Topic: Bayesian Gaussian Mixture Model

The ability to learn and adapt to cognitive demands is vital for survival, and mice serve as valuable models in neuroscience for studying these processes. In this study, we introduce a novel maze framework to investigate learning and adaptability in mice, specifically focusing on humanized App knock-in models of Alzheimer's disease. The maze mimics decision-making scenarios, similar to when foraging, with an optimal reward path leading to a target with sucrose pellets. Decision nodes introduce off-reward routes to dead-ends or loops, creating a challenge requiring mice to balance exploration w