Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts
Imported from OpenNeuro ds003825
- Participants
- 50
- Channels
- 63
- Citations
- 1
- Size
- 59.9 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
49 results for "oscillating probabilities" · page 4 of 5 · ranked by relevance
Imported from OpenNeuro ds003825
This dataset contains EEG recordings from a collaborative brain-computer interface (BCI) study using rapid serial visual presentation (RSVP) for target image detection. Fourteen healthy subjects, organized into seven pairs, performed synchronized RSVP tasks distinguishing human from non-human images, generating p300-like event-related potentials. The dataset is a BIDS-formatted derivative converted using the MOABB toolbox from the original data by Zheng et al. (2020).
This EEG dataset comprises recordings from 25 college-age participants performing a reinforcement learning task with affective feedback, collected in 2018 at the Clinical Research Center Laboratory (CRCL) at the University of New Mexico. The study investigates the reward positivity component of the event-related potential and its sensitivity to affective liking during probabilistic learning. The dataset includes raw EEG data, behavioral task parameters, and analysis scripts supporting the published findings in Cognitive, Affective, & Behavioral Neuroscience.
This dataset comprises EEG recordings from 16 healthy participants performing a code-modulated visual evoked potential (c-VEP) brain-computer interface task using p-ary m-sequences. The study investigates non-binary m-sequence stimulation patterns to enhance user comfort in c-VEP-based BCIs. Data were collected across 5 sessions per subject with 8 runs per session at 256 Hz sampling rate using 16 EEG channels, providing a comprehensive resource for BCI paradigm development and evaluation.
EEG dataset from Experiment 2 of Grootswagers et al. (2021) investigating neural dynamics of task-relevant information prioritization. Participants performed a rapid serial visual presentation (RSVP) task with small objects embedded in large letters while EEG was recorded. This dataset examines how the brain prioritizes and processes behaviorally relevant stimuli in visual attention tasks.
This dataset comprises continuous 2D trajectory decoding from attempted arm movements recorded via 60-channel EEG from 10 participants (9 able-bodied, 1 with spinal cord injury) across 3 sessions. Participants performed motor imagery tasks including target-tracking (snakerun) and self-paced shape tracing (freerun) with visual feedback. The preprocessed data, sampled at 20 Hz after extensive artifact removal and filtering, is designed for regression-based continuous decoding research and investigation of learning effects across sessions.
This dataset comprises behavioral event logs and intracranial electrophysiological (iEEG) recordings from a delayed free recall task, collected across multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania. Participants studied lists of visually presented words, performed arithmetic distractor tasks, and then freely recalled the words in any order. This preliminary cognitive electrophysiology study served as a predecessor to the later FR1 and CatFR1 datasets.
This dataset contains EEG recordings from twenty-one participants performing a continuous feedback learning task in which they predicted the final height of an animated rising bar following different predictive cues. The task manipulated outcome predictability (highly predictable, somewhat predictable, unpredictable) using cued gnome stimuli, allowing investigation of neural correlates of continuous feedback and reward prediction processing.
This dataset comprises EEG recordings from 139 subjects (94 individuals with Parkinson's disease and 45 controls) performing an Interval Timing task. EEG data were collected with a 64-channel BrainVision system while participants judged short (3-second) and long (7-second) time intervals following visual cues. The dataset is intended to support research into timing perception and its neural correlates in Parkinson's disease.
This dataset contains EEG recordings from Experiment 1 of a study investigating the neural dynamics of task-relevant information prioritization. Participants performed a rapid serial visual presentation (RSVP) task involving small letters superimposed on large objects. The data provides insights into how the brain selectively processes and prioritizes behaviorally relevant stimuli during visual attention tasks.