…Only electrodes passing through sensorimotor areas were used in the study (P…
This dataset contains intracranial EEG (stereo-EEG) recordings acquired during 41 high-frequency electrical cortical stimulations that evoked negative motor responses. Data come from 23 patients undergoing presurgical evaluation for drug-resistant epilepsy. Each recording spans about 24 seconds around a stimulation and includes pre- and post-stimulation 5-second epochs, which were used for connectivity analysis. Stimulation contact pairs, current intensities and evoked effects are annotated in the events files.
High-density surface EMG (HDsEMG) recordings from the right tibialis anterior of a single healthy participant performing submaximal isometric ankle dorsiflexions at 10 to 70 percent of maximal voluntary contraction. Signals were acquired with two 64-electrode arrays (128 electrodes total) alongside force measurements. The dataset includes labeled motor unit spike trains derived from concurrent invasive EMG, and supports motor unit decomposition research.
This dataset contains 32-channel EEG recordings from 8 healthy participants performing a combined steady-state visual evoked potential (SSVEP) brain-computer interface task. Spatially overlapping arrow stimuli at a single location, flickering at distinct frequencies derived from an 85 Hz CRT refresh rate, encode four directions (up, down, left, right). Participants covertly attended to one direction per trial, and the data cover three stimulation and attention schemes across two experiments.
This dataset contains EEG recordings from 24 pairs of participants performing a 4-way categorisation task based on rules they first agreed upon together. Participants also completed pre- and post-tests on the same stimuli. The data were collected to investigate how collaborative rule learning promotes information alignment between interacting brains.
This dataset contains EEG recordings from 34 participants (one session each) who viewed 242 object images, 121 challenge and 121 control images, selected from comparisons between human behavioural performance and AlexNet. The study examines adaptive recruitment of cortex-wide recurrent processing during visual object recognition. The derivatives folder contains outputs of the decoding analyses, including time-resolved decoding accuracy matrices for object identity (.npz).
EEG recordings from 10 BCI-naive participants acquired with a low-cost consumer-grade device during a motor imagery versus rest protocol. Participants performed kinesthetic imagination of a grasping movement with the dominant hand and rest/idle conditions across five runs, including an initial real-movement run. EMG of the dominant hand was recorded for protocol control, supporting evaluation of affordable brain-computer interface systems.
EEG recordings from 20 participants performing a novel finger motor imagery paradigm in which cues for individual fingers were presented in random and sequential order blocks. The order of blocks was counterbalanced across participants. Data were acquired with a 65-channel g.tec system at 512 Hz and organized in BIDS format.
An example functional near-infrared spectroscopy (fNIRS) dataset from five participants performing a finger tapping task, organized according to the draft fNIRS BIDS specification. Participants tapped their left or right thumb to fingers, or rested as a control, in response to auditory cues, with sensors placed over the motor cortex and short channels attached. The dataset demonstrates conversion of NIRx recordings to BIDS using MNE-BIDS.
This dataset provides simultaneous EEG and fNIRS recordings from 12 participants performing a silent naming task and three sensory-based imagery tasks (visual, auditory, tactile) on objects from the semantic categories of animals and tools. It supports research on semantic decoding and brain-computer interfacing. Stimulus images and example Python scripts for loading the data with MNE and MNE-BIDS are included.