Bayesian Brain

The "Bayesian brain" hypothesis posits that the brain operates by performing Bayesian inference, constantly updating internal models of the world based on sensory input and prior knowledge. Current research focuses on developing computational models, such as hierarchical Bayesian models and energy-based models, to simulate this process, often incorporating concepts like hierarchical temporal abstractions and neural sampling to improve efficiency and accuracy. This framework offers a powerful lens for understanding various cognitive functions, including perception, decision-making, and time perception, and has implications for advancing artificial intelligence and robotics through the development of more robust and adaptable systems.