Discover datasets

Summary This dataset forms part of a study supported by the Social Neuroscience and Neuromodulation Laboratory of Universidad del Desarrollo, Chile. The full dataset is described in a submission to Scientific Data. Abstract In our daily lives, we frequently encounter decisions where the potential outcomes are unclear, leading to a state of heightened uncertainty. The complete or partial lack of knowledge regarding the probability of outcomes is called ambiguity and presents significant challe

Participants

53

Size

37.5 GB

Updated

Jun 6, 2026

# General information The dataset provides resting-state EEG data (eyes open,partially eyes closed) from 71 participants who underwent two experiments involving normal sleep (NS---session1) and sleep deprivation(SD---session2) .The dataset also provide

Participants

71

Size

8.29 GB

Updated

Jun 6, 2026

This study is described at https://osf.io/qt2zh/. Scripts used for data processing are posted there. Here is the script from the manuscript that describes these data. Error-related negativity is a widely used measure of error monitoring, and many projects are independently moving ERN recorded during a flanker task towards standardization, optimization, and eventual clinical application. However, each project uses a different version of the flanker task and tacitly assumes ERN is functionally e

Participants

172

Size

123 GB

Updated

Jun 6, 2026

### pyFR: Delayed Free Recall of Word Lists, Preliminary Cognitive Electrophysiology Study #### Description This dataset contains behavioral events and intracranial electrophysiological recordings from a delayed free recall task. The experiment consists of participants studying a list of words, presented visually one at a time, completing simple arithmetic problems that function as a distractor, and then freely recalled the words from the just-presented list in any order. The data was collect

Participants

49

Size

97.8 GB

Updated

Jun 6, 2026

Participants

31

Size

3.79 GB

Updated

Jun 6, 2026

Participants

7

Size

2.27 GB

Updated

Jun 6, 2026

HID dataset This is a placeholder dataset.

Participants

1

Size

79.2 MB

Updated

Jun 6, 2026

TX22 dataset: Predicting and influencing trust-based decisions about control authority hand-off and take-over during simulated, semi-automated driving in a leader-follower paradigm.Vehicle survivability is critically important in todays military. Significant DoD investments have focused on developing and integrating autonomous vehicle technologies to mitigate the effects of human error and thus enhance surviability and mission effectiveness. In a previous experiment (SANDR designation: ARL_TX20)

Participants

17

Size

22.3 GB

Updated

Jun 6, 2026

TX16 dataset

Participants

14

Size

7.66 GB

Updated

Jun 6, 2026

TX15 dataset

Participants

14

Size

5.21 GB

Updated

Jun 6, 2026