An international research collaboration has developed a VR imaging system that can measure a wide range of neural activity in the cortices of mice during active behavior. This enabled them to illuminate the abnormalities in cortical functional network dynamics that are found in autism model mice. Using machine learning, they were also able to highly accurately distinguish between autism model mice and wild-type mice based on the cortical functional network patterns when the mice start or stop running. The results of this research have been published in Cell Reports on March 28. The research group was led by Professor Toru Takumi and Assistant Professor Nobuhiro Nakai (both of the Department of Physiology, Kobe University Graduate School of Medicine), and Masaaki Sato, (Lecturer, Department of Pharmacology, Graduate School of Medicine, Hokkaido University).