Our long-term goal is to reverse engineer the computational and neurobiological processes underlying cognition and decision-making and apply these insights to biological psychiatry. We start with quantifiable behavioral tasks, for both humans and rodents, that enable us to isolate and study distinct cognitive processes, such as decision confidence. We probe the neural basis of these processes in rodents using state-of-the-art electrophysiological, imaging, and optogenetic techniques to establish the underlying neural mechanisms. Given the complexity of behavior and the dynamics of neural networks producing it, we also develop new algorithms for analyzing data and models to help us interpret them. By understanding how brains accomplish cognitive tasks, often beyond the capacity of current machine learning algorithms, we also expect to uncover new computational principles. In terms of topics our approach is multifaceted, currently we study the neural basis of decision confidence, impulsivity, social value and foraging; the division of labor among cell-types in prefrontal cortex; communication across cortical regions; neuromodulatory systems and most recently brain-body interactions. By identifying the neural processes underlying specific behavioral capacities in rodent models of cognition, we also seek insights into what goes awry in the brain during mental illness to build a bridge from animal studies to psychiatry. Ultimately, we hope these insights will lead to develop novel therapeutic strategies for psychiatric disorders such as addiction, major depression, schizophrenia, and autism spectrum disorder.