Orbitofrontal modulation of dopamine during value-based decision-making

Project Summary Dopamine is an important neuromodulator that mediates learning from previous outcomes (“retrospective” learning) by encoding reward prediction errors — the difference between experienced and expected rewards. However, recent work has suggested that dopamine might use the prefrontal cortex to encode more abstract

prediction errors, such as errors about the hidden state of a task or environment. The exact circuit mechanisms underlying these abstract hidden-state prediction errors remains unclear. This proposal has two major goals. First, I will characterize dopamine activity related to hidden-state inference in rats performing a task with partially

observable states. Second, I will identify the circuit mechanisms that generate dopamine state prediction errors in this task. I will use computational modeling and state-of-the-art genetic and viral tools, including fiber photometry to measure dopamine activity and projection-specific chemogenetic silencing of prefrontal cortex, to

address these goals. I will measure dopamine activity both at the level of cell-body calcium dynamics, as well as at the level of axonal release, which can be dissociated. This proposal will describe the multi-regional neural circuits that underlie the acquisition and maintenance of abstract representations of the environment. The results

will provide insight into the pathology and treatment of neuropsychiatric disorders, which are characterized by disrupted reward processing. My co-sponsors at New York University (NYU), Dr. Christine Constantinople and Dr. Paul Glimcher, have complimentary experience in behavioral and systems neuroscience experiments in rats, and computational

modeling of decision-making, respectively. The training I will receive will allow me to pursue truly integrative research that involves the close interplay between experiments and theory. The strong, collaborative environment at NYU makes it an ideal place for me to pursue these research goals. My training plan provides a

detailed strategy for acquiring the necessary skills from a team of co-mentors with extensive, proven expertise in the relevant techniques. Technical training, as well as frequent data presentations, attendance of professional courses, seminars, and conferences, and development of my writing and leadership skills will equip me to

complete the proposed research, and transition to a post-doctoral position in my field of interest.