CCS Lab

The missions of the CCS Lab are (1) elucidate the neurocognitive mechanisms of decision-making using computational approaches and (2) develop cost-effective markers of psychiatric disorders, especially addictive disorders. To accomplish the missions, (1) we seek to develop optimal assays probing cognitive and neural mechanisms underlying addictive disorders and related phenotypes, and (2) we use cutting-edge computational and statistical methods to maximize prediction accuracy and generalizability. Recent advancements in reinforcement learning and decision neuroscience now provide a coherent and quantitative framework to investigate decision-making processes: How we perceive reward and risk, learn from past experiences, and select appropriate actions. Abundant evidence also suggests that the brain has multiple systems for decision-making: the hard-wired Pavlovian system, which sets a strong prior on our actions when we are faced with rewards or punishments and the instrumental system, which is further divided into habitual (efficient but inflexible) and goal-directed (effortful but flexible) systems. These systems are known to interact with one another, but the exact nature and the neural mechanisms of the interaction remain unclear. To disentangle the decision-making processes, we use computational modeling, which allows for the generation of quantitative explanations, creating new and testable hypotheses, and large-scale phenotyping of individuals using statistical/computational methods. We also use functional magnetic resonance imaging (fMRI) to probe the neural substrates of underlying cognitive processes and to examine the interactions among decision-making systems at the neural level. Computational Psychiatry: Quantifying the Decision-Making Deficits in Psychiatri