Ho, H;
Kejzar, N;
Sasaguri, H;
Saito, T;
Saido, TC;
De Strooper, B;
Bauza, M;
(2023)
A fully automated home cage for long-term continuous phenotyping of mouse cognition and behavior.
Cell Reports Methods
, 3
(7)
, Article 100532. 10.1016/j.crmeth.2023.100532.
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Abstract
Automated home-cage monitoring systems present a valuable tool for comprehensive phenotyping of natural behaviors. However, current systems often involve complex training routines, water or food restriction, and probe a limited range of behaviors. Here, we present a fully automated home-cage monitoring system for cognitive and behavioral phenotyping in mice. The system incorporates T-maze alternation, novel object recognition, and object-in-place recognition tests combined with monitoring of locomotion, drinking, and quiescence patterns, all carried out over long periods. Mice learn the tasks rapidly without any need for water or food restrictions. Behavioral characterization employs a deep convolutional neural network image analysis. We show that combined statistical properties of multiple behaviors can be used to discriminate between mice with hippocampal, medial entorhinal, and sham lesions and predict the genotype of an Alzheimer's disease mouse model with high accuracy. This technology may enable large-scale behavioral screening for genes and neural circuits underlying spatial memory and other cognitive processes.
| Type: | Article |
|---|---|
| Title: | A fully automated home cage for long-term continuous phenotyping of mouse cognition and behavior |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.crmeth.2023.100532 |
| Publisher version: | https://doi.org/10.1016/j.crmeth.2023.100532 |
| Language: | English |
| Additional information: | © 2023 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Alzheimer's disease, automated classification, home-cage system, longitudinal monitoring, machine learning, mouse behavioural cognitive testing, Mice, Animals, Cognition, Hippocampus, Alzheimer Disease, Computers, Behavior, Animal |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UK Dementia Research Institute HQ |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10174897 |
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