Explore a comprehensive lecture on advanced recurrent neural network models in cognitive neuroscience. Delve into Dr. Guangyu Robert Yang's insights on using machine learning-trained RNNs to explain complex behavior and neural activity patterns. Discover how these models generate rapid mechanistic hypotheses for cognitive computations and combine biological knowledge with computational goals. Examine the challenges faced in early works and learn about recent advancements in building next-generation RNN models. Investigate topics such as multi-task learning, continual learning, short-term memory mechanisms, and the development of multi-area models. Gain valuable perspectives on the future of artificial neural networks in understanding brains and minds.