P300 dataset from initial spot study
…analyzed=[1.5, 40.0] Hz ## Cross-Validation - **Method**: 13-fold - **Folds…
- Participants
- 13
- Citations
- 2
- HED
- v8.4.0
- Size
- 2.82 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
100 results for "cross-validation" · page 3 of 10 · ranked by relevance
…analyzed=[1.5, 40.0] Hz ## Cross-Validation - **Method**: 13-fold - **Folds…
Chisco is a Chinese imagined speech EEG dataset collected from five participants, each recorded over 5-6 sessions. The dataset includes raw EEG recordings and preprocessed data (in fif and pkl formats), along with accompanying text stimuli used to elicit imagined speech. It is intended to support research on imagined speech decoding and brain-computer interface applications using EEG signals.
…SPHARA, common-average reference ## Cross-Validation - **Method**: leave-one-pair-out cross…
…analyzed=[1.5, 40.0] Hz Cross-Validation ---------------- Method: 13-fold Folds…
…The factorial design crossed task mode (motor imagery or motor execution), action…
…alpha=[8, 13] Hz ## Cross-Validation - **Method**: leave-one-clip-out - **Evaluation…
…CSP Cross-Validation ---------------- Method: 10x5-fold Folds: 5 Evaluation type: within_subject…
This dataset contains EEG recordings from Experiment 2 of a study investigating memory reactivation under anticipated interference, using a working memory task with lateralized visual objects and dual-task distractor manipulations. Participants memorized cued objects, performed a secondary distractor identification task in some blocks, and were subsequently tested on their memory via a two-alternative forced-choice probe. The dataset is intended to examine how anticipated interference affects neural memory reactivation processes.
…Covariance/Riemannian ## Cross-Validation - **Method**: bootstrap - **Evaluation type**: cross_subject, cross_session…
A multicenter intracranial electroencephalography (iEEG) dataset comprising segmented 3-second single-channel clips from epilepsy patients, annotated for graphoelement classification and artifact detection. The dataset includes clinical metadata such as seizure onset zone (SOZ) flags, electrode anatomy, and reviewer annotations, making it suitable for developing and validating automated signal classification algorithms in clinical neurophysiology.