Behavioral Social Neuroscience Seminar

Current theories of decision-making suggest that there are multiple decision-making systems in the mammalian brain, each of which leads to selecting actions based on different information processing algorithms.  Using a combination of behavioral analysis, multi-electrode neurophysiology, and computational modeling, we've been able to directly measure the information processing driving those multiple decision-making systems.  The key difference is that some systems include transient (covert) representations of imagined expected outcomes, which can be detected through computational analyses of neural ensemble recording, while other systems do not.  I will present our continuing work on dissociations between hippocampus (capable of representing outcomes), ventral striatum and orbitofrontal cortex (capable of transiently representing reward expectations), and dorsolateral striatum (learning stimulus-action pairs and action-action chains).  In addition, I will present our recent work looking at the neuroeconomics of foraging in the rat, including evidence that rats can represent the counterfactual necessary for regret (and express behaviors reflecting regret), and that rats' decisions depend on retrospective evaluations of the work it took to get to a reward, consistent with sunk-cost errors.