Noninvasive Tracking of Every Individual in Unmarked Mouse Groups Using Multi-Camera Fusion and Deep Learning

作     者：Feng Su Yangzhen Wang Mengping Wei Chong Wang Shaoli Wang Lei Yang Jianmin Li Peijiang Yuan Dong-Gen Luo Chen Zhang 

作者机构：Department of NeurobiologySchool of Basic Medical SciencesBeijing Key Laboratory of Neural Regeneration and RepairCapital Medical UniversityBeijing100069China Chinese Institute for Brain ResearchBeijing102206China State Key Laboratory of Translational Medicine and Innovative Drug DevelopmentNanjing210000China Peking-Tsinghua Center for Life SciencesAcademy for Advanced Interdisciplinary StudiesPeking UniversityBeijing100871China School of Life SciencesTsinghua UniversityBeijing100084China School of Biological Science and Medical EngineeringBeihang UniversityBeijing100191China The Key Laboratory of Developmental Genes and Human DiseaseInstitute of Life SciencesSoutheast UniversityNanjing210096JiangsuChina Institute for Artificial Intelligencethe State Key Laboratory of Intelligence Technology and SystemsBeijing National Research Center for Information Science and TechnologyDepartment of Computer Science and TechnologyTsinghua UniversityBeijing100084China School of Mechanical Engineering and AutomationBeihang UniversityBeijing100191China 

出 版 物：《Neuroscience Bulletin》 (神经科学通报（英文版）)

年 卷 期：2023年第39卷第6期

页      面：893-910页

核心收录：

学科分类：1002[医学-临床医学] 100205[医学-精神病与精神卫生学] 10[医学] 

基　　金：supported by grants from the National Key R&D Program of China(2017YFA0105201) the National Natural Science Foundation of China(81925011,92149304,31900698,32170954,and 32100763 the Key-Area Research and Development Program of Guangdong Province(2019B030335001) The Youth Beijing Scholars Program(015),Support Project of High-level Teachers in Beijing Municipal Universities(CIT&TCD20190334) Beijing Advanced Innovation Center for Big Data-based Precision Medicine,Capital Medical University,Beijing,China(PXM2021_014226_000026) 

主　　题：Noninvasive tracking Deep learning Multi-camera Mouse group Social interaction 

摘      要：Accurate and efficient methods for identifying and tracking each animal in a group are needed to study complex behaviors and social *** tracking methods(e.g.,marking each animal with dye or surgically implanting microchips)can be invasive and may have an impact on the social behavior being *** overcome these shortcomings,video-based methods for tracking unmarked animals,such as fruit flies and zebrafish,have been ***,tracking individual mice in a group remains a challenging problem because of their flexible body and complicated interaction *** this study,we report the development of a multi-object tracker for mice that uses the Faster region-based convolutional neural network(R-CNN)deep learning algorithm with geometric transformations in combination with multi-camera/multi-image fusion *** system successfully tracked every individual in groups of unmarked mice and was applied to investigate chasing *** proposed system constitutes a step forward in the noninvasive tracking of individual mice engaged in social behavior.