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

eLife

Rui M Costa¹  Thomas Akam²  Mark E Walton³  James M Rowland⁴  Michael M Kohl⁵  Mariangela Panniello⁵  Dennis Kätzel⁶  Sampath KT Kapanaiah⁶  Joan Esteve-Agraz⁷  Cristina Márquez⁷  Andy Lustig⁸ 

[1] Champalimaud Neuroscience Program, Champalimaud Centre for the Unknown, Lisbon, Portugal;Department of Neuroscience and Neurology, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States;Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom;Champalimaud Neuroscience Program, Champalimaud Centre for the Unknown, Lisbon, Portugal;Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom;Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom;Department of Physiology Anatomy & Genetics, University of Oxford, Oxford, United Kingdom;Department of Physiology Anatomy & Genetics, University of Oxford, Oxford, United Kingdom;Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom;Institute of Applied Physiology, Ulm University, Ulm, Germany;Instituto de Neurociencias (Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas), Sant Joan d’Alacant, Spain;Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States;

关键词: Behaviour;    open source;    Software;    Hardware;    Mouse;   

DOI  :  10.7554/eLife.67846

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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.

【 授权许可】

CC BY