Nuo Li, Ph.D.


Nuo Li, Ph.D.
Associate Professor
Baylor College of Medicine
One Baylor Plaza, T632
City, State, ZIP
Houston, TX 77030
(713) 798-4301
[email protected]
Research field
Award year
Pew distinction
Innovation Fund investigator


The Li lab will investigate how multiple parts of the brain cooperate to guide decisions based on short-term memory. Deciding how to act appropriately to a stimulus—particularly one that occurred in the past—is a complex cognitive task that engages many areas of the brain. Whether these brain regions act simultaneously, feed information back and forth, or report to a central “node” to orchestrate their output is unknown. As a postdoctoral fellow, I identified a subregion of the brain that controls a mouse’s decision to make directional movements a second or two after a sensory instruction—a response that involves short-term memory, planning, and executing movement. Now, using a suite of cutting-edge techniques for monitoring and manipulating the activity of neurons in different parts of the brain, our lab will serially inactivate a number of different areas that are functionally coupled to the previously identified subregion and assess how these perturbations alter its activity—and affect the mouse’s decision-making abilities. By dissecting the neural circuits involved in such behavior, we could identify new targets for therapies that enhance cognitive processes or limit cognitive decline.

As an Innovation Fund investigator, Nuo Li, Ph.D., is teaming up with Roozbeh Kiani, M.D., Ph.D., to explore what happens in the brain when we change our minds, an underexplored and mysterious aspect of decision-making. The group will combine Li’s research on the neural circuits driving learning and memory in mice with Kiani’s work on the computational principles of decision-making in monkeys and humans. Together, they will develop a novel framework for studying decision-making across these species, allowing them to identify conserved brain areas and mechanisms that shape decisions. Their novel task and analysis approach will allow them to know when a change of mind is happening based on neural responses. Additionally, they will identify inputs that trigger a change of mind, such as new sensory information or memories. Using a combination of rigorous behavioral tests, computational modeling, and neural circuit dissection, this work will accelerate understanding of a crucial feature of decision-making across species.

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