Discover datasets

# Continuous Feedback Processing Twenty-one participants learned to predict the final level of an animated rising bar. Following the appearance of a fixation cross, participants used the mouse to indicate their guess (i.e., how high they thought the bar would rise). After a delay, participants watched the bar rise to its final level. Points were awarded based on the distance between their guess and the actual level. Each round was cued by the appearance of a gnome (cover story: the gnomes are p

Participants

21

Size

3.47 GB

Updated

Jun 6, 2026

# Overview The dataset consists of data from two experiments in which subjects were presented bursts of noise from loudspeakers at different elevations. Subjects who participated in either experiment were initially tested in their ability to localize elevated sound sources. Both experiments were conducted in a hemi-anechoic chamber. # Localization Tests Bursts of pink noise were presented from loudspeakers at different elevations and 10° azimuth (to the listeners right). In the localization tes

Participants

53

Size

18.2 GB

Updated

Jun 6, 2026

Note: only the data for participant 1 has been uploaded. The rest of the dataset will be released upon publication. The pre-print can be found here: https://doi.org/10.31234/osf.io/wp73u The analysis codes, results, and figures can be found on OSF: https://osf.io/r93es. The main folder contains the raw EEG data in standard bids format. The ‘derivatives’ folder contains the pre-processed & epoched EEG data, formatted in line with cosmomvpa. For codes, results, & figures, see OSF: Engeler,

Participants

1

Size

1.30 GB

Updated

Jun 6, 2026

ILABS amnoise MEG BIDS dataset ============================== This dataset contains MEG data from a single infant subject. For more information, see the following publications, which should be cited if you use this data: - Mittag, M., Larson, E., Clarke, M., Taulu, S., & Kuhl, P. K. (2021). Auditory deficits in infants at risk for dyslexia during a linguistic sensitive period predict future language. NeuroImage: Clinical, 30, 102578. https://doi.org/10.1016/j.nicl.2021.102578 - Mittag, M., Lar

Participants

1

Size

1.78 GB

Updated

Jun 6, 2026

# Dataset description This dataset consists of 74 patients age 4-51 years old where Cortico-Cortical Evoked Potentials (CCEPs) were measured with Electro-CorticoGraphy (ECoG) during single pulse electrical stimulation. For a detailed description see: - Developmental trajectory of transmission speed in the human brain. D. van Blooijs¹, M.A. van den Boom¹, J.F. van der Aar, G.J.M. Huiskamp, G. Castegnaro, M. Demuru, W.J.E.M. Zweiphenning, P. van Eijsden, K. J. Miller, F.S.S. Leijten, D. Hermes, N

Participants

74

Size

269 GB

Updated

Jun 6, 2026

# THINGS-MEG Understanding object representations visual and semantic processing of objects requires a broad, comprehensive sampling of the objects in our visual world with dense measurements of brain activity and behavior. This densely sampled fMRI dataset is part of THINGS-data, a multimodal collection of large-scale datasets comprising functional MRI, magnetoencephalographic recordings, and 4.70 million behavioral judgments in response to thousands of photographic images for up to 1,854 obje

Participants

4

Size

238 GB

Updated

Jun 6, 2026

# Temporal Scaling Twenty participants learned three temporal intervals. There were two subtasks, randomly interleaved. In the Production task, participants produced either a short, medium, or long temporal interval. In the Perception task, participants judged a computer-produced interval as correct or incorrect (again, for a short, medium, or long temporal interval). In both tasks participants received visual feedback (a checkmark or x). Preprint: https://doi.org/10.1101/2020.12.11.421180

Participants

20

Size

7.21 GB

Updated

Jun 6, 2026

Bimodal dataset on Inner Speech Code available: https://github.com/LTU-Machine-Learning/Inner\_Speech\_EEG\_FMRI Publication available: https://www.nature.com/articles/s41597-023-02286-w Abstract: The recognition of inner speech, which could give a `voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition.

Participants

4

Size

9.33 GB

Updated

Jun 6, 2026

## Details related to access to the data - Contact person Please contact Iris Groen ([email protected], https://orcid.org/0000-0002-5536-6128) for more information. Please see the following papers for more details on the data collection and preprocessing: Groen IIA, Piantoni G, Montenegro S, Flinker A, Devore S, Devinsky O, Doyle W, Dugan P, Friedman D, Ramsey N, Petridou N, Winawer JA (2022) Temporal dynamics of neural responses in human visual cortex. The Journal of Neuroscience 42(40):7

Participants

14

Size

14.3 GB

Updated

Jun 6, 2026

HBN EO/EC datasets The Healthy Brain Network recorded 2952 children's eyes-open and eyes-closed EEG. Eyes-open lasted for 20 seconds, and eyes closed for 40 seconds. Because such files are difficult to process, they have been segmented here with five runs for eyes open and five runs for eyes closed. See notes in the code folder for included datasets.

Participants

2951

Size

216 GB

Updated

Jun 2, 2026