Development of a 3D tracking system for multiple marmosets under free-moving conditions.
Terumi YurimotoWakako KumitaKenya SatoRika KikuchiGohei OkaYusuke ShibukiRino HashimotoMichiko KamiokaYumi HayasegawaEiko YamazakiYoko KurotakiNorio GodaJunichi KitakamiTatsuya FujitaTakashi InoueErika SasakiPublished in: Communications biology (2024)
Assessment of social interactions and behavioral changes in nonhuman primates is useful for understanding brain function changes during life events and pathogenesis of neurological diseases. The common marmoset (Callithrix jacchus), which lives in a nuclear family like humans, is a useful model, but longitudinal automated behavioral observation of multiple animals has not been achieved. Here, we developed a Full Monitoring and Animal Identification (FulMAI) system for longitudinal detection of three-dimensional (3D) trajectories of each individual in multiple marmosets under free-moving conditions by combining video tracking, Light Detection and Ranging, and deep learning. Using this system, identification of each animal was more than 97% accurate. Location preferences and inter-individual distance could be calculated, and deep learning could detect grooming behavior. The FulMAI system allows us to analyze the natural behavior of individuals in a family over their lifetime and understand how behavior changes due to life events together with other data.
Keyphrases
- deep learning
- machine learning
- artificial intelligence
- convolutional neural network
- loop mediated isothermal amplification
- depressive symptoms
- label free
- cross sectional
- electronic health record
- real time pcr
- big data
- mental health
- white matter
- cerebral ischemia
- bioinformatics analysis
- brain injury
- subarachnoid hemorrhage