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Autopilot: Automating behavioral experiments with lots of Raspberry Pis

View ORCID ProfileJonny L. Saunders, View ORCID ProfileMichael Wehr
doi: https://doi.org/10.1101/807693
Jonny L. Saunders
University of Oregon, Institute of Neuroscience, Department of Psychology Eugene, OR 97403, United States
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Michael Wehr
University of Oregon, Institute of Neuroscience, Department of Psychology Eugene, OR 97403, United States
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  • For correspondence: wehr@uoregon.edu
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Abstract

Neuroscience needs behavior, and behavioral experiments require the coordination of large numbers of heterogeneous hardware components and data streams. Currently available tools strongly limit the complexity and reproducibility of experiments. Here we introduce Autopilot, a complete, open-source Python framework for behavioral neuroscience that distributes experiments over networked swarms of Raspberry Pis. Autopilot enables qualitatively greater experimental flexibility by allowing arbitrary numbers of hardware components to be combined in arbitrary experimental designs. Research is made reproducible by documenting all data and task design parameters in a human-readable and publishable format at the time of collection. Autopilot provides an order-of-magnitude performance improvement over existing tools while also being an order of magnitude less costly to implement. Autopilot’s flexible, scalable architecture allows neuroscientists to design the next generation of experiments to investigate the behaving brain.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted October 17, 2019.
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Autopilot: Automating behavioral experiments with lots of Raspberry Pis
Jonny L. Saunders, Michael Wehr
bioRxiv 807693; doi: https://doi.org/10.1101/807693
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Autopilot: Automating behavioral experiments with lots of Raspberry Pis
Jonny L. Saunders, Michael Wehr
bioRxiv 807693; doi: https://doi.org/10.1101/807693

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