NEMO ERP Analysis Toolkit
ERP Pattern Segmentation
An Overview
NEMO Information Processing Pipeline
NEMO Information Processing Pipeline
Pattern Decomposition Component
NEMO Information Processing Pipeline
ERP 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 Tool
MATLAB 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
ERP Pattern Segmentation Tool
Metascript Configuration – Step 1 of 6: Data Parameters
 File_Name
 Electrode_Montage_ID
 Cell_Index
 Factor_Index
 ERP_Onset_Latency
 ERP_Offset_Latency
 ERP_Baseline_Latency
ERP Pattern Segmentation Tool
Metascript 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 Tool
Metascript 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 Tool
Metascript Configuration – Step 2 of 6: Experiment Parameters (Required)
 Lab_ID
 Experiment_ID
 Session_ID
 Subject_Group_ID
 Subject_ID
 Experiment_Info
ERP Pattern Segmentation Tool
Metascript 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 Tool
Metascript Configuration – Step 3 of 6: Experiment Parameters (Optional)
 Event_Type_Label
 Stimulus_Type_Label
 Stimulus_Modality_Label
 Cell_Label_Descriptor
ERP Pattern Segmentation Tool
Metascript 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 Tool
Metascript Configuration – Step 4 of 6: Pattern Segmentation Parameters
 Dimension_Flag
 Averaging_Protocol
 Microstate_Algorithm
 Minimum_Microstate _Duration
 Maximum_Transition _Duration
ERP Pattern Segmentation Tool
Metascript 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 singlequoted 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 Tool
Metascript 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 Tool
Metascript 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 Tool
Metascript Configuration – Step 5 of 6: Class Instantiation II
Instantiate Pattern
Segmentation class object
Initialize object parameters
ERP Pattern Segmentation Tool
Metascript Configuration – Step 6 of 6: Class Invocation for Grand Average Data
Call
ComputeMicrostateBoundaries
method: Computes microstate
boundaries 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 Tool
Metascript Configuration – Step 6 of 6: Class Invocation for Subject Average Data
Call
ComputeMicrostateBoundaries
method: Computes microstate
boundaries 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 Tool
Metascript Configuration – Step 6 of 6: Class Invocation for Subject-Specific Data
Call
ComputeMicrostateBoundaries
method: Computes microstate
boundaries 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 Tool
Plot Microstate Analysis GUI – 40 millisecond Minimum_Microstate_Duration
ERP Pattern Segmentation Tool
Plot Microstate Analysis GUI – 30 millisecond Minimum_Microstate_Duration
ERP Pattern Segmentation Tool
Folder Output for SimErpData.raw
Pattern Segmentation output folder contents
– NemoErpPatternSegmentation workspace object
in MATLAB (.mat) format
– That’s it for now
Input data file
Time stamp
ERP Pattern Segmentation Tool
Viewing Pattern Segmentation Class Properties in MATLAB
NemoErpPatternSegmentation object
 MATLAB Workspace view
EgiRawIO object
Double click
to open…
ERP Pattern Segmentation Tool
Viewing Pattern Segmentation Class Properties in MATLAB
 MATLAB Workspace view
Keep on double
clicking …
 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
ERP Pattern Segmentation Tool
Viewing Pattern Segmentation Class Properties in MATLAB
 MATLAB Workspace view
Keep on double
clicking …