Kiran Long-Iyer

Research Description

The serotonin (5HT) system modulates physiology and behavior in health and disease. It is the most widely used pharmacological target for treating depression and anxiety. However, the circuit mechanisms by which the 5HT system is organized to carry out its diverse functions remains elusive. Kiran aims to achieve a biological and theoretical understanding about the functional role of 5HT systems in reinforcement learning. The Tian lab has recently developed two types of genetically encoded 5HT sensors, iSeroSnFR and psychLight (Unger et al., Cell, 2020; Dong et al., Cell, 2021) to measure 5HT dynamics with high spatiotemporal resolutions in behaving animals.  Combined with other optogenetic tools developed in the Tian lab (i.e., dLight (Patriarchi et al., Science 2018; Nature Methods, 2020), Kiran will concurrently record subsecond DA and 5HT dynamics in the classic mesolimbic reward circuit across the full course of complex reinforcement tasks in mice. Kiran will also utilize computational modeling to further the theoretical understanding of 5HT in modulating learning. In the past year, Kiran has established a reinforcement learning probabilistic switching behavioral paradigm, piloted 5HT imaging during this task using fiber photometry, and developed Matlab, R, and Python imaging analysis scripts in collaboration with the Wilbrecht group at UC Berkeley. Kiran also developed a strong theoretical understanding of reinforcement learning models in collaboration with Tim Hanks at UC Davis.