Topic: immobility

Many neuroscience experiments involve manual scoring of animal behavior by a human operator. This operation is time consuming, is liable to bias and hinders reproducibility. For these reasons, automatic systems to score animal behavior from videos have gained increasing attention in recent years. Here, we present a machine learning approach to automatically score behavior in the Forced Swim Test (FST). During FST, animals perform three different behaviors: climbing, swimming and immobility. So far, these behaviors have been evaluated by an operator (a bias-prone method) or using automatic syst