The successful candidate will work with Prof. Todd Hare and other SNS Lab researchers on the neuro-computational basis of human learning and decision making using cutting-edge neuroimaging techniques. For example, the successful candidate will work on a project aimed to determine if reward learning and corresponding striatal responses incorporate causal knowledge during Pavlovian conditioning. Using theoretically grounded and empirically verified reward learning predictions – blocking, conditioned inhibition, and overexpectation – we will test how Pavlovian conditioning operates over stimuli that are known to be either causal generators or correlated predicters of reward outcomes. Knowledge of the causal mechanisms should, in principle, determine how a reward learning agent summates predictions over two or more conditioned stimuli and whether a specific conditioned inhibitor will block a given causal state. We will test these hypotheses using modified versions of the standard conditioned inhibition and overexpectation paradigms together with functional neuroimaging. The results of these studies will provide important new insights into the fundamental nature of reward learning. They will reveal if Pavlovian conditioning mechanisms, which are generally thought to be model-free, incorporate model-based knowledge of cause-and-effect relationships in the environment or if instead they remain agnostic about causality and operate via predictiveness alone.
https://jobs.uzh.ch/offene-stellen/postdoc-in-neuroscience-of-reward-learning/42c915eb-5f6a-430f-b06b-6f00e9efd794
