Jean-Paul Noel , PhD
Assistant Professor, Department of Neuroscience
Research Summary
The Noel Lab is interested in understanding how our brains infer hidden causes given sensory observations. Namely, to perceive, we must actively generate a hypothesis as to causal structure of the world that yielded the observed sensory data. We are also interested in understanding how this process goes awry in different neurodevelopmental and psychiatric conditions, with a focus on Autism Spectrum Disorders. Beyond trying to globally understand perception and inference, the topic of study is also central in building next-generation generative artificial intelligence. The lab takes an integrative approach, employing techniques from cognitive neuroscience in humans (e.g., EEG, psychophysics, and VR/AR), systems neuroscience in awake and behaving rodents (e.g., large-scale neurophysiology and optogenetics), and computational neuroscience (e.g., Bayesian modeling and artificial neural networks). The lab is always interested in hearing from motivated individuals seeking training across traditional disciplinary boundaries and with a strong technical background. To learn more about the Noel Lab, please visit: www.noel-lab.org
Publications:
Context-invariant beliefs are supported by dynamic reconfiguration of single unit functional connectivity in prefrontal cortex of male macaques. Nat Commun. 2024 Jul 9;15(1):5738.
Causal inference during closed-loop navigation: parsing of self- and object-motion. Philos Trans R Soc Lond B Biol Sci. 2023 Sep 25;378(1886):20220344.
A theory of autism bridging across levels of description. Trends Cogn Sci. 2023 Jul;27(7):631-641.
Aberrant causal inference and presence of a compensatory mechanism in autism spectrum disorder. Elife. 2022 May 17;11:e71866.
Individuals with autism spectrum disorder have altered visual encoding capacity. PLoS Biol. 2021 May 12;19(5):e3001215.
