Utilities (alpha version)
Here you will find some useful ERPLAB functions (alpha version) to facilitate your EEG and ERP analysis and interpretation. Some of them work on the ERPLAB's ERP structure but others work on the EEGLAB's EEG structure (continuous and/or epoched). We have even included a couple of functions oriented to deal with artifact detection in continuous data. Your feedback would be much appreciated (send an email to: matlabiano at gmail dot com)
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Fixing timing of EEG triggers (ERP structure)
- erptimeshift.m allows to adjust the ERP's time values (to the left or to the right) in a safe way. For instance, taking care that the zero value latency was moved without changing its "zeroness"
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Deleting short segments of continuos EEG
- delshortseg.m deletes segment of data between 2 event codes (string or number) if the size of the segment is lesser than a specified time in msec. For instance, after performing (automatic) artifact detection/rejection in continuous data, and inserting new 'boundary' codes, is probable that some EEG segments (between boundaries) got too short to be analyzed with ICA, or processed with some type of filters, etc. So, delshortseg.m will help with this.
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Removing white space from EEG alphanumeric event codes
- In case your EEG system uses alphanumeric event codes, and white spaces in them are messing up your life, wspacekiller.m will remove any white space from your event codes (EEGLAB's EEG structure).
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Obtaining mean values from individual epochs in an EEG dataset
- No few times people have asked us about how to get mean values, between latencies, from individual epochs instead from averaged ERPs. Well, here is meanepoch.m who will do the job for you.
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Making epoched data continuous
- epoch2continuous.m converts an epoched dataset (EEGLAB's structure) into a continuous one. Segments of data will be concatenated using a 'boundary' event.
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Closest
- Returns the closest value from a list
