Bruno Averbeck, Ph.D.
Laboratory of Neuropsychology (LN)
Research Topics
The work in the Section on Learning and Decision Making focuses on understanding the computational mechanisms and neural circuitry that underlies reinforcement learning. Reinforcement learning is the behavioral process of associating objects or actions with rewards or punishments. More colloquially, the lab tries to understand how we learn from experience to have preferences for certain decisions. The lab uses a combination of high-channel count neurophysiology and computational modeling. We also collaborate with clinical labs to examine changes in decision making processes in clinical populations thought to have pathology in the neural circuitry we study. In this work we maintain close similarity between the behaviors studied in the clinical groups, and those studied in animal models.
We are currently focusing on understanding how neural activity distributed across large cortical networks underlies the behaviors on which we focus. We are building computational models of cortical-basal ganglia-thalamocortical networks to understand how these structures coordinate their activity to drive behavior.
The lab is also carrying out projects to understand adolescent development. Late adolescence is a period during which many psychiatric disorders first emerge. There are also important ongoing developmental processes in the brain and in behavior during this period. Therefore, understanding normative developmental processes, as well as how these processes go wrong, can shed light on the conditions that lead to the development of mental health disorders.
Biography
Dr. Averbeck obtained a B.S. in Electrical Engineering from the University of Minnesota in 1994, worked in industry for three years, then returned to Minnesota to complete a doctorate in neuroscience under Dr. Apostolos Georgopoulos. Awarded a Ph.D. 2001, with a dissertation on Neural Mechanisms of Copying Geometrical Shapes . For his postdoctoral studies, Dr. Averbeck joined the laboratory of Dr. Daeyeol Lee at the University of Rochester, where he studied neural mechanisms underlying sequential learning, coding of vocalizations, and population coding. In 2006, as a Senior Lecturer at University College London, he began using neuroimaging of human study participants to investigate the role of frontal-striatal circuits in learning. Dr. Averbeck joined the NIMH Intramural Research Program as a Principal Investigator in 2009. A tenured member of the faculty since 2016, he is Chief of the Section on Learning and Decision Making.
Selected Publications
Tang H, Bartolo R, Averbeck BB (2024). Ventral frontostriatal circuitry mediates the computation of reinforcement from symbolic gains and losses. Neuron 112, 3782-3795.e5. https://doi.org/10.1016/j.neuron.2024.08.018. [Pubmed Link ]
Wang S, Falcone R, Richmond B, Averbeck BB (2023). Attractor dynamics reflect decision confidence in macaque prefrontal cortex. Nat Neurosci 26, 1970-1980. https://doi.org/10.1038/s41593-023-01445-x. [Pubmed Link ]
Averbeck BB (2022). Pruning recurrent neural networks replicates adolescent changes in working memory and reinforcement learning. Proc Natl Acad Sci U S A 119, e2121331119. https://doi.org/10.1073/pnas.2121331119. [Pubmed Link ]
Averbeck BB, Murray EA (2020). Hypothalamic Interactions with Large-Scale Neural Circuits Underlying Reinforcement Learning and Motivated Behavior. Trends Neurosci 43, 681-694. https://doi.org/10.1016/j.tins.2020.06.006. [Pubmed Link ]
Andujar M, Liuzzi L, Pine DS, Nelson CA, Zeanah CH, Fox NA, Averbeck BB (2026). Early psychosocial deprivation alters the refinement of neural dynamics across adolescence. Proc Natl Acad Sci U S A 123, e2514979123. https://doi.org/10.1073/pnas.2514979123. [Pubmed Link ]
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