Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments

Author:

Akam Thomas12ORCID,Lustig Andy3ORCID,Rowland James M4ORCID,Kapanaiah Sampath KT5,Esteve-Agraz Joan6,Panniello Mariangela47,Márquez Cristina6ORCID,Kohl Michael M47ORCID,Kätzel Dennis5,Costa Rui M28ORCID,Walton Mark E19ORCID

Affiliation:

1. Department of Experimental Psychology, University of Oxford

2. Champalimaud Neuroscience Program, Champalimaud Centre for the Unknown

3. Janelia Research Campus, Howard Hughes Medical Institute

4. Department of Physiology Anatomy & Genetics, University of Oxford

5. Institute of Applied Physiology, Ulm University

6. Instituto de Neurociencias (Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas)

7. Institute of Neuroscience and Psychology, University of Glasgow

8. Department of Neuroscience and Neurology, Zuckerman Mind Brain Behavior Institute, Columbia University

9. Wellcome Centre for Integrative Neuroimaging, University of Oxford

Abstract

Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends, we developed pyControl, a system of open-source hardware and software for controlling behavioural experiments comprising a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high-throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier, and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features. Here, we outline the system’s design and rationale, present validation experiments characterising system performance, and demonstrate example applications in freely moving and head-fixed mouse behaviour.

Funder

Wellcome Trust

Ministerio de Ciencia e Innovación

Generalitat Valenciana and European Union

Else-Kroner-Fresenius-Foundation/German-Scholars-Organization

Deutsche Forschungsgemeinschaft

Human Frontiers Science Programme

National Institutes of Health

H2020 European Research Council

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference40 articles.

1. Point_Grey_Bonsai_multi_camera_acquisition;Akam,2020

2. pyControl / manuscript;Akam,2021

3. The Anterior Cingulate Cortex Predicts Future States to Mediate Model-Based Action Selection;Akam;Neuron,2021

4. Layer-specific integration of locomotion and sensory information in mouse barrel cortex;Ayaz;Nature Communications,2019

5. 1,500 scientists lift the lid on reproducibility;Baker;Nature,2016

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