Behavioural Modeling
behavioural modeling
Rule learning representation in the fronto-parietal network
We must constantly adapt the rules we use to guide our attention. To understand how the brain learns these rules, we designed a novel task that required monkeys to learn which color is the most rewarded at a given time (the current rule). However, just as in real life, the monkey was never explicitly told the rule. Instead, they had to learn it through trial and error by choosing a color, receiving feedback (amount of reward), and then updating their internal rule. After the monkeys reached a behavioral criterion, the rule changed. This change was not cued but could be inferred based on reward feedback. Behavioral modeling found monkeys used rewards to learn the rules. After the rule changed, animals adopted one of two strategies. If the change was small, reflected in a small reward prediction error, the animals continuously updated their rule. However, for large changes, monkeys ‘reset’ their belief about the rule and re-learned the rule from scratch. To understand the neural correlates of learning new rules, we recorded neurons simultaneously from the prefrontal and parietal cortex. We found that the strength of the rule representation increased with the certainty about the current rule, and that the certainty about the rule was represented both implicitly and explicitly in the population.
Learning in abstract value spaces
Learning the consequences our choices have as we interact with our world is critical for flexible behavior. Relational knowledge of one’s environment gives structure to otherwise-individual one-to-one stimulus-outcome mappings, providing a substrate to globally update behavioral contingencies in the face of changes in the landscape of reward. In the brain, this relational knowledge is thought to be encoded in the hippocampus (HPC) in the form of a cognitive map, while prefrontal regions, such as orbitofrontal cortex (OFC), are thought to instantiate subjective estimates of location on the map, though direct neurophysiological evidence is lacking. In this talk, I will present recent work demonstrating the causal relationship between HPC and OFC as nonhuman primates perform a reward learning task requiring them to learn and maintain knowledge of changing stimulus-outcome associations. I will then provide direct evidence that single primate hippocampal neurons represent an abstract map of the value space defined by the task. Finally, I use behavioral modeling to highlight one possible strategy by which knowledge of value space is exploited by animals to detect changes in choice-outcome mappings and proactively update their behavior in response.