Erie Boorman Receives NIH Grant

Assistant Professor Erie Boorman earned an R56 NIH grant to study the first neural model of model-based credit assignment. How the brain forms, tunes, and uses predictive models that specify the causal links between stimuli in the environment, our choices, and their outcomes is a fundamental question in Psychology and Neuroscience. In order to make sound predictions in a complex world, the brain needs to attribute good and bad outcomes to their most likely causes, a problem known as “credit assignment”. There is little understanding of how outcomes are attributed to their most likely causes in structured real-world environments. Much real-world learning occurs in complex and structured environments, such as hierarchical systems (e.g. seasonal events, social hierarchies, contextual rules, hierarchical categories such as animal/plant taxonomy, etc.). Recent evidence suggests that humans can use an understanding of the environment’s causal structure to attribute outcomes to their most likely causes (called “model-based credit assignment)”, rather than simply attributing them to the most recently experienced stimuli and choices that were made (called “model-free” credit assignment), as standard models have proposed.