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NEMO ERP Analysis ToolkitERP Pattern Segmentation
An Overview
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NEMO Information Processing Pipeline
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NEMO Information Processing PipelinePattern Decomposition Component
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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)
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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
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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
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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
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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
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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
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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’
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ERP Pattern Segmentation ToolMetascript Configuration – Step 3 of 6: Experiment Parameters (Optional)
Event_Type_Label
Stimulus_Type_Label
Stimulus_Modality_Label
Cell_Label_Descriptor
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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’}
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ERP Pattern Segmentation ToolMetascript Configuration – Step 4 of 6: Pattern Segmentation Parameters
Dimension_Flag
Averaging_Protocol
Microstate_Algorithm
Minimum_Microstate - _Duration
Maximum_Transition - _Duration
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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
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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
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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
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ERP Pattern Segmentation ToolMetascript Configuration – Step 5 of 6: Class Instantiation II
Instantiate Pattern Segmentation class object
Initialize object parameters
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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
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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
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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
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ERP Pattern Segmentation ToolPlot Microstate Analysis GUI – 30 millisecond Minimum_Microstate_Duration
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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
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ERP Pattern Segmentation ToolViewing Pattern Segmentation Class Properties in MATLAB
MATLAB Workspace view
NemoErpPatternSegmentation object
EgiRawIO object
Double click to open…
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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
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ERP Pattern Segmentation ToolViewing Pattern Segmentation Class Properties in MATLAB
MATLAB Workspace view
Keep on double clicking …