Assistant Professor of Neurobiology
My research focuses on the application of machine learning methods to the analysis of brain data and behavior. I have a special interest in the neurobiology of reward and decision-making, particularly issues surrounding foraging, impulsivity, and self-control. More generally, I am interested in computational principles underlying brain organization at the mesoscale, and work in my lab studies phenomena that range from complex social behaviors to coding principles of the retina.
Appointments and Affiliations
- Assistant Professor of Neurobiology
- Assistant Professor in the Department of Electrical and Computer Engineering
- Assistant Research Professor in Neurobiology
- Member of the Center for Cognitive Neuroscience
- Office Location: Bryan Research Building, 101H, Durham, NC 27710
- Office Phone: (919) 660-4901
- Email Address: email@example.com
- B.S. University of Kentucky, 1999
- Ph.D. Princeton University, 2004
Awards, Honors, and Distinctions
- Early Career Mentoring Award in Basic — Translational Science. Duke University School of Medicine. 2022
- Gordon G. Hammes Faculty Teaching Award. Duke University School of Medicine. 2020
- EGR 491: Projects in Engineering
- NEUROBIO 393: Research Independent Study
- NEUROBIO 735: Quantitative Approaches in Neurobiology
- NEUROBIO 793: Research in Neurobiology
- NEUROSCI 493: Research Independent Study 1
- NEUROSCI 494: Research Independent Study 2
- NEUROSCI 755: Interdisciplinary Program in Cognitive Neuroscience (IPCN) Independent Research Rotation
In the News
- School of Medicine Celebrates 2022 Faculty Achievement Awards (Apr 15, 2022 | School of Medicine)
- Neuroscientists See How Practice Really Does Make Perfect (Oct 21, 2021)
- Living Retina Achieves Sensitivity and Efficiency Engineers Can Only Dream About (Sep 28, 2021)
- Why More Severe Crimes Are More Likely to Lead to Wrongful Convictions (Jul 24, 2019 | Duke Research Blog)
- John Pearson: Data Explorer Inside the Brain (Oct 29, 2015)
- Pearson, J., and A. Kumar. “Sophisticated models, minimum descriptions, and the Goldilocks zone of behavior: Comment on “Beyond simple laboratory studies: Developing sophisticated models to study rich behavior” by Maselli et al. (Accepted)” Physics of Life Reviews 47 (December 1, 2023): 137–38. https://doi.org/10.1016/j.plrev.2023.10.008.
- Subramanian, Divya, John M. Pearson, and Marc A. Sommer. “Bayesian and Discriminative Models for Active Visual Perception across Saccades.” ENeuro 10, no. 7 (July 2023). https://doi.org/10.1523/ENEURO.0403-22.2023.
- Brudner, Samuel, John Pearson, and Richard Mooney. “Generative models of birdsong learning link circadian fluctuations in song variability to changes in performance.” PLoS Comput Biol 19, no. 5 (May 2023): e1011051. https://doi.org/10.1371/journal.pcbi.1011051.
- Jiang, Yaoguang, Kelsey R. McDonald, John M. Pearson, and Michael L. Platt. “Neuronal mechanisms of dynamic strategic competition.,” March 20, 2023. https://doi.org/10.21203/rs.3.rs-2524549/v1.
- Castrellon, Jaime J., Shabnam Hakimi, Jacob M. Parelman, Lun Yin, Jonathan R. Law, Jesse A. G. Skene, David A. Ball, et al. “Social cognitive processes explain bias in juror decisions.” Soc Cogn Affect Neurosci 18, no. 1 (February 23, 2023). https://doi.org/10.1093/scan/nsac057.