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This fNIRS neuroimaging dataset captures prefrontal cortex activity from 20 participants during 14 types of highly automated driving scenarios in a simulator environment. The study examines risk cognition in passengers across different age groups, sexes, and driving experience levels using an 8-channel fNIRS device. The dataset aims to identify differences in prefrontal cortex activation between low-risk and high-risk driving episodes to support safety-of-the-intended-functionality (SOTIF) improvements and brain-computer interface applications.

Participants

20

Size

2.31 GB

Version

v1.0.0

Updated

Jun 18, 2026

This fNIRS neuroimaging dataset captures hemodynamic responses during complex scene analysis tasks, enabling investigation of spatial attention decoding mechanisms. The dataset comprises functional near-infrared spectroscopy recordings from multiple participants performing visual attention tasks on complex scenes, providing insights into cortical activation patterns associated with attentional processes. This resource supports research in cognitive neuroscience, brain-computer interfaces, and visual perception.

Participants

12

Size

2.19 GB

Version

v1.0.0

Updated

Jun 18, 2026

fNIRS finger tapping with lateralized auditory cues. 5 subjects, 56 NIRS channels (8 sources, 16 detectors incl. 8 short), NIRx NIRScout, 7.8 Hz, SNIRF format. 3 conditions x 30 trials. Zenodo DOI: 10.5281/zenodo.6575155

Participants

5

Size

47.4 MB

Version

v1.0.0

Updated

Jun 1, 2026

# Multimodal EEG-fNIRS-physio dataset during hierarchical cognitive-motor tasks This repository contains a raw multimodal dataset acquired in healthy adults performing a hierarchy of cognitive, motor, and combined cognitive-motor tasks. Data include neurophysiological (EEG, fNIRS), physiological (ECG and EMG), behavioral (push-button, torque), and subjective measures (sleepiness and cognitive load ratings), organized according to the Brain Imaging Data Structure (BIDS). The dataset is describe

Participants

30

Size

4.21 GB

Updated

Jun 19, 2026

References ---------- Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, 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., D

Participants

8

Size

2.90 GB

Updated

Jun 19, 2026

### Description This dataset contains simultaneous electroencephalography (EEG) and near-infrared spectroscopy (fNIRS) signals recorded from 12 participants while performing a silent naming task and three sensory-based imagery tasks using visual, auditory, and tactile perception. Participants were asked to visualize an object in their minds, imagine the sounds made by the object, and imagine the feeling of touching the object. ### EEG EEG data were acquired with a BioSemi ActiveTwo system with

Participants

12

Size

24.1 GB

Updated

Jun 19, 2026