From 604c56843c15411f5bd80190f81d845ac57d8592 Mon Sep 17 00:00:00 2001 From: mms-neuro <54677017+mms-neuro@users.noreply.github.com> Date: Tue, 17 May 2022 16:29:46 +0200 Subject: [PATCH 01/98] Development (#190) TAPAS release 6.0.1 --- CHANGELOG.md | 5 ++ HGF/README.md | 4 + HGF/tapas_ehgf_ar1_binary_plotTraj.m | 107 +++++++++++++++++++++++++++ HGF/tapas_simModel.m | 20 ++--- README.md | 2 +- misc/log_tapas.txt | 1 + 6 files changed, 129 insertions(+), 10 deletions(-) create mode 100644 HGF/tapas_ehgf_ar1_binary_plotTraj.m diff --git a/CHANGELOG.md b/CHANGELOG.md index 25be266b..4823565d 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,6 +1,11 @@ # Changelog TAPAS toolbox +## [6.0.1] 2022-05-17 + +### Fixed +- HGF: [Version 7.1](HGF/README.md#release-notes): Fixed bug in `tapas_simModel`. + ## [6.0.0] 2022-04-08 For this major release of TAPAS, we have decided to move currently unmaintained toolboxes to a dedicated [TAPAS Legacy repository](https://github.com/translationalneuromodeling/tapas_legacy). diff --git a/HGF/README.md b/HGF/README.md index cdf3c479..5a271aef 100644 --- a/HGF/README.md +++ b/HGF/README.md @@ -54,6 +54,10 @@ hgf_demo.pdf. ## Release notes +### v7.1 +- Add ehgf_ar1_plotTraj +- Bugfix + ### v7.0 - Numerical stability improvements to optimization - Combined response models (more than one observation per trial) diff --git a/HGF/tapas_ehgf_ar1_binary_plotTraj.m b/HGF/tapas_ehgf_ar1_binary_plotTraj.m new file mode 100644 index 00000000..0b19756b --- /dev/null +++ b/HGF/tapas_ehgf_ar1_binary_plotTraj.m @@ -0,0 +1,107 @@ +function tapas_ehgf_ar1_binary_plotTraj(r) +% Plots the estimated or generated trajectories for the binary HGF perceptual model +% Usage example: est = tapas_fitModel(responses, inputs); tapas_hgf_binary_plotTraj(est); +% +% -------------------------------------------------------------------------------------------------- +% Copyright (C) 2012-2020 Christoph Mathys, TNU, UZH & ETHZ +% +% This file is part of the HGF toolbox, which is released under the terms of the GNU General Public +% Licence (GPL), version 3. You can redistribute it and/or modify it under the terms of the GPL +% (either version 3 or, at your option, any later version). For further details, see the file +% COPYING or . + +% Optional plotting of standard deviations (true or false) +plotsd = true; + +% Optional plotting of responses (true or false) +ploty = true; + +% Set up display +scrsz = get(0,'screenSize'); +outerpos = [0.2*scrsz(3),0.2*scrsz(4),0.8*scrsz(3),0.8*scrsz(4)]; +figure(... + 'OuterPosition', outerpos,... + 'Name', 'HGF trajectories'); + +% Time axis +if size(r.u,2) > 1 + t = r.u(:,end)'; +else + t = ones(1,size(r.u,1)); +end + +ts = cumsum(t); +ts = [0, ts]; + +% Number of levels +try + l = r.c_prc.n_levels; +catch + l = (length(r.p_prc.p)+1)/5; +end + +% Upper levels +for j = 1:l-1 + + % Subplots + subplot(l,1,j); + + if plotsd == true + upperprior = r.p_prc.mu_0(l-j+1) +sqrt(r.p_prc.sa_0(l-j+1)); + lowerprior = r.p_prc.mu_0(l-j+1) -sqrt(r.p_prc.sa_0(l-j+1)); + upper = [upperprior; r.traj.mu(:,l-j+1)+sqrt(r.traj.sa(:,l-j+1))]; + lower = [lowerprior; r.traj.mu(:,l-j+1)-sqrt(r.traj.sa(:,l-j+1))]; + + plot(0, upperprior, 'ob', 'LineWidth', 1); + hold all; + plot(0, lowerprior, 'ob', 'LineWidth', 1); + fill([ts, fliplr(ts)], [(upper)', fliplr((lower)')], ... + 'b', 'EdgeAlpha', 0, 'FaceAlpha', 0.15); + end + plot(ts, [r.p_prc.mu_0(l-j+1); r.traj.mu(:,l-j+1)], 'b', 'LineWidth', 2); + hold all; + plot(0, r.p_prc.mu_0(l-j+1), 'ob', 'LineWidth', 2); % prior + xlim([0 ts(end)]); + title(['Posterior expectation of x_' num2str(l-j+1)], 'FontWeight', 'bold'); + ylabel(['\mu_', num2str(l-j+1)]); +end + +% Input level +subplot(l,1,l); + +plot(ts, [tapas_sgm(r.p_prc.mu_0(2), 1); tapas_sgm(r.traj.mu(:,2), 1)], 'r', 'LineWidth', 2); +hold all; +plot(0, tapas_sgm(r.p_prc.mu_0(2), 1), 'or', 'LineWidth', 2); % prior +plot(ts(2:end), r.u(:,1), '.', 'Color', [0 0.6 0]); % inputs +plot(ts(2:end), r.traj.wt(:,1), 'k') % implied learning rate +if (ploty == true) && ~isempty(find(strcmp(fieldnames(r),'y'))) && ~isempty(r.y) + if ~isempty(find(strcmp(fieldnames(r),'c_sim'))) && strcmp(r.c_sim.obs_model,'tapas_beta_obs') + y = r.y(:,1); + else + y = r.y(:,1) -0.5; y = 1.16 *y; y = y +0.5; % stretch + if ~isempty(find(strcmp(fieldnames(r),'irr'))) + y(r.irr) = NaN; % weed out irregular responses + plot(ts(r.irr), 1.08.*ones([1 length(r.irr)]), 'x', 'Color', [1 0.7 0], 'Markersize', 11, 'LineWidth', 2); % irregular responses + plot(ts(r.irr), -0.08.*ones([1 length(r.irr)]), 'x', 'Color', [1 0.7 0], 'Markersize', 11, 'LineWidth', 2); % irregular responses + end + end + plot(ts(2:end), y, '.', 'Color', [1 0.7 0]); % responses + title(['Response y (orange), input u (green), learning rate (fine black), and posterior expectation of input s(\mu_2) ', ... + '(red) for \phi=', num2str(r.p_prc.phi(2:end)), ', m=', num2str(r.p_prc.m(2:end)), ... + '\rho=', num2str(r.p_prc.rho(2:end)), ', \kappa=', ... + num2str(r.p_prc.ka(2:end)), ', \omega=', num2str(r.p_prc.om(2:end))], ... + 'FontWeight', 'bold'); + ylabel('y, u, s(\mu_2)'); + axis([0 ts(end) -0.15 1.15]); +else + title(['Input u (green), learning rate (fine black), and posterior expectation of input s(\mu_2) ', ... + '(red) for \phi=', num2str(r.p_prc.phi(2:end)), ', m=', num2str(r.p_prc.m(2:end)), ... + '\rho=', num2str(r.p_prc.rho(2:end)), ', \kappa=', ... + num2str(r.p_prc.ka(2:end)), ', \omega=', num2str(r.p_prc.om(2:end))], ... + 'FontWeight', 'bold'); + ylabel('u, s(\mu_2)'); + axis([0 ts(end) -0.1 1.1]); +end +plot(ts(2:end), 0.5, 'k'); +xlabel('Trial number'); +hold off; diff --git a/HGF/tapas_simModel.m b/HGF/tapas_simModel.m index 10c9ddbd..97c59e33 100644 --- a/HGF/tapas_simModel.m +++ b/HGF/tapas_simModel.m @@ -164,15 +164,17 @@ [r.traj, infStates] = prc_fun(r, r.p_prc.p); % Check inferred states for NaN values (due to numerical problems when taking log) -r.traj.muhat(r.ign,:) = []; % weed out ignored trials -if any(any(isnan(r.traj.muhat))) - error('tapas:hgf:VarApproxInvalid',... - 'NaNs in infStates (muhat). Probably due to numerical problems when taking logarithms close to 1.'); -end -r.traj.sahat(r.ign,:) = []; % weed out ignored trials -if any(any(isnan(r.traj.sahat))) - error('tapas:hgf:VarApproxInvalid',... - 'NaNs in infStates (muhat). Probably due to numerical problems when taking logarithms close to 1.'); +if contains(prc_model,'hgf') && contains(prc_model,'binary') + r.traj.muhat(r.ign,:) = []; % weed out ignored trials + if any(any(isnan(r.traj.muhat))) + error('tapas:hgf:VarApproxInvalid',... + 'NaNs in infStates (muhat). Probably due to numerical problems when taking logarithms close to 1.'); + end + r.traj.sahat(r.ign,:) = []; % weed out ignored trials + if any(any(isnan(r.traj.sahat))) + error('tapas:hgf:VarApproxInvalid',... + 'NaNs in infStates (muhat). Probably due to numerical problems when taking logarithms close to 1.'); + end end if nargin > 4 diff --git a/README.md b/README.md index 2d30e3df..4f6fc2ce 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ ![TAPAS Logo](misc/TapasLogo.png?raw=true "TAPAS Logo") -*Version 6.0.0* +*Version 6.0.1* T A P A S - Translational Algorithms for Psychiatry-Advancing Science. ======================================================================== diff --git a/misc/log_tapas.txt b/misc/log_tapas.txt index 11cd3387..d80976b3 100644 --- a/misc/log_tapas.txt +++ b/misc/log_tapas.txt @@ -1,3 +1,4 @@ +6.0.1 https://www.tapas.tnu-zurich.com/examples_v6.0.0.zip b4bf7601b9a521159af00b00019989b6 6.0.0 https://www.tapas.tnu-zurich.com/examples_v6.0.0.zip b4bf7601b9a521159af00b00019989b6 5.1.2 https://www.tapas.tnu-zurich.com/examples_v5.0.0.zip 24c1248d3054f025b853b5ab7ce08a1a 5.1.1 https://www.tapas.tnu-zurich.com/examples_v5.0.0.zip 24c1248d3054f025b853b5ab7ce08a1a From 400f458370d396b5fb8bdca933581b6581a37ed0 Mon Sep 17 00:00:00 2001 From: Johanna Bayer Date: Sat, 30 Jul 2022 16:19:25 +1000 Subject: [PATCH 02/98] add try catch for nanmean --- PhysIO/code/preproc/tapas_physio_filter_respiratory.m | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/PhysIO/code/preproc/tapas_physio_filter_respiratory.m b/PhysIO/code/preproc/tapas_physio_filter_respiratory.m index 6c3d0305..38442899 100644 --- a/PhysIO/code/preproc/tapas_physio_filter_respiratory.m +++ b/PhysIO/code/preproc/tapas_physio_filter_respiratory.m @@ -62,8 +62,14 @@ %% Basic preproc and outlier removal % If rpulset has nans, replace them with zeros -rpulsetOffset = nanmean(rpulset); -rpulset(isnan(rpulset)) = nanmean(rpulset); + +try + rpulsetOffset = mean(rpulset, 'omitnan'); % 'omitnan' is recommended for versions after matlab 2016 + rpulset(isnan(rpulset)) = mean(rpulset, 'omitnan'); +catch + rpulsetOffset = nanmean(rpulset); + rpulset(isnan(rpulset)) = nanmean(rpulset); +end rpulset = detrend(rpulset, 3); % Demean / detrend to reduce edge effects From b26ea667a48474404029a09d6db868d181d4fb2c Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Tue, 9 Aug 2022 23:33:56 -0400 Subject: [PATCH 03/98] New pre-release v8.2.0-beta, fixing GitHub issue #204, see CHANGELOG.md for details --- PhysIO/CHANGELOG.md | 9 + ...apas_physio_create_noise_rois_regressors.m | 40 +-- .../tapas_physio_plot_raw_physdata_siemens.m | 33 +-- .../preproc/tapas_physio_filter_respiratory.m | 10 +- .../tapas_physio_read_physlogfiles_bids.m | 2 +- .../tapas_physio_read_physlogfiles_siemens.m | 40 ++- ...pas_physio_read_physlogfiles_siemens_raw.m | 39 +-- .../readin/tapas_physio_siemens_line2table.m | 237 ++++++++++-------- .../tapas_physio_siemens_table2cardiac.m | 45 ++-- PhysIO/code/tapas_physio_version.m | 2 +- PhysIO/code/utils/tapas_physio_pca.m | 15 +- 11 files changed, 277 insertions(+), 195 deletions(-) diff --git a/PhysIO/CHANGELOG.md b/PhysIO/CHANGELOG.md index f44a9145..7d10f373 100644 --- a/PhysIO/CHANGELOG.md +++ b/PhysIO/CHANGELOG.md @@ -8,6 +8,15 @@ Current Release April 5th, 2022 +Upcoming Release Notes (v8.2.0-beta) +------------------------------------ + +### Added +- Added suport for logfile version 3 of Siemens physio recordings + - multi ECG/Resp channels and interleaved status messages +### Fixed +- Removed dependence on `nanmean` (Statistics Toolbox) + - See GitHub issue #205 and Minor Release Notes (v8.1.0) ---------------------------- diff --git a/PhysIO/code/model/tapas_physio_create_noise_rois_regressors.m b/PhysIO/code/model/tapas_physio_create_noise_rois_regressors.m index 4b72dc22..1fbee3f2 100644 --- a/PhysIO/code/model/tapas_physio_create_noise_rois_regressors.m +++ b/PhysIO/code/model/tapas_physio_create_noise_rois_regressors.m @@ -178,18 +178,7 @@ [fpRoi,fnRoi] = fileparts(Vroi.fname); Vroi.fname = fullfile(fpRoi, sprintf('noiseROI_%s.nii', fnRoi)); spm_write_vol(Vroi,roi); - - % Overlay the final noise ROI (code from spm_orthviews:add_c_image) - if verbose.level >= 2 - spm_orthviews('addcolouredimage',r,Vroi.fname ,[1 0 0]); - hlabel = sprintf('%s (%s)',Vroi.fname ,'Red'); - c_handle = findobj(findobj(st.vols{r}.ax{1}.cm,'label','Overlay'),'Label','Remove coloured blobs'); - ch_c_handle = get(c_handle,'Children'); - set(c_handle,'Visible','on'); - uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',[1 0 0],... - 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);'); - spm_orthviews('redraw') - end + final_roi_files{r} = Vroi.fname; Yroi = Yimg(roi(:)==1, :); % Time series of the fMRI volume in the noise ROIs @@ -274,7 +263,7 @@ % plot if verbose.level >=2 - stringFig = sprintf('Model: Noise\\_rois: Extracted principal components for ROI %d', r); + stringFig = sprintf('Model: Noise Rois: Extracted principal components for ROI %d', r); verbose.fig_handles(end+1) = tapas_physio_get_default_fig_params(); set(gcf, 'Name', stringFig); plot(R); @@ -299,6 +288,29 @@ R_noise_rois = [R_noise_rois, R]; -end % nROI +end % nROIs + + +%% Summary plot noise roise location +% Overlay intial and final noise ROI (code from spm_orthviews:add_c_image) +% (before/after reslice, threshold and erosion) +if verbose.level >= 2 + spm_check_registration( roi_files{:} ); + spm_orthviews('context_menu','interpolation',3); % disable interpolation // 3->NN , 2->Trilin , 1->Sinc + for r = 1:nRois + Vroi.fname = final_roi_files{r}; + spm_orthviews('addcolouredimage',r,Vroi.fname ,[1 0 0]); + hlabel = sprintf('%s (%s)',Vroi.fname ,'Red'); + + if isprop(st.vols{r}.ax{1}, 'cm') + c_handle = findobj(findobj(st.vols{r}.ax{1}.cm,'label','Overlay'),'Label','Remove coloured blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',[1 0 0],... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);'); + end + end + spm_orthviews('redraw') +end end % function diff --git a/PhysIO/code/plot/tapas_physio_plot_raw_physdata_siemens.m b/PhysIO/code/plot/tapas_physio_plot_raw_physdata_siemens.m index 564d6299..3df8c2b1 100644 --- a/PhysIO/code/plot/tapas_physio_plot_raw_physdata_siemens.m +++ b/PhysIO/code/plot/tapas_physio_plot_raw_physdata_siemens.m @@ -1,17 +1,16 @@ -function fh = tapas_physio_plot_raw_physdata_siemens(dataCardiac) +function fh = tapas_physio_plot_raw_physdata_siemens(dataPhysio) % plots cardiac data as extracted from Siemens log file % -% output = tapas_physio_plot_raw_physdata_siemens(input) +% fh = tapas_physio_plot_raw_physdata_siemens(dataCardiac) % % IN -% +% dataPhysio output struct from tapas_physio_siemens_table2cardiac % OUT % % EXAMPLE % tapas_physio_plot_raw_physdata_siemens % -% See also tapas_physio_read_physlogfiles_siemens -% See also tapas_physio_siemens_table2cardiac +% See also tapas_physio_read_physlogfiles_siemens tapas_physio_siemens_table2cardiac % Author: Lars Kasper % Created: 2016-02-29 @@ -23,7 +22,7 @@ % (either version 3 or, at your option, any later version). For further details, see the file % COPYING or . -tapas_physio_strip_fields(dataCardiac); +tapas_physio_strip_fields(dataPhysio); stringTitle = 'Read-In: Raw Siemens physlog data'; fh = tapas_physio_get_default_fig_params(); @@ -31,22 +30,28 @@ stem(cpulse_on, ampl*ones(size(cpulse_on)), 'g'); hold all; stem(cpulse_off, ampl*ones(size(cpulse_off)), 'r'); stem(t(stopSample), ampl , 'm'); -plot(t, channel_1); -plot(t, channel_AVF); -plot(t, meanChannel); -stringLegend = { ... - 'cpulse on', 'cpulse off', 'assumed last sample of last scan volume', ... - 'channel_1', 'channel_{AVF}', 'mean of channels'}; +stringLegend = {'physio trigger on', 'physio trigger off', ... + 'assumed last sample of last scan volume'}; + +nChannels = size(recordingChannels, 2); + +for iChannel = 1:nChannels + plot(t, recordingChannels(:,iChannel)); + stringLegend{end+1} = sprintf('channel %d', iChannel); +end + +plot(t, meanChannel); +stringLegend{end+1} = 'mean of channels'; if ~isempty(recording_on) stem(recording_on, ampl*ones(size(recording_on)), 'k'); - stringLegend{end+1} = 'phys recording on'; + stringLegend{end+1} = 'physio recording on'; end if ~isempty(recording_off) stem(recording_off, ampl*ones(size(recording_off)), 'k'); - stringLegend{end+1} = 'phys recording off'; + stringLegend{end+1} = 'physio recording off'; end legend(stringLegend); title(stringTitle); diff --git a/PhysIO/code/preproc/tapas_physio_filter_respiratory.m b/PhysIO/code/preproc/tapas_physio_filter_respiratory.m index 6c3d0305..17a72160 100644 --- a/PhysIO/code/preproc/tapas_physio_filter_respiratory.m +++ b/PhysIO/code/preproc/tapas_physio_filter_respiratory.m @@ -61,9 +61,13 @@ %% Basic preproc and outlier removal -% If rpulset has nans, replace them with zeros -rpulsetOffset = nanmean(rpulset); -rpulset(isnan(rpulset)) = nanmean(rpulset); +% If rpulset has nans, replace them with mean of valid values +try + rpulsetOffset = mean(rpulset, 'omitnan'); +catch % for backwards compatibility < Matlab 2016a + rpulsetOffset = nanmean(rpulset); +end +rpulset(isnan(rpulset)) = rpulsetOffset; rpulset = detrend(rpulset, 3); % Demean / detrend to reduce edge effects diff --git a/PhysIO/code/readin/tapas_physio_read_physlogfiles_bids.m b/PhysIO/code/readin/tapas_physio_read_physlogfiles_bids.m index 0e8a58e6..386898a1 100644 --- a/PhysIO/code/readin/tapas_physio_read_physlogfiles_bids.m +++ b/PhysIO/code/readin/tapas_physio_read_physlogfiles_bids.m @@ -12,7 +12,7 @@ % physiological recordings can be found here: % % https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/ -% 06-physiological-and-other-continous-recordings.html +% 06-physiological-and-other-continuous-recordings.html % % [c, r, t, cpulse, acq_codes, verbose] = tapas_physio_read_physlogfiles_biopac_txt(... % log_files, cardiac_modality, verbose, varargin) diff --git a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m index 0050768a..5e00df88 100755 --- a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m +++ b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m @@ -139,31 +139,27 @@ [lineData, logFooter] = tapas_physio_read_physlogfiles_siemens_raw(... log_files.cardiac); - tLogTotal = logFooter.LogStopTimeSeconds - logFooter.LogStartTimeSeconds; + tLogTotal = logFooter.StopTimeSeconds - logFooter.StartTimeSeconds; if hasScanTimingDicomImage - tStartScan = tStartScanDicom; % this is just the start of the selected DICOM volume - tStopScan = tStopScanDicom; + tStartScan = tStartScanDicom; % this is the start of the DICOM volume selected for sync + tStopScan = tStopScanDicom; % this is the end time (start + TR) of the DICOM volume selected for sync else - % Just different time scale, gives bad scaling in plots, and not - % needed... - % tStartScan = logFooter.ScanStartTimeSeconds; - % tStopScan = logFooter.ScanStopTimeSeconds; - tStartScan = logFooter.LogStartTimeSeconds; - tStopScan = logFooter.LogStopTimeSeconds; + tStartScan = logFooter.StartTimeSeconds; + tStopScan = logFooter.StopTimeSeconds; end switch log_files.align_scan case 'first' relative_start_acquisition = tStartScan ... - - logFooter.LogStartTimeSeconds; + - logFooter.StartTimeSeconds; case 'last' % shift onset of first scan by knowledge of run duration and % onset of last scan in run relative_start_acquisition = ... (tStopScan - sqpar.Nscans*sqpar.TR) ... - - logFooter.LogStartTimeSeconds; + - logFooter.StartTimeSeconds; end @@ -214,30 +210,26 @@ if hasRespData [lineData, logFooter] = tapas_physio_read_physlogfiles_siemens_raw(... log_files.respiration); - tLogTotal = logFooter.LogStopTimeSeconds - logFooter.LogStartTimeSeconds; + tLogTotal = logFooter.StopTimeSeconds - logFooter.StartTimeSeconds; if hasScanTimingDicomImage - tStartScan = tStartScanDicom; - tStopScan = tStopScanDicom; % is incorrect, use tStartScan + TR! - else - % Just different time scale, gives bad scaling in plots, and not - % needed... - % tStartScan = logFooter.ScanStartTimeSeconds; - % tStopScan = logFooter.ScanStopTimeSeconds; - tStartScan = logFooter.LogStartTimeSeconds; - tStopScan = logFooter.LogStopTimeSeconds; + tStartScan = tStartScanDicom; % this is the start of the DICOM volume selected for sync + tStopScan = tStopScanDicom; % this is the end time (start + TR) of the DICOM volume selected for sync + else + tStartScan = logFooter.StartTimeSeconds; + tStopScan = logFooter.StopTimeSeconds; end switch log_files.align_scan case 'first' relative_start_acquisition = tStartScan - ... - logFooter.LogStartTimeSeconds; + logFooter.StartTimeSeconds; case 'last' % shift onset of first scan by knowledge of run duration and % onset of last scan in run relative_start_acquisition = ... - (tStartScan - (sqpar.Nscans-1)*sqpar.TR) ... - - logFooter.LogStartTimeSeconds; + (tStopScan - sqpar.Nscans*sqpar.TR) ... + - logFooter.StartTimeSeconds; end diff --git a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens_raw.m b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens_raw.m index 4e69458e..0f478cc3 100644 --- a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens_raw.m +++ b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens_raw.m @@ -47,25 +47,32 @@ linesFooter = C{1}(2:end); lineData = C{1}{1}; -%Get time stamps from footer: +% Get time stamps from footer: -logFooter.LogStartTimeSeconds = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... +% MPCU = Computer who controls the physiological logging in real-time => physio logging happens here +% MDH = Computer who is the host (Measurement Data Header); console => DICOM time stamp here +logFooter.StartTimeSecondsScannerClock = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... 'LogStartMDHTime'))),'\D',''))) / 1000; -logFooter.LogStopTimeSeconds = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... +logFooter.StopTimeSecondsScannerClock = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... 'LogStopMDHTime'))),'\D',''))) / 1000; -% MPCU = Computer who controls the scanner => physio logging happens here -% MDH = Compute who is the host; console => DICOM time stamp here! -% -% - according to Chris Rorden, PART -% (http://www.mccauslandcenter.sc.edu/crnl/tools/part) - MDH is the time we -% should use for phys logging synchronization, since DICOM conversion uses -% this clock +logFooter.StartTimeSecondsRecordingClock = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... + 'LogStartMPCUTime'))),'\D',''))) / 1000; +logFooter.StopTimeSecondsRecordingClock = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... + 'LogStopMPCUTime'))),'\D',''))) / 1000; -% This is just a different time-scale (of the phys log computer), it does -% definitely NOT match with the Acquisition time in the DICOM-headers -logFooter.ScanStartTimeSeconds = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... - 'LogStartMPCUTime'))),'\D',''))); -logFooter.ScanStopTimeSeconds = str2num(char(regexprep(linesFooter(~cellfun(@isempty,strfind(linesFooter,... - 'LogStopMPCUTime'))),'\D',''))); +% +% We use the time stamp of the clock of the Measurement Data Header (MDH), +% i.e., computer that controls the scanner, to synchronize with the DICOMs, +% because this computer also controls the creation of the scan data, i.e., +% reconstructed DICOM images. This is in accordance to other packages +% reading Siemens physiological logfile data, e.g., Chris Rorden's PART +% (https://github.com/neurolabusc/Part#usage), +% with a detailed explanation on the DICOM timestamp in AcquisitionTime +% found here (https://github.com/nipy/heudiconv/issues/450#issuecomment-645003447) +% +% MPCU is the clock of the computer that controls the physiological +% recording (same as MARS?), but does not know about the scan volume and DICOM timing +logFooter.StartTimeSeconds = logFooter.StartTimeSecondsScannerClock; +logFooter.StopTimeSeconds = logFooter.StopTimeSecondsScannerClock; \ No newline at end of file diff --git a/PhysIO/code/readin/tapas_physio_siemens_line2table.m b/PhysIO/code/readin/tapas_physio_siemens_line2table.m index 103702d6..4a72d0fa 100755 --- a/PhysIO/code/readin/tapas_physio_siemens_line2table.m +++ b/PhysIO/code/readin/tapas_physio_siemens_line2table.m @@ -1,6 +1,6 @@ -function data_table = tapas_physio_siemens_line2table(lineData, cardiacModality) -% transforms data line of Siemens log file into table (sorting amplitude -% and trigger signals) +function [data_table, log_parts] = tapas_physio_siemens_line2table(lineData, cardiacModality) +% transforms data line of Siemens log file (before linebreak after 5003 +% signal for recording end) into table (sorting amplitude and trigger signals) % % data_table = tapas_physio_siemens_line2table(input) % @@ -9,12 +9,13 @@ % of file. See also tapas_physio_read_physlogfiles_siemens_raw % % OUT -% data_table [nSamples,3] table of channel_1, channels_AVF and trigger +% data_table [nSamples,nChannels+1] table of recording channel_1, ..., channel_N and trigger % signal with trigger codes: % 5000 = cardiac pulse on % 6000 = cardiac pulse off % 6002 = phys recording on % 6003 = phys recording off +% log_parts part of logfile according to markers by Siemens % % EXAMPLE % tapas_physio_siemens_line2table @@ -32,120 +33,160 @@ % COPYING or . -% signals start of data logging -iTrigger = regexpi(lineData, ' 6002 '); +% NOTE: The following extraction of data from the logfiles might seem +% parsimonious, but it's written in a way to support all different physio +% trace modalities and logfile versions (more detail below) + +% The ypical logfile structure is as follows (all data in first line of +% logfile, the footer is in the next line (after 5003), not used in this +% file, but tapas_physio_read_physlogfiles_siemens_raw)L +% +%
5002 6002 +% <[optional] training trace data> 5002 uiHwRevisionPeru ... [optional] 6002 +% 5002 6002 5002 6002 ... 5002 6002 +% ... +% 5002 6002 +% ... +% 5002 6002 ... +% ... 5003 +% +% Since the number and content of actual info regions and number of data +% channels differs by trace modality and logfile version, we have to cut +% data out carefully: +% +% 1. Cut away header +% 2. Cut away logfile version +% 3. Cut away optional training trace +% 4. Remove all infoRegions can be interleaved with trace data, e.g., +% cushionGain for RESP trace) +% 5. Remove all trigger markers (5000, 6000), but remmember position +% 6. Sort remaining trace into coresponding channels (number of channels is +% logfile-version dependent) +% 7. Re-insert trigger markers as extra column -if ~isempty(iTrigger) - % crop string after trigger - lineData = lineData((iTrigger(end)+6):end); - doCropLater = false; -else - % crop first 4 values as in UPenn manual after conversion - doCropLater = true; -end -data = textscan(lineData, '%d', 'Delimiter', ' ', 'MultipleDelimsAsOne',1); -if doCropLater - % crop first 4 values; - data{1} = data{1}(5:end); +%% 1. Header goes from start of line to first occurence of 5002 +[iStartHeader, iEndHeader, logHeader] = regexp(lineData, '^(.*?) (?=\<5002\>)', 'start', 'end', 'tokens' ); +logHeader = logHeader{1}{1}; +lineData(iStartHeader:iEndHeader) = []; % remove header, but keep 5002 for next step + + +%% 2. Logfile version (which alters no of channels etc.) +% stored in first 5002/6002 info region +% 5002 LOGVERSION 1 6002% +% 5002 LOGVERSION_RESP 3 6002% +% 5002 LOGVERSION_PULS 3 6002% +[iStartVersionInfo, iEndVersionInfo, logVersion] = regexp(lineData, '^\<5002\> LOGVERSION[^0-9]*(\d+)\s\<6002\>', 'start', 'end', 'tokens' ); +logVersion = str2double(logVersion{1}{1}); +lineData(iStartVersionInfo:iEndVersionInfo) = []; % remove version info region incl. 5002/6002 markers + + +%% 3. Optional training data (for Siemens own peak detection) is after +% "6002" of Logversion info and "5002 uiHwRevisionPeru" +[iStartTraining, iEndTraining, dataTraining] = regexp(lineData, '^\s*(.*?) (?=\<5002\> uiHwRevisionPeru)', 'start', 'end', 'tokens'); +if ~isempty(iStartTraining) % training trace does not always exist + dataTraining = dataTraining{1}{1}; + lineData(iStartTraining:iEndTraining) = []; % remove training trace, but keep following 5002 for next step end + +%% 4. Identify and remove info regions between 5002 and 6002 (may be +% interleaved with trace data (e.g., messages or cushion Gain for RESP) +[iStartInfoRegion, iEndInfoRegion, logInfoRegion] = regexp(lineData, '\<5002\>(.*?)\<6002\>', 'start', 'end', 'tokens' ); +logInfoRegion = cellfun(@(x) x{1,1}, logInfoRegion, 'UniformOutput', false)'; +traceData = regexprep(lineData, '\<5002\>(.*?)\<6002\>\s', ''); +traceData = regexprep(traceData, '\<5003\>$', ''); % remove 5003 mark of trace end + +log_parts.logHeader = logHeader; +log_parts.logInfoRegion = logInfoRegion; +log_parts.logVersion = logVersion; + +% convert remaining data (all numbers string) to number (int32) +data = textscan(traceData, '%d', 'Delimiter', ' ', 'MultipleDelimsAsOne', true); + + +%% 5. Remove all trigger markers (5000, 6000), but remmember position % Remove the systems own evaluation of triggers. cpulse = find(data{1} == 5000); % System uses identifier 5000 as trigger ON cpulse_off = find(data{1} == 6000); % System uses identifier 5000 as trigger OFF -recording_on = find(data{1} == 6002);% Scanner trigger to Stim PC? -recording_off = find(data{1} == 5003); - - % Filter the trigger markers from the ECG data % Note: depending on when the scan ends, the last size(t_off)~=size(t_on). -iNonEcgSignals = [cpulse; cpulse_off; recording_on; recording_off]; -codeNonEcgSignals = [5000*ones(size(cpulse)); ... - 6000*ones(size(cpulse_off)); ... - 6002*ones(size(recording_on)) - 5003*ones(size(recording_off))]; - -% data_stream contains only the 2 ECG-channel time courses (with -% interleaved samples +iTriggerMarker = [cpulse; cpulse_off]; +codeTriggerMarker = [5000*ones(size(cpulse)); ... + 6000*ones(size(cpulse_off))]; + +% data_stream contains only the time courses (with +% interleaved samples for each channel) data_stream = data{1}; -data_stream(iNonEcgSignals) = []; +data_stream(iTriggerMarker) = []; -%iDataStream contains the indices of all true ECG signals in the full -%data{1}-Array that contains also non-ECG-signals +%iDataStream contains the indices of all true trace signals in the full +%data{1}-Array that contains also the trigger markers iDataStream = 1:numel(data{1}); -iDataStream(iNonEcgSignals) = []; +iDataStream(iTriggerMarker) = []; -nSamples = numel(data_stream); +%% 6. Sort remaining trace into coresponding channels (number of channels is +% logfile-version dependent) +nSamples = numel(data_stream); switch upper(cardiacModality) % ecg has two channels, resp and puls only one case 'ECG' - nRows = ceil(nSamples/2); - - % create a table with channel_1, channels_AVF and trigger signal in - % different Columns - % - iData_table is a helper table that maps the original indices of the - % ECG signals in data{1} onto their new positions - data_table = zeros(nRows,3); - iData_table = zeros(nRows,3); - - data_table(1:nRows,1) = data_stream(1:2:end); - iData_table(1:nRows,1) = iDataStream(1:2:end); - - if mod(nSamples,2) == 1 - data_table(1:nRows-1,2) = data_stream(2:2:end); - iData_table(1:nRows-1,2) = iDataStream(2:2:end); - else - data_table(1:nRows,2) = data_stream(2:2:end); - iData_table(1:nRows,2) = iDataStream(2:2:end); + switch logVersion + case 1 + nChannels = 2; + case 3 + nChannels = 4; end - - % now fill up 3rd column with trigger data - % - for each trigger index in data{1}, check where ECG data with closest - % smaller index ended up in the data_table ... and put trigger code in - % same row of that table - nTriggers = numel(iNonEcgSignals); - - for iTrigger = 1:nTriggers - % find index before trigger event in data stream and - % detect it in table - iRow = find(iData_table(:,2) == iNonEcgSignals(iTrigger)-1); - - % look in 1st column as well whether maybe signal detected there - if isempty(iRow) - iRow = find(iData_table(:,1) == iNonEcgSignals(iTrigger)-1); - end - - data_table(iRow,3) = codeNonEcgSignals(iTrigger); + case 'PPU' + nChannels = 1; + case 'RESP' + switch logVersion + case 1 + nChannels = 1; + case 3 + nChannels = 5; % breathing belt plus 4 channel biomatrix end - case {'RESP', 'PPU'} % only one channel available, fill second row with zeros - nRows = nSamples; - - % create a table with channel_1 and trigger signal in - % different Columns - % - iData_table is a helper table that maps the original indices of the - % ECG signals in data{1} onto their new positions - data_table = zeros(nRows,3); - iData_table = zeros(nRows,3); - - data_table(1:nRows,1) = data_stream; - iData_table(1:nRows,1) = iDataStream; - - % now fill up 3rd column with trigger data - % - for each trigger index in data{1}, check where ECG data with closest - % smaller index ended up in the data_table ... and put trigger code in - % same row of that table - nTriggers = numel(iNonEcgSignals); - - for iTrigger = 1:nTriggers - % find index before trigger event in data stream and - % detect it in table - iRow = find(iData_table(:,1) == iNonEcgSignals(iTrigger)-1); - if ~isempty(iRow) - data_table(iRow,3) = codeNonEcgSignals(iTrigger); - end - end otherwise error('unknown cardiac/respiratory logging modality: %s', cardiacModality); +end + +nRows = ceil(nSamples/nChannels); + +% create a table with channel_1, channels_AVF and trigger signal in +% different Columns +% - iData_table is a helper table that maps the original indices of the +% ECG signals in data{1} onto their new positions +data_table = zeros(nRows,nChannels+1); +iData_table = zeros(nRows,nChannels+1); + +for iChannel = 1:nChannels + data_table(1:nRows,iChannel) = data_stream(iChannel:nChannels:end); + iData_table(1:nRows,iChannel) = iDataStream(iChannel:nChannels:end); +end + +% TODO: deal with mod(nSamples, nChannels) > 0 (incomplete data?) + + +%% 7. Re-insert trigger markers as extra column +% now fill up nChannel+1. column with trigger data +% - for each trigger index in data{1}, check where ECG data with closest +% smaller index ended up in the data_table ... and put trigger code in +% same row of that table +nTriggers = numel(iTriggerMarker); + +for iTrigger = 1:nTriggers + % find index before trigger event in data stream and + % detect it in table, look in last columns first, then go + % backwards + iRow = []; + iChannel = nChannels; + while isempty(iRow) + + iRow = find(iData_table(:,iChannel) == iTriggerMarker(iTrigger)-1); + iChannel = iChannel - 1; + end + + data_table(iRow,nChannels+1) = codeTriggerMarker(iTrigger); end \ No newline at end of file diff --git a/PhysIO/code/readin/tapas_physio_siemens_table2cardiac.m b/PhysIO/code/readin/tapas_physio_siemens_table2cardiac.m index 7f07762a..9ae6cfea 100644 --- a/PhysIO/code/readin/tapas_physio_siemens_table2cardiac.m +++ b/PhysIO/code/readin/tapas_physio_siemens_table2cardiac.m @@ -18,19 +18,24 @@ % onset of first scan (t=0) % % OUT +% % dataCardiac = struct(... % 'cpulse_on', cpulse_on, ... % 'cpulse_off', cpulse_off, ... % 'recording_on', recording_on, ... % 'recording_off', recording_off, ... -% 'channel_1', channel_1, ... -% 'channel_AVF', channel_AVF, ... +% 'recordingChannels', recordingChannels, ... % 'meanChannel', meanChannel, ... % 'c', c, ... % 't', t, ... % 'ampl', ampl, ... % 'stopSample', stopSample ... % ); +% +% AVF means "Augmented Vector Foot" and is a label for a unipolar lead +% of the ECG electrode setup. For .ecg- LOGVERSIOM one, this was the 2nd +% column ("channel") in the data (based on Siemens' Physioload function), +% but for later versions, it's not clear % % EXAMPLE % tapas_physio_siemens_table2cardiac @@ -49,27 +54,32 @@ % COPYING or . -% set new indices to actual -cpulse_on = find(data_table(:,3) == 5000); -cpulse_off = find(data_table(:,3) == 6000); -recording_on = find(data_table(:,3) == 6002); -recording_off = find(data_table(:,3) == 5003); +% set new indices to actual, last column contains +cpulse_on = find(data_table(:,end) == 5000); +cpulse_off = find(data_table(:,end) == 6000); +recording_on = find(data_table(:,end) == 6002); +recording_off = find(data_table(:,end) == 5003); % Split a single stream of ECG data into channel 1 and channel 2. -channel_1 = data_table(:,1); -channel_AVF = data_table(:,2); -meanChannel = mean([channel_1(:) channel_AVF(:)],2); +nChannels = size(data_table,2) - 1; + +for iChannel = 1:nChannels + recordingChannels(:,iChannel) = data_table(:,iChannel); +end + +meanChannel = mean(recordingChannels, 2); % Make them the same length and get time estimates. -switch ecgChannel +switch lower(ecgChannel) case 'mean' c = meanChannel - mean(meanChannel); - case 'v1' - c = channel_1 - mean(channel_1); - - case 'v2' - c = channel_AVF - mean(channel_AVF); + case {'v1', 'v2', 'v3', 'v4'} + iChannel = str2double(ecgChannel(2)); + c = recordingChannels(:,iChannel) - mean(recordingChannels(:,iChannel)); + case {'avf'} + iChannel =2; + c = recordingChannels(:,iChannel) - mean(recordingChannels(:,iChannel)); end % compute timing vector and time of detected trigger/cpulse events @@ -94,8 +104,7 @@ 'cpulse_off', cpulse_off, ... 'recording_on', recording_on, ... 'recording_off', recording_off, ... - 'channel_1', channel_1, ... - 'channel_AVF', channel_AVF, ... + 'recordingChannels', recordingChannels, ... 'meanChannel', meanChannel, ... 'c', c, ... 't', t, ... diff --git a/PhysIO/code/tapas_physio_version.m b/PhysIO/code/tapas_physio_version.m index a6db2ee0..512e1d63 100644 --- a/PhysIO/code/tapas_physio_version.m +++ b/PhysIO/code/tapas_physio_version.m @@ -23,4 +23,4 @@ % version 3 or, at your option, any later version). For further details, % see the file COPYING or . % -versionPhysio = 'R2022a-v8.1.0'; +versionPhysio = 'R2022a-v8.2.0-beta'; diff --git a/PhysIO/code/utils/tapas_physio_pca.m b/PhysIO/code/utils/tapas_physio_pca.m index 34d996a9..a1a313e1 100644 --- a/PhysIO/code/utils/tapas_physio_pca.m +++ b/PhysIO/code/utils/tapas_physio_pca.m @@ -29,14 +29,17 @@ [nVoxels,nVolumes] = size(timeseries); -if nVoxels <= nVolumes - error([mfilename ':NotEnoughVoxels'], 'nVoxels <= nVolumes') -end - if nargin < 2 method = 'svd'; end +if nVoxels <= nVolumes + % TODO: reimplement using PCA of COV((X-mu)'*(X-mu)) + method = 'stats-pca'; + % error([mfilename ':NotEnoughVoxels'], 'nVoxels <= nVolumes') +end + + switch lower(method) case 'svd' @@ -56,8 +59,8 @@ LATENT = eigen_values; % [nPCs, 1] % Eigen_values -> Variance explained - vairance_explained = 100*eigen_values/sum(eigen_values); % in percent (%) - EXPLAINED = vairance_explained; % [nPCs, 1] + variance_explained = 100*eigen_values/sum(eigen_values); % in percent (%) + EXPLAINED = variance_explained; % [nPCs, 1] % Sign convention : the max(abs(PCs)) is positive [~,maxabs_idx] = max(abs(v)); From e248d9dff5115196e740cdfb5d0cfe30f967d7c9 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 02:02:54 -0400 Subject: [PATCH 04/98] Updated to PhysIO R2022b-v8.2.0 with new interface to tapas_test and Siemens Logversion 3 reader --- PhysIO/CHANGELOG.md | 9 ++-- PhysIO/README.md | 2 +- PhysIO/docs/documentation.html | 28 ++++++++--- PhysIO/docs/documentation.pdf | Bin 1950217 -> 1955861 bytes PhysIO/tests/tapas_physio_test.m | 78 +++++++++++++++++++++++++++++++ 5 files changed, 106 insertions(+), 11 deletions(-) create mode 100644 PhysIO/tests/tapas_physio_test.m diff --git a/PhysIO/CHANGELOG.md b/PhysIO/CHANGELOG.md index 7d10f373..92cd279d 100644 --- a/PhysIO/CHANGELOG.md +++ b/PhysIO/CHANGELOG.md @@ -4,14 +4,15 @@ RELEASE INFORMATION Current Release --------------- -*Current version: PhysIO Toolbox Release R2022a, v8.1.0* +*Current version: PhysIO Toolbox Release R2022b, v8.2.0* -April 5th, 2022 +September 5th, 2022 -Upcoming Release Notes (v8.2.0-beta) ------------------------------------- +Minor Release Notes (v8.2.0) +---------------------------- ### Added +- Interface `tapas_physio_test` to TAPAS-generic `tapas_test` function - Added suport for logfile version 3 of Siemens physio recordings - multi ECG/Resp channels and interleaved status messages ### Fixed diff --git a/PhysIO/README.md b/PhysIO/README.md index a4ef3bf0..b0876c8e 100644 --- a/PhysIO/README.md +++ b/PhysIO/README.md @@ -1,7 +1,7 @@ TAPAS PhysIO Toolbox ==================== -*Current version: Release 2022a, v8.1.0* +*Current version: Release 2022b, v8.2.0* > Copyright (C) 2012-2022 > Lars Kasper diff --git a/PhysIO/docs/documentation.html b/PhysIO/docs/documentation.html index 8e66b2aa..393e2bd9 100644 --- a/PhysIO/docs/documentation.html +++ b/PhysIO/docs/documentation.html @@ -825,9 +825,9 @@

Troubleshoot

Readme

TAPAS PhysIO Toolbox

-

Current version: Release 2022a, v8.1.0

+

Current version: Release 2022b, v8.2.0

-

Copyright (C) 2012-2022
Lars Kasper
kasper@biomed.ee.ethz.ch

+

Copyright (C) 2012-2022
Lars Kasper
kasper@biomed.ee.ethz.ch

Translational Neuromodeling Unit (TNU)
Institute for Biomedical Engineering
University of Zurich and ETH Zurich

Download

@@ -1661,6 +1661,7 @@

Brain Imaging Data Structure (BIDS)< ], "StartTime": -255.45 } +
  • Note that StartTime refers to when the physiological recording started relative to the first scan volume of the fMRI run, which means that typically this value is negative, because one starts the recording before the onset of scan volumes.
  • See tapas_physio_read_physlogfiles_bids.m for more details and technical documentation.
    • @@ -1729,8 +1730,9 @@

    Philips

    Siemens

    Manual Recording

    Physiological data collection on the Siemens scanners uses the physiological monitoring unit (PMU). The initial sampling is performed at 400 Hz, but through the PMU buffer the effective sampling intervals are ECG: 2.5 ms, RESP: 20 ms, PULS: 20 ms and EXT: 5 ms.

    -

    There are several ways to control the physiological data collection. The 'manual' version is available on all platforms. It uses the telnet mpcu/ideacmdtool to manually start and stop the log file acquisition. The log files (logFileName.ecg, logFileName.resp, logFileName.puls, logFileName.ext) are stored in \MedCom\log. More details on how to record these data can be found here or in the "Other Miscellaneous Topics" slides from the IDEA course.

    -

    An example of a .puls logfile is given below. The data are stored in one long line. The text between 5002 and 6002 forms the header, and the text between 5003 and 6003 the footer. Important information in the footer is the LogStartMDHTime and the LogStopMDHTime (in ms since midnight), which can be used to synchronize the logfiles with the dicom images using the AcquisitionTime in the dicom header (in hhmmss.ms). The values 5000 and 6000 are inserted into the signal trace and indicate trigger events. Note that only the modality which is selected to be displayed during the acquisition will have triggers.

    +

    There are several ways to control the physiological data collection. The 'manual' version is available on all platforms. It uses the telnet mpcu/ideacmdtool to manually start and stop the log file acquisition. The log files (logFileName.ecg, logFileName.resp, logFileName.puls, logFileName.ext) are stored in \MedCom\log. More details on how to record these data can be found here or in the "Other Miscellaneous Topics" slides from the IDEA course.

    +

    An example of a .puls logfile is given below. The data are stored in one long line. The text between 5002 and 6002 forms the header, and the text between 5003 and 6003 the footer. Important information in the footer is the LogStartMDHTime and the LogStopMDHTime (in ms since midnight), which can be used to synchronize the logfiles with the DICOM images using the AcquisitionTime in the DICOM header (in hhmmss.ms). The values 5000 and 6000 are inserted into the signal trace and indicate trigger events. Note that only the modality which is selected to be displayed during the acquisition will have triggers.

    +

    We use the time stamp of the clock of the Measurement Data Header (MDH), i.e., computer that controls the scanner, to synchronize with the DICOMs, because this computer also controls the creation of the scan data, i.e., reconstructed DICOM images. This is in accordance to other packages reading Siemens physiological logfile data, e.g., Chris Rorden's PART, with a detailed explanation on the DICOM timestamp in AcquisitionTime found here. 

    1 2 40 280 5002 Logging PULSE signal: reduction factor = 1, PULS_SAMPLES_PER_SECOND = 50; PULS_SAMPLE_INTERVAL = 20000 6002 1653 1593 1545 1510 1484 ...
 ACQ FINISHED
  6002 3093 3096 3064 5000 3016 2926 5003
@@ -1826,8 +1828,22 @@ 
    Human Connectome Project
    
 1    1904    1780

    Version History (Changelog)

    RELEASE INFORMATION

    Current Release

    -

    Current version: PhysIO Toolbox Release R2022a, v8.1.0

    -

    April 5th, 2022

    +

    Current version: PhysIO Toolbox Release R2022b, v8.2.0

    +

    September 5th, 2022

    +

    Minor Release Notes (v8.2.0)

    +

    Added

    +
      +
    • Interface tapas_physio_test to TAPAS-generic tapas_test function
      • +
    • Added suport for logfile version 3 of Siemens physio recordings
        +
      • multi ECG/Resp channels and interleaved status messages

        Fixed

        +
        • +
      +
      • +
    • Removed dependence on nanmean (Statistics Toolbox)
        +
      • See GitHub issue #205 and
        • +
      +
      • +

    Minor Release Notes (v8.1.0)

    Added

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z-oT&AfyqM$=wV^t6CA{{fx`kz6N3v{?ZiR}=s|r)6p+axgO4@uiTQv(dHl1MP}P7PHc zv8;r;od1RFBk1wqI+DX8`55o?5*Tw~!@@tFKVmZOCTI$ehJl;lLX-p}UfqE^;atQa zoY(;foo?b}XpRw=6C8}FBs{1?NO%n5%>ponL&A_ELnn3sk~GHMPORXe>?PMQuo;tb z00&YEF^fWCAOX`nF*8F zEC!8PgjWkN7ym~Pn#bYNMr{auCR_$7&%=S3*pJ}A`IR)63!50x?_euZ?uP}7TM*y> zhtnwZ_Q;Ikl9sfyap4Mt82wO_kQu{^8`$uy;6)Xw zXoYt!#QXtwadc9!a(PTB*a<%2!d)!UPhfpgHN>TJNy!Hu6p-gKXrwa`7y82ZD#7hP zw2N`La6L_oRxX1}Y^Z@IaNR=`nn}YSOpSIY$V_q*)DR<94$dD^FbG3p44>vATLzv? z5ShTm2ni3`^CZS_3?T`~;enHh1o5qi2*d3~f{kqb2wrnRqlTFKp;7Zc@Te3)9RT_d znICUM5rYe0&<-8V7@9YvJP$BvP?PY8j~HOXf@b+hYXN@%Lcu_&Pyt5DgaCsKPGo|& z^NBDhZ%OnZ6v%jN9x;NU!$~D>#{gpzml(jHeM4jn{bZ80*l;8z;lWnPhyAPn@FYbH zE`X7CMSzj67N9mD9lHR=|2DOeD*|8yt3v$;K)6pDEg@u9D$(x%BR=YamBXcvTuy@3 z1iedAP(!LFSqnBw!XqOP2C8L}3E_M|SUP|Qr-9Kz1MGh=p~4jq5f6^#g9;DVe-P=U zTT_TuxOyc{romkd2?j?)A`HInkHi?R!$vE|!=s;c9|yfq3NZ%&3=XP9CeX$v3CMs- zg@i}C*#Ua6rxNNvE`. + +if nargin < 1 + level = 0; +end + +tic + +testResults = []; + +if level >= 0 + testResults = [testResults tapas_physio_run_unit_tests()]; +else + nTestTotal = 0; + nTestFailed = 0; + return +end + +if level == 1 + % code adapted from run_integration_tests, but chooses only tests with + % 'matlab' in the name (SPM GUI tests have SPM in the name) + import matlab.unittest.TestSuite; + + pathTests = fullfile(fileparts(mfilename('fullpath')), 'integration'); + suiteFolder = TestSuite.fromFolder(pathTests, ... + 'IncludingSubfolders', true, 'Name', '*matlab_only*'); + testResults = [testResults run(suiteFolder)]; +end + +if level >= 2 + testResults = [testResults tapas_physio_run_integration_tests()]; +end + +nTestTotal = numel(testResults); +nTestFailed = sum([testResults.Failed]); + +% pretty summary output +fprintf('\n\n\n\tTable of all executed PhysIO Tests:\n\n'); +disp(testResults.table); + +toc From 997992aef98114fc03fc16fcb636831d92ae1250 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 02:52:53 -0400 Subject: [PATCH 05/98] Updated tapas toolbox infos for PhysIO --- misc/tapas_get_toolbox_infos.m | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/misc/tapas_get_toolbox_infos.m b/misc/tapas_get_toolbox_infos.m index 9ea13b3f..8b5e64ba 100644 --- a/misc/tapas_get_toolbox_infos.m +++ b/misc/tapas_get_toolbox_infos.m @@ -41,9 +41,11 @@ infos.physio.init_dir = strcat('PhysIO',filesep,'code'); infos.physio.init_function = 'tapas_physio_init'; - infos.physio.dependencies = []; + infos.physio.dependencies = {'Signal Processing Toolbox', ... + 'Image Processing Toolbox', ... + 'Statistics and Machine Learning Toolbox'}; infos.physio.diagnose_files = 'tapas_physio_main_create_regressors'; - infos.physio.test_function_name = ''; + infos.physio.test_function_name = 'tapas_physio_test'; infos = tapas_default_toolbox_info(infos,'rDCM'); From c29743e9e26a0e27bbcc0102b8789e931f3d99f2 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 02:53:36 -0400 Subject: [PATCH 06/98] Updated PhysIO init to include tests folders for test functions --- PhysIO/code/tapas_physio_init.m | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/PhysIO/code/tapas_physio_init.m b/PhysIO/code/tapas_physio_init.m index fd8e5a41..9a34919e 100644 --- a/PhysIO/code/tapas_physio_init.m +++ b/PhysIO/code/tapas_physio_init.m @@ -46,6 +46,12 @@ fprintf('OK.\n'); end +% Adding test paths as well to run tapas_physio_test via tapas_test +% TODO: does not work, if code folder in SPM/toolbox +if ~exist('tapas_physio_test') + pathPhysIOTest = fullfile(fileparts(pathPhysIO), 'tests'); + addpath(genpath(pathPhysIOTest)); +end %% Check and add SPM path fprintf('Checking Matlab SPM path now...'); From f7b09a1bbd9ecde74f547f96b4f0728de037c49f Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 02:54:14 -0400 Subject: [PATCH 07/98] First attempt on generic examples path --- .../integration/tapas_physio_examples_test.m | 5 +-- PhysIO/tests/tapas_physio_get_path_examples.m | 39 +++++++++++++++++++ .../tapas_physio_filter_cardiac_test.m | 7 ++-- .../readin/tapas_physio_readin_bids_test.m | 9 ++--- .../unit/utils/tapas_physio_findpeaks_test.m | 3 +- 5 files changed, 49 insertions(+), 14 deletions(-) create mode 100644 PhysIO/tests/tapas_physio_get_path_examples.m diff --git a/PhysIO/tests/integration/tapas_physio_examples_test.m b/PhysIO/tests/integration/tapas_physio_examples_test.m index e2c1aec4..3fff778e 100644 --- a/PhysIO/tests/integration/tapas_physio_examples_test.m +++ b/PhysIO/tests/integration/tapas_physio_examples_test.m @@ -41,10 +41,9 @@ % path to examples, needed for all test cases function setupOnce(testCase) -% run GE example and extract physio +% Get PhysIO public repo base folder from this file's location testCase.TestData.pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..'); -% TODO: Make generic! -testCase.TestData.pathExamples = fullfile(testCase.TestData.pathPhysioPublic, '..', 'examples'); +testCase.TestData.pathExamples = tapas_physio_get_path_examples(testCase.TestData.pathPhysioPublic); end diff --git a/PhysIO/tests/tapas_physio_get_path_examples.m b/PhysIO/tests/tapas_physio_get_path_examples.m new file mode 100644 index 00000000..2bad4565 --- /dev/null +++ b/PhysIO/tests/tapas_physio_get_path_examples.m @@ -0,0 +1,39 @@ +function pathExamples = tapas_physio_get_path_examples(pathPhysioPublic) +% Returns GitLab-internal or TAPAS-public PhysIO Examples folder, based on +% location of public PhysIO directory +% +% pathExamples = tapas_physio_get_path_examples(pathPhysioPublic) +% +% IN +% pathPhysioPublic location of public PhysIO folder, e.g., +% 'tapas/PhysIO' +% OUT +% +% EXAMPLE +% tapas_physio_get_path_examples('tapas/PhysIO') +% +% See also + +% Author: Lars Kasper +% Created: 2022-09-05 +% Copyright (C) 2022 TNU, Institute for Biomedical Engineering, +% University of Zurich and ETH Zurich. +% +% This file is part of the TAPAS PhysIO Toolbox, which is released under +% the terms of the GNU General Public License (GPL), version 3. You can +% redistribute it and/or modify it under the terms of the GPL (either +% version 3 or, at your option, any later version). For further details, +% see the file COPYING or . + +if nargin < 1 + pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..'); +end + +% try PhysIO-internal GitLab examples first +pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); + +% otherwise use public TAPAS examples +if ~isfolder(fullfile(pathExamples, 'BIDS')) + pathExamples = fullfile(pathPhysioPublic, ... + '..', 'examples', tapas_get_current_version(), 'PhysIO'); +end diff --git a/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m b/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m index 4d932985..31630ab2 100644 --- a/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m +++ b/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m @@ -29,10 +29,10 @@ function test_philips_ppu7t_filter_cheby2(testCase) %% Compares previously saved Chebychev Type 2 IIR-filtered cropped cardiac % time course with current re-run of same batch from Philips 7T PPU data -% run GE example and extract physio +% Get PhysIO public repo base folder from this file's location pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); pathCurrentExample = fullfile(pathExamples, 'Philips/PPU7T'); cd(pathCurrentExample); % for prepending absolute paths correctly @@ -71,8 +71,7 @@ function test_philips_ppu7t_filter_butter(testCase) % run GE example and extract physio pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); pathCurrentExample = fullfile(pathExamples, 'Philips/PPU7T'); cd(pathCurrentExample); % for prepending absolute paths correctly diff --git a/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m b/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m index 4688a394..3ee96ca2 100644 --- a/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m +++ b/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m @@ -31,10 +31,10 @@ % results function test_readin_bids_ppu3t(testCase) -% run BIDS PPU example and extract physio +% Get PhysIO public repo base folder from this file's location pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); + % load SPM matlabbatch, but convert to pure script before executing % remove unnecessary (beyond read-in) part from job exeuction (e.g. @@ -79,8 +79,7 @@ function test_readin_bids_cpulse3t(testCase) % run BIDS cpulse3t example and extract physio pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); % load SPM matlabbatch, but convert to pure script before executing % remove unnecessary (beyond read-in) part from job exeuction (e.g. diff --git a/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m b/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m index 826bffa2..889f3889 100644 --- a/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m +++ b/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m @@ -41,8 +41,7 @@ function test_ge_ppu3t_peaks(testCase) % run GE example and extract physio pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); if doUseSpm pathCurrentExample = fullfile(pathExamples, 'GE/PPU3T'); From 32c49ea91759fa0c4ed910789f04f19c8c884b54 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 20:24:21 -0400 Subject: [PATCH 08/98] updated tapas_physio_version to R2022b-v8.2.0 --- PhysIO/code/tapas_physio_version.m | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/PhysIO/code/tapas_physio_version.m b/PhysIO/code/tapas_physio_version.m index 512e1d63..beebfd62 100644 --- a/PhysIO/code/tapas_physio_version.m +++ b/PhysIO/code/tapas_physio_version.m @@ -23,4 +23,4 @@ % version 3 or, at your option, any later version). For further details, % see the file COPYING or . % -versionPhysio = 'R2022a-v8.2.0-beta'; +versionPhysio = 'R2022b-v8.2.0'; From bb0596e03ba0c3506bf2b692f0d40c7d44dda8f6 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Wed, 7 Sep 2022 17:45:28 -0400 Subject: [PATCH 09/98] Added tapas_download_example_data suggestion if missing for test --- PhysIO/tests/tapas_physio_get_path_examples.m | 6 ++++++ PhysIO/tests/tapas_physio_test.m | 3 +++ 2 files changed, 9 insertions(+) diff --git a/PhysIO/tests/tapas_physio_get_path_examples.m b/PhysIO/tests/tapas_physio_get_path_examples.m index 2bad4565..5b6aac1e 100644 --- a/PhysIO/tests/tapas_physio_get_path_examples.m +++ b/PhysIO/tests/tapas_physio_get_path_examples.m @@ -37,3 +37,9 @@ pathExamples = fullfile(pathPhysioPublic, ... '..', 'examples', tapas_get_current_version(), 'PhysIO'); end + +% If no examples folder found, suggest to download them via tapas-function +if ~isfolder(fullfile(pathExamples, 'BIDS')) + physio = tapas_physio_new(); + tapas_physio_log('No PhysIO examples data found. Please download via tapas_download_example_data()', physio.verbose, 2); +end diff --git a/PhysIO/tests/tapas_physio_test.m b/PhysIO/tests/tapas_physio_test.m index 2bd0b578..e5a30ffa 100644 --- a/PhysIO/tests/tapas_physio_test.m +++ b/PhysIO/tests/tapas_physio_test.m @@ -45,6 +45,9 @@ testResults = []; +% Returns an error message, if no example data found +tapas_physio_get_path_examples(); + if level >= 0 testResults = [testResults tapas_physio_run_unit_tests()]; else From 6d11a2cd9d22104eed94a1dd5b5c33be584f3e9b Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Fri, 9 Sep 2022 15:17:20 -0400 Subject: [PATCH 10/98] Check other possible SPM toolbox locations in spm (my) defaults for compatibility with lmod (GitHub issue #211) --- PhysIO/CHANGELOG.md | 6 ++++-- ...s_physio_check_spm_batch_editor_integration.m | 16 ++++++++++++---- 2 files changed, 16 insertions(+), 6 deletions(-) diff --git a/PhysIO/CHANGELOG.md b/PhysIO/CHANGELOG.md index 92cd279d..037f53ad 100644 --- a/PhysIO/CHANGELOG.md +++ b/PhysIO/CHANGELOG.md @@ -6,7 +6,7 @@ Current Release *Current version: PhysIO Toolbox Release R2022b, v8.2.0* -September 5th, 2022 +September 9th, 2022 Minor Release Notes (v8.2.0) ---------------------------- @@ -17,7 +17,9 @@ Minor Release Notes (v8.2.0) - multi ECG/Resp channels and interleaved status messages ### Fixed - Removed dependence on `nanmean` (Statistics Toolbox) - - See GitHub issue #205 and + - See GitHub issue #205 +- Compatibility with multiple SPM toolbox locations for `lmod` ([GitHUb issue #211](https://github.com/translationalneuromodeling/tapas/issues/211)) + - as listed in `spm_get_defaults('tbx')` Minor Release Notes (v8.1.0) ---------------------------- diff --git a/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m b/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m index 642f4ba3..1425914e 100644 --- a/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m +++ b/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m @@ -32,14 +32,22 @@ [isSpmOnPath, pathSpm] = tapas_physio_check_spm(); -isPhysioVisibleForSpmBatchEditor = isSpmOnPath; % minimum requirement for integration: SPM works! +isPhysioVisibleForSpmBatchEditor = false; % checked below, need SPM visible for that % check for config matlabbatch file if isSpmOnPath - filePhysioCfgMatlabbatch = ... - dir(fullfile(pathSpm, 'toolbox', '**/tapas_physio_cfg_matlabbatch.m')); - isPhysioVisibleForSpmBatchEditor = ~isempty(filePhysioCfgMatlabbatch); + % check all possible SPM toolbox locations, as listed in its defaults: + tbx = spm_get_defaults('tbx'); % SPM toolbox parameter struct + + iDir = 1; + while (iDir <= numel(tbx.dir)) && ~isPhysioVisibleForSpmBatchEditor + filePhysioCfgMatlabbatch = ... + dir(fullfile(tbx.dir{iDir}, '**/tapas_physio_cfg_matlabbatch.m')); + + isPhysioVisibleForSpmBatchEditor = ~isempty(filePhysioCfgMatlabbatch); + iDir = iDir + 1; + end % also important to set default modality of spm to fMRI and % initialize batch editor, if not done before From 53679b522a2ea6c6abd5e57d36606a1c212f7f6d Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Sun, 11 Sep 2022 22:07:55 -0400 Subject: [PATCH 11/98] Added Siemens_VB/RESP3T_Logversion_3 integration tests, updated wiki and changelog for R2022b-v8.2.0 --- PhysIO/CHANGELOG.md | 3 +- .../tapas_physio_read_physlogfiles_siemens.m | 2 +- .../readin/tapas_physio_siemens_line2table.m | 4 +- PhysIO/docs/documentation.html | 217 +++++++++--------- PhysIO/docs/documentation.pdf | Bin 1955861 -> 1966717 bytes .../integration/tapas_physio_examples_test.m | 57 ++++- 6 files changed, 166 insertions(+), 117 deletions(-) diff --git a/PhysIO/CHANGELOG.md b/PhysIO/CHANGELOG.md index 037f53ad..0a50c69b 100644 --- a/PhysIO/CHANGELOG.md +++ b/PhysIO/CHANGELOG.md @@ -6,7 +6,7 @@ Current Release *Current version: PhysIO Toolbox Release R2022b, v8.2.0* -September 9th, 2022 +September 12th, 2022 Minor Release Notes (v8.2.0) ---------------------------- @@ -15,6 +15,7 @@ Minor Release Notes (v8.2.0) - Interface `tapas_physio_test` to TAPAS-generic `tapas_test` function - Added suport for logfile version 3 of Siemens physio recordings - multi ECG/Resp channels and interleaved status messages + - new integration test for Siemens VB Logversion 3 ### Fixed - Removed dependence on `nanmean` (Statistics Toolbox) - See GitHub issue #205 diff --git a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m index 5e00df88..2e370de8 100755 --- a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m +++ b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m @@ -68,7 +68,7 @@ % used channel depends on cardiac modality switch cardiac_modality case 'ECG' - defaults.ecgChannel = 'mean'; %'mean'; 'v1'; 'v2' + defaults.ecgChannel = 'mean'; %'mean'; 'v1'; 'v2'; 'v3'; 'v4' otherwise defaults.ecgChannel = 'v1'; end diff --git a/PhysIO/code/readin/tapas_physio_siemens_line2table.m b/PhysIO/code/readin/tapas_physio_siemens_line2table.m index 4a72d0fa..a65349e4 100755 --- a/PhysIO/code/readin/tapas_physio_siemens_line2table.m +++ b/PhysIO/code/readin/tapas_physio_siemens_line2table.m @@ -37,9 +37,9 @@ % parsimonious, but it's written in a way to support all different physio % trace modalities and logfile versions (more detail below) -% The ypical logfile structure is as follows (all data in first line of +% The typical logfile structure is as follows (all data in first line of % logfile, the footer is in the next line (after 5003), not used in this -% file, but tapas_physio_read_physlogfiles_siemens_raw)L +% file, but tapas_physio_read_physlogfiles_siemens_raw) % %
      5002 6002 % <[optional] training trace data> 5002 uiHwRevisionPeru ... [optional] 6002 diff --git a/PhysIO/docs/documentation.html b/PhysIO/docs/documentation.html index 393e2bd9..da41aad7 100644 --- a/PhysIO/docs/documentation.html +++ b/PhysIO/docs/documentation.html @@ -827,7 +827,7 @@

      Troubleshoot

      TAPAS PhysIO Toolbox

      Current version: Release 2022b, v8.2.0

      -

      Copyright (C) 2012-2022
      Lars Kasper
      kasper@biomed.ee.ethz.ch

      +

      Copyright (C) 2012-2022
      Lars Kasper
      kasper@biomed.ee.ethz.ch

      Translational Neuromodeling Unit (TNU)
      Institute for Biomedical Engineering
      University of Zurich and ETH Zurich

      Download

      @@ -1523,29 +1523,21 @@

      Example Datasets for PhysIO

      The following datasets are available to explore the read-in and modeling capabilities of PhysIO. They can be downloaded by running the function tapas_download_example_data() in Matlab, which is located in the misc subfolder of the TAPAS software release you downloaded (probably here).

      Afterwards, the examples can be found in tapas/examples/<tapasVersion>/PhysIO as different subfolders (vendor/device) and shall be run directly from within these individual folders.

      -

      Besides the raw physiological logfiles, each example contains example scripts to run PhysIO as

      +

      Besides the raw physiological logfiles, each example contains example scripts to run PhysIO as

        -
      • SPM job (*spm_job.mat)
        • -
      • editable SPM job (*spm_job.m)
        • -
      • plain matlab script (*matlab_script.m)
        • +
      • SPM job (\\\*spm_job.mat)
        • +
      • editable SPM job (\\\*spm_job.m)
        • +
      • plain matlab script (\\\*matlab_script.m)

      Brain Imaging Data Structure (BIDS)

      CPULSE 3T

      -

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry -and Ageing Research, University College London

      -

      Vendor-computed (software: Spike2) cardiac pulse events from PPU (finger -plethysmograph) data, Siemens 3T scanner, Multiband CMRR sequence

      -

      Description: This datasets contains the (compressed) tab-separated value -(.tsv.gz) files as well as the meta-file (.json) holding sampling rate of -the physiological recording, and its relative onset to scanning, in adherence -with the BIDS standard for peripheral recordings -files.

      +

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London

      +

      Vendor-computed (software: Spike2) cardiac pulse events from PPU (finger plethysmograph) data, Siemens 3T scanner, Multiband CMRR sequence

      +

      Description: This datasets contains the (compressed) tab-separated value (.tsv.gz) files as well as the meta-file (.json) holding sampling rate of the physiological recording, and its relative onset to scanning, in adherence with the BIDS standard for peripheral recordings files.

      PPU 3T

      -

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry -and Ageing Research, University College London

      +

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London

      PPU (finger plethysmograph) and breathing belt, Siemens 3T scanner, Multiband CMRR sequence

      -

      Description: Similar to CPULSE3T (same acquisition system), but now with analog -data instead of vendor-detected pulses, data from different subject

      +

      Description: Similar to CPULSE3T (same acquisition system), but now with analog data instead of vendor-detected pulses, data from different subject

      PPU 3T Separate Files

      Courtesy of Alexandre Sayal CIBIT, University of Coimbra

      PPU (finger plethysmograph) and breathing belt, Siemens 3T scanner, Multiband CMRR sequence

      @@ -1553,70 +1545,67 @@

      PPU 3T Separate Files

      General Electric

      PPU 3T

      Courtesy of Steffen Bollmann, Kinderspital Zurich and ETH Zurich

      -

      PPU (finger plethysmograph) and breathing belt, General Electric 3T -scanner

      -

      Description: Similar to PPU, but acquired on a GE system with two -separate output logfiles for pulse oximetry and breathing amplitude, -sampled with 40 Hz. The quality of the signal is particularly -challenging, stemming from a patient population.

      +

      PPU (finger plethysmograph) and breathing belt, General Electric 3T scanner

      +

      Description: Similar to PPU, but acquired on a GE system with two separate output logfiles for pulse oximetry and breathing amplitude, sampled with 40 Hz. The quality of the signal is particularly challenging, stemming from a patient population.

      Philips

      ECG 3T

      -

      Courtesy of Sandra Iglesias, Translational Neuromodeling Unit, ETH & -University of Zurich

      +

      Courtesy of Sandra Iglesias, Translational Neuromodeling Unit, ETH & University of Zurich

      4-electrode ECG and breathing belt, Philips 3T Achieva scanner

      -

      Description: Standard example; shows how to use volume counting either -from beginning or end of run to synchronize physiological logfile with -acquisition onsets of fMRI scans.

      +

      Description: Standard example; shows how to use volume counting either from beginning or end of run to synchronize physiological logfile with acquisition onsets of fMRI scans.

      ECG 7T

      Courtesy of Zina-Mary Manjaly, University Hospital Zurich

      4-electrode ECG and breathing belt, Philips 7T Achieva scanner

      -

      Description: The ECG data for ultra-high field data is typically much -noisier than at 3 Tesla. Therefore, R-wave peaks are frequently missed -by prospective trigger detection and not marked correctly in the -logfile. This example shows how to select typical R-wave-peaks manually -and let the algorithm find the heartbeat events.

      +

      Description: The ECG data for ultra-high field data is typically much noisier than at 3 Tesla. Therefore, R-wave peaks are frequently missed by prospective trigger detection and not marked correctly in the logfile. This example shows how to select typical R-wave-peaks manually and let the algorithm find the heartbeat events.

      PPU 3T

      Courtesy of Diana Wotruba, University and University Hospital of Zurich

      -

      PPU (finger plethysmograph) and breathing belt, Philips 3T Achieva -scanner

      -

      Description: Similar to ECG3T, but a plethysmograph instead of an ECG -was used to monitor the cardiac pulsation. Example shows how to extract -heart and breathing rate.

      +

      PPU (finger plethysmograph) and breathing belt, Philips 3T Achieva scanner

      +

      Description: Similar to ECG3T, but a plethysmograph instead of an ECG was used to monitor the cardiac pulsation. Example shows how to extract heart and breathing rate.

      PPU 7T

      Courtesy of Jakob Heinzle and Lars Kasper, TNU, University Zurich and ETH Zurich

      -

      PPU (finger plethysmograph) and breathing belt, Philips 7T Achieva -scanner

      +

      PPU (finger plethysmograph) and breathing belt, Philips 7T Achieva scanner

      Description: Challenging cardiac data that requires bandpass-filtering during preprocessing, since it is compromised by both high frequency noise (from the scanner, modulated at every slice TR) and low frequency noise (breathing modulation).

      Siemens - VB

      Siemens has different physiological logfile formats, for which examples are provided here. A detailed description of these formats is on a different wiki page.

      -

      This is the older Siemens log file format (also available via manual recording), which is part of software release VB, and can be determined by the file extensions .resp, .ecg, .puls, in combination with an optional .dcm DICOM header file for the first (or last) acquired volume.

      -

      A lot of 7T scanners still use this format.

      +

      This is the older Siemens log file format (also available via manual recording), which is part of software release _VB_, and can be determined by the file extensions .resp, .ecg, .puls, in combination with an optional .dcm DICOM header file for the first (or last) acquired volume.

      +

      A lot of 7T scanners still use this format, but it is also the default on modern 3T systems, if you don't have C2P sequences for fMRI (e.g., from CMRR) or WIPs from Siemens (see below).

      ECG 3T

      Courtesy of Miriam Sebold, Charite Berlin, and Quentin Huys, TNU Zurich

      -

      4-electrode ECG data, Siemens 3T scanner

      +

      4-electrode ECG data, Siemens 3T scanner, logfile version 1

      Description: Similar to ECG 3T, but acquired on a Siemens system with only one logfile for ECG data. The quality of the signal is challenging, stemming from a patient population.

      PPU3T (Sync First and Sync Last)

      Courtesy of Alexander Ritter, University of Jena, Germany

      -

      Siemens 3T pulse oximetry and respiratory bellows data from a complete scan session of a healthy volunteer, plus the DICOM header file of the first and last (382nd) volume of an fMRI run, respectively.

      -

      This showcases scan timing synchronization using the DICOM timestamps in an intricate case, where the physiological logfile spans the whole scan session (and not only the fMRI run). See TAPAS github issue #55 for further details.

      +

      Siemens 3T pulse oximetry and respiratory bellows data, logfile version 1 DICOM header file of first and last (382nd) volume of an fMRI run, respectively.

      +

      Description: This data covering a complete scan session of a healthy volunteer showcases scan timing synchronization using the DICOM timestamps in an intricate case, where the physiological logfile spans the whole scan session (and not only the fMRI run). See TAPAS github issue #55 for further details.

      +

      ECG 3T - Logversion 3

      +

      Courtesy of Shahin Safa, see TAPAS GitHub issue 204

      +

      4-electrode ECG data, Siemens scanner, logfile version 3 corresponding respiratory data: Resp 3T - Logversion 1

      +

      Description: This is an fMRI study on the auditory system of the brain, which explains the long TR (10 s), to put scanning gaps when presenting the sound to the subject.

      +

      Resp 3T - Logversion 1

      +

      Courtesy of Shahin Safa, see TAPAS GitHub issue 204

      +

      Respiratory bellows data, Siemens scanner, logfile version 1 corresponding cardiac data: ECG 3T - Logversion 3

      +

      Description: This is an fMRI study on the auditory system of the brain, which explains the long TR (10 s), to put scanning gaps when presenting the sound to the subject.

      +

      Resp 3T - Logversion 3

      +

      Courtesy of Lars Kasper, University Health Network Toronto, Canada

      +

      Respiratory bellows data, Siemens Prisma 3T, logfile version 3

      +

      Description: Short fingertapping run with logging automatically switched off after about 2 minutes (nominally 5) due to ECG channels not connected, but requested for recording. Biomatrix sensors were not available, but are logged as 4 extra channels with constant values here.

      Siemens - HCP

      -

      The Human Connectome Project uses Siemens scanners, and the logfile format that comes with their published data seems to be pre-converted and custom (even though the documentation desribes the VB format). We have implemented an own reader for that and written a little tutorial for a single subject dataset of the HCP.

      +

      The Human Connectome Project uses Siemens scanners, and the logfile format that comes with their published data seems to be pre-converted and custom (even though the documentation desribes the VB format). We have implemented an own reader for that and written a little tutorial for a single subject dataset of the HCP.

      https://github.com/translationalneuromodeling/tapas/issues/6#issuecomment-361001716

      If you download the whole dataset (including functional image files), this example with the additional batches mentioned below also demonstrates how to use the toolbox for model assessment using statistical maps (F-contrasts).

      HCP (Subject 178748)

      You will have to download the dataset from the HCP yourself, we just provide the matlab batches and the physiological logfile tfMRI_MOTOR_LR_Physio_log.txt here.

      For consistency with the other example files, the batch files have been renamed compared to the blog entry:

        -
      • batch_preproc.m -> batch_preproc.m
        • -
      • batch_physio.m -> siemens_hcp_ppu3t_spm_job.m
        • -
      • batch_glm.m -> batch_glm.m
        • +
      • batch_preproc.m -> batch_preproc.m
        • +
      • batch_physio.m -> siemens_hcp_ppu3t_spm_job.m
        • +
      • batch_glm.m -> batch_glm.m

      If you want to run the preproc and glm batch, place them on the same level as the subject folder 178748 for the downloaded data. The physio-batch shall reside in the same folder as the physiological logfile tfMRI_MOTOR_LR_Physio_log.txt.

      Siemens - VD/VE Tics

      -

      This is the most recent logfile format of Siemens, included in Software releases VD, VE and sometimes referred to as the Tics format, because all time stamps in all files refer to the same reference point (start of the day) and count in the same intervals or "tics" of 2.5 ms from there.

      -

      You will recognize this file format via the extensions _Info.log (or _AcquisitionInfo.log), _RESP.log, _ECG.log and _PULS.log. Sometimes, it is also written into the DICOM header (.dcm) file of your functional data directly. In this case, use extractCMRRPhysio.m to convert it to the above separate files before using PhysIO.

      +

      This is the most recent logfile format of Siemens, included in Software releases _VD_, _VE_ and sometimes referred to as the Tics format, because all time stamps in all files refer to the same reference point (start of the day) and count in the same intervals or "tics" of 2.5 ms from there.

      +

      You will recognize this file format via the extensions \\\_Info.log (or \\\_AcquisitionInfo.log), \\\_RESP.log, \\\_ECG.log and \\\_PULS.log. Sometimes, it is also written into the DICOM header (.dcm) file of your functional data directly. In this case, use extractCMRRPhysio.m to convert it to the above separate files before using PhysIO.

      Most modern Siemens scanners, such as the Prisma or 7T Terra, use this format.

      -

      There are a couple of variants for this format around (e.g., with the WIP Multiband Protocol that is distributed to multiple sites), and PhysIO tries to support all of them.

      +

      There are a couple of variants for this format around (e.g., with the WIP Multiband Protocol that is distributed to multiple sites), and PhysIO tries to support all of them.

      PPU 3T

      Courtesy of Saskia Bollmann, Centre for Advanced Imaging, University of Queensland, Brisbane, Australia

      Pulse oximetry and breathing belt data, Siemens Prisma 3T, logfile version EJA_1, multi-echo fMRI (3 echoes)

      @@ -1624,46 +1613,41 @@

      PPU 3T

      PPU 3T Separate Files

      Courtesy of Alexandre Sayal CIBIT, University of Coimbra

      PPU (finger plethysmograph) and breathing belt, Siemens 3T scanner, Multiband CMRR sequence

      -

      Description: Raw data that was used to convert to two separate BIDS files above (BIDS/PPU3T_Separate_Files) for cardiac and respiratory recordings, because of differing sampling rate (5 vs 20 ms).

      +

      Description: Raw data that was used to convert to two separate BIDS files above (BIDS/PPU3T_Separate_Files) for cardiac and respiratory recordings, because of differing sampling rate (5 vs 20 ms).

      The UUID and date/time stamps were altered for anonymization.

      Technical Documentation: Read-in

      Brain Imaging Data Structure (BIDS)

      PhysIO supports physiological logfiles prepared according to the BIDS standard

        -
      • In brief, BIDS files are (optionally compressed) tab-separated values -(*.tsv[.gz]) files that contain raw traces of peripheral recordings from -cardiac and respiratory sources, as well as scan trigger events
        • -
      • The header of the columns of this *.tsv file, as well as meta-information, -such as sampling rate and relative onset of physiological logging to MRI scan -onset is described in an accompanying *.json file
          -
        • It is assumed to have the that this *.json file has the same name -(apart from the extension) as the *.tsv file
          • -
        • If PhysIO does not find this file, you can manually enter the timing -information in the log_files structure, and a default column order of -(cardiac, respiratory, trigger) is assumed
          • -
        -
        • -
      • Example *.tsv file (with cardiac, respiratory, trigger column -:
                                   -0.949402 -0.00610382 0
-                           -0.949402 -0.00610382 0
-                           -0.951233 -0.00915558 0
-                           -0.951233 -0.00915558 0
-                           -0.953064 -0.0122073  0
-                           -0.953064 -0.0122073  0
-                           -0.95459  -0.0076297  1
-                           -0.95459  -0.0076297  0
        • -
      • Example *.json file:
        {
-  "SamplingFrequency": 50.0, 
-  "Columns": [
-      "cardiac", 
-      "respiratory", 
-      "trigger"
-  ], 
-  "StartTime": -255.45
-}
        • +
      • In brief, BIDS files are (optionally compressed) tab-separated values (\*.tsv\[.gz\]) files that contain raw traces of peripheral recordings from cardiac and respiratory sources, as well as scan trigger events
        • +
      • The header of the columns of this \*.tsv file, as well as meta-information, such as sampling rate and relative onset of physiological logging to MRI scan onset is described in an accompanying \*.json file
          +
        • It is assumed to have the that this \*.json file has the same name (apart from the extension) as the \*.tsv file
          • +
        • If PhysIO does not find this file, you can manually enter the timing information in the log_files structure, and a default column order of (cardiac, respiratory, trigger) is assumed
          • +
        +
        • +
      • Example \*.tsv file (with cardiac, respiratory, trigger column :
        • +
      +
                                   -0.949402 -0.00610382 0
+                             -0.949402 -0.00610382 0
+                             -0.951233 -0.00915558 0
+                             -0.951233 -0.00915558 0
+                             -0.953064 -0.0122073  0
+                             -0.953064 -0.0122073  0
+                             -0.95459  -0.0076297  1
+                             -0.95459  -0.0076297  0
        +
      • Example \*.json file:
        • +
      +
      {
+    "SamplingFrequency": 50.0, 
+    "Columns": [
+        "cardiac", 
+        "respiratory", 
+        "trigger"
+    ], 
+    "StartTime": -255.45
+}
      • Note that StartTime refers to when the physiological recording started relative to the first scan volume of the fMRI run, which means that typically this value is negative, because one starts the recording before the onset of scan volumes.
        • -
      • See tapas_physio_read_physlogfiles_bids.m for more details and technical -documentation.
        • +
      • See tapas_physio_read_physlogfiles_bids.m for more details and technical documentation.

      BioPac

      Mat-file Export (.mat)

      @@ -1685,13 +1669,12 @@

      Single Text File Export (.txt

    • Export your traces from cardiac and breathing recording devices into 2 text files and select log_files.vendor = 'Custom'. The format is explained in tapas_physio_new or the help window of the Batch Editor:

      • 'Custom' expects the logfiles (separate files for cardiac and respiratory) to be plain text, with one cardiac (or respiratory) sample per row;
        • -

      • If heartbeat (R-wave peak) events are recorded as well, they have to be put as a 2nd column in the cardiac logfile by specifying a 1; 0 in all other rows, e.g.

        +
      • If heartbeat (R-wave peak) events are recorded as well, they have to be put as a 2nd column in the cardiac logfile by specifying a 1; 0 in all other rows, e.g.
        • +
      0.2  0
 0.4  1 <- cardiac pulse event
 0.2  0
 -0.3 0
      • -

    -
  • You have to specify the sampling intervals for these log files (in seconds), via log_files.sampling_interval, e.g. [0.01 0.02] if you have 10 ms (100 Hz) and 20 ms (50 Hz) sampling intervals (frequencies) for cardiac and respiratory data, respectively
  • You will probably have to change log_files.relative_start_acquisition, if logging of your physiological recording device does not start synchronized to the first fMRI volume.
    • @@ -1699,17 +1682,19 @@

    General Electric (GE)

    • Very similar to custom format
    • One text file each for ECG, pulse oximetry and respiratory data, e.g., ECGData_epiRT_phys_0921201215_38_08 or RespData_epiRT_phys_0921201215_38_08
      • -
    • One amplitude entry per line, e.g.,
      2626
-2649
-2673
-2699
-2727
-2755
      • +
    • One amplitude entry per line, e.g.,
      • +
    +
     2626
+ 2649
+ 2673
+ 2699
+ 2727
+ 2755
    • sampling rate is determined as a setting beforehand, has to be noted manually (not in log file)

    Philips

    @@ -1729,8 +1730,9 @@

    Philips

    Siemens

    Manual Recording

    Physiological data collection on the Siemens scanners uses the physiological monitoring unit (PMU). The initial sampling is performed at 400 Hz, but through the PMU buffer the effective sampling intervals are ECG: 2.5 ms, RESP: 20 ms, PULS: 20 ms and EXT: 5 ms.

    -

    There are several ways to control the physiological data collection. The 'manual' version is available on all platforms. It uses the telnet mpcu/ideacmdtool to manually start and stop the log file acquisition. The log files (logFileName.ecg, logFileName.resp, logFileName.puls, logFileName.ext) are stored in \MedCom\log. More details on how to record these data can be found here or in the "Other Miscellaneous Topics" slides from the IDEA course.

    -

    An example of a .puls logfile is given below. The data are stored in one long line. The text between 5002 and 6002 forms the header, and the text between 5003 and 6003 the footer. Important information in the footer is the LogStartMDHTime and the LogStopMDHTime (in ms since midnight), which can be used to synchronize the logfiles with the dicom images using the AcquisitionTime in the dicom header (in hhmmss.ms). The values 5000 and 6000 are inserted into the signal trace and indicate trigger events. Note that only the modality which is selected to be displayed during the acquisition will have triggers.

    +

    There are several ways to control the physiological data collection. The 'manual' version is available on all platforms. It uses the telnet mpcu/ideacmdtool to manually start and stop the log file acquisition. The log files (logFileName.ecg, logFileName.resp, logFileName.puls, logFileName.ext) are stored in \MedCom\log. More details on how to record these data can be found here or in the "Other Miscellaneous Topics" slides from the IDEA course.

    +

    An example of a .puls logfile is given below. The data are stored in one long line. The text between 5002 and 6002 forms the header, and the text between 5003 and 6003 the footer. Important information in the footer is the LogStartMDHTime and the LogStopMDHTime (in ms since midnight), which can be used to synchronize the logfiles with the DICOM images using the AcquisitionTime in the DICOM header (in hhmmss.ms). The values 5000 and 6000 are inserted into the signal trace and indicate trigger events. Note that only the modality which is selected to be displayed during the acquisition will have triggers.

    +

    We use the time stamp of the clock of the Measurement Data Header (MDH), i.e., computer that controls the scanner, to synchronize with the DICOMs, because this computer also controls the creation of the scan data, i.e., reconstructed DICOM images. This is in accordance to other packages reading Siemens physiological logfile data, e.g., Chris Rorden's PART, with a detailed explanation on the DICOM timestamp in AcquisitionTime found here. 

    1 2 40 280 5002 Logging PULSE signal: reduction factor = 1, PULS_SAMPLES_PER_SECOND = 50; PULS_SAMPLE_INTERVAL = 20000 6002 1653 1593 1545 1510 1484 ...
 ACQ FINISHED
  6002 3093 3096 3064 5000 3016 2926 5003
@@ -1826,8 +1828,22 @@ 
    Human Connectome Project
    
 1    1904    1780

    Version History (Changelog)

    RELEASE INFORMATION

    Current Release

    -

    Current version: PhysIO Toolbox Release R2022a, v8.1.0

    -

    April 5th, 2022

    +

    Current version: PhysIO Toolbox Release R2022b, v8.2.0

    +

    September 5th, 2022

    +

    Minor Release Notes (v8.2.0)

    +

    Added

    +
      +
    • Interface tapas_physio_test to TAPAS-generic tapas_test function
      • +
    • Added suport for logfile version 3 of Siemens physio recordings
        +
      • multi ECG/Resp channels and interleaved status messages

        Fixed

        +
        • +
      +
      • +
    • Removed dependence on nanmean (Statistics Toolbox)
        +
      • See GitHub issue #205 and
        • +
      +
      • +

    Minor Release Notes (v8.1.0)

    Added

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z-oT&AfyqM$=wV^t6CA{{fx`kz6N3v{?ZiR}=s|r)6p+axgO4@uiTQv(dHl1MP}P7PHc zv8;r;od1RFBk1wqI+DX8`55o?5*Tw~!@@tFKVmZOCTI$ehJl;lLX-p}UfqE^;atQa zoY(;foo?b}XpRw=6C8}FBs{1?NO%n5%>ponL&A_ELnn3sk~GHMPORXe>?PMQuo;tb z00&YEF^fWCAOX`nF*8F zEC!8PgjWkN7ym~Pn#bYNMr{auCR_$7&%=S3*pJ}A`IR)63!50x?_euZ?uP}7TM*y> zhtnwZ_Q;Ikl9sfyap4Mt82wO_kQu{^8`$uy;6)Xw zXoYt!#QXtwadc9!a(PTB*a<%2!d)!UPhfpgHN>TJNy!Hu6p-gKXrwa`7y82ZD#7hP zw2N`La6L_oRxX1}Y^Z@IaNR=`nn}YSOpSIY$V_q*)DR<94$dD^FbG3p44>vATLzv? z5ShTm2ni3`^CZS_3?T`~;enHh1o5qi2*d3~f{kqb2wrnRqlTFKp;7Zc@Te3)9RT_d znICUM5rYe0&<-8V7@9YvJP$BvP?PY8j~HOXf@b+hYXN@%Lcu_&Pyt5DgaCsKPGo|& z^NBDhZ%OnZ6v%jN9x;NU!$~D>#{gpzml(jHeM4jn{bZ80*l;8z;lWnPhyAPn@FYbH zE`X7CMSzj67N9mD9lHR=|2DOeD*|8yt3v$;K)6pDEg@u9D$(x%BR=YamBXcvTuy@3 z1iedAP(!LFSqnBw!XqOP2C8L}3E_M|SUP|Qr-9Kz1MGh=p~4jq5f6^#g9;DVe-P=U zTT_TuxOyc{romkd2?j?)A`HInkHi?R!$vE|!=s;c9|yfq3NZ%&3=XP9CeX$v3CMs- zg@i}C*#Ua6rxNNvE`. + +if nargin < 1 + level = 0; +end + +tic + +testResults = []; + +if level >= 0 + testResults = [testResults tapas_physio_run_unit_tests()]; +else + nTestTotal = 0; + nTestFailed = 0; + return +end + +if level == 1 + % code adapted from run_integration_tests, but chooses only tests with + % 'matlab' in the name (SPM GUI tests have SPM in the name) + import matlab.unittest.TestSuite; + + pathTests = fullfile(fileparts(mfilename('fullpath')), 'integration'); + suiteFolder = TestSuite.fromFolder(pathTests, ... + 'IncludingSubfolders', true, 'Name', '*matlab_only*'); + testResults = [testResults run(suiteFolder)]; +end + +if level >= 2 + testResults = [testResults tapas_physio_run_integration_tests()]; +end + +nTestTotal = numel(testResults); +nTestFailed = sum([testResults.Failed]); + +% pretty summary output +fprintf('\n\n\n\tTable of all executed PhysIO Tests:\n\n'); +disp(testResults.table); + +toc From 05d380bc92d358bad797e42ea9435299676beda6 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 02:52:53 -0400 Subject: [PATCH 16/98] Updated tapas toolbox infos for PhysIO --- misc/tapas_get_toolbox_infos.m | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/misc/tapas_get_toolbox_infos.m b/misc/tapas_get_toolbox_infos.m index 9ea13b3f..8b5e64ba 100644 --- a/misc/tapas_get_toolbox_infos.m +++ b/misc/tapas_get_toolbox_infos.m @@ -41,9 +41,11 @@ infos.physio.init_dir = strcat('PhysIO',filesep,'code'); infos.physio.init_function = 'tapas_physio_init'; - infos.physio.dependencies = []; + infos.physio.dependencies = {'Signal Processing Toolbox', ... + 'Image Processing Toolbox', ... + 'Statistics and Machine Learning Toolbox'}; infos.physio.diagnose_files = 'tapas_physio_main_create_regressors'; - infos.physio.test_function_name = ''; + infos.physio.test_function_name = 'tapas_physio_test'; infos = tapas_default_toolbox_info(infos,'rDCM'); From 7c03e30fce633a97d73a44745187dd31adcfc0ef Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 02:53:36 -0400 Subject: [PATCH 17/98] Updated PhysIO init to include tests folders for test functions --- PhysIO/code/tapas_physio_init.m | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/PhysIO/code/tapas_physio_init.m b/PhysIO/code/tapas_physio_init.m index fd8e5a41..9a34919e 100644 --- a/PhysIO/code/tapas_physio_init.m +++ b/PhysIO/code/tapas_physio_init.m @@ -46,6 +46,12 @@ fprintf('OK.\n'); end +% Adding test paths as well to run tapas_physio_test via tapas_test +% TODO: does not work, if code folder in SPM/toolbox +if ~exist('tapas_physio_test') + pathPhysIOTest = fullfile(fileparts(pathPhysIO), 'tests'); + addpath(genpath(pathPhysIOTest)); +end %% Check and add SPM path fprintf('Checking Matlab SPM path now...'); From 08d3d584c7ff8b80bbcee24d5f55a0689a1df347 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 02:54:14 -0400 Subject: [PATCH 18/98] First attempt on generic examples path --- .../integration/tapas_physio_examples_test.m | 5 +-- PhysIO/tests/tapas_physio_get_path_examples.m | 39 +++++++++++++++++++ .../tapas_physio_filter_cardiac_test.m | 7 ++-- .../readin/tapas_physio_readin_bids_test.m | 9 ++--- .../unit/utils/tapas_physio_findpeaks_test.m | 3 +- 5 files changed, 49 insertions(+), 14 deletions(-) create mode 100644 PhysIO/tests/tapas_physio_get_path_examples.m diff --git a/PhysIO/tests/integration/tapas_physio_examples_test.m b/PhysIO/tests/integration/tapas_physio_examples_test.m index e2c1aec4..3fff778e 100644 --- a/PhysIO/tests/integration/tapas_physio_examples_test.m +++ b/PhysIO/tests/integration/tapas_physio_examples_test.m @@ -41,10 +41,9 @@ % path to examples, needed for all test cases function setupOnce(testCase) -% run GE example and extract physio +% Get PhysIO public repo base folder from this file's location testCase.TestData.pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..'); -% TODO: Make generic! -testCase.TestData.pathExamples = fullfile(testCase.TestData.pathPhysioPublic, '..', 'examples'); +testCase.TestData.pathExamples = tapas_physio_get_path_examples(testCase.TestData.pathPhysioPublic); end diff --git a/PhysIO/tests/tapas_physio_get_path_examples.m b/PhysIO/tests/tapas_physio_get_path_examples.m new file mode 100644 index 00000000..2bad4565 --- /dev/null +++ b/PhysIO/tests/tapas_physio_get_path_examples.m @@ -0,0 +1,39 @@ +function pathExamples = tapas_physio_get_path_examples(pathPhysioPublic) +% Returns GitLab-internal or TAPAS-public PhysIO Examples folder, based on +% location of public PhysIO directory +% +% pathExamples = tapas_physio_get_path_examples(pathPhysioPublic) +% +% IN +% pathPhysioPublic location of public PhysIO folder, e.g., +% 'tapas/PhysIO' +% OUT +% +% EXAMPLE +% tapas_physio_get_path_examples('tapas/PhysIO') +% +% See also + +% Author: Lars Kasper +% Created: 2022-09-05 +% Copyright (C) 2022 TNU, Institute for Biomedical Engineering, +% University of Zurich and ETH Zurich. +% +% This file is part of the TAPAS PhysIO Toolbox, which is released under +% the terms of the GNU General Public License (GPL), version 3. You can +% redistribute it and/or modify it under the terms of the GPL (either +% version 3 or, at your option, any later version). For further details, +% see the file COPYING or . + +if nargin < 1 + pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..'); +end + +% try PhysIO-internal GitLab examples first +pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); + +% otherwise use public TAPAS examples +if ~isfolder(fullfile(pathExamples, 'BIDS')) + pathExamples = fullfile(pathPhysioPublic, ... + '..', 'examples', tapas_get_current_version(), 'PhysIO'); +end diff --git a/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m b/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m index 4d932985..31630ab2 100644 --- a/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m +++ b/PhysIO/tests/unit/preproc/tapas_physio_filter_cardiac_test.m @@ -29,10 +29,10 @@ function test_philips_ppu7t_filter_cheby2(testCase) %% Compares previously saved Chebychev Type 2 IIR-filtered cropped cardiac % time course with current re-run of same batch from Philips 7T PPU data -% run GE example and extract physio +% Get PhysIO public repo base folder from this file's location pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); pathCurrentExample = fullfile(pathExamples, 'Philips/PPU7T'); cd(pathCurrentExample); % for prepending absolute paths correctly @@ -71,8 +71,7 @@ function test_philips_ppu7t_filter_butter(testCase) % run GE example and extract physio pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); pathCurrentExample = fullfile(pathExamples, 'Philips/PPU7T'); cd(pathCurrentExample); % for prepending absolute paths correctly diff --git a/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m b/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m index 4688a394..3ee96ca2 100644 --- a/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m +++ b/PhysIO/tests/unit/readin/tapas_physio_readin_bids_test.m @@ -31,10 +31,10 @@ % results function test_readin_bids_ppu3t(testCase) -% run BIDS PPU example and extract physio +% Get PhysIO public repo base folder from this file's location pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); + % load SPM matlabbatch, but convert to pure script before executing % remove unnecessary (beyond read-in) part from job exeuction (e.g. @@ -79,8 +79,7 @@ function test_readin_bids_cpulse3t(testCase) % run BIDS cpulse3t example and extract physio pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); % load SPM matlabbatch, but convert to pure script before executing % remove unnecessary (beyond read-in) part from job exeuction (e.g. diff --git a/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m b/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m index 826bffa2..889f3889 100644 --- a/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m +++ b/PhysIO/tests/unit/utils/tapas_physio_findpeaks_test.m @@ -41,8 +41,7 @@ function test_ge_ppu3t_peaks(testCase) % run GE example and extract physio pathPhysioPublic = fullfile(fileparts(mfilename('fullpath')), '..', '..', '..'); -% TODO: Make generic! -pathExamples = fullfile(pathPhysioPublic, '..', 'examples'); +pathExamples = tapas_physio_get_path_examples(pathPhysioPublic); if doUseSpm pathCurrentExample = fullfile(pathExamples, 'GE/PPU3T'); From 4c41db1beaff8271e8ad84c68812c3b1bee96e87 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Mon, 5 Sep 2022 20:24:21 -0400 Subject: [PATCH 19/98] updated tapas_physio_version to R2022b-v8.2.0 --- PhysIO/code/tapas_physio_version.m | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/PhysIO/code/tapas_physio_version.m b/PhysIO/code/tapas_physio_version.m index 512e1d63..beebfd62 100644 --- a/PhysIO/code/tapas_physio_version.m +++ b/PhysIO/code/tapas_physio_version.m @@ -23,4 +23,4 @@ % version 3 or, at your option, any later version). For further details, % see the file COPYING or . % -versionPhysio = 'R2022a-v8.2.0-beta'; +versionPhysio = 'R2022b-v8.2.0'; From 2733c6b350c15b45eacbd51224776c1f8d382dc4 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Wed, 7 Sep 2022 17:45:28 -0400 Subject: [PATCH 20/98] Added tapas_download_example_data suggestion if missing for test --- PhysIO/tests/tapas_physio_get_path_examples.m | 6 ++++++ PhysIO/tests/tapas_physio_test.m | 3 +++ 2 files changed, 9 insertions(+) diff --git a/PhysIO/tests/tapas_physio_get_path_examples.m b/PhysIO/tests/tapas_physio_get_path_examples.m index 2bad4565..5b6aac1e 100644 --- a/PhysIO/tests/tapas_physio_get_path_examples.m +++ b/PhysIO/tests/tapas_physio_get_path_examples.m @@ -37,3 +37,9 @@ pathExamples = fullfile(pathPhysioPublic, ... '..', 'examples', tapas_get_current_version(), 'PhysIO'); end + +% If no examples folder found, suggest to download them via tapas-function +if ~isfolder(fullfile(pathExamples, 'BIDS')) + physio = tapas_physio_new(); + tapas_physio_log('No PhysIO examples data found. Please download via tapas_download_example_data()', physio.verbose, 2); +end diff --git a/PhysIO/tests/tapas_physio_test.m b/PhysIO/tests/tapas_physio_test.m index 2bd0b578..e5a30ffa 100644 --- a/PhysIO/tests/tapas_physio_test.m +++ b/PhysIO/tests/tapas_physio_test.m @@ -45,6 +45,9 @@ testResults = []; +% Returns an error message, if no example data found +tapas_physio_get_path_examples(); + if level >= 0 testResults = [testResults tapas_physio_run_unit_tests()]; else From a708ccc82da62efa5fcf484116f87dcd0456e943 Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Fri, 9 Sep 2022 15:17:20 -0400 Subject: [PATCH 21/98] Check other possible SPM toolbox locations in spm (my) defaults for compatibility with lmod (GitHub issue #211) --- PhysIO/CHANGELOG.md | 6 ++++-- ...s_physio_check_spm_batch_editor_integration.m | 16 ++++++++++++---- 2 files changed, 16 insertions(+), 6 deletions(-) diff --git a/PhysIO/CHANGELOG.md b/PhysIO/CHANGELOG.md index 92cd279d..037f53ad 100644 --- a/PhysIO/CHANGELOG.md +++ b/PhysIO/CHANGELOG.md @@ -6,7 +6,7 @@ Current Release *Current version: PhysIO Toolbox Release R2022b, v8.2.0* -September 5th, 2022 +September 9th, 2022 Minor Release Notes (v8.2.0) ---------------------------- @@ -17,7 +17,9 @@ Minor Release Notes (v8.2.0) - multi ECG/Resp channels and interleaved status messages ### Fixed - Removed dependence on `nanmean` (Statistics Toolbox) - - See GitHub issue #205 and + - See GitHub issue #205 +- Compatibility with multiple SPM toolbox locations for `lmod` ([GitHUb issue #211](https://github.com/translationalneuromodeling/tapas/issues/211)) + - as listed in `spm_get_defaults('tbx')` Minor Release Notes (v8.1.0) ---------------------------- diff --git a/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m b/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m index 642f4ba3..1425914e 100644 --- a/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m +++ b/PhysIO/code/utils/tapas_physio_check_spm_batch_editor_integration.m @@ -32,14 +32,22 @@ [isSpmOnPath, pathSpm] = tapas_physio_check_spm(); -isPhysioVisibleForSpmBatchEditor = isSpmOnPath; % minimum requirement for integration: SPM works! +isPhysioVisibleForSpmBatchEditor = false; % checked below, need SPM visible for that % check for config matlabbatch file if isSpmOnPath - filePhysioCfgMatlabbatch = ... - dir(fullfile(pathSpm, 'toolbox', '**/tapas_physio_cfg_matlabbatch.m')); - isPhysioVisibleForSpmBatchEditor = ~isempty(filePhysioCfgMatlabbatch); + % check all possible SPM toolbox locations, as listed in its defaults: + tbx = spm_get_defaults('tbx'); % SPM toolbox parameter struct + + iDir = 1; + while (iDir <= numel(tbx.dir)) && ~isPhysioVisibleForSpmBatchEditor + filePhysioCfgMatlabbatch = ... + dir(fullfile(tbx.dir{iDir}, '**/tapas_physio_cfg_matlabbatch.m')); + + isPhysioVisibleForSpmBatchEditor = ~isempty(filePhysioCfgMatlabbatch); + iDir = iDir + 1; + end % also important to set default modality of spm to fMRI and % initialize batch editor, if not done before From 6406bbea422c27c18b4e2aec4e3d2c3b53fa001e Mon Sep 17 00:00:00 2001 From: Lars Kasper Date: Sun, 11 Sep 2022 22:07:55 -0400 Subject: [PATCH 22/98] Added Siemens_VB/RESP3T_Logversion_3 integration tests, updated wiki and changelog for R2022b-v8.2.0 --- PhysIO/CHANGELOG.md | 3 +- .../tapas_physio_read_physlogfiles_siemens.m | 2 +- .../readin/tapas_physio_siemens_line2table.m | 4 +- PhysIO/docs/documentation.html | 217 +++++++++--------- PhysIO/docs/documentation.pdf | Bin 1955861 -> 1966717 bytes .../integration/tapas_physio_examples_test.m | 57 ++++- 6 files changed, 166 insertions(+), 117 deletions(-) diff --git a/PhysIO/CHANGELOG.md b/PhysIO/CHANGELOG.md index 037f53ad..0a50c69b 100644 --- a/PhysIO/CHANGELOG.md +++ b/PhysIO/CHANGELOG.md @@ -6,7 +6,7 @@ Current Release *Current version: PhysIO Toolbox Release R2022b, v8.2.0* -September 9th, 2022 +September 12th, 2022 Minor Release Notes (v8.2.0) ---------------------------- @@ -15,6 +15,7 @@ Minor Release Notes (v8.2.0) - Interface `tapas_physio_test` to TAPAS-generic `tapas_test` function - Added suport for logfile version 3 of Siemens physio recordings - multi ECG/Resp channels and interleaved status messages + - new integration test for Siemens VB Logversion 3 ### Fixed - Removed dependence on `nanmean` (Statistics Toolbox) - See GitHub issue #205 diff --git a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m index 5e00df88..2e370de8 100755 --- a/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m +++ b/PhysIO/code/readin/tapas_physio_read_physlogfiles_siemens.m @@ -68,7 +68,7 @@ % used channel depends on cardiac modality switch cardiac_modality case 'ECG' - defaults.ecgChannel = 'mean'; %'mean'; 'v1'; 'v2' + defaults.ecgChannel = 'mean'; %'mean'; 'v1'; 'v2'; 'v3'; 'v4' otherwise defaults.ecgChannel = 'v1'; end diff --git a/PhysIO/code/readin/tapas_physio_siemens_line2table.m b/PhysIO/code/readin/tapas_physio_siemens_line2table.m index 4a72d0fa..a65349e4 100755 --- a/PhysIO/code/readin/tapas_physio_siemens_line2table.m +++ b/PhysIO/code/readin/tapas_physio_siemens_line2table.m @@ -37,9 +37,9 @@ % parsimonious, but it's written in a way to support all different physio % trace modalities and logfile versions (more detail below) -% The ypical logfile structure is as follows (all data in first line of +% The typical logfile structure is as follows (all data in first line of % logfile, the footer is in the next line (after 5003), not used in this -% file, but tapas_physio_read_physlogfiles_siemens_raw)L +% file, but tapas_physio_read_physlogfiles_siemens_raw) % %
      5002 6002 % <[optional] training trace data> 5002 uiHwRevisionPeru ... [optional] 6002 diff --git a/PhysIO/docs/documentation.html b/PhysIO/docs/documentation.html index 393e2bd9..da41aad7 100644 --- a/PhysIO/docs/documentation.html +++ b/PhysIO/docs/documentation.html @@ -827,7 +827,7 @@

      Troubleshoot

      TAPAS PhysIO Toolbox

      Current version: Release 2022b, v8.2.0

      -

      Copyright (C) 2012-2022
      Lars Kasper
      kasper@biomed.ee.ethz.ch

      +

      Copyright (C) 2012-2022
      Lars Kasper
      kasper@biomed.ee.ethz.ch

      Translational Neuromodeling Unit (TNU)
      Institute for Biomedical Engineering
      University of Zurich and ETH Zurich

      Download

      @@ -1523,29 +1523,21 @@

      Example Datasets for PhysIO

      The following datasets are available to explore the read-in and modeling capabilities of PhysIO. They can be downloaded by running the function tapas_download_example_data() in Matlab, which is located in the misc subfolder of the TAPAS software release you downloaded (probably here).

      Afterwards, the examples can be found in tapas/examples/<tapasVersion>/PhysIO as different subfolders (vendor/device) and shall be run directly from within these individual folders.

      -

      Besides the raw physiological logfiles, each example contains example scripts to run PhysIO as

      +

      Besides the raw physiological logfiles, each example contains example scripts to run PhysIO as

        -
      • SPM job (*spm_job.mat)
        • -
      • editable SPM job (*spm_job.m)
        • -
      • plain matlab script (*matlab_script.m)
        • +
      • SPM job (\\\*spm_job.mat)
        • +
      • editable SPM job (\\\*spm_job.m)
        • +
      • plain matlab script (\\\*matlab_script.m)

      Brain Imaging Data Structure (BIDS)

      CPULSE 3T

      -

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry -and Ageing Research, University College London

      -

      Vendor-computed (software: Spike2) cardiac pulse events from PPU (finger -plethysmograph) data, Siemens 3T scanner, Multiband CMRR sequence

      -

      Description: This datasets contains the (compressed) tab-separated value -(.tsv.gz) files as well as the meta-file (.json) holding sampling rate of -the physiological recording, and its relative onset to scanning, in adherence -with the BIDS standard for peripheral recordings -files.

      +

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London

      +

      Vendor-computed (software: Spike2) cardiac pulse events from PPU (finger plethysmograph) data, Siemens 3T scanner, Multiband CMRR sequence

      +

      Description: This datasets contains the (compressed) tab-separated value (.tsv.gz) files as well as the meta-file (.json) holding sampling rate of the physiological recording, and its relative onset to scanning, in adherence with the BIDS standard for peripheral recordings files.

      PPU 3T

      -

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry -and Ageing Research, University College London

      +

      Courtesy of Hrvoje Stojic, Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London

      PPU (finger plethysmograph) and breathing belt, Siemens 3T scanner, Multiband CMRR sequence

      -

      Description: Similar to CPULSE3T (same acquisition system), but now with analog -data instead of vendor-detected pulses, data from different subject

      +

      Description: Similar to CPULSE3T (same acquisition system), but now with analog data instead of vendor-detected pulses, data from different subject

      PPU 3T Separate Files

      Courtesy of Alexandre Sayal CIBIT, University of Coimbra

      PPU (finger plethysmograph) and breathing belt, Siemens 3T scanner, Multiband CMRR sequence

      @@ -1553,70 +1545,67 @@

      PPU 3T Separate Files

      General Electric

      PPU 3T

      Courtesy of Steffen Bollmann, Kinderspital Zurich and ETH Zurich

      -

      PPU (finger plethysmograph) and breathing belt, General Electric 3T -scanner

      -

      Description: Similar to PPU, but acquired on a GE system with two -separate output logfiles for pulse oximetry and breathing amplitude, -sampled with 40 Hz. The quality of the signal is particularly -challenging, stemming from a patient population.

      +

      PPU (finger plethysmograph) and breathing belt, General Electric 3T scanner

      +

      Description: Similar to PPU, but acquired on a GE system with two separate output logfiles for pulse oximetry and breathing amplitude, sampled with 40 Hz. The quality of the signal is particularly challenging, stemming from a patient population.

      Philips

      ECG 3T

      -

      Courtesy of Sandra Iglesias, Translational Neuromodeling Unit, ETH & -University of Zurich

      +

      Courtesy of Sandra Iglesias, Translational Neuromodeling Unit, ETH & University of Zurich

      4-electrode ECG and breathing belt, Philips 3T Achieva scanner

      -

      Description: Standard example; shows how to use volume counting either -from beginning or end of run to synchronize physiological logfile with -acquisition onsets of fMRI scans.

      +

      Description: Standard example; shows how to use volume counting either from beginning or end of run to synchronize physiological logfile with acquisition onsets of fMRI scans.

      ECG 7T

      Courtesy of Zina-Mary Manjaly, University Hospital Zurich

      4-electrode ECG and breathing belt, Philips 7T Achieva scanner

      -

      Description: The ECG data for ultra-high field data is typically much -noisier than at 3 Tesla. Therefore, R-wave peaks are frequently missed -by prospective trigger detection and not marked correctly in the -logfile. This example shows how to select typical R-wave-peaks manually -and let the algorithm find the heartbeat events.

      +

      Description: The ECG data for ultra-high field data is typically much noisier than at 3 Tesla. Therefore, R-wave peaks are frequently missed by prospective trigger detection and not marked correctly in the logfile. This example shows how to select typical R-wave-peaks manually and let the algorithm find the heartbeat events.

      PPU 3T

      Courtesy of Diana Wotruba, University and University Hospital of Zurich

      -

      PPU (finger plethysmograph) and breathing belt, Philips 3T Achieva -scanner

      -

      Description: Similar to ECG3T, but a plethysmograph instead of an ECG -was used to monitor the cardiac pulsation. Example shows how to extract -heart and breathing rate.

      +

      PPU (finger plethysmograph) and breathing belt, Philips 3T Achieva scanner

      +

      Description: Similar to ECG3T, but a plethysmograph instead of an ECG was used to monitor the cardiac pulsation. Example shows how to extract heart and breathing rate.

      PPU 7T

      Courtesy of Jakob Heinzle and Lars Kasper, TNU, University Zurich and ETH Zurich

      -

      PPU (finger plethysmograph) and breathing belt, Philips 7T Achieva -scanner

      +

      PPU (finger plethysmograph) and breathing belt, Philips 7T Achieva scanner

      Description: Challenging cardiac data that requires bandpass-filtering during preprocessing, since it is compromised by both high frequency noise (from the scanner, modulated at every slice TR) and low frequency noise (breathing modulation).

      Siemens - VB

      Siemens has different physiological logfile formats, for which examples are provided here. A detailed description of these formats is on a different wiki page.

      -

      This is the older Siemens log file format (also available via manual recording), which is part of software release VB, and can be determined by the file extensions .resp, .ecg, .puls, in combination with an optional .dcm DICOM header file for the first (or last) acquired volume.

      -

      A lot of 7T scanners still use this format.

      +

      This is the older Siemens log file format (also available via manual recording), which is part of software release _VB_, and can be determined by the file extensions .resp, .ecg, .puls, in combination with an optional .dcm DICOM header file for the first (or last) acquired volume.

      +

      A lot of 7T scanners still use this format, but it is also the default on modern 3T systems, if you don't have C2P sequences for fMRI (e.g., from CMRR) or WIPs from Siemens (see below).

      ECG 3T

      Courtesy of Miriam Sebold, Charite Berlin, and Quentin Huys, TNU Zurich

      -

      4-electrode ECG data, Siemens 3T scanner

      +

      4-electrode ECG data, Siemens 3T scanner, logfile version 1

      Description: Similar to ECG 3T, but acquired on a Siemens system with only one logfile for ECG data. The quality of the signal is challenging, stemming from a patient population.

      PPU3T (Sync First and Sync Last)

      Courtesy of Alexander Ritter, University of Jena, Germany

      -

      Siemens 3T pulse oximetry and respiratory bellows data from a complete scan session of a healthy volunteer, plus the DICOM header file of the first and last (382nd) volume of an fMRI run, respectively.

      -

      This showcases scan timing synchronization using the DICOM timestamps in an intricate case, where the physiological logfile spans the whole scan session (and not only the fMRI run). See TAPAS github issue #55 for further details.

      +

      Siemens 3T pulse oximetry and respiratory bellows data, logfile version 1 DICOM header file of first and last (382nd) volume of an fMRI run, respectively.

      +

      Description: This data covering a complete scan session of a healthy volunteer showcases scan timing synchronization using the DICOM timestamps in an intricate case, where the physiological logfile spans the whole scan session (and not only the fMRI run). See TAPAS github issue #55 for further details.

      +

      ECG 3T - Logversion 3

      +

      Courtesy of Shahin Safa, see TAPAS GitHub issue 204

      +

      4-electrode ECG data, Siemens scanner, logfile version 3 corresponding respiratory data: Resp 3T - Logversion 1

      +

      Description: This is an fMRI study on the auditory system of the brain, which explains the long TR (10 s), to put scanning gaps when presenting the sound to the subject.

      +

      Resp 3T - Logversion 1

      +

      Courtesy of Shahin Safa, see TAPAS GitHub issue 204

      +

      Respiratory bellows data, Siemens scanner, logfile version 1 corresponding cardiac data: ECG 3T - Logversion 3

      +

      Description: This is an fMRI study on the auditory system of the brain, which explains the long TR (10 s), to put scanning gaps when presenting the sound to the subject.

      +

      Resp 3T - Logversion 3

      +

      Courtesy of Lars Kasper, University Health Network Toronto, Canada

      +

      Respiratory bellows data, Siemens Prisma 3T, logfile version 3

      +

      Description: Short fingertapping run with logging automatically switched off after about 2 minutes (nominally 5) due to ECG channels not connected, but requested for recording. Biomatrix sensors were not available, but are logged as 4 extra channels with constant values here.

      Siemens - HCP

      -

      The Human Connectome Project uses Siemens scanners, and the logfile format that comes with their published data seems to be pre-converted and custom (even though the documentation desribes the VB format). We have implemented an own reader for that and written a little tutorial for a single subject dataset of the HCP.

      +

      The Human Connectome Project uses Siemens scanners, and the logfile format that comes with their published data seems to be pre-converted and custom (even though the documentation desribes the VB format). We have implemented an own reader for that and written a little tutorial for a single subject dataset of the HCP.

      https://github.com/translationalneuromodeling/tapas/issues/6#issuecomment-361001716

      If you download the whole dataset (including functional image files), this example with the additional batches mentioned below also demonstrates how to use the toolbox for model assessment using statistical maps (F-contrasts).

      HCP (Subject 178748)

      You will have to download the dataset from the HCP yourself, we just provide the matlab batches and the physiological logfile tfMRI_MOTOR_LR_Physio_log.txt here.

      For consistency with the other example files, the batch files have been renamed compared to the blog entry:

        -
      • batch_preproc.m -> batch_preproc.m
        • -
      • batch_physio.m -> siemens_hcp_ppu3t_spm_job.m
        • -
      • batch_glm.m -> batch_glm.m
        • +
      • batch_preproc.m -> batch_preproc.m
        • +
      • batch_physio.m -> siemens_hcp_ppu3t_spm_job.m
        • +
      • batch_glm.m -> batch_glm.m

      If you want to run the preproc and glm batch, place them on the same level as the subject folder 178748 for the downloaded data. The physio-batch shall reside in the same folder as the physiological logfile tfMRI_MOTOR_LR_Physio_log.txt.

      Siemens - VD/VE Tics

      -

      This is the most recent logfile format of Siemens, included in Software releases VD, VE and sometimes referred to as the Tics format, because all time stamps in all files refer to the same reference point (start of the day) and count in the same intervals or "tics" of 2.5 ms from there.

      -

      You will recognize this file format via the extensions _Info.log (or _AcquisitionInfo.log), _RESP.log, _ECG.log and _PULS.log. Sometimes, it is also written into the DICOM header (.dcm) file of your functional data directly. In this case, use extractCMRRPhysio.m to convert it to the above separate files before using PhysIO.

      +

      This is the most recent logfile format of Siemens, included in Software releases _VD_, _VE_ and sometimes referred to as the Tics format, because all time stamps in all files refer to the same reference point (start of the day) and count in the same intervals or "tics" of 2.5 ms from there.

      +

      You will recognize this file format via the extensions \\\_Info.log (or \\\_AcquisitionInfo.log), \\\_RESP.log, \\\_ECG.log and \\\_PULS.log. Sometimes, it is also written into the DICOM header (.dcm) file of your functional data directly. In this case, use extractCMRRPhysio.m to convert it to the above separate files before using PhysIO.

      Most modern Siemens scanners, such as the Prisma or 7T Terra, use this format.

      -

      There are a couple of variants for this format around (e.g., with the WIP Multiband Protocol that is distributed to multiple sites), and PhysIO tries to support all of them.

      +

      There are a couple of variants for this format around (e.g., with the WIP Multiband Protocol that is distributed to multiple sites), and PhysIO tries to support all of them.

      PPU 3T

      Courtesy of Saskia Bollmann, Centre for Advanced Imaging, University of Queensland, Brisbane, Australia

      Pulse oximetry and breathing belt data, Siemens Prisma 3T, logfile version EJA_1, multi-echo fMRI (3 echoes)

      @@ -1624,46 +1613,41 @@

      PPU 3T

      PPU 3T Separate Files

      Courtesy of Alexandre Sayal CIBIT, University of Coimbra

      PPU (finger plethysmograph) and breathing belt, Siemens 3T scanner, Multiband CMRR sequence

      -

      Description: Raw data that was used to convert to two separate BIDS files above (BIDS/PPU3T_Separate_Files) for cardiac and respiratory recordings, because of differing sampling rate (5 vs 20 ms).

      +

      Description: Raw data that was used to convert to two separate BIDS files above (BIDS/PPU3T_Separate_Files) for cardiac and respiratory recordings, because of differing sampling rate (5 vs 20 ms).

      The UUID and date/time stamps were altered for anonymization.

      Technical Documentation: Read-in

      Brain Imaging Data Structure (BIDS)

      PhysIO supports physiological logfiles prepared according to the BIDS standard

        -
      • In brief, BIDS files are (optionally compressed) tab-separated values -(*.tsv[.gz]) files that contain raw traces of peripheral recordings from -cardiac and respiratory sources, as well as scan trigger events
        • -
      • The header of the columns of this *.tsv file, as well as meta-information, -such as sampling rate and relative onset of physiological logging to MRI scan -onset is described in an accompanying *.json file
          -
        • It is assumed to have the that this *.json file has the same name -(apart from the extension) as the *.tsv file
          • -
        • If PhysIO does not find this file, you can manually enter the timing -information in the log_files structure, and a default column order of -(cardiac, respiratory, trigger) is assumed
          • -
        -
        • -
      • Example *.tsv file (with cardiac, respiratory, trigger column -:
                                   -0.949402 -0.00610382 0
-                           -0.949402 -0.00610382 0
-                           -0.951233 -0.00915558 0
-                           -0.951233 -0.00915558 0
-                           -0.953064 -0.0122073  0
-                           -0.953064 -0.0122073  0
-                           -0.95459  -0.0076297  1
-                           -0.95459  -0.0076297  0
        • -
      • Example *.json file:
        {
-  "SamplingFrequency": 50.0, 
-  "Columns": [
-      "cardiac", 
-      "respiratory", 
-      "trigger"
-  ], 
-  "StartTime": -255.45
-}
        • +
      • In brief, BIDS files are (optionally compressed) tab-separated values (\*.tsv\[.gz\]) files that contain raw traces of peripheral recordings from cardiac and respiratory sources, as well as scan trigger events
        • +
      • The header of the columns of this \*.tsv file, as well as meta-information, such as sampling rate and relative onset of physiological logging to MRI scan onset is described in an accompanying \*.json file
          +
        • It is assumed to have the that this \*.json file has the same name (apart from the extension) as the \*.tsv file
          • +
        • If PhysIO does not find this file, you can manually enter the timing information in the log_files structure, and a default column order of (cardiac, respiratory, trigger) is assumed
          • +
        +
        • +
      • Example \*.tsv file (with cardiac, respiratory, trigger column :
        • +
      +
                                   -0.949402 -0.00610382 0
+                             -0.949402 -0.00610382 0
+                             -0.951233 -0.00915558 0
+                             -0.951233 -0.00915558 0
+                             -0.953064 -0.0122073  0
+                             -0.953064 -0.0122073  0
+                             -0.95459  -0.0076297  1
+                             -0.95459  -0.0076297  0
        +
      • Example \*.json file:
        • +
      +
      {
+    "SamplingFrequency": 50.0, 
+    "Columns": [
+        "cardiac", 
+        "respiratory", 
+        "trigger"
+    ], 
+    "StartTime": -255.45
+}
      • Note that StartTime refers to when the physiological recording started relative to the first scan volume of the fMRI run, which means that typically this value is negative, because one starts the recording before the onset of scan volumes.
        • -
      • See tapas_physio_read_physlogfiles_bids.m for more details and technical -documentation.
        • +
      • See tapas_physio_read_physlogfiles_bids.m for more details and technical documentation.

      BioPac

      Mat-file Export (.mat)

      @@ -1685,13 +1669,12 @@

      Single Text File Export (.txt

    • Export your traces from cardiac and breathing recording devices into 2 text files and select log_files.vendor = 'Custom'. The format is explained in tapas_physio_new or the help window of the Batch Editor:

      • 'Custom' expects the logfiles (separate files for cardiac and respiratory) to be plain text, with one cardiac (or respiratory) sample per row;
        • -

      • If heartbeat (R-wave peak) events are recorded as well, they have to be put as a 2nd column in the cardiac logfile by specifying a 1; 0 in all other rows, e.g.

        +
      • If heartbeat (R-wave peak) events are recorded as well, they have to be put as a 2nd column in the cardiac logfile by specifying a 1; 0 in all other rows, e.g.
        • +
      0.2  0
 0.4  1 <- cardiac pulse event
 0.2  0
 -0.3 0
      • -

    -
  • You have to specify the sampling intervals for these log files (in seconds), via log_files.sampling_interval, e.g. [0.01 0.02] if you have 10 ms (100 Hz) and 20 ms (50 Hz) sampling intervals (frequencies) for cardiac and respiratory data, respectively
  • You will probably have to change log_files.relative_start_acquisition, if logging of your physiological recording device does not start synchronized to the first fMRI volume.
    • @@ -1699,17 +1682,19 @@

    General Electric (GE)

    • Very similar to custom format
    • One text file each for ECG, pulse oximetry and respiratory data, e.g., ECGData_epiRT_phys_0921201215_38_08 or RespData_epiRT_phys_0921201215_38_08
      • -
    • One amplitude entry per line, e.g.,
      2626
-2649
-2673
-2699
-2727
-2755
      • +
    • One amplitude entry per line, e.g.,
      • +
    +
     2626
+ 2649
+ 2673
+ 2699
+ 2727
+ 2755
    • sampling rate is determined as a setting beforehand, has to be noted manually (not in log file)

    Philips