Discover datasets

### Free Recall of Word Lists with Repeated Items #### Description This dataset contains behavioral events and intracranial electrophysiological recordings from a repated item free recall task. The experiment consists of participants studying a list of words, presented visually one at a time, and then freely recalling the words from the just-presented list in any order. On each list, there is a 7-second delay period between the encoding and recall phases. The data were collected at clinical s

Participants

48

Size

157 GB

Updated

Jun 6, 2026

Semantic conditioning task The dataset was used in this article: Pavlov YG, Menger NS, Keil A, Kotchoubey B. 2024. Contingency awareness shapes neural responses in fear conditioning. https://doi.org/10.1101/2024.08.13.607803

Participants

81

Size

19.8 GB

Updated

Jun 6, 2026

README ------ Details related to access to the data ------------------------------------- Please contact the following authors for further information: Melissa Polonenko(email: [email protected]) Ross Maddox (email: [email protected]) Overview -------- This is the "peaky_snr" dataset for the paper Polonenko MJ & Maddox RK (2024), with citation listed below. BioRxiv: The effect of speech masking on the subcortical response to speech Auditory brainstem responses (ABR

Participants

25

Size

15.3 GB

Updated

Jun 6, 2026

README ------ Details related to access to the data ------------------------------------- Please contact the following authors for further information: Melissa Polonenko(email: [email protected]) Ross Maddox (email: [email protected]) Overview -------- This is the "peaky_snr" dataset for the paper Polonenko MJ & Maddox RK (2024), with citation listed below. BioRxiv: The effect of speech masking on the subcortical response to speech Auditory brainstem responses (ABR

Participants

25

Size

37.8 GB

Updated

Jun 2, 2026

References ---------- Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896).https://doi.org/10.21105/joss.01896 Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C.

Participants

29

Size

13.3 GB

Updated

Jun 6, 2026

Notes ---------- Electroglottography (EGG) and audio are included in the EEG files themselves, rather than in sidecar files, as they were converted from analog to digital on the same hardware. The audio is the audio the subject heard, i.e. their delayed auditory feedback. If you want the speech waveform aligned to the time the subject produced it, you can shift the audio back by the timestamps recorded (for each trial) in the delay field of the events sidecar file. EGG has already been minimal

Participants

32

Size

118 GB

Updated

Jun 6, 2026

This dataset was utilized for the publication of the manuscript by Zhang et al. (in preparation). A subset of the data has been employed in [1] and [2]. Summary: This data set comprises the de-identified subjects with interictal iEEG recordings with sleep from University of California Los Angels Mattel Children’s Hospital, and Children’s Hospital of Michigan, Detroit. Subject-wise information is contained in each folder, including iEEGs collected from 185 subjects during sleep. The channel nam

Participants

185

Size

102 GB

Updated

Jun 6, 2026

An EEG dataset and behavioural response data for a task that required participants to view images of scenes and rate their aesthetic properties (beauty, complexity, interestingness), or rate their appropriateness for either a reading activity, or a social activity. You can also find the behavioural data already extracted from the EEG events for convenience, and the full stimuli set with identifiable file names. For detailed information about the methods and an analysis of the data please see

Participants

26

Size

12.0 GB

Updated

Jun 6, 2026

Participants

608

Size

74.1 GB

Updated

Jun 6, 2026

# TMNRED Dataset - Chinese Natural Reading EEG for Fuzzy Semantic Target Identification ## Overview This dataset, named TMNRED, consists of electroencephalogram (EEG) recordings obtained from 30 participants engaged in natural reading tasks. The aim is to investigate the mechanisms of semantic processing in the Chinese language within a natural reading environment. ## Data Collection - Participants: 30 healthy, right-handed individuals (average age: 22.07 years, standard deviation: 2.7 years;

Participants

30

Size

358 MB

Updated

Jun 6, 2026