NEMO Information Processing Pipeline

NEMO Information Processing Pipeline

NEMO Information Processing Pipeline
 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 Tool
 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

ERP Metric Extraction 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 Metric Extraction 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_ 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 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 Metric Extraction Tool
Metascript Configuration – Step 2 of 6: Experiment Parameters (Required)
 Lab_ID
 Experiment_ID
 Session_ID
 Subject_Group_ID
 Subject_ID
 Experiment_Info

ERP Metric Extraction 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 Metric Extraction Tool
Metascript Configuration – Step 3 of 6: Experiment Parameters (Optional)
 Event_Type_Label
 Stimulus_Type_Label
 Stimulus_Modality_Label
 Cell_Label_Descriptor

ERP Metric Extraction 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 Metric Extraction Tool
Metascript 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 Tool
Metascript 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 Tool
Metascript 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

ERP Metric Extraction Tool
Folder Output for SimErpData_tPCA_GAV.raw
 Metric Extraction output folder contents
– CSV files, one per condition
– RDF files, one per condition
– NemoErpMetricExraction object in MATLAB (.mat) format
Input data file Time stamp

ERP Metric Extraction Tool
Example Output for SimErpData_tPCA_GAV.raw
 Comma Separated Value (CSV) format output file
– Column 1: Factor Label
– Column 2: Metric Label
– Column 3: Metric Value (microvolts | milliseconds)
PCAfactor#001 Mean_Intensity_LATEMP
PCAfactor#002 Mean_Intensity_LATEMP
PCAfactor#003 Mean_Intensity_LATEMP
PCAfactor#004 Mean_Intensity_LATEMP
PCAfactor#005 Mean_Intensity_LATEMP
PCAfactor#006 Mean_Intensity_LATEMP
PCAfactor#001 Mean_Intensity_LFRONT
PCAfactor#002 Mean_Intensity_LFRONT
PCAfactor#003 Mean_Intensity_LFRONT
PCAfactor#004 Mean_Intensity_LFRONT
PCAfactor#005 Mean_Intensity_LFRONT
PCAfactor#006 Mean_Intensity_LFRONT
PCAfactor#001 Mean_Intensity_LOCC
PCAfactor#002 Mean_Intensity_LOCC
PCAfactor#003 Mean_Intensity_LOCC
PCAfactor#004 Mean_Intensity_LOCC
PCAfactor#005 Mean_Intensity_LOCC
PCAfactor#006 Mean_Intensity_LOCC
PCAfactor#001 Mean_Intensity_LORB
PCAfactor#002 Mean_Intensity_LORB
PCAfactor#003 Mean_Intensity_LORB
PCAfactor#004 Mean_Intensity_LORB
PCAfactor#005 Mean_Intensity_LORB
PCAfactor#006 Mean_Intensity_LORB
-1.32205108
2.20884825
-0.13632037
0.32797573
-0.80275749
0.04743715
-0.65896539
-1.63287792
-1.73317912
-2.09422301
-1.42150766
-0.03723651
0.28687667
-3.38753124
1.40419426
0.61821343
3.22377541
-0.28709995
-1.91178549
3.14364142
-0.85076154
0.35483038
-1.20096476
0.07527227
PCAfactor#001 Mean_Intensity_RORB
PCAfactor#002 Mean_Intensity_RORB
PCAfactor#003 Mean_Intensity_RORB
PCAfactor#004 Mean_Intensity_RORB
PCAfactor#005 Mean_Intensity_RORB
PCAfactor#006 Mean_Intensity_RORB
PCAfactor#001 Mean_Intensity_RPAR
PCAfactor#002 Mean_Intensity_RPAR
PCAfactor#003 Mean_Intensity_RPAR
PCAfactor#004 Mean_Intensity_RPAR
PCAfactor#005 Mean_Intensity_RPAR
PCAfactor#006 Mean_Intensity_RPAR
PCAfactor#001 Mean_Intensity_RPTEMP
PCAfactor#002 Mean_Intensity_RPTEMP
PCAfactor#003 Mean_Intensity_RPTEMP
PCAfactor#004 Mean_Intensity_RPTEMP
PCAfactor#005 Mean_Intensity_RPTEMP
PCAfactor#006 Mean_Intensity_RPTEMP
PCAfactor#001 Peak_Latency_Measurement_Datum
PCAfactor#002 Peak_Latency_Measurement_Datum
PCAfactor#003 Peak_Latency_Measurement_Datum
PCAfactor#004 Peak_Latency_Measurement_Datum
PCAfactor#005 Peak_Latency_Measurement_Datum
PCAfactor#006 Peak_Latency_Measurement_Datum
-1.92933138
3.13058562
-0.63761322
0.36211667
-1.21687127
0.07518651
2.80682594
-1.13138179
-0.0710425
-0.35024415
-0.38600676
0.15280392
-0.3813105
0.12308511
0.92244155
0.72990109
0.92419572
-0.0698178
484
216
260
252
116
204

ERP Metric Extraction Tool
Example 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 Tool
Viewing Metric Extraction Class Properties in MATLAB
NemoErpMetricExtraction object

EgiRawIO object
Double click to open…

ERP Metric Extraction Tool
Viewing Metric Extraction Class Properties in MATLAB

Keep on double clicking …