Deep-Learning Approach for Revealing Latent Behaviors in Mice: Development of Walking Trajectories Prediction Model and Applications

In neuroscience research, in vivo imaging techniques for mice are used to observe brain activity and link it to their behavior. Brain activity can often only be associated with observed behavioral outcomes. In other words, it is difficult to speculate on unmanifested behavior due to factors such as 'hesitation' in humans. When a prediction model can predict mice behavior, if brain activity is observed in a specific brain region during incorrect predictions, that would be strong evidence of unmanifest behavior. In this study, we developed a trajectory prediction model to predict the walking trajectory of mice as a prelude to the behavior prediction model. The prediction model was applied to the behavioral analysis of mice administered an anxiolytic drug (diazepam) or saline, revealing significantly different outcomes.