3.12: Review of Processing Steps
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To review, here are the steps we carried out in this chapter:
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Processed the single-participant to get an ERPset for each of our 10 participants
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I provided 3 different ways of doing this
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Examined the number of accepted and rejected trials, ERP waveforms, and data quality measures for each participant to check for problems
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EEGLAB > ERPLAB > Summarize artifact detection > Summarize ERP artifacts in a table (or type ERP.ntrials in the Matlab command window)
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EEGLAB > ERPLAB > Plot ERP > Plot ERP waveforms
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EEGLAB > ERPLAB > Data Quality options > Show Data Quality measures in a table
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Made a grand average from our 10 participants
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EEGLAB > ERPLAB > Average across ERPsets (Grand Average)
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Applied a low-pass filter to the grand average to attenuate the high-frequency noise
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EEGLAB > ERPLAB > Filter & Frequency Tools > Filters for ERP data
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Obtained N400 amplitude “scores” (mean voltage from 300-500 ms) for the related and unrelated targets in each participant’s averaged ERP waveforms
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EEGLAB > ERPLAB > ERP Measurement Tool
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Used the Viewer to see the measurements for each waveform
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Performed a simple statistical analysis with the data from a single channel and a more complex analysis with the data from multiple channels
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The N400 amplitude scores were exported into a text file and then imported into a statistical package
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ERPLAB does not perform statistical analyses—we did not want to “reinvent the wheel,” and it is difficult to anticipate every possible statistical analysis someone would want to perform
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We also compared the table of means from the statistical analyses with our grand average ERP waveforms to make sure that the analysis was performed correctly
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Created a new “cluster” channel that was an average of 9 of the original channels
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EEGLAB > ERPLAB > ERP Operations > ERP Channel operations
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Created a difference wave by subtracting one bin from another
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EEGLAB > ERPLAB > ERP Operations > ERP Bin operations