Mehrdad Jazayeri

Mehrdad Jazayeri is a Professor in the Department of Brain and Cognitive Sciences at MIT and an Investigator at the McGovern Institute for Brain Research. He directs educational initiatives in the department and teaches 9.014: Quantitative Methods and Computational Models in Neuroscience, focusing on mathematical tools for analyzing neurobiological data. His research centers on the neural mechanisms of timing, sensorimotor integration, and decision-making, with contributions to understanding how the brain encodes time and generates flexible behaviors.

Education and Background: Jazayeri earned his PhD in Neuroscience from New York University (NYU) and completed postdoctoral training there, supported by the Helen Hay Whitney Foundation. His work has been honored with prestigious awards including the Howard Hughes Medical Institute Investigator designation (2024), McKnight Scholars Award (2017), and multiple teaching awards from MIT.

Research Interests: His lab explores how neural circuits in the frontal cortex and other regions support temporal processing, mental simulation, and hierarchical reasoning. Key topics include neural dynamics underlying interval timing, Bayesian computation in sensory-motor systems, and mechanisms of cognitive control. Recent work highlights the role of entorhinal cortex in mental navigation and the dynamics of working memory.

Awards: Over 20 awards/fellowships span career milestones, including the 2024 HHMI Investigatorship, Sloan Research Fellowship (2014), and recognition for both research and teaching excellence. His early career was supported by the Goldsmith Fellowship (NYU) and NSERC Scholarship (Canada).

Teaching and Education: As Director of Education in BCS, he shapes curricula for MIT’s Brain and Cognitive Sciences programs. His 9.014 course emphasizes computational modeling, MATLAB programming, and analysis of neurobiological data, reflecting his commitment to bridging theory and experiment.

Lab and Collaborations: The JazLab develops innovative techniques like MEDiCINe for neural recordings and leverages primate models to study decision-making circuits. Collaborations integrate experimental neuroscience with computational modeling, addressing questions in temporal processing and neural plasticity.