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Brain imaging (fMRI, EEG), neural recordings, connectome, cognitive experiments, psychology
2,288 datasets
The Allen Institute for Brain Science - Synaptic Physiology Public Data Set is a large-scale survey describing the physiology of thousands of synapses. The data originates from patch clamp experiments conducted in mouse visual cortex and human middle temporal gyrus, measuring synaptic strength, kinetics, and short-term plasticity. It is hosted on the AWS Open Data platform.
Pipeline_omega23.py is a script published on Kaggle. The dataset's specific content, size, and structure are unknown from the provided metadata. Its nature and potential applications must be verified after download.
A Data Management and Sharing Plan outlines the scientific data to be generated and used for the research project 'Story Talk Kindergarten - Developing a Cognitive-based Vocabulary Intervention'. The plan describes a strategy for managing and sharing project data. The author is Annemarie Hindman, and the record was last updated on April 27, 2026.
Li Tengfei's Data Management and Sharing Plan outlines the scientific data to be generated and/or used for research on infant cognitive growth prediction. The plan describes a strategy for managing and sharing project data. It was last updated on 2026-04-27.
A Data Management and Sharing Plan outlines the strategy for handling scientific data from a research project on glucose instability and neurocognitive outcomes in older adults. The plan was authored by David Couper and harvested by ODUM for the Dataverse platform. It was last updated on April 27, 2026.
A Data Management and Sharing Plan authored by Ben Philpot, last updated on 2026-04-27. The plan describes the scientific data to be generated and/or used in research on preclinical testing of antisense oligonucleotide therapeutics with EEG. It outlines a strategy for managing and sharing the project's data.
The MegaScenes Dataset is a collection of around 430,000 scenes, featuring over 100,000 structure-from-motion reconstructions and over 2 million registered images. It includes a diverse array of scenes such as minarets, building interiors, statues, bridges, towers, religious buildings, and natural landscapes. The dataset was contributed by Cornell University and is available under a CC-BY-4.0 license.
Global AI Mega Data Centers 2026 likely contains information about large-scale artificial intelligence computing facilities worldwide. The dataset is published on Kaggle, but its author, organization, and specific creation date are unknown. Its columns and data volume are unspecified, requiring verification after download.
The dataset title references a 2026 time frame. It likely contains information on technology companies, such as SpaceX and OpenAI, that are speculated to undergo initial public offerings. The dataset is hosted on Kaggle, but its specific contents, size, and authorship are unknown.
ADHD200 Fmriprep is a neuroimaging dataset hosted on HuggingFace by user beotborry. It was last updated on May 11, 2026. The dataset likely contains preprocessed functional MRI (fMRI) scans, potentially from the ADHD-200 Consortium, which are used to study brain activity patterns.
A study by Gigi Luk of York University compared cognitive control performance across three participant groups. The dataset likely contains behavioral data from flanker tasks administered to 15 monolinguals, 15 bimodal bilinguals, and 15 unimodal bilinguals. Results trace the bilingual advantage in cognitive control to unimodal bilinguals' experience controlling two languages in the same modality.
Data from a study by Yuval Rottenstreich of the University of Chicago investigating the affective psychology of risk. The dataset likely contains experimental results comparing choices for affect-rich versus affect-poor outcomes across different probabilities, testing predictions of prospect theory.
Four experiments tested how consumers manage multiple debts using an incentive-compatible game. The study, by Moty Amar of Ono Academic College, found evidence of 'debt account aversion,' where participants consistently paid off small debts first despite higher interest rates on larger debts. The data likely contains experimental results on repayment choices, interest accumulation, and interventions tested.
Firn air samples from the Megadunes site in Antarctica were analyzed for O2/N2/Ar ratios and the isotopic composition of O2 and N2. The data was collected by a program led by Jeffrey Severinghaus at the Scripps Institution of Oceanography to study convection and gravitational fractionation in snow dunes. The specific temporal coverage and sample size are not provided in the input.
Mass-normalized magnetic susceptibility and rockmagnetic measurements from discrete subsamples of sediment cores collected during USAP cruises NBP10-01 and NBP12-03. The data were produced by the SCIOPS organization as part of the Larsen Ice Shelf System Antarctica (LARISSA) program. Study areas include the Larsen Ice Shelf embayments and several fjords and bays on the western Antarctic Peninsula.
Patricia Genius provides supplementary data from a study on sex-specific early cognitive changes linked to Alzheimer's genetic risk. The dataset includes variables related to polygenic risk scores, cognitive performance, and participant characteristics. It is a 1.3 MB ZIP file under a CC BY + CC0 license, last updated in March 2026.
A dataset of electroencephalography (EEG) signals, likely containing recordings of brain activity. It was published on Kaggle, but the specific collection date, size, and author are unknown. The data may be used for analyzing neural patterns or developing brain-computer interfaces.
EEG data likely contains recordings of brain electrical activity. The dataset is published on Kaggle, but specifics on its size, source, and collection date are unknown. The author and organization are not provided.
Alljoined 1.6M provides over 1.6 million electroencephalography (EEG) visual stimulus trials collected from 20 participants as part of the THINGS initiative. Created by the Alljoined team and documented in arXiv:2508.18571, it contains more than double the volume of the previous THINGS-EEG2 benchmark.
A multimodal dataset containing simultaneous electroencephalography, electrocardiography, and RGB video recordings from yoga practitioners and control participants. The data was collected during resting state, mind-wandering, and concentration tasks, with primary data in BrainVision format. The dataset was authored by alexeykashevnik and last updated on 2026-03-27.