on005059
Paired Associates Learning: Memory for Word Pairs in Cued Recall
BEH iEEG
…so we have done the scaling to provide all voltage values in…
- Participants
- 72
- Size
- 167 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
Discover datasets
100 results for "temporal scaling" · page 3 of 10 · ranked by relevance
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- on007964
Disentangling objects' contextual associations from perceptual and conceptual attributes using time-resolved neural decoding
EEGThis dataset contains 128-channel EEG recordings from 20 observers (19 included in final analysis) viewing object images at 3.33 Hz to investigate how contextual associations, perceptual attributes, and conceptual properties of objects are represented in neural activity. One participant was excluded due to a technical error in EEG recording. Time-resolved neural decoding was applied to disentangle these distinct representational dimensions from the EEG signals.
- Participants
- 20
- Citations
- 2
- Size
- 18.9 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004809
Categorized Free Recall: Delayed Free Recall of Word Lists Organized by Semantic Categories
BEH iEEG…so we have done the scaling to provide all voltage values in…
- Participants
- 258
- Citations
- 1
- Size
- 477 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004843
T16
EEGT16 is an EEG neuroimaging dataset containing electroencephalography recordings organized according to the Brain Imaging Data Structure (BIDS) standard version 1.8.0. The dataset includes hierarchical event descriptors (HED) version 8.1.0 for detailed annotation of experimental events and conditions. The dataset comprises 185 files totaling 8.2 GB of EEG data with standardized metadata and event annotations to support reproducible neuroscience research.
- Participants
- 14
- Channels
- 64 (10-10)
- HED
- v8.1.0
- Size
- 7.66 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004706
Spatial memory and non-invasive closed-loop stimulus timing
BEH EEGThis dataset contains behavioral events and electrophysiological recordings from a hybrid spatial-navigation and free recall experiment conducted at the University of Pennsylvania (2021-2022). Participants performed a virtual courier task delivering items across a town, followed by recall testing. The experiment comprised two phases: read-only sessions for generating classifier training data, and closed-loop sessions where stimulus presentation timing was optimized based on real-time neural predictions of memory encoding. The dataset supports investigation of spatial memory dynamics and the efficacy of classifier-based closed-loop stimulation for memory enhancement.
- Participants
- 34
- Channels
- 128 (biosemi)
- Citations
- 5
- Size
- 1.30 TB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004252
Rotation-tolerant representations elucidate the time course of high-level object processing
EEGThis dataset contains EEG recordings from 16 participants viewing object images presented in eight different 2-D rotations, using rapid visual streams at two presentation rates (5 Hz and 20 Hz). The data support investigation of rotation-tolerant object representations and the time course of high-level visual object processing. EEG data are formatted according to the BIDS standard.
- Participants
- 16
- Size
- 18.3 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on005411
Free Recall of Word Lists with Repeated Items
BEH iEEG…We have completed the scaling to provide values in V. #### Contact For…
- Participants
- 48
- Size
- 157 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on003922
Multisensory Correlation Detector
ANAT MEG…16 - 'Temporal/DD':21 - 'Temporal/DC':22 - 'Temporal/CC':23 - 'Temporal/AA…
- Participants
- 14
- Citations
- 27
- Size
- 75.7 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on006563
Dimension-based attention modulates early visual processing
EEGThis dataset contains continuous 64-channel scalp EEG recordings from 12 right-handed subjects performing a visual attention task designed to examine dimension-based attentional modulation of early visual processing. The data include independent component analysis (ICA) decompositions with expert-annotated component labels, originally collected for a study on visual attention and later reused for research on automatic classification of independent components. The dataset was converted to BIDS format from the original recordings with permission from the original authors.
- Participants
- 12
- Channels
- 64 (10-10)
- Citations
- 35
- Size
- 5.63 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004123
BCIT Traffic Complexity
EEGThis dataset contains EEG, eye-tracking, and vehicle performance data collected during the BCIT Traffic Complexity study, in which subjects performed a simulated driving task under varying visual complexity and perturbation frequency conditions. The study aimed to identify biomarkers of driver fatigue by comparing EEG-based predictive algorithms to objective performance measures and subjective fatigue scales. Data collection took place at Teledyne Corporation in Durham, NC, and is related to companion datasets on Baseline Driving and Calibration Driving tasks.
- Participants
- 29
- Channels
- 64 (10-10)
- Citations
- 39
- HED
- v8.0.0
- Size
- 17.5 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026