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Data collection took place at the Meditation Research Institute (MRI) in Rishikesh, India, under the supervision of Arnaud Delorme, Ph.D. The project was approved by the local MRI Indian ethical committee and the ethical committee of the University of California San Diego (IRB project # 090731). Participants sat either on a blanket on the floor or on a chair for both experimental periods depending on their personal preference. Participants were asked to keep their eyes closed, and all lighting

Participants

98

Size

54.5 GB

Updated

Jun 6, 2026

Resting EEG and MEG data was gathered for two independently collected samples of healthy and First Episode Psychosis (FEP) individuals. To obtain resting data, EEG channels were recorded for 5 minutes using an Elekta Neuromag Vectorview system. EEG was recorded using a low-impedance 10-10 system 60-channel cap. The second collected sample of EEG data is provided here. This sample excludes a portion of subjects that have been included with the first acquisition (EEG: First Episode Psychosis v

Participants

61

Size

12.5 GB

Updated

Jun 6, 2026

Resting EEG and MEG data was gathered for two independently collected samples of healthy and First Episode Psychosis (FEP) individuals. To obtain resting data, EEG channels were recorded for 5 minutes using an Elekta Neuromag Vectorview system. EEG was recorded using a low-impedance 10-10 system 60-channel cap. The first collected sample of EEG data is provided here. This sample includes a portion of subjects from the second acquisition (EEG: First Episode Psychosis vs. Control Resting Task

Participants

82

Size

6.15 GB

Updated

Jun 6, 2026

### DESCRIPTION Magnetoencephalography (MEG) dataset recorded during the presentation of audiovisual sequences with a causality judgment task and temporal order judgment task. This MEG dataset was prepared in the Brain Imaging Data Structure (MEG-BIDS, Niso et al. 2018) format using MNE-BIDS (Appelhoff et al. 2019). ### PUBLISHED IN Pesnot Lerousseau, J., Parise, C., Ernst, MO., van Wassenhove, V. (2022). Multisensory correlation computations in the human brain identified by a time-resolved enc

Participants

13

Size

75.7 GB

Updated

Jun 6, 2026

Overview —————————————————— This data is from the paper "Capacity for movement is a major organisational principle in object representations". This is the data of Experiment 2 (EEG: movement). The paper is now published in NeuroImage: https://doi.org/10.1016/j.neuroimage.2022.119517 Abstract: The ability to perceive moving objects is crucial for threat identification and survival. Recent neuroimaging evidence has shown that goal-directed movement is an important element of object processing in

Participants

24

Size

45.7 GB

Updated

Jun 6, 2026

Overview —————————————————— This data is from the paper "Capacity for movement is a major organisational principle in object representations". This is the data of Experiment 1 (EEG: aliveness). The paper is now published in NeuroImage: https://doi.org/10.1016/j.neuroimage.2022.119517 Abstract: The ability to perceive moving objects is crucial for threat identification and survival. Recent neuroimaging evidence has shown that goal-directed movement is an important element of object processing in

Participants

24

Size

46.1 GB

Updated

Jun 6, 2026

Epilepsy Interictal Dataset ===================== This dataset was updated and prepared for release as part of a manuscript by Bernabei & Li et al. (in preparation). A subset of the data has been featured in [1] and [2]. Summary ------------- This dataset comprises of de-identified subjects with interictal iEEG recordings possibly with sleep or awake state annotated. The subjects come from the following centers: - National Institute of Health (NIH) - Johns Hopkins Hospital (JHH) - University

Participants

39

Size

5.00 GB

Updated

Jun 6, 2026

Dataset description This dataset is part of a bigger dataset of intracranial EEG (iEEG) called RESPect (Registry for Epilepsy Surgery Patients), a dataset recorded at the University Medical Center of Utrecht, the Netherlands. It consists of 12 patients: six patients recorded intraoperatively using electrocorticography (acute ECoG), six patients with long-term recordings (3 patients recorded with ECoG and 3 patients recorded with stereo-encephalography SEEG). For a detailed description see Demur

Participants

6

Size

65.0 GB

Updated

Jun 6, 2026

### Prediction Error EEG & Motion Study This is the dataset of the study "prediction error". In short, 19 participants were tested in a virtual reality (VR) reach-to-object task. In the task participants experienced visual, visual with vibrotactile or visual with vibrotactile (all subjects) and electrical muscle stimulation (EMS) feedback (10 subjects) . In 25\% of trials the feedback, 'button selection', was provided prematurely, resulting in prediction error / mismatch ERPs (oddball style para

Participants

19

Size

10.6 GB

Updated

Jun 6, 2026

Dataset description This dataset is part of a bigger dataset of intracranial EEG (iEEG) called RESPect (Registry for Epilepsy Surgery Patients), a dataset recorded at the University Medical Center of Utrecht, the Netherlands. It consists of 12 patients: six patients recorded intraoperatively using electrocorticography (acute ECoG), six patients with long-term recordings (3 patients recorded with ECoG and 3 patients recorded with stereo-encephalography SEEG). For a detailed description see (Demu

Participants

6

Size

2.60 GB

Updated

Jun 6, 2026