Open-eyed resting-state recordings with magnetoencephalography and retrospective time estimation

This repository contains recordings from 56 human participants, collected during quiet wakefulness using magnetoencephalography (MEG). Participants were asked to remain quietly awake with their eyes open, fixating on a monitor screen for a few minutes. Following the resting-state MEG recording, participants were unexpectedly asked to estimate its duration as precisely as possible in minutes and seconds. MEG resting-state durations ranged from 2 to 5 minutes. The experimenter further ensured participants did not guess the timing nature of the task beforehand, so that this task is a pure retrospective duration estimation (episodic time). Additionally, they provided a judgment of the passage of time using a Likert scale ranging from 1 (very slow) to 5 (very fast). See the associated publication (Azizi et al., 2023) for details. Repository structure Raw data. We provide the raw MEG and anatomical MRI data in the archive files named rs-meg_sub* by batches of 10 participants. Each resting-state is associated with an empty-room MEG recording located in the archive rs-meg_emptyrooms, organized by session date. Anonymized session dates that match resting-state and empty-room recordings are available in the tsv sidecar files for each MEG recording. Empty-room recordings were already SSS-, Maxwell-, and notch-filtered, and downsampled to 500 Hz. Derivatives. The derivatives archive contains the transformation file (*-trans.fif), the cortical reconstruction files from FreeSurfer, and the MEG continuous raw data, preprocessed using MNE-Python and following the analyses described in Azizi et al. (2023). Data exclusion. We also provide the raw MEG data of participants excluded from Azizi et al. (2023). For simplicity, participant numbers were remapped: sub-e57 and onward are excluded. Exclusion details are in the participants.tsv file. Download Decompressing all files into the same root directory yields a BIDS-compliant data structure. On Linux and macOS, data extraction of *.tar.gz files can be performed with tar -xzf derivatives.tar.gz -C /path/to/output-directory. On Windows, it can be done with tools such as 7-Zip or WinRAR. MEG recording Electromagnetic brain activity was recorded using a whole-head Elekta Neuromag Vector View 306 MEG system (Neuromag Elekta LTD) equipped with 102 triple-sensor elements (one magnetometer and two orthogonal planar gradiometers) in a magnetically shielded room. Data were sampled at 2 kHz or 1 kHz, as indicated in the .json file associated with each MEG recording. An online low-pass filter was set at 500 Hz for data sampled at 2 kHz and 330 Hz for data sampled at 1 kHz. No high-pass filter (DC recordings) was applied. Horizontal and vertical electrooculograms (EOG) and electrocardiogram (ECG) were also recorded. Participants’ head position was measured before MEG recording by means of four head position coils (HPI) placed over the frontal and mastoid areas. Anatomical MRI recording The T1-weighted aMRI was recorded using a 3-T Siemens Trio MRI scanner. Parameters of the sequence were: voxel size: 1.0 x 1.0 x 1.1 mm, acquisition time: 466 s, repetition time TR: 2300 ms, and echo time TE: 2.98 ms.