An automated maze task for assessing hippocampus-sensitive memory in mice ^☆

Highlights

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  Alternation procedures in rodents are highly sensitive to manipulations of the hippocampus.

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  However as they require hand testing, they are low throughput and stressful for the animal.

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  An automated maze was developed for assessing alternation performance in mice.

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  Alternation performance was shown to be impaired in mice with lesions to the hippocampus.

Abstract

Memory deficits associated with hippocampal dysfunction are a key feature of a number of neurodegenerative and psychiatric disorders. The discrete-trial rewarded alternation T-maze task is highly sensitive to hippocampal dysfunction. Normal mice have spontaneously high levels of alternation, whereas hippocampal-lesioned mice are dramatically impaired. However, this is a hand-run task and handling has been shown to impact crucially on behavioural responses, as well as being labour-intensive and therefore unsuitable for high-throughput studies. To overcome this, a fully automated maze was designed. The maze was attached to the mouse's home cage and the subject earned all of its food by running through the maze. In this study the hippocampal dependence of rewarded alternation in the automated maze was assessed. Bilateral hippocampal-lesioned mice were assessed in the standard, hand-run, discrete-trial rewarded alternation paradigm and in the automated paradigm, according to a cross-over design. A similarly robust lesion effect on alternation performance was found in both mazes, confirming the sensitivity of the automated maze to hippocampal lesions. Moreover, the performance of the animals in the automated maze was not affected by their handling history whereas performance in the hand-run maze was affected by prior testing history. By having more stable performance and by decreasing human contact the automated maze may offer opportunities to reduce extraneous experimental variation and therefore increase the reproducibility within and/or between laboratories. Furthermore, automation potentially allows for greater experimental throughput and hence suitability for use in assessment of cognitive function in drug discovery.