100 results for "Temporal Lobe" · page 9 of 10 · ranked by relevance
This dataset contains physiological EEG recordings organized according to the BIDS standard, focused on capturing motion-related artifacts during EEG acquisition. It is derived from a source OpenNeuro dataset and formatted using MNE-BIDS tools to facilitate reproducible analysis of physiological artifacts in EEG signals.
This dataset contains behavioural and EEG hyperscanning data collected from 32 pairs of participants performing a musical joint action task. The data were collected to examine cognitive and neural signals underlying the sense of joint agency during synchronized musical performance. Each pair's data includes behavioural ratings and synchronization measures alongside dual-participant 64-channel EEG recordings in BrainVision format.
…The study is designed to temporally isolate and measure the neural correlates…
This dataset comprises simultaneous EEG, fMRI, and diffusion-weighted imaging (DWI) recordings from 28 healthy adults performing a sustained attention gradual-onset continuous performance task (gradCPT), along with resting-state, checkerboard, and imagery task data. The dataset supports multimodal investigation of sustained attention and its neural correlates using combined electrophysiological, hemodynamic, and structural connectivity measures.
…spatio-temporal features, averaged voltages within time windows - **Frequency bands**: alpha=[7…
This dataset contains EEG recordings from 14 healthy participants performing a covert attention task with real-time neurofeedback based on alpha power lateralization. The study investigates whether real-time EEG feedback on alpha power lateralization can lead to behavioral improvements in a covert attention task, employing a single-blinded crossover design comparing real versus sham feedback conditions across three recording sessions.
…Synchronization between devices and laptop 3. **Temporal alignment**: Left/right wristband sample…
BigP3BCI Study P is a P300-based brain-computer interface dataset comprising EEG recordings from 19 healthy subjects across 2 sessions each, using a 9x8 character grid spelling paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with target and non-target visual stimuli annotated using HED 8.4.0 schema. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset, and is optimized for machine learning applications in BCI research.
…CNN spatial filtering (8x1 kernel, 16 filters), CNN temporal filtering (1x32 kernel…
…under ambulatory conditions, with trials temporally divided into training, validation, and test…