Matteo Visconti di Oleggio Castello, Ph.D.

me-pic2.jpg

I’m an Assistant Project Scientist in the Department of Neuroscience at the University of California, Berkeley, working in Jack Gallant’s lab. I’m interested in how our brains build and represent meaning from the world around us. My current research focuses on how these representations differ between people.

To study these questions, I build computational models to predict brain activity when we watch movies, listen to stories, or interact with each other. Then I break these models apart, and see if I can learn something interesting about the brain.

Before coming to Berkeley, I received a Ph.D. in Cognitive Neuroscience at Dartmouth, working with Ida Gobbini and Jim Haxby. At Dartmouth, I studied how our brains represent the identity of our friends and colleagues. I used psychophysics and fMRI to study familiar face perception.

News

Aug 23, 2025 My latest work on individual differences in conceptual representation is available as a preprint on bioRxiv. This paper introduces a new statistical framework to measure and interpret person-specific functional brain representations, establishing a new paradigm for precision neuroscience.
Apr 25, 2025 We published our tutorial introduction to the Voxelwise Encoding Model framework in Imaging Neuroscience. Check the paper and the tutorials.
Oct 07, 2024 I gave a talk at SFN in Chicago on my work on individual differences in lexical-semantic representations.
Jun 20, 2024 We released a set of tutorials on the Voxelwise Encoding Model framework. Check the preprint and the associated website.
Jul 19, 2023 We have a new preprint on model connectivity, a powerful and more interpretable alternative to functional connectivity.

Selected publications

  1. Individual differences shape conceptual representation in the brain
    Matteo Visconti di Oleggio Castello, Tom Dupré la Tour, and Jack L. Gallant
    bioRxiv, 2025
  2. Model connectivity: leveraging the power of encoding models to overcome the limitations of functional connectivity
    Emily X Meschke*Matteo Visconti di Oleggio Castello*, Tom Dupré la Tour, and Jack L. Gallant
    bioRxiv, 2023
    * equal contribution
  1. The Voxelwise Encoding Model framework: a tutorial introduction to fitting encoding models to fMRI data
    Tom Dupré la Tour*Matteo Visconti di Oleggio Castello*, and Jack L. Gallant
    Imaging Neuroscience, 2025
    * equal contribution
  2. Shared neural codes for visual and semantic information about familiar faces in a common representational space
    Matteo Visconti di Oleggio Castello, James V. Haxby, and M. Ida Gobbini
    Proceedings of the National Academy of Sciences, 2021
  3. The neural representation of personally familiar and unfamiliar faces in the distributed system for face perception
    Matteo Visconti di Oleggio Castello*, Yaroslav O. Halchenko*, J. Swaroop Guntupalli, Jason D. Gors, and M. Ida Gobbini
    Scientific Reports, 2017
    * equal contribution