The assessment of mouse spontaneous locomotor activity using motion picture

Abstract

Spontaneous locomotor activity (SLA) is a useful parameter reflecting physical and mental status of experimental animals. Here we aimed to establish a novel and simple method to assess mouse SLA using motion picture. Movement of C57BL/6 mice was continuously recorded by an infrared video camera connected with a single board computer. The geometric center of mouse outline in each frame was calculated using an image processing library, OpenCV in a programming language Python. Moving distance of the geometric center every second was utilized as an index of mouse SLA. Twenty-four hours assessment of SLA showed that mice repeated active and resting phase. Mice moved more actively during the dark period compared with the light period. Time-frequency analysis of SLA followed by unsupervised clustering classified their active and resting phase. Administration of a sedative, chlorpromazine (5 mg/kg) abolished mouse SLA for 8 h. In contrast, administration of a central nervous stimulant, caffeine (25 mg/kg) increased SLA for 3 h. In conclusion, we here established the automatic measurement system of mouse SLA using motion picture. This system is composed of common equipment and analysis software written in freely available programming language. We also confirmed that it is applicable for drug assessment.