NEMO ERP Analysis ToolkitERP Metric Extraction

An Overview

NEMO Information Processing Pipeline

NEMO Information Processing PipelineMetric Extraction Component

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)

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

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

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

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

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

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’

ERP Metric Extraction ToolMetascript Configuration – Step 3 of 6: Experiment Parameters (Optional)

Event_Type_Label

Stimulus_Type_Label

Stimulus_Modality_Label

Cell_Label_Descriptor

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’}

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’

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

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

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

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

…

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

ERP Metric Extraction ToolViewing Metric Extraction Class Properties in MATLAB

MATLAB Workspace viewNemoErpMetricExtraction object

EgiRawIO object

Double click to open…

ERP Metric Extraction ToolViewing Metric Extraction Class Properties in MATLAB

MATLAB Workspace view

Keep on double clicking …