20 datasets found

EEG classification aims to classify EEG recordings that consist of C sensor readings regularly sampled, e.g., at a set frequency in Hz, usually for a short time range of a few...

The WithMe dataset contains EEG signals from subjects performing an auditory-visual attention task.

The proposed method uses two publicly available motor imagery EEG datasets for validation.

ECoG recordings from 8 epilepsy patients, comparing finger flexion and hand gestures for BCI control

WAY-EEG-GAL dataset is used for motor kinematics prediction analysis. The dataset contains synchronous EEG and hand kinematics data collected during the grasp-and-lift task.

The dataset contains kinematic data of hand movements and neural activity from sensorimotor cortex during grasping

The dataset used in this paper is a collection of local field potentials (LFPs) recorded from the macaque prefrontal cortex during memory-guided saccades.

A new EEG dataset where the attention of the participants is detected and used to guide the collection of the EEG signals in each experiment.

The dataset contains EEG data recorded from 10 healthy subjects.

The dataset contains EEG data recorded from 35 healthy subjects.

The dataset used in the paper is an fMRI dataset obtained during a passive natural language listening task. The dataset comprises fMRI data from 8 subjects recorded while they...

The Magnetoencephalography (MEG) dataset is a MEG dataset containing brain activity patterns of 3 subjects while they were watching 1200 images of 200 distinct object categories...

The Generic Object Decoding (GOD) dataset is a fMRI dataset containing brain activity patterns of 5 subjects while they were watching 1200 images of 200 distinct object...

The OpenBMI dataset is a large benchmark containing 2 sessions of 2-class MI-EEG data (left hand, right hand) from 54 right-handed healthy subjects.

A large-scale benchmark for evaluating the brain-likeness of neural networks.

A shallow recurrent model that follows neuroanatomy more closely than standard machine learning ANNs, and is among the top models on Brain-Score yet remains competitive on...

The study proposes the spatio-temporal controlled diffusion model (SCDM) for cross-modal generation of synthetic fNIRS signals from EEG data.

A large-scale, cross-subject fMRI dataset for brain captioning, containing high-resolution 7-Tesla fMRI scans captured from 8 subjects viewing images from the COCO dataset.

ERP-based EEG detection gaining increasing attention in the field of brain-computer interfaces. However, due to the complexity of ERP signal components, their low...

The dataset used in the paper is a collection of local field potentials (LFPs) from two macaque monkeys, Monkey A and Monkey B, performing memory-guided visual saccades to one...