EEG audio-tactile detection task under reduced alertness

This dataset contains raw EEG data recorded at the University of Granada (CIMCYC) between February and April 2023 during an audio–tactile detection task. The experiment was conducted with healthy easy-sleepers seated in a reclining armchair for approximately 2 hours, as part of the project “Redundancy effect of multisensory interactions under reduced alertness” (pre-registration available at: https://osf.io/mu6ne/overview). Due to technical limitations when uploading the full EEG dataset converted to the BIDS format, the data have been divided into three compressed archives, each containing a subset of participants: Subject_1_to_9.zip: data for participants sub-001 to sub-009 Subject_10_to_18.zip: data for participants sub-010 to sub-018 Subject_19_to_26.zip: data for participants sub-019 to sub-026 Each compressed archive follows the BIDS specification and contains raw EEG recordings, metadata, and event files corresponding to the audio–tactile detection task. In addition to the EEG data, the dataset includes the following files: task-AudiotactileDetectionDrowsy_events.json: Description of the event structure and event codes used in the task. participants.tsv and participants.json: Demographic and experimental information for each participant, following the BIDS standard. dataset_description.json: General description of the dataset in accordance with the BIDS specification. README: Overview of the dataset structure and content. CHANGES: Log of relevant changes and updates to the dataset. RedundancyTask22023_3h_noise.mp3: Auditory stimulus used in the redundancy task. BIDS_export_2.m: MATLAB script used to convert the original EEG recordings into BIDS format. chanlocs.mat: Channel location file containing electrode position information. The sorted data and MATLAB code used for EEG preprocessing, classification of alertness states, and data analysis (including ERP cluster-based permutation tests and MVPA analyses) are available on the Open Science Framework (OSF) of the project at: https://osf.io/7pt86/files/osfstorage.