The Jazayeri lab aims to understand the building blocks of cognition. The brain has a remarkable ability to generate complex behaviors by combining sensory evidence, prior experience, and cost-benefit considerations. Jazayeri’s research probes the neural mechanisms that allow the brain to integrate this plethora of cues, resulting in flexible, goal-directed behavior. The lab makes this problem accessible by breaking it down into three fundamental objectives: 1) parsing cognition into a set of simple and generalizable computational modules, 2) discovering neural circuits and mechanisms that implement those modules, and 3) understanding how the nervous system synthesizes those modules to flexibly control cognitive behaviors. To address these objectives, Jazayeri and his lab combine behavioral experiments in humans with in vivo experiments in animal models and in silico experiments in artificial neural network models.
The long-term objective of research in the Jazayeri lab is to understand the underpinnings of cognitive control. They aim to gain insight into how neurons and neural circuits generate and control dynamic patterns of activity. Equally important is how those patterns encode behaviorally relevant information. The Jazayeri lab uses multidisciplinary approaches to elucidate the architecture and dynamics of cognitive control, approaches that have contributed to the following domains of research in cognitive control:
Using tasks that involve anticipation and planning, Jazayeri and colleagues have probed the control principles that enable the brain to coordinate internally generated dynamic patterns of activity with external events. This work has led to the discovery of the so-called temporal scaling phenomenon – the capacity of the brain to flexibly stretch or compress neural activity patterns to anticipate external events and plan for upcoming actions.
Using estimation tasks, the lab has characterized how biological and artificial neural systems use statistical regularities in the environment to establish prior beliefs and integrate those beliefs with sensory cues (i.e., perform Bayesian integration). This work has provided evidence that prior beliefs exert their force on behavior by changing the coupling between neurons and warping the underlying neural representations.
Using tasks that involve solving decision trees, Jazayeri has begun to understand how the nervous system supports hierarchical reasoning. This work has uncovered a distributed network of regions within the frontal cortex that implement hierarchical computations, and enable the brain to make causal inferences when the sources of error are ambiguous.
Mehrdad Jazayeri joined the MIT faculty in January 2013 as a McGovern investigator and an assistant professor in the Department of Brain and Cognitive Sciences. Jazayeri, who is originally from Iran, obtained a BSc in Electrical Engineering from Sharif University of Technology in Tehran. He received his PhD from New York University, where he studied with J. Anthony Movshon, winning the 2007 Dean’s award for the most outstanding dissertation in the university. After graduating, he was awarded a Helen Hay Whitney fellowship to join the laboratory of Michael Shadlen at the University of Washington. In 2014 he was named a Sloan Research Fellow.
Honors and Awards
McKnight Scholar Award, 2017
Klingenstein-Simons Fellowship Award in the Neurosciences, 2015
Cadena-Valencia, J, García-Garibay, O, Merchant, H, Jazayeri, M, de Lafuente, V. Entrainment and maintenance of an internal metronome in supplementary motor area. Elife. 2018;7 :. doi: 10.7554/eLife.38983. PubMed PMID:30346275 PubMed Central PMC6249004.
Remington, ED, Egger, SW, Narain, D, Wang, J, Jazayeri, M. A Dynamical Systems Perspective on Flexible Motor Timing. Trends Cogn. Sci. (Regul. Ed.). 2018;22 (10):938-952. doi: 10.1016/j.tics.2018.07.010. PubMed PMID:30266152 PubMed Central PMC6166486.