nemo erp analysis toolkit erp metric extraction an overview
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NEMO ERP Analysis ToolkitERP Metric Extraction
An Overview
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NEMO Information Processing Pipeline
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NEMO Information Processing PipelineMetric Extraction Component
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NEMO Information Processing PipelineERP Pattern Extraction, 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 Metric Extraction 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 script 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 Metric Extraction 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_tPCA_GAV.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 Metric Extraction 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 Metric Extraction ToolMetascript Configuration – Step 1 of 6: Data Parameters
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ERP Metric Extraction 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 Metric Extraction 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 Metric Extraction 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 Metric Extraction 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 Metric Extraction ToolMetascript Configuration – Step 4 of 6: NemoErpMetricExtraction Parameters
ERP_Component_Label
ERP_Component_Analysis_Method_Label
ERP_Component_Label– ERP individual component identification label, as a single-quoted string
Example: ‘PcaFactor#’ or ‘MicrostateSegment#’
ERP_Component_Analysis_Method_Label– ERP component-generation-procedure identification label, as a single-quoted string
Example: ‘tPCA with Infomax rotation’ or ‘Microstate segmentation via Centroid Dissimilarity’
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ERP Metric Extraction ToolMetascript Configuration – Step 5 of 6: Class Instantiation
Instantiate EGI reader class object
Initialize object parameters
Import metadata
Import signal (ERP) data
Instantiate Metric Extraction class object
Initialize object parameters
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ERP Metric Extraction ToolMetascript Configuration – Step 6 of 6: Class Invocation
Call RDF method: Generate RDF-formatted metric info
Call CSV method: Generate CSV-formatted metric info
Call XLS method: Generate XLS-formatted metric info
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Metric Extraction output folder contents– CSV files, one per condition– RDF files, one per condition– NemoErpMetricExraction object in MATLAB (.mat) format
ERP Metric Extraction ToolFolder Output for SimErpData_tPCA_GAV.raw
Input data file Time stamp
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Comma Separated Value (CSV) format output file– Column 1: Factor Label– Column 2: Metric Label– Column 3: Metric Value (microvolts | milliseconds)
ERP Metric Extraction ToolExample Output for SimErpData_tPCA_GAV.raw
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Resource Description Format (RDF) format output file– RDF N-Triple syntax– Subject, Predicate (Relation), Object triple– Example: Subject, has property, object property
ERP Metric Extraction ToolExample Output for SimErpData_tPCA_GAV.raw
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ERP Metric Extraction ToolViewing Metric Extraction Class Properties in MATLAB
MATLAB Workspace viewNemoErpMetricExtraction object
EgiRawIO object
Double click to open…
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ERP Metric Extraction ToolViewing Metric Extraction Class Properties in MATLAB
MATLAB Workspace view
Keep on double clicking …