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# EPOC July 2023 - July 2025 ## Project discription A project to investigate neurophysiological correlates of Post-COVID-19 by the means of EEG. ## Contact Person M. Sc. Christian Neumann Neurology Department University Medical Center Schleswig-Holstein, Campus Kiel Arnold-Heller-Straße 3 24105 Kiel Germany E-Mail: [email protected] ## Supervisors * Prof. Dr. med. Walter Maetzler * Dr. Julius Welzel ## ### Overview ##### Psychomotor vigilance Task (PVT

Participants

97

Size

21.7 GB

# Different Doors Forty participants selected one of two doors, then received feedback indicating either a monetary gain or loss. Blocks lasted 20 trials and, unbeknownst to participants, were of two types. In learnable blocks, one of the doors was better because choosing it was associated with a 60% likelihood of a win. The other door only paid out 10% of the time. In unlearnable blocks, outcomes were not yoked to participant actions but were instead drawn from the learnable blocks and present

Participants

40

Size

3.34 GB

Participants

2

Size

1.87 GB

Version

v1.0.0

Updated

May 16, 2026

Participants

85

Size

126 GB

Version

v1.0.0

Updated

May 16, 2026

Participants

10

Size

159 GB

Version

v1.0.1

Updated

May 16, 2026

# No effect of rhythmic visual stimulation on experimental pain perception This dataset contains EEG recordings from 41 participants, collected as part of a study investigating the effect of rhythmic visual stimulation on experimental pain perception. Data were collected at Université Laval, Québec, Canada. This work was funded by the Fonds de recherche du Québec – Santé (FRQS) and the Quebec Pain Research Network (QPRN). For full details on the dataset and study design, please refer to the r

Participants

41

Size

24.3 GB

# Dataset of Emotion Recognition Using Validated Video Stimuli with Large-scale Behavioral Survey and MEG Recordings ## General Description This dataset was developed as part of research focused on brain signal-based emotion recognition by capturing high-fidelity Magnetoencephalography (MEG) signals during induced different emotional states. The dataset is organized into three primary components: 1. **Phenotype (Online Survey)**: Stored within the 'phenotype' directory, this component contain

Participants

23

Size

88.8 GB

64-ch EEG, 95 subjects, 2 sessions, 6 paradigms (13 tasks). BrainAmp 250Hz Easycap 64-ch. DOI:10.1016/j.neuroimage.2022.119666

Participants

95

Size

21.6 GB

Version

v1.0.0

Updated

May 18, 2026

# ROAMM: Reading Observed At Mindless Moments **ROAMM** is a large-scale multimodal dataset featuring simultaneous **EEG and eye-tracking** data collected during naturalistic reading with **span-level mind-wandering annotations**. ROAMM provides a benchmark dataset for MW detection and EEG-to-text decoding tasks, and enables the study of attention-related degradation in language decoding from brain activity in naturalistic reading. ## Dataset Status * **Raw EEG (BIDS):** **Work in Progress.**

Participants

1

Size

224 MB

# EEG-Speech Brain Decoding Dataset ## Overview This dataset contains EEG recordings and audio data. ## Sessions Sessions are labeled by recording date in YYYYMMDD format. - Example: `ses-20240401` = recorded on April 1, 2024 Multiple recordings on the same day are distinguished by run numbers: - `run-N`: Nth recording of the day ## Tasks - **speechopen**: Overt speech production task - Participants vocalize visually presented text - **listening**: Auditory listening task - Participants

Participants

3

Size

955 GB