Post on 19-Dec-2015
NEMO ERP Analysis ToolkitERP Pattern Segmentation
An Overview
NEMO Information Processing Pipeline
NEMO Information Processing PipelinePattern Decomposition Component
NEMO Information Processing PipelineERP Pattern Segmentation, Identification and Labeling
Obtain ERP data sets with compatible functional constraints– NEMO consortium data
Decompose / segment ERP data into discrete spatio-temporal patterns– ERP Pattern Decomposition / ERP Pattern Segmentation
Mark-up patterns with their spatial, temporal & functional characteristics– ERP Metric Extraction
Meta-Analysis Extracted ERP pattern labeling
Extracted ERP pattern clustering
Protocol incorporates and integrates: ERP pattern extraction
ERP metric extraction/RDF generation
NEMO Data Base (NEMO Portal / NEMO FTP Server)
NEMO Knowledge Base (NEMO Ontology/Query Engine)
ERP Pattern Segmentation ToolMATLAB and Directory Configuration
Get Latest Toolkit Version (NEMO Wiki : Screencasts : Versions)
– Update your local (working) copy of the NEMO Sourceforge Repository
Configure MATLAB (NEMO Wiki : Screencasts : NEMO ERP Analysis Toolkit I)
– MATLAB R2010a / R2010b, Optimization and Statistics Toolboxes
– Add to the MATLAB path, with subfolders: NEMO_ERP_Dataset_Import / NEMO_ERP_Dataset_Information
NEMO_ERP_Metric_Extraction / NEMO_ERP_Pattern_Decomposition / NEMO_ERP_Pattern_Segmentation
Configure Experiment Folder (NEMO Wiki : Screencasts : NEMO ERP Analysis Toolkit I & II)
– Create an experiment-specific parent folder containing Data, Metric Extraction, Pattern
Decomposition and Pattern Segmentation subfolders
– Copy the metric extraction, decomposition and segmentation script templates from your NEMO
Sourceforge Repository working copy to their respective script subfolders
– Add the experiment-specific parent folder, with its subfolders, to the MATLAB path
File_Name
Electrode_Montage_ID
Cell_Index
Factor_Index
ERP_Onset_Latency
ERP_Offset_Latency
ERP_Baseline_Latency
ERP Pattern Segmentation ToolMetascript Configuration – Step 1 of 6: Data Parameters
File_Name
– Name of an EGI segmented simple binary file, as a single-quoted string Example: ‘SimErpData.raw’
At present, Metric Extraction only accepts factor files from the Pattern Decomposition tool
Electrode_Montage_ID
– Name of an EGI/Biosemi electrode montage file, as a single-quoted string Valid montage strings: ‘GSN-128’, ‘GSN-256’, ‘HCGSN-128’, ‘HCGSN-256’, ‘Biosemi-64+5exg’, ‘Biosemi-64-
sansNZ_LPA_RPA’
The NEMO ERP Analysis Toolkit will require EEGLAB channel location file (.ced) format for all proprietary,
user-specified, montages
Cell_Index
– Indices of cells / conditions to import, as a MATLAB vector Indices correspond to the ordering of cells in the data file
See Metric_obj.Dataset.Metadata.SrcFileInfo.Cellcode for the ordered list of conditions
Factor_Index
– Indices of PCA factors to import, as a MATLAB vector Indices correspond to the ordering of factors in the data file
ERP Pattern Segmentation ToolMetascript Configuration – Step 1 of 6: Data Parameters
ERP_Onset_Latency– Time, in milliseconds, of the first ERP sample point to import, as a MATLAB scalar
0 ms = stimulus onset
Positive values specify post-stimulus time points, negative values pre-stimulus time points
All latencies must be in integer multiples of the sampling interval (for example, +’ve / -’ve multiples of 4 ms @ 250
Hz)
ERP_Offset_Latency– Time, in milliseconds, of the last ERP sample point to import, as a MATLAB scalar
0 ms = stimulus onset
Positive values specify post-stimulus time points, and must be greater than the ERP_Onset_Latency
ERP_Offset_Latency must not exceed the final data sample point (for example, a 1000 ms ERP with a 200 ms
baseline: maximum 800 ms ERP_Offset_Latency)
ERP_Baseline_Latency– Time, in negative milliseconds, of the pre-stimulus ERP sample points to exclude from import, as a MATLAB
scalar ERP_Baseline_Latency = 0 no baseline
To import pre-stimulus sample points, specify ERP_Baseline_Latency < ERP_Onset_Latency < 0
All latencies must be within the data range (for example, a 1000 ms ERP with a 200 ms baseline:
ERP_Baseline_Latency = -200 ms, ERP_Onset_Latency = 0 ms and ERP_Offset_Latency = 800 ms imports the 800
ms post-stimulus interval, including stimulus onset)
ERP Pattern Segmentation ToolMetascript Configuration – Step 1 of 6: Data Parameters
ERP Pattern Segmentation ToolMetascript Configuration – Step 2 of 6: Experiment Parameters (Required)
Lab_ID
Experiment_ID
Session_ID
Subject_Group_ID
Subject_ID
Experiment_Info
ERP Pattern Segmentation ToolMetascript Configuration – Step 2 of 6: Experiment Parameters (Required)
Lab_ID– Laboratory identification label, as a single-quoted string
Example: ‘My Simulated Lab’
Experiment_ID– Experiment identification label, as a single-quoted string
Example: ‘My Simulated Experiment’
Session_ID– Session identification label, as a single-quoted string
Example: ‘My Simulated Session’
Subject_Group_ID– Subject group identification label, as a single-quoted string
Example: ‘My Simulated Subject Group’
Subject_ID– Subject identification label, as a single-quoted string
Example: ‘My Simulated Subject # 1’
Experiment_Info– Experiment note, as a single-quoted string
Example: ‘tPCA with Infomax rotation’
ERP Pattern Segmentation ToolMetascript Configuration – Step 3 of 6: Experiment Parameters (Optional)
Event_Type_Label
Stimulus_Type_Label
Stimulus_Modality_Label
Cell_Label_Descriptor
ERP Pattern Segmentation ToolMetascript Configuration – Step 3 of 6: Experiment Parameters (Optional)
Event_Type_Label– MATLAB cell array of cell/condition event type labels
One label per cell/condition, as a single-quoted string
Example: {‘SimEventType1’, ‘SimEventType2’, ‘SimEventType3’}
Stimulus_Type_Label– MATLAB cell array of cell/condition stimulus type labels
One label per cell/condition, as a single-quoted string
Example: {‘SimStimulusType1’, ‘SimStimulusType2’, ‘SimStimulusType3’}
Stimulus_Modality_Label– MATLAB cell array of cell/condition stimulus modality labels
One label per cell/condition, as a single-quoted string
Example: {‘SimStimulusModality1’, ‘SimStimulusModality2’, ‘SimStimulusModality3’}
Cell_Label_Descriptor– MATLAB cell array of cell/condition description labels
One label per cell/condition, as a single-quoted string
Optional Labels: E-prime assigned cell codes imported from input data file
Example: {‘SimConditionDescription1’, ‘SimConditionDescription2’, ‘SimConditionDescription3’}
ERP Pattern Segmentation ToolMetascript Configuration – Step 4 of 6: Pattern Segmentation Parameters
Dimension_Flag
Averaging_Protocol
Microstate_Algorithm
Minimum_Microstate - _Duration
Maximum_Transition - _Duration
ERP Pattern Segmentation ToolMetascript Configuration – Step 4 of 6: Pattern Segmentation Parameters
Dimension_Flag– Specifies dimensionality of the coordinate space containing the +’ve / -’ve potential centroids, as a MATLAB
scalar Potential centroids are the locations of the centers of scalp-recorded positvity / negativity
Dimension_Flag = 2: Potential centroids are locations in 2D scalp “flat-map” space
Dimension_Flag = 3: Potential centroids are locations in 3D “head-volume” space
Averaging_Protocol– Specifies averaging precedence w.r.t. microstate boundary probability curve extraction, as a single-quoted
string
‘ExtractThanAverage’: Extract subject-specific microstate boundary probability curves, then average across
subjects within each cell
‘AverageThanExtract’: Average ERPs across subjects within each cell, then extract grand average microstate
boundary probability curve
Microstate_Algorithm– Specifies the microstate boundary probability computation algorithm, as a MATLAB function handle
@CentroidDissimilarity1D: Considers changes in a 1-parameter centroid location function
@CentroidDissimilarity2D: Considers changes in a 2-parameter centroid location function
@GlobalMapDissimilarity: Considers changes in successive topographic map correlations
@GlobalFieldPower: Considers locations of minimum global field power
ERP Pattern Segmentation ToolMetascript Configuration – Step 4 of 6: Pattern Segmentation Parameters
Minimum_Microstate_Duration
– Specifies the minimum allowable interval for a stable topography to be designated a
microstate
– Specify Minimum_Microstate_Duration in milliseconds, as a MATLAB scalar
Maximum_Transition_Duration
– Specifies the maximum allowable interval of unstable topography to be excluded
from the beginning or end of a microstate region
– Specify Maximum_Transition_Duration, in milliseconds, as a MATLAB scalar
ERP Pattern Segmentation ToolMetascript Configuration – Step 5 of 6: Class Instantiation I
Instantiate EGI reader class object
Initialize object parameters
Import metadata
Import signal (ERP) data
ERP Pattern Segmentation ToolMetascript Configuration – Step 5 of 6: Class Instantiation II
Instantiate Pattern Segmentation class object
Initialize object parameters
ERP Pattern Segmentation ToolMetascript Configuration – Step 6 of 6: Class Invocation for Grand Average Data
Call ComputeMicrostateBoundaries method: Computes microstateboundaries via specified microstate algorithm
Call ComputeMicrostateStatistics method: Exclude invalid microstates and compute microstate statistics
Call PlotMicrostateAnalysis method: Plot microstate boundary probability curve, microstate statistics and microstate topographies
ERP Pattern Segmentation ToolMetascript Configuration – Step 6 of 6: Class Invocation for Subject Average Data
Call ComputeMicrostateBoundaries method: Computes microstateboundaries via specified microstate algorithm
Call ComputeMicrostateStatistics method: Exclude invalid microstates and compute microstate statistics
Call PlotMicrostateAnalysis method: Plot microstate boundary probability curve, microstate statistics and microstate topographies
ERP Pattern Segmentation ToolMetascript Configuration – Step 6 of 6: Class Invocation for Subject-Specific Data
Call ComputeMicrostateBoundaries method: Computes microstateboundaries via specified microstate algorithm
Call ComputeMicrostateStatistics method: Exclude invalid microstates and compute microstate statistics
Call PlotMicrostateAnalysis method: Plot microstate boundary probability curve, microstate statistics and microstate topographies
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ERP Pattern Segmentation ToolPlot Microstate Analysis GUI – 40 millisecond Minimum_Microstate_Duration
ERP Pattern Segmentation ToolPlot Microstate Analysis GUI – 30 millisecond Minimum_Microstate_Duration
Pattern Segmentation output folder contents– NemoErpPatternSegmentation workspace object
in MATLAB (.mat) format
– That’s it for now
ERP Pattern Segmentation ToolFolder Output for SimErpData.raw
Input data file Time stamp
ERP Pattern Segmentation ToolViewing Pattern Segmentation Class Properties in MATLAB
MATLAB Workspace view
NemoErpPatternSegmentation object
EgiRawIO object
Double click to open…
ERP Pattern Segmentation ToolViewing Pattern Segmentation Class Properties in MATLAB
EPreadDataInput: MATLAB structure of input parameters to ep_readData
Epdata: MATLAB structure of output data and metadata from ep_readData
EGIreadDataInput: MATLAB structure of (optional) input parameters to EGI_readData and EGI_readMetaData
Metadata: MATLAB structure of output metadata from EGI_readMetadata
Data: MATLAB structure of output data from EGI_readData
Keep on double clicking …
MATLAB Workspace view
ERP Pattern Segmentation ToolViewing Pattern Segmentation Class Properties in MATLAB
MATLAB Workspace view
Keep on double clicking …