The geometry of abstraction

A longstanding challenge in both neuroscience and machine learning is relating a model system’s internal representations to its behavior. In both animals and machines, recent work has revealed the importance of neural geometry in inferential cognitive processes. In line with this work, the goal of this research is to clearly demonstrate, and causally manipulate, the relationship between geometric properties of neural representations in the human hippocampus and abstract reasoning.