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 The aim of the project is to automate the analysis of videotaped studies of rodent behaviour, for use in drug discovery and functional genomics. It involves a partnership between the Wolfson Image Analysis Unit - one of the leading computer vision groups in the UK - and Cerebrus - an SME specialising in neuroscience, and providing state-of-the-art facilities for central nervous system (CNS) drug discovery, contract research and consultancy. Over the past 25 years, systematic studies of rodent
behaviour have become important in creating animal models of psychiatric and neurological
disorders such as anxiety, depression and Parkinson’s disease. Recent advances in
mouse genetics have created a similar and pressing need to characterise behaviour. The
complete mapping of the mouse genome has generated a large body of novel DNA sequence data
and it is now vital to assess the function of proteins coded for by specific DNA sequences
- functional genomics - both in normal and disease states. A powerful method of inferring
function from genetic sequence is the production of targeted (e.g. knockout) or random
(e.g. gene trap) mutations, followed by behavioural studies to establish the behavioural
consequences - the behavioural phenotype - of these mutations. This approach should
provide insight into the function of the mammalian central nervous system and lead to more
sophisticated animal models of disease. It will, however, require very large-scale
experimentation - hence, efficient methods of collecting and analysing data will be
essential. This has been shown to be important in creating sufficiently rich descriptions of behaviour to identify subtle phenotype variation in mouse mutants and to assess the effects of drugs in realistic rodent models of psychiatric and neurological disorders. Consequently, most analyses currently involve human observation and recording of behaviour, which is labour-intensive, subjective and prone to operator bias. We intend to apply methods of model-based image analysis, developed in the Wolfson Unit, to track animals in video sequences, recovering posture as well as position. In collaboration with Cerebrus, we have already conducted a small pilot study, which demonstrated the feasibility of the approach. We now plan to develop and test the elements of a complete automated system, capable of routine application to behavioural analysis. The research will address Priority Areas 1 (Sequence to function) and 3 (Understanding how CS and IT techniques can aid biological research) in the 1998 call for proposals under the joint research councils’ Bioinformatics Initiative. Leading edge computer vision techniques have not been applied previously to the problem of systematic behavioural analysis in laboratory animals, though there is growing interest in ‘understanding’ the behaviour of both humans and farm animals from video surveillance data. The proposed project should contribute to biological research by developing new tools for behavioural analysis and to computer vision research by extending existing model-based methods to deal with behaviour. The collaboration with Cerebrus - who are major users/developers of behavioural analysis for use in drug development for CNS disorders - should also ensure the industrial relevance of the work. The specific objectives of the research are to:
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