WB_EEG_CalcERP

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WeBrainTool
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Joined: Mon Apr 19, 2021 10:56 am

WB_EEG_CalcERP

Post by WeBrainTool » Mon May 24, 2021 9:44 pm

WB_EEG_CalcERP is a tool to create averaged event related potential (ERP) for each EEG channel at scalp level. Calculating ERP consists of:
[1] Filter data using Hamming windowed sinc FIR filter. This step is optional, and default is no filtered (i.e. set passband as []).
[2] Extract epochs (default is [-0.2 0.8] sec) and baseline correction ( [-0.2, 0] sec): A continuous EEG dataset will be converted to epoched data by extracting data epochs time locked to specified event types or event indices. If applicable, time locked events corresponding to correct-reaction marker will be extracted (i.e. marker1). In addition, events in bad block (label 9999, marked by WB_EEG_Mark) will also be rejected automatically.
[3] Artifact rejection in epoched data using simple voltage threshold. Three criterions including amplitude, gradient and max-min criterions were used to reject artifact trials.
[4] ERP will be obtained from averaged clean epochs (default is [-0.2 0.8] sec).

Image
Fig. 8: Pipeline of ERP analysis. (1) Raw EEG data with events. As an example, S22 is a specified event type (e.g. target stimulus), and S22 is correct reaction marker corresponding to S22 if applicable). (2) Filtering EEG data, if applicable. The data can be filtered first using Hamming windowed sinc FIR filter. (3) Extract epochs (e.g. [-0.2, 0] sec), baseline correction and artifact rejection. A continuous EEG dataset will be converted to epoched data by extracting data epochs time locked to specified event types or event indices. Then, baseline correction (e.g. -[0.2, 0] sec) and artifact rejection will be conducted on epoched data. Three criterions of simple voltage threshold, including amplitude, gradient and max min criterions, will be used to reject artifact trials. If applicable, time locked events corresponding to correct reaction marker will be extracted only (i.e. marker1). In addition, events in bad block (label 9999, marked by WB_EEG_Mark) will also be rejected automatically. (4) Averaging. ERP will be obtained from clean epoched data.

Parameters
event1: specified event types or event indices (e.g. event label). If event label is not found, NO data will be epoched and calculated. DO NOT contain blank spaces in the event label (e.g. S 22). Strings of events will be compared ignoring space characters. Default is ‘[]’. The letters are case-sensitive.
epochlimits: epoch latency range [start, end] in seconds relative to the time-locking events. Default is ‘[-0.2,0.8]’ sec.
valuelim_1: threshold of amplitude criterion to reject artifact trials: Lower and upper bound latencies for trial data. If one positive value is given, the opposite value is used for lower bound. For example, use [-100,100] microvolts (μV) to remove artificial epoch. Default is [-100,100] (μV).
valuelim_2: threshold of gradient criterion to reject artifact trials: maximum allowed voltage step/sampling point. Default is 50 microvolts (μV).
valuelim_3: threshold of max-min criterion to reject artifact trials: maximum allowed absolute difference in the segment/epoch. Default is 150 microvolts (μV).
selechanns: number with indices of the selected channels (e.g. ‘[1:4,7:30]’ or ‘all’). Default is ‘all’.
marker1: correct-reaction marker corresponding to the specified event (e.g. event1). DO NOT contain blank spaces in the marker1 (e.g. S 222). Default is ‘[]’.
t1: duration (in seconds) before correct-reaction marker. Default is 2s.
passband: passband of filtering (e.g. ‘[1,30]’). Default is NO filtered (i.e. ‘[]’).
srate: sampling rate of EEG data. It can be automatically detected in EEG data. But for ASCII/Float .txt File or MATLAB .mat File, user should fill the sampling rate by hand. Default is ‘[]’.

Note:
(1)EEG data will be imported as EEG structure using EEGLAB. EEG.data should be channels × time points OR channels × time points × epochs. If size of EEG.data is channels × time points × epochs (has been epoched), all data will be used to create ERP.
(2)Clean trials are satisfying 3 criterion of artifact rejection for each channel at same time.

Outputs
For each subject, a zip file which contain the ERP data will be generated (saved as ERP .set file which contains the ERP potentials, EEG.data with dimension channels × time points × trials). The ERP .set file can be imported and used in EEGLAB. Following fields will be further added in the ERP .set file.

EEG.eventlist: list of accepted events;
EEG.erp: averaged event-related potentials for each channel;
EEG.trials: No. of trials;
EEG.xmin: Epoch latency limits [start] in seconds;
EEG.xmax: Epoch latency limits [end] in seconds;
EEG.epoch: filling with values of other events in the same epochs.

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