Dateien hochladen nach 'code_MATLAB'

code_MATLAB/Load_Data_Example_Script.m

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+%% Add nix to path
+% Path for the folder 'nix-mx_Win64_1.4.1'
+addpath('nix-mx_Win64_1.4.1\')
+
+%% Open NIX file
+% Path of the selected file
+file_path = 'Data_Subject_01_Session_01.h5';
+f = nix.File(file_path,nix.FileMode.ReadOnly);
+
+%% Read metadata 
+% Display names of all sections
+cellfun(@(x) disp(x.name),f.sections)
+
+%% General information
+sectionGeneral = f.openSection('General');
+% Properties
+cellfun(@(x) disp(x.name),sectionGeneral.properties)
+% Institution
+fprintf(['Institution: ',sectionGeneral.openProperty('Institution').values{1}.value,'\n'])
+% Recording location
+fprintf(['Recording location: ',sectionGeneral.openProperty('Recording location').values{1}.value,'\n'])
+% Sections
+cellfun(@(x) disp(x.name),sectionGeneral.sections)
+% Publications
+sectionPublications = sectionGeneral.openSection('Related publications');
+cellfun(@(x) disp(x.name),sectionPublications.properties)
+fprintf(['Publication name: ',sectionPublications.openProperty('Publication name').values{1}.value,'\n'])
+fprintf(['Publication DOI: ',sectionPublications.openProperty('Publication DOI').values{1}.value,'\n'])
+% Recording setup
+sectionRecordingSetup = sectionGeneral.openSection('Recording setup');
+cellfun(@(x) disp(x.name),sectionRecordingSetup.properties)
+fprintf(['Recording setup iEEG: ',sectionRecordingSetup.openProperty('Recording setup iEEG').values{1}.value,'\n'])
+fprintf(['Recording setup EEG: ',sectionRecordingSetup.openProperty('Recording setup EEG').values{1}.value,'\n'])
+
+%% Task information
+sectionTask = f.openSection('Task');
+% Properties
+cellfun(@(x) disp(x.name),sectionTask.properties)
+% Task characteristics
+fprintf(['Task name: ',sectionTask.openProperty('Task name').values{1}.value,'\n'])
+fprintf(['Task description: ',sectionTask.openProperty('Task description').values{1}.value,'\n'])
+fprintf(['Task URL: ',sectionTask.openProperty('Task URL').values{1}.value,'\n'])
+
+%% Subject information
+sectionSubject = f.openSection('Subject');
+% Properties
+cellfun(@(x) disp(x.name),sectionSubject.properties)
+% Subject characteristics
+fprintf(['Age: ',num2str(sectionSubject.openProperty('Age').values{1}.value),'\n'])
+fprintf(['Sex: ',sectionSubject.openProperty('Sex').values{1}.value,'\n'])
+fprintf(['Handedness: ',sectionSubject.openProperty('Handedness').values{1}.value,'\n'])
+fprintf(['Pathology: ',sectionSubject.openProperty('Pathology').values{1}.value,'\n'])
+fprintf(['Depth electrodes: ',sectionSubject.openProperty('Depth electrodes').values{1}.value,'\n'])
+fprintf(['Electrodes in seizure onset zone (SOZ): ',sectionSubject.openProperty('Electrodes in seizure onset zone (SOZ)').values{1}.value,'\n'])
+
+%% Session information
+sectionSession = f.openSection('Session');
+% Properties
+cellfun(@(x) disp(x.name),sectionSession.properties)
+% Session characteristics
+fprintf(['Number of trials: ',num2str(sectionSession.openProperty('Number of trials').values{1}.value),'\n'])
+fprintf(['Trial duration: ',num2str(sectionSession.openProperty('Trial duration').values{1}.value),' ',sectionSession.openProperty('Trial duration').unit,'\n'])
+% Sections
+cellfun(@(x) disp(x.name),sectionSession.sections)
+
+%% Trial information
+sectionTrialProperties = sectionSession.openSection('Trial properties');
+% Sections
+cellfun(@(x) disp(x.name),sectionTrialProperties.sections)
+% Each section is for a single trial
+% Select trial
+nTrial = 1;
+sectionSingleTrial = sectionTrialProperties.sections{nTrial};
+
+%% Single trial
+% Properties
+cellfun(@(x) disp(x.name),sectionSingleTrial.properties)
+for nProperty = 1:length(sectionSingleTrial.properties)
+    switch sectionSingleTrial.properties{nProperty}.datatype
+        case {'double','logical'}
+            fprintf([sectionSingleTrial.properties{nProperty}.name,': ',num2str(sectionSingleTrial.properties{nProperty}.values{1}.value),'\n'])
+        otherwise
+    fprintf([sectionSingleTrial.properties{nProperty}.name,': ',sectionSingleTrial.properties{nProperty}.values{1}.value,'\n'])
+    end
+end
+
+%% Blocks
+cellfun(@(x) disp(x.name),f.blocks)
+block = f.blocks{1};
+
+%% Groups of data arrays, tags, multitags
+groups = block.groups;
+cellfun(@(x) disp(x.name),block.groups)
+
+%% Select trial
+nTrial = 1;
+
+%% iEEG data
+group_iEEG = block.openGroup('iEEG data');
+% Data array
+dataArray_iEEG = group_iEEG.dataArrays{nTrial};
+
+% Electrode labels
+striEEGLabels = dataArray_iEEG.dimensions{1}.labels;
+% Time axis
+tiEEG = (0:(double(dataArray_iEEG.dataExtent(2))-1))*dataArray_iEEG.dimensions{2}.samplingInterval+dataArray_iEEG.dimensions{2}.offset;
+% Read data
+data_iEEG = dataArray_iEEG.readAllData;
+
+% Plot trial data
+figure
+plot(tiEEG,data_iEEG)
+title(['iEEG data - Trial ',num2str(nTrial)])
+xlabel(['Time (',dataArray_iEEG.dimensions{2}.unit,')'])
+ylabel(['Voltage (',dataArray_iEEG.unit,')'])
+legend(striEEGLabels)
+
+%% Scalp EEG data
+group_ScalpEEG = block.openGroup('Scalp EEG data');
+% Data array
+dataArray_ScalpEEG = group_ScalpEEG.dataArrays{nTrial};
+
+% Electrode labels
+strScalpEEGLabels = dataArray_ScalpEEG.dimensions{1}.labels;
+% Time axis
+tScalpEEG = (0:(double(dataArray_ScalpEEG.dataExtent(2))-1))*dataArray_ScalpEEG.dimensions{2}.samplingInterval+dataArray_ScalpEEG.dimensions{2}.offset;
+% Read data
+data_ScalpEEG = dataArray_ScalpEEG.readAllData;
+
+% Plot trial data
+figure
+plot(tScalpEEG,data_ScalpEEG)
+title(['Scalp data - Trial ',num2str(nTrial)])
+xlabel(['Time (',dataArray_ScalpEEG.dimensions{2}.unit,')'])
+ylabel(['Voltage (',dataArray_ScalpEEG.unit,')'])
+legend(strScalpEEGLabels)
+
+%% Trial events
+group_TrialEvents_iEEG = block.openGroup('Trial events single tags iEEG');
+group_TrialEvents_ScalpEEG = block.openGroup('Trial events single tags scalp EEG');
+
+%% Trial events for a single trial
+indTrialTags_iEEG = contains(cellfun(@(x) x.name,group_TrialEvents_iEEG.tags,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
+indTrialTags_ScalpEEG = contains(cellfun(@(x) x.name,group_TrialEvents_ScalpEEG.tags,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
+
+TrialEvents_iEEG = group_TrialEvents_iEEG.tags(indTrialTags_iEEG);
+TrialEvents_ScalpEEG = group_TrialEvents_iEEG.tags(indTrialTags_ScalpEEG);
+
+cellfun(@(x) disp(x.name),TrialEvents_iEEG)
+cellfun(@(x) disp(x.name),TrialEvents_ScalpEEG)
+
+%% Time of a single event 
+nEvent = 3; % Maintenance
+fprintf(['Event name: ',TrialEvents_iEEG{nEvent}.name,'\n'])
+fprintf([sprintf('Time w.r.t. fixation: %.1f %s',TrialEvents_iEEG{nEvent}.position(2),TrialEvents_iEEG{nEvent}.units{1}),'\n'])
+fprintf([sprintf('Duration: %.1f %s',TrialEvents_iEEG{nEvent}.extent(2),TrialEvents_iEEG{nEvent}.units{1}),'\n'])
+% The values are the same for TrialEvents_ScalpEEG
+
+%% Units
+group_SpikeTimes = block.openGroup('Spike times');
+
+%% Select unit and trial
+nUnit = 1;
+nTrial = 5;
+indUnitSpikeTimes = contains(cellfun(@(x) x.name,group_SpikeTimes.dataArrays,'UniformOutput',0),['Unit_',num2str(nUnit),'_'])&...
+    contains(cellfun(@(x) x.name,group_SpikeTimes.dataArrays,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
+
+dataArray_SpikeTimes = group_SpikeTimes.dataArrays{indUnitSpikeTimes};
+% Read data
+SpikeTimes = dataArray_SpikeTimes.readAllData;
+
+figure
+stem(dataArray_SpikeTimes.readAllData,ones(length(SpikeTimes),1))
+title(['Spike times - Unit ',num2str(nUnit),' - Trial ',num2str(nTrial)])
+xlabel(['Time (',dataArray_SpikeTimes.dimensions{1}.unit,')'])
+
+%% Multitag for the unit
+indMultiTagUnitSpikeTimes = contains(cellfun(@(x) x.name,block.multiTags,'UniformOutput',0),['Unit_',num2str(nUnit),'_'])&...
+    contains(cellfun(@(x) x.name,block.multiTags,'UniformOutput',0),['Trial_',num2str(nTrial,'%.2d')]);
+
+multiTag_SpikeTimes = block.multiTags{indMultiTagUnitSpikeTimes};
+
+%% Waveform for the unit
+dataArray_Waveform = multiTag_SpikeTimes.features{1}.openData;
+% Time axis
+tWaveform = (0:(double(dataArray_Waveform.dataExtent(2))-1))*dataArray_Waveform.dimensions{2}.samplingInterval+dataArray_Waveform.dimensions{2}.offset;
+% Read data
+waveform = dataArray_Waveform.readAllData;
+% Plot
+figure
+plot(tWaveform,waveform(1,:),'b')
+hold on
+plot(tWaveform,waveform(1,:)+waveform(2,:),'b--')
+plot(tWaveform,waveform(1,:)-waveform(2,:),'b--')
+title(['Waveform - Unit',num2str(nUnit)])
+xlabel(['Time (',dataArray_Waveform.dimensions{2}.unit,')'])
+ylabel(['Voltage (',dataArray_Waveform.unit,')'])
+legend({'Mean','Std'})
+
+%% Source of the unit
+sourceUnit = dataArray_SpikeTimes.sources{1};
+% Electrode label
+sourceUnit.sources{1}.name
+% Anatomical location
+sourceUnit.sources{2}.name
+
+%% Use electrode map to get properties of the macroelectrode the unit is on
+groupiEEGElecrodes = block.openGroup('iEEG electrode information');
+ 
+nElectrode = find(strcmpi(cellfun(@(x) x.name,groupiEEGElecrodes.sources,'UniformOutput',0),sourceUnit.name));
+
+% MNI coordinates of the electrode
+groupiEEGElecrodes.multiTags{1}.retrieveFeatureData(nElectrode,'iEEG_Electrode_MNI_Coordinates')
+% Was the anatomical location manually entered?
+groupiEEGElecrodes.multiTags{1}.retrieveFeatureData(nElectrode,'iEEG_Electrode_Manual_Entry')
+