Award details

Machine Intelligence for Neuroscience Experimental Control

ReferenceBB/W019132/1
Principal Investigator / Supervisor Professor Thomas Mrsic-Flogel
Co-Investigators /
Co-Supervisors
Dr Joaquin Rapela, Professor Maneesh Sahani
Institution University College London
DepartmentSainsbury Wellcome Centre
Funding typeResearch
Value (£) 708,152
StatusCurrent
TypeResearch Grant
Start date 01/01/2023
End date 31/12/2025
Duration36 months

Abstract

To understand the brain, scientists aim to explain how animal behaviour relates to neural activity. This requires the design and precise control of behavioural experiments, wherein animals perform particular tasks while experimenters either record or manipulate neural activity in specific neural circuits. Such experiments require data acquisition software that integrates and controls hardware from multiple recording devices (cameras, electrodes, sensors), and analysis tools that can interpret large and complex datasets. Progress is held back by the lack of standardised tools for design and implementation of experimental protocols, and the difficulty of integrating state-of-the-art data processing and neuroinformatics into custom experimental designs. The fields of behavioural and brain sciences have consequently suffered from both inefficiency and poor reproducibility, due to disparate data acquisition and analysis solutions created independently across laboratories. To address these challenges, we propose to extend, enhance, maintain and support \textbf{Bonsai}, a fully integrated software environment to enable cutting-edge reproducible systems neuroscience experiments using animal models, with a particular emphasis on machine-intelligence-enabled, real-time neuroinformatics methods. While Bonsai is already adopted by hundreds of scientists worldwide, we aim to extend Bonsai's functionality with a toolbox of online and offline Machine Intelligence tools for analysis of behavioural and neural data (video-based analysis of behavioural motifs, real-time and offline analysis of neural signals), and create an open-access platform for software sharing and integration with multiple programming languages. Enhancing Bonsai's ecosystem will be a game-changer for behavioural and brain science experiments by enabling new types of research, increasing and diversifying user base, and dramatically improve efficiency and reproducibility of research.

Summary

Understanding the brain and the behaviour it generates is a major scientific challenge of our era. To succeed, scientists must be able to explain how animal behaviour relates to neural activity across different brain regions. This requires careful design and manipulation of behavioural experiments, where experimenters either record or manipulate neural activity while the animals (e.g. non-human primates, rodents, fish, insects) engage in specific behaviours which need to be carefully observed and quantified. Experiments in behavioural and brain science laboratories require software that integrates and controls hardware from multiple recording devices (video, electrodes for neural activity measurement, sensors), and analysis tools that can interpret large and complex behavioural and neural datasets. Scientists studying brain and behaviour dedicate the majority of their time designing experiments and analysing the data, with least time spent on data acquisition itself, which may impact the quality of data. Moreover, hundreds of neuroscience research groups worldwide develop their own experimental and analytical tools, most using different programming languages, leading to inefficiencies in data sharing and analysis, and impacting reproducibility (i.e. how easy it is for someone else to repeat the same experiment). Here we propose to provide the scientific community with a software tool that will dramatically increase the efficiency of experimental control and data analysis. We will do so by developing a new set of functionalities to an existing software platform, Bonsai. Bonsai is a fully integrated software environment that emphasises performance, flexibility, and ease-of-use, allowing scientists with no previous programming experience to quickly develop their own high-performance data acquisition and experimental control systems. Thus far, Bonsai has been adopted by hundreds of scientists worldwide to provide interactive experimental control in behavioural and brain sciences. In this proposal, we aim to extend Bonsai's functionality with a toolbox of online and offline Machine Intelligence tools for analysis of behavioural and neural datasets, and to create an open-access platform for software sharing. Bonsai's enhanced functionality will enable new types of research, and speed up discovery and improve efficiency by (i) providing access to such tools to laboratories lacking expertise, (ii) reducing the need to reinvent the same tools in multiple labs and (iii) standardising the data processing streams, thus increasing reproducibility across laboratories. We believe this effort will enable and accelerate new discoveries in how the brain generates behaviour.
Committee Research Committee A (Animal disease, health and welfare)
Research TopicsX – not assigned to a current Research Topic
Research PriorityX – Research Priority information not available
Research Initiative Bioinformatics and Biological Resources Fund (BBR) [2007-2015]
Funding SchemeX – not Funded via a specific Funding Scheme
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