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Brain imaging (fMRI, EEG), neural recordings, connectome, cognitive experiments, psychology
2,285 datasets
Source estimated EEG data from 40 participants in an overt naming experiment. The data has been processed using a complete denoising procedure including gradient artifact and ECG removal, plus regression of signals near the eyes and upper jaw. The dataset was authored by Adrian Gilmore and last updated on April 25, 2026.
EEG spectral power density data was calculated using the PWelch function in Matlab from recordings in two animal cohorts (C and D). The dataset includes measurements from frontal (ch1) and occipital (ch2) derivations under baseline and sleep deprivation conditions. An accompanying information file provides details on the baseline and sleep deprivation experiments.
Supporting data for the manuscript 'Rapid, Growth Factor-Reduced Differentiation of Functional Neurons from hiPSCs.' The dataset contains raw and processed files from differentiation, characterization, and functional assessment experiments. It was contributed by Natalie Parker of the Iyer Lab and last updated on April 27, -2026.
ST-CORE-TOKENS is an ultra-refined, high-density tokenized dataset developed by SKT AI LABS. The dataset is intended for training Indian large language models and is described as containing distilled logic. It was last updated on the platform in April 2026.
Omegamax-weights is a dataset of model parameters published on Kaggle. The dataset likely contains the learned weights for a machine learning model, possibly related to the Sberbank platform. Specific details regarding the model architecture, training data, and performance are unavailable from the provided metadata.
Megamax-weights is a dataset of model weights published on Kaggle. The dataset's specific architecture, training data, and performance characteristics are not detailed in the available metadata. Its content and intended application must be verified after download.
Juan Chen's dataset, updated in April 2026, supports research on how individuals learn to use Generative AI. It examines dual pathways: cognitive-utility factors like task-technology fit and socio-affective factors like emotion and appraisal. The data likely contains survey measures related to behavioral intention and learning outcomes.
EEG_Dataset is a collection of electroencephalogram data shared on Kaggle. The dataset's specific size, recording parameters, and subject details are not provided in the available metadata. Its content and structure require verification after download.
Juan Moises de la Serna compiled this integrated database in 2026, synthesizing molecular biomarkers, neuroimaging metrics, and clinical progression scales for Alzheimer's, Parkinson's, and Multiple Sclerosis. The data covers research and clinical reports published between 2013 and 2026, focusing specifically on neuroinflammatory mechanisms across these three conditions.
76,831 user queries annotated with complexity labels (easy, medium, or hard) to indicate the cognitive effort required for an answer. The dataset was created by regolo.ai to train a LoRA adapter for the Brick Semantic Router. It was last updated on Hugging Face in April 2026.
These data show responses to sensory stimulation in the nodulus/uvula region of the cerebellum. The dataset contains sensitivity to motion data for Purkinje cells in response to motion in anteroposterior and mediolateral directions. It also includes gain coefficients for velocity, acceleration, and jerk kinematic terms, which could be used for additional computations on neuron responses.
MATLAB scripts and simulated data from a review paper comparing Bayesian solvers for EEG distributed source models. The dataset includes inversion methods like Weighted Minimum Norm Estimate and Conditional Laplace, along with visualization scripts and simulated observations. Author Joonas Lahtinen published this resource on Harvard Dataverse in April 2026.
Geoscience Australia data documents cross-bedded tidal mega-ripples in King Sound, northwestern Australia. The dataset likely contains geospatial and multimedia records related to coastal and marine geology. Its content appears to be a legacy product with associated documentation in PDF and HTML formats.
13.5 KB of tabular data in XLS format, showing correlations between Diffusion Tensor Imaging (DTI) metrics and cognitive impairment, filtered for statistical significance (p < .05). The dataset was authored by Marlon Gonzales and last updated on April 8, 2026, under a CC-BY-4.0 license.
A dataset titled 'boss_megalith' is hosted on Kaggle. The dataset's content is inferred to relate to megalithic structures or archaeological sites. No further metadata on its origin, size, or specific contents is provided.
57 studies published between 2020 and 2025 were integrated for this systematic review. The text document analyzes neuroplastic mechanisms in substance use disorder and brain recovery, authored by Roberto Estrada-Medina and last updated in March 2026. The review identifies alterations in synaptic density, BDNF signaling, and neuroimaging changes, along with four core therapeutic domains.
EEG-MSST-TFMaps likely contains electroencephalogram data transformed into time-frequency representations. The dataset is hosted on Kaggle, but its author, organization, and creation date are unknown. Its exact size, format, and specific content require verification after download.
EEG-EA-TFMaps likely contains electroencephalography data processed into time-frequency representations. The dataset is hosted on Kaggle, but specifics on size, source, and collection date are unknown. Its title suggests it may be used for analyzing brain signal patterns.
A curated dataset for training AI models on psychology and mental health conversations. It was cleaned and filtered from multiple public HuggingFace datasets by author nayaksomkar, with a last recorded update in April 2026. The data is optimized for fine-tuning mental health chatbots.
38 participants aged 18–35 contributed over 31 hours of EEG recordings during sleep, paired with verbatim dream reports and AI-generated images derived from those reports. The dataset was created by opsecsystems and last updated on April 6, 2026. It is described as the world's first multimodal resource linking these three data types for research at the intersection of neuroscience, psychology, and artificial intelligence.