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Brain imaging (fMRI, EEG), neural recordings, connectome, cognitive experiments, psychology
2,288 datasets
18 subjects listened to competing speech streams in simulated rooms with varying reverberation. The dataset contains EEG recordings from a 64-channel Biosemi system sampled at 512 Hz, alongside the original speech audio stimuli. It is organized for the COCOHA Matlab Toolbox and was collected to study noise-robust cortical tracking of attended speech.
Survey data examines how family life-cycle stages influence migrants' settlement intentions in Chinese mega-cities, linked to hukou reform policies. The dataset is 74.5 MB in size, stored as an XLSX file. It was uploaded by 'For Reviewer' to figshare and last updated in April 2026.
NeuroScore is a dataset of 17,175 text items scored by predicted human brain activation using Meta's TRIBE v2 brain encoding model. The model predicts fMRI responses based on training data from over 700 human subjects, providing activation scores across 6 cortical regions, a composite engagement score, and an emotion profile. The dataset was created by author tushar710 and last updated on Hugging Face in April 2026.
King Sound in northwestern Australia provides the geographic scope for this dataset on cross-bedded tidal mega-ripples. The dataset was published by the Australian Ocean Data Network, with a record last updated in April 2026. It is a legacy product for which a detailed abstract is not available.
A dataset containing health, lifestyle, and psychological indicators for detecting cognitive impairment. The data likely originates from community-based studies, though the specific geography is unspecified. It was uploaded to Kaggle by an unknown author.
Relative EEG power data, likely derived from electroencephalogram recordings. The dataset is hosted on Kaggle, but its specific source, collection method, and scale are not detailed in the available metadata. Further details such as the number of subjects, recording parameters, and the specific frequency bands analyzed require verification after download.
An EEG dataset published on Kaggle. The dataset likely contains electroencephalography recordings of brain activity. Specific details on size, collection method, and origin are not provided in the available metadata.
An R software package providing several cluster-robust variance estimators for linear regression models. It implements methods from Bell and McCaffrey (2002) and Pustejovsky and Tipton (2017), including bias-reduced linearization and small-sample corrections for hypothesis testing. The package author is James E. Pustejovsky.
A BIDS-compliant dataset contains structural and task-based functional MRI data from a study investigating neural responses. Participants viewed visual stimuli associated with dignity-related and non-dignity-related contexts while undergoing fMRI. The dataset was authored by xenificity and last updated on Hugging Face in April 2026.
Maps of global vegetation mega-biomes for two key paleoclimate periods: the Mid-Holocene (approximately 6000 years ago) and the Last Glacial Maximum (approximately 21000 years ago). The dataset, created by the SCIOPS organization for the Paleoclimate Modelling Intercomparison Project Phase II (PMIP2), groups observed biomes into broader functional units like tropical forest, savanna, and tundra to facilitate direct comparison with dynamic vegetation model outputs.
NeuroBrain-4Stage is an EEG dataset published on Kaggle. The dataset's title suggests it contains electroencephalography recordings, likely related to four distinct stages or conditions. Specific details on the number of subjects, recording duration, and collection methodology are not provided in the available metadata.
Kaggle hosts the EEGMMIDB dataset, which likely contains electroencephalogram (EEG) recordings. The dataset's title suggests a focus on motor movement and motor imagery tasks, common in brain-computer interface research. Specific details on data volume, collection methodology, and authorship are not provided in the available metadata.
EEG for ADHD is a dataset hosted on Kaggle. The dataset likely contains electroencephalogram (EEG) recordings related to Attention-Deficit/Hyperactivity Disorder. Metadata such as author, size, and specific collection details are currently unavailable.
EEG_DATASET_original_subjectwise is a collection of electroencephalography (EEG) brain signal recordings. The dataset is organized by individual subjects, suggesting a focus on per-participant analysis. It was published on the Kaggle platform, but details on the number of subjects, recording parameters, and collection methodology are not provided in the available metadata.
Images and data from a 2026 iScience publication by Prowse et al. The collection includes western blots of wild-type and mutant huntingtin expression in engineered human embryonic stem cells and live-cell imaging of BDNF endosomes and lysosomes in derived forebrain neurons. The dataset was authored by Adam G. Hendricks and last updated in April 2026.
84.4 MB of CSV files contain behavioral state variables and neuronal activity data for bumblebees. The data was collected by Inga Fuchs for a study on neural correlates of object and panorama matching. It was last updated in March 2026.
40 participants performed an overt naming experiment while their brain activity was recorded. Source estimated EEG data has been processed to remove gradient artifacts, ECG signals, and regressed signals near the eyes and upper jaw. This version does not include the independent component analysis (ICA) denoising step present in a related dataset.
Electroencephalography (EEG) data from 40 participants in an overt naming experiment. The data has been processed using a denoising pipeline that removed gradient artifacts, ECG signals, and regressed out signals near the eyes and upper jaw. It was authored by Adrian Gilmore and last updated on April 25, 2026.
25 participants' fMRI surface data from a covert naming experiment. The dataset contains statistical map files for each modeled effect per participant and group-averaged results, supporting research on repetition-related neural activity. It was authored by Adrian Gilmore and last updated in April 2026.
Analyzed fMRI surface data for 40 participants in an overt naming task from a study on repetition-related neural activity. The dataset contains statistical map files for each modeled effect per participant and group-averaged results. Author Adrian Gilmore contributed this data, which was last updated on April 25, 2026.