0:00 / 0:00
research
What AI can teach us about how our brains map our world, with Quinn Lee and Marlos C. Machado
Amii21 July 2026Watch on YouTube
Description
How do we know where we are, and where we are going? While we use our eyes to take in the information, it is our brains that are doing the heavy computing as we navigate the world. Now, new research using machine learning models is perhaps giving us a glimpse into what is going on inside our minds, and how the cells needed to navigate the world might form. On this episode of Approximately Correct, we are joined by two Amii Fellows and Canada CIFAR AI Chairs — Marlos C. Machado and Quinn Lee — who combined their expertise in machine learning and neuroscience to better understand the mysteries of navigation.
What you'll learn
- Machine learning models help neuroscientists understand how the brain processes spatial navigation and self-orientation in the world.
- Research combines expertise from machine learning and neuroscience to unravel the neural mechanisms behind navigation and localization.
- AI models provide insights into how brain cells organize and work together to process navigation tasks.
Frequently asked questions
How do machine learning models assist neuroscientists in studying the brain?
Machine learning models can simulate complex patterns in brain activity and help neuroscientists gain insight into how cells and networks in the brain function, especially in processes like spatial navigation.
What role does the brain play in navigation compared to our senses?
While our eyes perceive information, the brain performs the heavy computing needed for navigation and localization. The brain processes perceived information and determines our position and direction of movement.
What is the goal of the research by Marlos C. Machado and Quinn Lee?
Their research combines machine learning and neuroscience expertise to better understand the mysteries of navigation, focusing on how neural cells form and organize to enable navigation tasks.