The ToMCAT Dataset

Welcome to the ToMCAT dataset! The dataset currently is served via a single SQLite database, but we may add additional ones in the future.

For users who are not familiar with SQL, we will provide some sample SQL queries to demonstrate how to use this database and the associated Datasette interface.

For more advanced users, feel free to try different queries, use the programmatic APIs provided by Datasette, or simply download the whole SQLite database. Note that queries that take too long to execute (i.e., > 10 seconds) will be aborted, in order to keep the site running smoothly. If you would like to perform such complex queries, we recommend downloading the database locally to perform them.

The entity relationship diagram describing the database schema diagram is available here: ERD diagram.

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If you use this dataset, please cite our NeurIPS 2023 paper that introduces the dataset.

BibTeX Format

        title={The To{MCAT} Dataset},
            Adarsh Pyarelal
            and Eric Duong
            and Caleb Jones Shibu
            and Paulo Soares
            and Savannah Boyd
            and Payal Khosla
            and Valeria Pfeifer
            and Diheng Zhang
            and Eric S Andrews
            and Rick Champlin
            and Vincent Paul Raymond
            and Meghavarshini Krishnaswamy
            and Clayton Morrison
            and Emily Butler
            and Kobus Barnard
        booktitle={Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track},

APA Format

Adarsh Pyarelal, Eric Duong, Caleb Jones Shibu, Paulo Soares, Savannah Boyd, Payal Khosla, Valeria Pfeifer, Diheng Zhang, Eric S Andrews, Rick Champlin, Vincent Paul Raymond, Meghavarshini Krishnaswamy, Clayton Morrison, Emily Butler, & Kobus Barnard (2023). The ToMCAT Dataset. In Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track.


973,223,862 rows in 23 tables

eeg_raw, gaze_raw, fnirs_sync, gsr_sync, eeg_sync, ...

Funding Acknowledgment

  • The creation of this dataset was funded by the Army Research Office and was accomplished under Grant Number W911NF-20-1-0002. The grant was awarded through the Defense Advanced Research Projects Agency (DARPA).
  • We would also like to acknowledge intramural seed funding from the University of Arizona's SensorLab.
  • Continued support (documentation updates, replying to questions from dataset users, etc.) is supported by Army Research Office (ARO) Award Number W911NF-24-2-0034.