Ensuring NHP welfare through in-cage cognitive testing and remote sensing of physiological parameters

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Neuroscientific experiments in NHPs typically involve a set of experimental procedures rarely found in other areas of research. In this project we work towards a systematic quantification of their potential effects on animal welfare in NHPs, with a focus on fluid control, movement restraint, and putative cumulative severity due to long-term participation in experiments. We already made important progress towards our long-term goal of improving the welfare of NHPs in neuroscience research. First, by measuring the daily fluid uptake of captive rhesus monkeys, we show substantial intra- and inter-individual variability and conclude that simple normalization models (fluid volume per animal weight) are not well suited for describing fluid consumption behaviour in rhesus monkeys. Second, we used and advanced our automated cage-based testing system to demonstrate the possible reduction of movement restraints in certain phases of the behavioural training of animals. Third, we developed a database for registering experimental, behavioural and physiological parameters of animals from different labs over long periods of time with tools for standardized data collection across labs. Forth, as a proof-of-concept, we quantified short-term salivary cortisol responses in different exper-imental conditions and developed an SOP for sampling longer-term hair cortisol measures. For the renewal project, we propose to make our cage-based testing system most similar to conventional experimental settings regarding interfaces and behavioural control by adding new technical features and advanced algorithms for automated behavioural training. With the latter we will characterize the variability and commonalities in learning behaviour of rhesus monkeys trained on cognitive tasks in their cages. Further, we will systematically collect physiological parameters from several labs in our database and run meta-analyses on the data to identify welfare-relevant biomarkers.