100 results for "spatial filtering" · page 3 of 10 · ranked by relevance
…Two-stage visual speller using covert spatial attention and non-spatial feature…
…bandpass filtering, downsampling - **Bandpass filter**: {'low_cutoff_hz': 0.05, 'high_cutoff…
Imported from OpenNeuro ds004362
…bandpass filtering (5-48 Hz), notch filtering (50 Hz), artifact removal (AMUSE…
This dataset comprises high-density diffuse optical tomography (HD-DOT) neuroimaging data from 5 participants performing functional localizer and naturalistic movie viewing tasks. Data are provided in SNIRF format with optode positions and anatomical landmarks registered to subject-specific head models, enabling investigation of brain function during audiovisual stimulation using optical neuroimaging methods.
This magnetoencephalography (MEG) dataset comprises recordings from 10 participants performing a human visual motion area (hMT+) localizer task involving passive viewing of coherent and incoherent moving dot stimuli. The dataset includes concurrent anatomical MRI scans and auxiliary physiological recordings (EOG, ECG), formatted according to MEG-BIDS standards. The data were acquired to investigate visual perceptual learning and motion perception mechanisms.
…Preprocessing included 5th-order Butterworth bandpass filtering (8-70 Hz), 60 Hz…
THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.
…These include higher signal sensitivity, improved spatial resolution, and more uniform scalp…
A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing motor imagery tasks. The dataset comprises 2,520 trials across 63 sessions, with participants performing left and right hand motor imagery in response to visual cues. Recorded at 1000 Hz using a 64-channel EEG montage with standardized electrode placement, this dataset supports brain-computer interface research and analysis of ocular activity patterns during motor imagery paradigms.