Silvia Lopez-Guzman, M.D., Ph.D.

The decisions we make are a central feature of who we are as individuals. They have consequences that affect us directly and influence the people around us. Decisions can manifest in overt behavior, but they reflect the inner workings of a complex network of brain areas that include subcortical structures in the brainstem and basal ganglia, as well as regions of parietal, temporal, and prefrontal cortex. This circuit processes noisy information from external (exteroceptive) and internal (interoceptive) inputs in a state- and context-dependent way, influenced by prior learning and experience and by our individuality (personal preferences). In many mental health conditions, ranging from depression to substance use disorder, decision-making is altered, sometimes leading a person to put themselves or others at risk of serious outcomes.

The Computational Decision Neuroscience lab studies how the computations that subserve decision making are implemented in the brain and how this may be different in individuals with mental illness. States of decompensation or exacerbated symptomatology, often brought about by increased stress, incidental negative emotion, and pain, are of special interest because they present opportunities for deploying interventions that could prevent negative outcomes. Our group combines economic theory-inspired behavioral tasks, biosensor data, passive and active mobile device data, clinical information, model-based fMRI, and computational modeling to understand how these states influence value representations and computations that underlie intertemporal decisions, decisions under uncertainty, and higher-order reasoning about those decisions.

Dr. Silvia Lopez-Guzman received her MD degree from Pontificia Universidad Javeriana in Bogotá, Colombia. She then completed her PhD in Neuroscience at New York University’s Center for Neural Science, thanks to a Fulbright Commission award, working in the lab of Dr. Paul Glimcher. Her doctoral dissertation entitled “Neuroeconomic markers of opioid use disorder outcomes: a computational psychiatry approach” centered on the use of computational markers of decision-making for the identification of outcomes and clinical states in opioid addiction treatment. Dr. Lopez-Guzman was a faculty member at the School of Medicine and Health Sciences at Universidad del Rosario in Bogotá, before joining NIMH as Chief of the Unit on Computational Decision Neuroscience and becoming a 2021 NIH Distinguished Scholar. She also holds a joint appointment with the National Institute on Drug Abuse (NIDA), where she is part of the Translational Addiction Medicine Branch. Her lab studies the computational and neurobiological bases of decision-making and how this process is altered in depression, addiction, and chronic pain.