Behavior phenotyping using motion sensors

Research on animal models has been a key turning point for understanding the neural circuitry underlying behavior. Nevertheless, adequately capturing the complex behavior repertoire of animals is challenging as the traditional simple video-tracking approach loses rich dynamic information and more modern approaches can be computationally challenging. To overcome these limitations we propose the use of motion sensors to quantify behavior. Motion sensors allow the acquisition of high-resolution data with great accuracy and reproducibility at low computational costs. Even though there can be a high correlation between video-based and motion sensor data in certain situations they in fact provide very different results. Besides its potential in basic neuroscience, motion sensors may also provide an accessible and easily scalable way to evaluate the behavior of animal models in pre-clinical studies. We are using motion sensors to phenotype MitoPark mice, which progressively develop symptoms similar to Parkinson’s Disease (PD). We use this type of sensor to evaluate movement but also sleep patterns, aiming to uncover novel biomarkers of progressive degeneration of dopamine neurons (the neurons that are lost in PD).

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