:length(sAvgSrcEeg) 492 bst_process('CallProcess', 'process_snapshot', sAvgSrcEeg(i), [], ... 493 'target', 8, ... % Sources (one time) 494 'orient', 4, ... % bottom 495 'time', 0.11, ... 496 'threshold', 10, ... 497 'Comment', ['EEG sources: ' sFilesAvg(i).FileName]); 498 end 499 end 500 % Save report 501 ReportFile = bst_report('Save', []); 502 if ~isempty(reports_dir) && ~isempty(ReportFile) 503 bst_report('Export', ReportFile, bst_fullfile(reports_dir, ['report_' ProtocolName '_sources.html'])); 504 end 505 506 507 %% ===== TIME-FREQUENCY ===== 508 % Start a new report (one report for the time-frequency of all the subjects) 509 bst_report('Start'); 510 % List of conditions to process separately 511 AllConditions = {'Famous', 'Scrambled', 'Unfamiliar'}; 512 % Channels to display in the screen capture, by order of preference (if the first channel is bad, use the following) 513 SelChannel = {'EEG070','EEG060','EEG065','EEG050','EEG003'}; 514 % Compute one separate time-frequency average for each subject/run/condition 515 for iSubj = 1:length(SubjectNames) 516 disp(sprintf('\n===== TIME-FREQUENCY: SUBJECT #%d =====\n', iSubj)); 517 for iRun = 1:6 518 % Process: Select data files in: Subject/Run 519 sTrialsAll = bst_process('CallProcess', 'process_select_files_data', [], [], ... 520 'subjectname', SubjectNames{iSubj}, ... 521 'condition', sprintf('sub-%02d_ses-meg_task-facerecognition_run-%02d_proc-sss_meg_notch', iSubj, iRun)); 522 % Loop on the conditions 523 for iCond = 1:length(AllConditions) 524 % Comment describing this average 525 strComment = [SubjectNames{iSubj}, ' / ', sprintf('run_%02d', iRun), ' / ', AllConditions{iCond}]; 526 disp(['BST> ' strComment]); 527 % Find the first good channel in the display list 528 if isempty(BadChannels{iSubj}{iRun}) 529 iSel = 1; 530 else 531 iSel = find(~ismember(SelChannel,BadChannels{iSubj}{iRun}), 1); 532 end 533 % Process: Select file comments with tag: Avg 534 sTrialsCond = bst_process('CallProcess', 'process_select_tag', sTrialsAll, [], ... 535 'tag', [AllConditions{iCond}, '_trial'], ... 536 'search', 1, ... % Search the file names 537 'select', 1); % Select only the files with the tag 538 % Process: Time-frequency (Morlet wavelets), averaged across trials 539 sTimefreq = bst_process('CallProcess', 'process_timefreq', sTrialsCond, [], ... 540 'sensortypes', 'MEG MAG, EEG', ... 541 'edit', struct(... 542 'Comment', ['Avg: ' AllConditions{iCond} ', Power, 6-60Hz'], ... 543 'TimeBands', [], ... 544 'Freqs', [6, 6.8, 7.6, 8.6, 9.7, 11, 12.4, 14, 15.8, 17.9, 20.2, 22.8, 25.7, 29, 32.7, 37, 41.7, 47.1, 53.2, 60], ... 545 'MorletFc', 1, ... 546 'MorletFwhmTc', 3, ... 547 'ClusterFuncTime', 'none', ... 548 'Measure', 'power', ... 549 'Output', 'average', ... 550 'RemoveEvoked', 0, ... 551 'SaveKernel', 0), ... 552 'normalize', 'none'); % None: Save non-standardized time-frequency maps 553 % Process: Extract time: [-200ms,900ms] 554 sTimefreq = bst_process('CallProcess', 'process_extract_time', sTimefreq, [], ... 555 'timewindow', [-0.2, 0.9], ... 556 'overwrite', 1); 557 % Screen capture of one sensor 558 hFigTf = view_timefreq(sTimefreq.FileName, 'SingleSensor', SelChannel{iSel}); 559 bst_report('Snapshot', hFigTf, strComment, 'Time-frequency', [200, 200, 400, 250]); 560 close(hFigTf); 561 end 562 end 563 end 564 % Save report 565 ReportFile = bst_report('Save', []); 566 if ~isempty(reports_dir) && ~isempty(ReportFile) 567 bst_report('Export', ReportFile, bst_fullfile(reports_dir, ['report_' ProtocolName '_timefreq.html'])); 568 end 569 end 570 571 572 573 574 %% ===== SUPPORT FUNCTIONS ===== 575 function BadSeg = GetBadSegments(iSubj, iRun) 576 BadSegments{1} = {... 577 [247.867 248.185; 598.999 598.999; 598.999 598.999; 611.999 611.999; 612.999 612.999; 613.999 613.999; 616.999 616.999; 617.999 617.999; 623.999 623.999; 715.209 715.467], ... 578 [84.791 85.166], ... 579 [79.183 80.167], ... 580 [64.309 65.185], ... 581 [90.958 91.167; 178.005 178.355; 293.282 295.919; 312.298 316.479; 353.835 357.716], ... 582 [60.292 66.802; 69.975 71.210; 105.233 107.586; 108.822 109.506; 376.225 376.325]}; 583 BadSegments{2} = {... 584 [223.806 224.199; 279.772 279.895; 453.241 455.108; 692.423 692.593], ... 585 [65.298 66.194; 304.727 306.178; 399.165 400.732], ... 586 [203.141 205.085; 281.579 287.883; 420.395 421.128], ... 587 [387.118 388.229; 440.318 441.900; 554.825 558.744], ... 588 [71.000 80.999; 82.750 87.367; 149.528 149.667; 264.747 267.995; 368.415 371.973; 376.263 378.763; 398.334 401.551; 537.410 541.645], ... 589 [38.000 47.999; 47.825 50.046; 61.298 61.384; 249.653 253.379; 282.917 283.820; 286.135 287.616; 298.167 300.196; 328.254 329.511; 335.957 337.817; 478.277 480.707]}; 590 BadSegments{3} = {... 591 [406.312 407.207; 727.055 728.714], ... 592 [84.894 85.156; 152.028 152.946; 297.835 298.915; 418.272 421.845; 554.084 554.794], ... 593 [73.758 74.159; 378.212 378.536; 406.065 407.099; 470.541 471.698; 488.900 491.168; 529.596 530.453], ... 594 [94.874 95.152; 317.385 321.374; 325.696 327.055; 439.220 439.829; 454.473 455.175; 486.196 486.829; 518.660 522.015; 524.400 525.249; 562.417 570.325], ... 595 [96.208 97.181; 98.942 99.096; 135.005 135.754; 143.990 144.599; 250.139 250.247; 300.459 300.559; 338.265 339.322; 545.913 546.067], ... 596 [91.415 92.156; 284.843 286.525; 297.886 298.404; 317.046 317.163; 332.698 332.791; 358.946 359.402; 428.405 428.775; 478.374 478.690; 549.866 550.128]}; 597 BadSegments{4} = {... 598 [22.967 22.967; 50.036 50.098; 52.058 52.058; 156.653 156.653; 171.565 173.386; 239.544 242.105; 268.162 270.175; 268.992 268.992; 316.032 316.032; 338.283 339.000; 357.959 361.909; 370.871 370.871; 381.579 383.677; 437.731 437.731; 463.482 468.505; 476.135 479.838; 486.652 488.272; 504.860 508.999], ... 599 [309.493 311.707; 342.681 344.525; 354.019 357.321; 390.023 391.225; 393.926 395.855; 404.221 405.069; 432.522 435.932; 459.048 460.715; 471.763 478.529; 549.387 551.999; 591.087 594.143; 608.541 611.079; 624.847 626.615; 649.648 651.570], ... 600 [57.411 58.198; 88.346 88.955; 200.761 202.335; 227.016 227.688; 257.726 258.054; 356.798 359.005; 404.260 411.003], ... 601 [46.000 54.823; 61.000 70.332; 203.005 207.125; 275.875 278.121; 313.500 314.824; 337.973 338.636; 422.505 426.239], ... 602 [58.000 62.479; 78.250 85.166; 89.955 91.360; 116.322 117.888; 130.013 131.987; 149.509 150.489; 174.650 175.823; 182.030 183.334; 196.758 197.384; 204.458 204.697; 205.236 208.663; 311.028 316.383; 320.700 327.181; 332.437 335.354; 344.205 346.133; 374.208 374.865; 385.519 386.214; 441.942 444.241; 453.957 456.997; 486.039 487.004; 501.238 504.185; 512.962 514.675; 553.398 556.215], ... 603 [41.406 45.743; 58.681 59.144; 108.086 108.896; 140.633 143.750; 196.110 199.474; 210.778 210.971; 234.649 235.143; 258.081 259.632; 339.101 340.805; 390.277 390.609; 438.935 442.122; 528.221 534.031]}; 604 BadSegments{5} = {... 605 [265.539 265.778; 266.334 266.495; 268.479 268.965; 367.428 367.636; 439.655 442.779; 453.497 453.853; 504.997 505.329; 519.513 519.683; 595.674 595.982; 602.000 602.463], ... 606 [121.113 121.499; 124.971 126.213; 253.735 254.075; 272.232 272.464; 272.895 273.104; 346.368 346.645; 368.812 369.052; 406.382 406.605; 452.920 453.113; 454.903 455.112; 507.655 507.840; 508.766 509.013; 584.853 585.030; 594.831 595.656; 597.261 602.249], ... 607 [37.251 37.497; 38.825 39.056; 40.615 41.849; 43.624 44.758; 53.333 53.641; 54.698 55.076; 57.668 59.196; 79.129 79.360; 81.475 81.714; 122.658 123.375; 284.787 285.296; 288.754 288.993; 345.790 346.022; 421.212 421.459; 481.428 482.207; 503.408 503.685; 504.272 504.449; 524.451 524.714; 526.913 531.499], ... 608 [87.322 88.178; 91.085 91.325; 95.121 95.491; 114.174 114.397; 129.874 130.113; 151.220 151.544; 281.689 281.959; 532.966 533.345], ... 609 [59.176 60.218; 74.854 75.317; 308.180 309.877; 380.705 381.059], ... 610 [182.382 183.245; 196.220 196.736; 276.018 276.327; 292.490 294.086; 370.755 370.847; 435.644 436.624; 467.535 468.460; 522.838 525.847]}; 611 BadSegments{6} = {... 612 [141.690 142.424; 157.070 157.417; 355.138 356.025; 423.999 423.999; 424.999 424.999; 426.999 426.999; 427.999 427.999; 486.430 488.151; 493.999 493.999; 501.511 501.619; 501.549 501.549; 501.585 501.585; 502.999 502.999; 503.999 503.999; 540.999 540.999; 541.999 541.999; 555.999 555.999; 556.999 556.999; 561.999 561.999; 563.999 563.999; 564.999 564.999; 565.999 565.999; 567.999 567.999], ... 613 [64.898 65.161; 71.700 72.718; 226.185 226.740; 324.124 324.425; 329.062 329.301; 486.143 486.975], ... 614 [62.300 63.148; 266.254 266.639; 409.920 410.221], ... 615 [54.048 55.214; 330.893 331.255], ... 616 [185.616 186.495; 331.411 331.796; 386.843 387.028; 387.999 387.999; 389.999 389.999; 434.575 434.875; 519.802 519.995], ... 617 [44.720 45.167; 211.446 211.964; 368.955 369.172]}; 618 BadSegments{7} = {... 619 [154.966 155.144; 551.639 551.855], ... 620 [88.774 89.167; 107.999 107.999; 109.999 109.999; 110.999 110.999; 112.999 112.999; 113.999 113.999; 114.999 114.999; 119.999 119.999; 121.999 121.999; 124.223 125.465; 137.011 138.871], ... 621 [81.627 82.136; 377.953 381.046], ... 622 [241.136 242.171; 543.849 544.196; 596.639 598.553; 600.227 601.075; 603.999 603.999; 605.999 605.999; 609.999 609.999; 611.305 612.809; 614.999 614.999; 615.803 616.937; 623.694 625.877; 653.999 653.999; 655.055 655.756; 663.999 663.999], ... 623 [68.852 69.481; 74.034 75.200; 78.426 78.600; 104.497 105.963; 253.951 254.034; 256.964 257.038; 257.915 258.048; 323.254 324.156; 365.880 368.131; 369.952 370.060; 371.728 372.999; 430.931 431.965; 535.521 542.999], ... 624 [70.271 71.205; 94.441 96.445; 98.613 99.126; 112.318 112.749; 131.686 132.265; 148.935 150.615; 161.120 161.600; 205.325 208.214; 215.035 215.863; 217.403 218.818; 286.178 287.171; 399.075 404.853]}; 625 BadSegments{8} = {... 626 [238.505 238.546; 256.354 257.224; 316.116 316.167; 341.519 341.558; 356.493 356.566; 380.095 380.170; 391.906 392.048; 448.457 448.562; 469.931 470.028; 530.488 530.575; 555.180 558.136; 562.152 562.245; 588.403 588.502; 625.205 625.662; 638.019 638.438; 649.982 650.008; 650.691 651.357; 651.925 652.061; 665.445 665.472; 695.923 696.015; 706.528 706.720; 729.706 732.534], ... 627 [99.546 106.114; 113.245 114.199; 150.885 154.989; 277.486 278.075; 333.645 335.574; 339.358 340.646; 371.860 375.394; 497.459 499.156], ... 628 [49.008 50.205; 231.446 233.406; 329.590 329.659; 355.101 356.019; 360.733 360.973; 372.955 374.891; 389.283 392.068; 453.610 455.431; 464.632 465.265; 489.209 489.996; 514.777 515.295], ... 629 [178.368 179.232; 293.865 294.521; 418.252 418.314; 450.124 450.209; 480.236 480.445; 492.725 493.975; 495.170 497.624; 500.382 500.459; 504.247 504.402; 628.017 628.079; 628.827 628.905; 630.209 630.332], ... 630 [100.616 101.172; 107.691 108.539; 188.814 188.875; 193.119 193.281; 207.964 208.033; 432.254 432.385; 489.834 489.911; 517.960 518.037; 518.955 519.040; 520.938 521.062; 521.945 522.037; 523.959 524.052; 525.942 526.057; 526.945 527.015; 528.958 529.059; 531.138 531.192; 531.979 532.048; 532.951 533.028; 533.962 534.024], ... 631 [135.997 137.232; 383.565 383.657; 418.763 418.955]}; 632 BadSegments{9} = {... 633 [215.107 216.187; 262.388 262.388; 287.519 287.635; 289.895 290.135; 311.999 311.999; 350.161 351.179; 526.154 527.033; 564.999 564.999; 584.935 585.059; 587.999 587.999; 601.999 601.999; 603.999 603.999; 608.999 608.999; 612.999 612.999], ... 634 [47.667 47.775; 49.172 54.681; 67.195 70.805; 78.988 80.477; 138.701 138.948; 138.727 138.727; 138.728 138.728; 138.728 138.728; 138.734 138.734; 138.734 138.734; 138.881 138.881; 138.881 138.881; 138.907 138.907; 140.993 141.093; 141.037 141.037; 141.045 141.045; 155.795 155.864; 155.822 155.822; 155.849 155.849; 168.999 168.999; 206.999 206.999; 219.999 219.999; 225.999 225.999; 226.999 226.999; 228.999 228.999; 236.999 236.999; 242.463 242.463; 242.463 242.463; 242.487 242.487; 247.999 247.999; 251.999 251.999; 252.483 252.483; 253.315 254.163; 265.999 265.999; 267.999 267.999; 272.358 272.358; 272.410 272.410; 298.999 298.999; 300.999 300.999; 314.037 314.037; 314.047 314.047; 321.813 321.813; 321.813 321.813; 321.833 321.833; 329.117 329.117; 329.117 329.117; 329.156 329.156; 346.999 346.999; 347.999 347.999; 349.320 349.320; 349.329 349.329; 352.528 355.869; 364.040 364.040; 396.278 397.420; 404.865 404.865; 407.905 407.905; 407.905 407.905; 407.954 407.954; 418.454 418.454; 418.454 418.454; 418.486 418.486; 441.999 441.999; 444.999 444.999; 447.999 447.999; 453.550 453.650; 454.931 455.055; 457.999 457.999; 479.964 480.079; 481.999 481.999; 482.949 483.073; 488.948 489.064; 511.999 511.999; 520.999 520.999; 523.999 523.999; 526.954 527.069; 533.999 533.999; 537.999 537.999], ... 635 [82.889 83.198; 206.143 207.424; 403.873 404.096; 406.790 407.485; 413.936 414.075; 415.912 416.112; 536.621 537.532], ... 636 [182.999 182.999; 182.999 182.999; 183.999 183.999; 195.999 195.999; 208.999 208.999; 209.999 209.999; 278.601 278.955; 413.913 414.067; 415.250 417.792; 419.940 420.087; 420.999 420.999; 512.999 512.999; 514.363 516.254; 521.917 522.134; 522.999 522.999; 523.915 524.101; 533.999 533.999; 538.999 538.999; 539.892 540.062; 543.999 543.999; 548.874 549.089; 549.900 550.062; 552.755 554.075; 585.999 585.999; 587.957 588.073; 588.999 588.999; 594.999 594.999; 603.971 604.056; 604.928 605.097; 615.986 618.495; 623.999 623.999], ... 637 [53.215 54.203; 164.227 168.965; 201.433 202.775; 292.973 295.889; 303.961 304.817; 309.354 311.236; 313.123 313.639; 322.547 323.017; 331.141 334.852; 356.637 356.985; 367.855 368.079; 369.995 373.459; 377.849 378.142; 406.072 407.306; 436.164 436.665; 458.033 458.905; 516.889 518.656; 517.812 518.684], ... 638 [113.945 115.225; 198.570 198.863; 264.162 264.795; 383.705 385.641; 396.477 397.064; 399.706 406.457; 452.261 453.179; 486.338 487.102; 498.869 499.579; 507.968 508.925; 546.266 547.285; 558.825 560.128]}; 639 BadSegments{10} = {... 640 [235.104 236.184; 324.272 325.028; 330.799 331.401; 541.062 541.826; 564.747 565.072], ... 641 [100.581 101.229; 285.644 285.644; 285.644 285.644; 297.979 298.033; 298.999 298.999; 300.949 301.026; 301.999 301.999; 303.999 303.999; 304.999 304.999; 306.999 306.999; 307.999 307.999; 310.999 310.999; 311.999 311.999; 313.971 314.025; 314.999 314.999; 316.995 317.035; 317.999 317.999; 319.999 319.999; 320.923 321.046; 326.971 327.048; 327.999 327.999; 329.999 329.999; 330.999 330.999; 332.974 333.028; 333.999 333.999; 335.971 336.025; 336.999 336.999; 338.973 339.035; 339.999 339.999; 341.951 342.044; 343.999 343.999; 344.964 345.033; 346.999 346.999; 347.999 347.999; 452.015 453.411; 458.735 459.776; 467.974 468.089], ... 642 [41.266 41.675; 53.905 55.240; 159.159 159.345; 220.255 220.394], ... 643 [66.751 67.190; 201.674 201.812; 294.119 295.168; 303.188 303.528; 316.992 317.037; 317.999 317.999; 317.999 317.999; 319.999 319.999; 320.980 321.042; 322.999 322.999; 325.999 325.999; 326.955 327.048; 328.999 328.999; 333.999 333.999; 334.999 334.999; 342.999 342.999; 343.999 343.999; 351.915 352.038; 352.999 352.999; 407.979 408.056; 409.999 409.999; 411.999 411.999; 415.405 416.154; 435.999 435.999; 436.962 437.046; 468.885 469.100; 469.999 469.999; 470.999 470.999; 516.210 516.357], ... 644 [105.369 106.172; 141.468 142.178; 199.008 199.818; 201.269 201.716; 352.851 353.083; 449.865 452.041; 459.508 459.802], ... 645 [229.948 230.033; 230.999 230.999; 230.999 230.999; 259.588 259.990; 343.970 345.798; 361.999 361.999; 362.970 363.046; 364.999 364.999; 366.999 366.999; 367.962 368.031; 372.521 374.179; 405.999 405.999; 409.999 409.999; 411.999 411.999; 412.999 412.999; 434.999 434.999; 435.970 436.031; 516.999 516.999; 519.999 519.999]}; 646 BadSegments{11} = {... 647 [179.045 180.225; 323.999 323.999; 323.999 323.999; 324.999 324.999; 327.978 328.025; 328.966 329.028; 330.999 330.999; 365.999 365.999; 367.999 367.999; 370.999 370.999; 371.999 371.999; 373.999 373.999; 375.965 376.042; 377.999 377.999], ... 648 [52.107 53.156; 521.077 521.155], ... 649 [65.331 66.156], ... 650 [81.579 82.143; 108.565 108.565; 108.566 108.566; 112.176 112.176; 122.377 122.377; 122.565 122.565; 213.882 213.882; 215.305 215.305; 224.851 224.851; 224.919 224.919; 255.815 255.815; 257.893 257.893; 359.952 359.952; 361.630 361.754; 370.285 370.285; 376.853 376.853; 511.600 511.600; 513.631 513.631; 513.988 513.988; 518.215 518.215], ... 651 [63.205 64.154; 170.951 171.036; 176.841 176.841; 176.842 176.842; 177.282 177.282; 223.886 223.971; 259.963 259.963; 261.547 261.547; 341.185 341.302; 368.999 368.999; 370.999 370.999; 374.999 374.999; 382.971 383.033; 383.999 383.999; 386.999 386.999; 388.958 389.035; 390.999 390.999; 391.955 392.031; 394.955 395.040; 396.999 396.999; 398.999 398.999; 400.999 400.999; 402.999 402.999; 404.963 405.033; 406.999 406.999; 429.829 429.829; 430.346 430.346; 465.184 465.184; 470.290 470.290], ... 652 [50.195 51.145; 158.850 159.012]}; 653 BadSegments{12} = {... 654 [193.435 194.175; 500.000 501.000; 08.988 509.868; 528.999 528.999; 528.999 528.999; 529.999 529.999; 531.999 531.999; 547.999 547.999], ... 655 [133.484 134.185; 134.911 135.065; 553.999 553.999; 553.999 553.999; 554.999 554.999; 557.999 557.999; 558.999 558.999; 564.999 564.999; 565.977 566.046; 568.999 568.999; 569.951 570.028; 571.999 571.999; 579.959 580.028; 580.977 581.055; 583.971 584.033; 583.999 583.999; 585.999 585.999; 586.999 586.999; 588.980 589.026; 590.999 590.999; 591.958 592.044; 595.999 595.999], ... 656 [46.028 47.216; 129.557 130.236; 200.999 200.999; 200.999 200.999; 201.975 202.075; 203.999 203.999; 204.967 205.053; 213.627 214.515; 218.958 219.044; 222.959 228.252; 309.999 309.999; 311.897 317.537; 311.999 311.999; 351.968 353.234; 399.999 399.999; 446.508 451.454; 487.999 487.999; 512.278 512.926], ... 657 [82.535 84.062; 102.247 102.355; 134.999 134.999; 134.999 134.999; 136.999 136.999; 138.973 139.042; 147.999 147.999; 148.999 148.999; 149.999 149.999; 193.999 193.999; 194.999 194.999; 224.984 226.095; 241.954 242.077; 243.948 244.087; 280.999 280.999; 281.999 281.999; 305.000 305.451; 310.945 311.068; 328.999 328.999; 352.999 352.999; 353.999 353.999; 397.025 397.411; 415.944 418.096; 415.999 415.999; 470.999 470.999; 477.971 478.041; 483.997 484.737; 492.958 493.089; 493.999 493.999; 494.999 494.999; 522.999 522.999; 523.999 523.999; 524.955 525.039], ... 658 [175.183 176.155; 246.112 246.991; 412.005 413.340; 483.915 484.061; 485.959 486.028; 497.360 498.880; 594.457 594.944; 596.641 598.006; 615.277 618.710], ... 659 [66.900 72.232; 75.510 78.688; 543.495 545.999]}; 660 BadSegments{13} = {... 661 [307.246 308.179; 627.881 628.089; 629.941 630.049], ... 662 [171.506 172.301; 172.999 172.999; 430.999 430.999; 432.999 432.999; 434.999 434.999; 448.999 448.999; 479.999 479.999; 489.999 489.999; 490.999 490.999; 491.999 491.999], ... 663 [92.059 93.209], ... 664 [52.791 53.231; 54.999 54.999; 65.985 68.138; 91.240 91.386; 92.137 92.207; 105.346 105.493; 121.120 121.398; 146.546 146.955; 194.025 197.652; 242.985 243.571; 247.101 247.556; 269.889 270.083; 270.946 271.070; 274.408 275.866; 294.565 295.267; 319.370 319.879; 365.999 365.999; 375.913 376.044; 376.869 377.055; 377.999 377.999; 390.130 393.225; 403.965 404.035; 404.953 405.075; 419.265 419.565; 427.015 427.154; 427.879 428.118; 427.999 427.999; 428.913 429.067; 480.945 482.095; 484.285 484.571; 516.929 517.099; 517.963 518.079], ... 665 [115.921 116.060; 117.999 117.999; 120.999 120.999; 126.896 127.058; 130.955 131.039; 131.957 132.043; 132.961 133.015; 134.999 134.999; 135.950 136.043; 139.999 139.999; 143.999 143.999; 144.850 145.066; 145.999 145.999; 146.999 146.999; 160.929 161.045; 161.999 161.999; 189.086 189.310; 193.939 194.063; 195.975 196.045; 199.961 200.045; 201.952 202.059; 202.939 205.084; 210.999 210.999; 211.738 213.629; 217.954 218.061; 218.987 219.049; 219.975 220.028; 258.953 259.037; 259.952 260.045; 260.963 261.032; 261.958 262.043; 262.954 263.054; 262.999 262.999; 288.999 288.999; 295.477 295.655; 298.976 299.054; 299.979 300.018; 300.975 301.005; 336.952 337.044; 337.977 338.032; 338.988 339.027; 338.999 338.999; 339.991 340.045; 340.975 341.029; 341.978 342.016; 343.976 344.054; 361.961 362.045; 365.942 366.050; 370.999 370.999; 384.961 385.045; 409.977 410.047; 415.984 416.030; 426.944 427.059; 430.999 430.999; 436.999 436.999; 448.999 448.999; 449.500 452.131; 481.962 482.055; 482.973 483.027; 484.975 485.060; 503.999 503.999; 504.999 504.999; 507.967 508.028; 508.955 509.032; 510.999 510.999; 512.999 512.999; 518.865 520.292; 522.958 523.043; 523.999 523.999; 524.948 525.034; 525.959 526.044; 526.946 527.055; 527.942 528.027; 528.961 529.053; 529.945 530.022; 535.999 535.999; 536.957 537.058; 538.967 539.036; 539.963 540.040; 541.976 542.045; 543.999 543.999; 551.956 552.034; 552.990 553.028; 553.977 554.024; 555.968 556.022; 556.204 557.454; 557.963 558.032; 559.969 560.023; 563.973 564.035; 563.999 563.999], ... 666 [87.308 87.639; 107.039 108.189; 427.943 428.035; 437.965 438.027; 439.973 440.026; 491.275 492.571]}; 667 BadSegments{14} = {... 668 [365.982 367.194; 368.999 368.999; 368.999 368.999; 369.999 369.999; 371.999 371.999; 373.999 373.999; 375.942 376.050; 376.999 376.999; 378.999 378.999; 380.999 380.999; 382.999 382.999; 383.999 383.999; 386.999 386.999; 387.999 387.999; 418.999 418.999; 444.999 444.999; 690.178 693.218], ... 669 [101.796 102.183; 218.999 218.999; 219.999 219.999; 221.999 221.999; 222.999 222.999; 227.999 227.999; 229.999 229.999; 230.999 230.999; 232.999 232.999; 233.999 233.999; 235.999 235.999; 237.999 237.999; 238.985 239.031; 240.999 240.999; 242.999 242.999; 243.999 243.999; 246.999 246.999; 247.999 247.999; 253.999 253.999; 258.999 258.999; 259.999 259.999; 260.227 261.123; 264.999 264.999; 265.999 265.999; 268.999 268.999; 269.999 269.999; 274.999 274.999; 276.999 276.999; 277.999 277.999; 280.999 280.999; 282.966 283.021; 284.999 284.999; 285.999 285.999; 360.999 360.999; 362.973 363.026; 364.999 364.999; 365.999 365.999; 367.999 367.999; 368.985 369.024; 370.999 370.999; 371.999 371.999; 378.999 378.999; 379.999 379.999; 381.999 381.999; 383.999 383.999; 385.999 385.999; 387.999 387.999; 388.999 388.999; 398.999 398.999; 415.999 415.999; 417.999 417.999; 418.999 418.999; 421.999 421.999; 422.999 422.999], ... 670 [89.285 90.187], ... 671 [85.991 87.179; 88.999 88.999; 89.999 89.999; 92.966 93.027; 93.999 93.999; 107.999 107.999; 110.999 110.999; 111.971 112.025; 118.999 118.999; 121.999 121.999; 122.999 122.999; 166.999 166.999; 168.957 169.035; 173.999 173.999; 174.999 174.999; 175.957 176.035; 198.999 198.999; 199.999 199.999; 202.999 202.999; 203.999 203.999; 205.999 205.999; 207.999 207.999; 208.999 208.999; 210.974 211.044; 211.999 211.999; 212.999 212.999; 232.984 233.023; 234.999 234.999; 235.999 235.999; 236.999 236.999; 239.958 240.044; 240.999 240.999], ... 672 [71.132 72.227], ... 673 [98.134 98.827; 110.497 110.814; 114.000 117.272; 279.999 279.999; 279.999 279.999; 280.999 280.999; 282.999 282.999; 283.999 283.999; 284.999 284.999; 286.999 286.999; 287.999 287.999; 288.999 288.999; 289.999 289.999; 291.966 292.044; 292.999 292.999; 346.999 346.999; 437.608 437.646; 518.988 519.104; 522.969 523.015; 534.999 534.999; 536.967 537.029; 562.725 563.426]}; 674 BadSegments{15} = {... 675 [66.755 67.172; 257.988 258.042; 258.714 259.385; 260.958 261.044; 265.931 266.062; 267.968 268.022; 268.978 269.033; 270.992 271.031; 272.964 273.017; 273.968 274.030; 275.975 276.059; 276.970 277.046; 288.976 289.038; 289.984 290.015; 295.994 296.025; 296.982 297.013; 300.966 301.152; 364.730 364.800], ... 676 [46.531 46.555; 65.156 66.148; 87.535 87.642; 183.896 183.934; 294.342 294.375; 330.004 330.528; 333.785 333.815; 345.177 345.203; 399.544 399.573; 480.964 480.980], ... 677 [53.557 54.175; 148.851 149.136], ... 678 [43.681 44.214; 361.255 361.587; 409.462 411.021], ... 679 [90.868 91.130; 410.935 411.044], ... 680 [64.786 65.141; 132.385 132.786; 177.735 178.252; 278.747 278.902; 313.959 314.028; 314.970 315.031]}; 681 BadSegments{16} = {... 682 [38.958 44.335; 305.280 312.826; 324.778 326.067; 393.183 398.367; 403.410 422.854], ... 683 [49.726 50.251; 58.675 65.465; 263.918 264.088; 321.795 322.195; 522.881 523.081], ... 684 [61.245 62.325; 65.628 65.905; 315.686 317.275; 335.184 336.449; 387.870 388.117; 389.892 390.062], ... 685 [56.020 57.255; 60.711 61.096; 64.353 64.924; 73.202 73.757; 76.134 76.844; 95.625 96.859; 171.436 172.625; 178.359 178.715; 212.828 213.415; 352.425 352.617; 367.755 369.097; 488.400 489.426], ... 686 [71.665 72.513; 76.347 77.181; 127.134 128.862], ... 687 [46.190 47.209; 53.461 55.752; 194.317 194.510; 213.101 213.240; 216.356 216.442; 225.962 226.286; 245.163 245.464; 252.041 253.422; 254.648 254.856; 292.966 294.340; 340.928 341.067; 346.298 346.452]}; 688 BadSeg = BadSegments{iSubj}{iRun}'; 689 end 690

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