Luiz Pessoa.

Luiz Pessoa

Professor of psychology
University of Maryland, College Park

Luiz Pessoa is professor of psychology and director of the Maryland Neuroimaging Center at the University of Maryland, College Park. His research interests center around studying interactions between emotion, motivation and cognition in the brain. He is also interested in the conceptual and philosophical foundations of neuroscience. He is the author of two books: “The Cognitive-Emotional Brain: From Interactions to Integration” (MIT Press, 2013) and “The Entangled Brain: How Perception, Cognition, and Emotion Are Woven Together” (MIT Press, 2022).

Pessoa received a B.Sc. in computer science and a master’s in computer engineering from the Federal University of Rio de Janeiro. He obtained a Ph.D. in computational neuroscience at Boston University. After returning to Brazil for a few years and being on the faculty of the computer science department at the Federal University of Rio de Janeiro, he returned to the United States to take a position as visiting fellow at the National Institute of Mental Health, in Leslie Ungerleider’s lab. He has been at the University of Maryland, College Park since 2011.

Explore more from The Transmitter

Grace Hwang and Joe Monaco discuss the future of NeuroAI

Hwang and Monaco organized a recent workshop to hear from leaders in the field about how best to integrate NeuroAI research into the BRAIN Initiative.

By Paul Middlebrooks
4 December 2024 | 97 min listen

Hessameddin Akhlaghpour outlines how RNA may implement universal computation

Could the brain’s computational abilities extend beyond neural networks to molecular mechanisms? Akhlaghpour describes how natural universal computation may have evolved via RNA mechanisms.

By Paul Middlebrooks
26 November 2024 | 107 min listen
Illustration of a person holding a box that is emitting laser-like beams and projecting a large curved black surface.

Imagining the ultimate systems neuroscience paper

A growing body of papers on systems neuroscience and on giant simulations of neural circuits involves data beyond the point that anyone can reasonably understand end to end. Looking ahead, “paper-bots” could solve that problem.

By Mark Humphries
2 December 2024 | 8 min read

privacy consent banner

Privacy Preference

We use cookies to provide you with the best online experience. By clicking “Accept All,” you help us understand how our site is used and enhance its performance. You can change your choice at any time. To learn more, please visit our Privacy Policy.