Multimodal Cognitive Workload n-back Task, 4 Difficulties

This dataset was generated from LSL/XDF recordings. Converted to BIDS with instructions and code [presented here](https://github.com/LMBooth/QT-nback_study/tree/main/conversion_package)

- Original recordings are stored under sourcedata/xdf/ as .xdf files (non-BIDS).
- EEG was converted to BrainVision format (.vhdr/.eeg/.vmrk) under each sub-*/eeg/.
- *_events.tsv was generated from marker streams and then aligned so onset is relative to the EEG start time.
- Marker streams include task markers (n-backMarkers) and acquisition dropout annotations (UoHDataOffsetStream); events include a marker_stream column and marker definitions are in task-nback_events.json.
- Pupil Labs gaze/pupil data was exported from the XDF pupil_capture stream into sub-*/pupil as *_task-nback_pupil.tsv + *_task-nback_eyetrack.json (PhysioType=eyetrack).
- ECG is captured on the EEG system; the ECG channel is typed in *_channels.tsv and exported as *_recording-ecg_physio.tsv + *_recording-ecg_physio.json under sub-*/ecg.
- Analysis note: participants excluded from the analysis remain in participants.tsv with analysis_included=false; no epoch rejection was applied to this raw dataset.
- Participant IDs match the original XDF filenames; missing IDs correspond to excluded participants.

Participants
- N_recorded: 20
- N_released: 18
- Exclusions: 2 participants excluded due to data quality failures (sub-013, sub-017).
- Demographics in participants.tsv: age (years), sex, handedness.
- Excluded IDs remain in participants.tsv with analysis_included=false.

Hardware and data collection
- Combined EEG+ECG mobile EEG system (Bateson and Asghar, 2021; Clewett et al., 2016) and Pupil Labs Pupil Core, synchronized via Lab Streaming Layer (LSL).
- EEG: 19-channel 10-20 montage (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2), Ag/AgCl electrodes with linked-ear reference, 250 Hz; impedances checked and Neurgel EEG gel applied.
- ECG: 3-lead on the same system; positive lead right shoulder/clavicle, negative lead left shoulder/clavicle, feedback lead lower left torso.
- Pupillometry: Pupil Labs Pupil Core eye tracking with infrared illuminators; LSL relay with asynchronous sampling (timestamps per sample).

Protocol summary
- Tutorial phase with feedback: 20 trials at each level (1-back through 4-back) after a 60 s fixation.
- Main experiment: 100 trials at each level (1-back through 4-back) with no feedback.
- Each level begins with a 6.0 s instruction screen ("Remember N steps back").
- Each trial shows a letter for 1.0 s, followed by a 0.7 s blank interval.
- Task events encode nback_level, key_press, matched, response_accuracy, and tutorial flags in task-nback_events.json.
Task: nback

Release notes
- Recorded 20 participants; released 18.
- Reason: data quality failures.
- Participant IDs match original XDF filenames; missing IDs indicate excluded participants.

References
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Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Hochenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896).https://doi.org/10.21105/joss.01896

Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103.https://doi.org/10.1038/s41597-019-0104-8

Clewett CJ, Langley P, Bateson AD et al (2016) Non-invasive, home-based electroencephalography hypoglycaemia warning system for personal monitoring using skin surface electrodes: a single-case feasibility study. Healthc Technol Lett 3:2-5. https://doi.org/10.1049/htl.2015.0037

Bateson AD, Asghar AUR (2021) Development and evaluation of a smartphone-based electroencephalography (EEG) system. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3079992