Face processing EEG dataset for EEGLAB

OpenNeuro/NEMAR Dataset:ds002718 #Files:582 Dataset size:4.3 GB #EEG Channels:70 #EOG Channels:2 #Misc Channels:4

BIDS Version: v1.2.0 HED Version: Version: 1.0.5

On Brain life: True Published Date: 2020-04-21 23:09:57 Tasks: FaceRecognition

Available Modalities

.fdt, .set

#Sessions: 1 #Scans/session: 0 #Participants: 18 Ages (yrs): 23 - 31 License: CC0

Dataset DOI: 10.18112/openneuro.ds002718.v1.0.5

Uploaded by Dung Truong on 2020-04-21 20:15:53

Daniel G. Wakeman, Richard N Henson


How to Acknowledge

  • This work was supported by the UK Medical Research Council (MC_A060_5PR10) and Elekta Ltd.
  • References and Links
  • Wakeman, D., Henson, R. A multi-subject, multi-modal human neuroimaging dataset. Sci Data 2, 150001 (2015). https://doi.org/10.1038/sdata.2015.1
  • Ethics Approvals


    Multi-subject, multi-modal (sMRI+EEG) neuroimaging dataset on face processing. Original data described at https://www.nature.com/articles/sdata20151 This is repackaged version of the EEG data in EEGLAB format. The data has gone through minimal preprocessing including (see wh_extracteeg_BIDS.m):

    • Ignoring fMRI and MEG data (sMRI preserved for EEG source localization)
    • Extracting EEG channels out of the MEG/EEG fif data
    • Adding fiducials
    • Renaming EOG and EKG channels
    • Extracting events from event channel
    • Removing spurious events 5, 6, 7, 13, 14, 15, 17, 18 and 19
    • Removing spurious event 24 for subject 3 run 4
    • Renaming events taking into account button assigned to each subject
    • Correcting event latencies (events have a shift of 34 ms)
    • Resampling data to 250 Hz (this is a step that is done because this dataset is used as tutorial for EEGLAB and need to be lightweight)
    • Merging run 1 to 6
    • Removing event fields urevent and duration
    • Filling up empty fields for events boundary and stim_file.
    • Saving as EEGLAB .set format

    Ramon Martinez, Dung Truong, Scott Makeig, Arnaud Delorme (UCSD, La Jolla, CA, USA)