100 results for "Temporal Lobe" · page 3 of 10 · ranked by relevance
…mean amplitudes in six temporal intervals per channel ## Cross-Validation - **Method**: leave…
…nemar.on004200) # Temporal Scaling Twenty participants learned three temporal intervals. There were…
…The dataset primarily supports studies of auditory temporal processing, temporal pattern discrimination…
MIPDB is a multimodal neuroimaging resource comprising high-density EEG (128-channel, 500 Hz) and eye-tracking data collected from 111 participants spanning childhood to adulthood. Participants completed a standardized battery of cognitive and perceptual tasks including resting state, surround suppression, naturalistic viewing, contrast-change detection, sequence learning, and symbol search. This dataset enables investigation of information-processing maturation across human development.
…16 - 'Temporal/DD':21 - 'Temporal/DC':22 - 'Temporal/CC':23 - 'Temporal/AA…
…combination of the spatialpattern and temporalpattern stimuli. 5. sixcatloctemporal: color images of…
This dataset comprises raw magnetoencephalography (MEG) recordings, T1-weighted anatomical MRI scans, and behavioural logfiles collected during an audiovisual speech memory paradigm. Participants performed encoding, distractor, and retrieval tasks designed to probe theta oscillatory dynamics underlying audiovisual integration and memory replay of speech content. The data support analyses of neocortical and hippocampal theta oscillations reported in an associated Journal of Neuroscience publication.
This dataset comprises EEG recordings from 54 healthy participants performing a P300-based brain-computer interface speller task, designed to investigate BCI illiteracy. The study includes 62 EEG channels and 4 EMG channels sampled at 1000 Hz, with participants completing offline training and online test phases using a 36-symbol row-column speller paradigm. The dataset achieved 96.7% accuracy with an 11.1% BCI illiteracy rate, providing a comprehensive resource for evaluating P300-based BCI performance and individual differences in BCI competence.
This dataset comprises 64-channel EEG recordings from 7 participants performing an auditory imagery task, in which they imagined sounds associated with animals and tools following visual stimulus cues. The dataset is intended to support research on semantic decoding of imagined auditory content and brain-computer interface applications.
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