Modality-specific predictive templates in pre-stimulus EEG activity

The dataset includes raw EEG recordings collected during a perceptual decision-making task involving anticipatory cues for auditory and visual stimuli. Folder Structure The dataset is organized by participant: [participant ID]/ participantID_calib_000[block number].eeg participantID_calib_000[block number].vhdr participantID_calib_000[block number].vmrk ... participantID_test_000[block number].eeg participantID_test_000[block number].vhdr participantID_test_000[block number].vmrk ... Description Each folder contains all data for a single participant (whose ID is the folder name). Each participant completed two phases: calibXXXX: calibration phase testXXXX: main experimental phase Each phase contains multiple recording blocks: 4 calibration bloacks and 3 test blocks Data Format EEG data are stored in BrainVision format, consisting of three files per recording: .eeg → raw signal data .vhdr → header file (metadata, channel info, sampling rate) .vmrk → marker file (event triggers) These files should always be kept together. Recording Parameters Sampling rate: 1000 Hz Number of channels: 32 Electrode layout: standard 10–20 system Reference: FCz Relevant event markers Marker Description 1 Visual cue onset 2 Auditory cue onset 11 Visual stimulus onset 12 Auditory stimulus onset 13 Neutral cue onset (beginning of the pre-stimulus period in uncued settings) 1001 Right response onset 1002 Left response onset 1003 Time out response Recommended tools We recommend using Python MNE to visualize and process this raw data. Analysis code The code used to analyze this data is available on GitHub.