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Brain imaging (fMRI, EEG), neural recordings, connectome, cognitive experiments, psychology
2,184 datasets
Electroencephalography (EEG) signals recorded from 11 subjects during a Steady-State Visually Evoked Potential (SSVEP) experiment. The data was captured using a 256-channel EGI 300 Geodesic EEG System at a sampling rate of 250 Hz, with visual stimulation at five distinct frequencies. The dataset was created by Spiros Nikolopoulos and is associated with an open-access technical report and a processing toolbox.
21 healthy participants completed an auditory oddball paradigm, with data recorded using a 64-channel EEG Biosemi system at the Queensland Brain Institute, Australia. The dataset is associated with a 2017 study by Garrido et al. and a 2018 methods paper by Harris et al. Analysis scripts are available on GitHub.
EEG spectrogram data from 14 patients undergoing propofol anesthesia infusion, published by Niklas Brake et al. in Nature Communications in 2024. The dataset contains computed spectrograms from the Cz recording electrode, with time encoded relative to the moment of loss of consciousness. It is provided to support the reproduction of figures from the associated manuscript.
5.5 KB of synthetic TLX score statistics generated by an agent-based model simulating future lunar missions. The dataset, created by Raymond Vera and shared under CC-BY-4.0, was last updated on 2026-05-27. It supports analysis of astronaut productivity and psychological well-being in simulated long-term space missions.
Raymond Vera's dataset contains average tension statistics from an agent-based model simulating social interactions for NASA's Artemis program. The model, created in 2026, uses a Monte Carlo approach with tens of thousands of iterations to explore astronaut productivity and psychological well-being on the Moon. It is a 5.5 KB Excel file.
A small dataset of 5.5 KB containing simulation results from an agent-based model of astronaut social interactions for the Artemis program. The model, created by Raymond Vera, uses a Monte Carlo approach with tens of thousands of iterations to explore trade-offs in productivity and psychological well-being. The data was last updated on 2026-05-27.
Raymond Vera's dataset from 2026 contains simulation results from an agent-based model exploring human factors in future lunar missions. The model, representing astronauts with cognitive and emotional states, uses Monte Carlo simulations to show trade-offs in productivity and psychological well-being. It was created to support mission planning for the Artemis program.
An agent-based model simulating social interactions and human factors for future lunar missions under the Artemis program. The model, created by Raymond Vera, uses a Monte Carlo approach with tens of thousands of iterations to explore trade-offs in productivity and psychological well-being. The dataset was last updated on 2026-05-27 and is shared under a CC-BY-4.0 license.
Raymond Vera created an agent-based model simulating social interactions and mission outcomes for future lunar bases under the Artemis program. The model uses a Monte Carlo approach with tens of thousands of iterations to explore trade-offs in productivity and psychological well-being. The dataset, last updated on 2026-05-27, contains simulation output data in an XLS format with a file size of 5.5 KB.
Raymond Vera's dataset, last updated May 27, 2026, contains simulation data from an agent-based model exploring human factors in future lunar missions. The 5.5 KB XLS file likely contains parameters and outputs from tens of thousands of Monte Carlo simulations of the Lunar Base ABM. The model uses an Agent_Astronaut framework with cognitive skills, emotional states, and personality traits to simulate social and environmental interactions for the Artemis IV and V missions.
An agent-based model simulates daily schedules and social interactions for astronauts in a future lunar base. The model uses a custom Agent_Astronaut framework with cognitive, emotional, and personality traits to explore mission outcomes. Created by Raymond Vera and shared under CC-BY-4.0, the dataset is a 9.5 KB Excel file.
Raymond Vera's dataset, last updated May 27, 2026, contains agent attributes for an agent-based model simulating social interactions and human factors in future lunar missions. The 5.5 KB XLS file models astronaut agents with cognitive skills, emotional states, and personality traits to explore factors affecting mission outcomes. Monte Carlo simulations with tens of thousands of iterations examine trade-offs in productivity and psychological well-being for missions like Artemis IV and V.
An agent-based model simulating astronaut interactions for the Artemis lunar missions. The dataset likely contains attributes for the Agent_Astronaut framework, including cognitive skills, emotional states, and personality traits. It was created by Raymond Vera and published on figshare under a CC-BY-4.0 license, with a last update in May 2026.
Agent attributes for a simulation of astronaut interactions in future lunar missions. The dataset was created by Raymond Vera and published on figshare under a CC-BY-4.0 license, with a last update recorded for May 2026. It is a small dataset, 5.5 KB in size, stored in an XLS file format.
Raymond Vera created an agent-based model simulating astronaut interactions for the Artemis program's Lunar Gateway and South Pole Base missions. The model, published on figshare in May 2026, uses a framework with cognitive, emotional, and personality traits to explore mission outcomes. Monte Carlo simulations consisting of tens of thousands of iterations analyze trade-offs in productivity and psychological well-being.
Moon Base agent attributes is a dataset created by Raymond Vera, last updated on 2026-05-27. It contains data from an agent-based model simulating astronaut interactions for the Artemis IV and V missions. The model uses an Agent_Astronaut framework with cognitive, emotional, and personality traits to explore factors affecting mission outcomes.
Raymond Vera created an agent-based model simulating astronaut interactions for the Artemis program. The model uses an Agent_Astronaut framework with cognitive, emotional, and personality traits to explore mission outcomes. The dataset, last updated in 2026, is a 5.5 KB Excel file containing the agent attributes for this simulation.
An Agent_Astronaut framework simulates social interactions and human factors for NASA's Artemis program. Monte Carlo simulations of tens of thousands of iterations explore trade-offs in productivity and psychological well-being for astronauts on the Lunar Gateway and South Pole Base. The 5.5 KB Excel file, created by Raymond Vera and last updated in 2026, uses agent-based modeling to help mission planners evaluate operational resilience.
A 5.5 KB Excel file containing data from an agent-based model simulating social interactions for future lunar missions like Artemis IV and V. The dataset, authored by Raymond Vera and last updated on 2026-05-27, likely contains parameters and outcomes from tens of thousands of Monte Carlo simulation iterations exploring trade-offs in productivity and psychological well-being.
21 healthy participants completed an auditory oddball paradigm, with data recorded at the Queensland Brain Institute, Australia, using a 64-channel EEG Biosemi system. The dataset is associated with a published methods paper and analysis scripts are available on GitHub. It was created for research into neural responses to predicted and unpredicted stimuli.