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.