Topic: swimming

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

The ability to maintain a stable state in the presence of perturbations, known as robustness, is a defining feature of living systems. Most animals demonstrate adaptability by adjusting their position when confronted with external stimuli, a crucial skill for survival. How the brain dynamically regulates behavior in response to a changing environment remains a fundamental question in neuroscience. We investigated it using Danionella cerebrum, the smallest known vertebrate amenable to brain-wide functional imaging at cellular resolution across all developmental stages. We developed a 2D virtual