Thomas Naselaris, PhD

Associate Professor, Department of Neuroscience

Thomas Naselaris

Contact Info

nase0005@umn.edu

Office Phone 612-554-7116

Office Address:
Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN 55455, USA

Summary

Expertise

fMRI, 2 photon microscopy, computational neurobiology

Research

Research Summary/Interests

Our lab studies the computations that make it possible to see and think. Taking inspiration from the tools and concepts of AI, we use computational models to bridge observations of brain activity at many spatial and temporal scales, from fMRI in humans to 2-photon microscopy in animal models.

We are especially interested in the generative capabilities of the visual system. Much of life is spent imagining or dreaming of internal images that one has never actually observed. Why is the visual system so good at generating images, and how does this remarkable ability help us to see? We are addressing this question by monitoring the human brain as it engages complex, real-world scenery and as it calls upon memory to generate mental images.

Publications

Breedlove, J, St-Yves, G, Olman, CA, Naselaris, T (2020) Generative feedback explains distinct brain activity codes for seen and mental images. Current Biology, 30, 2211-2224.

Sabra, Z, Bonilha, L, Naselaris, T (2020) Spectral encoding of seen and attended object categories. Journal of Neuroscience, 40, 327-342.

St-Yves, G, Naselaris, T (2019) Generative adversarial networks conditioned on brain activity reconstruct seen images. Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics. Miyazaki, Japan.

Naselaris, T, Bassett, DS, Fletcher, AK, Kording, K, Kriegeskorte, N, Nienborg, H, Poldrack, R, Shohamy, D, Kay, KN (2018) Cognitive Computational Neuroscience: A new conference for an emerging discipline. Trends in Cognitive Sciences, 22, 365–367.

St-Yves, G, Naselaris, T (2017) The feature-weighted receptive field: an interpretable encoding model for complex feature spaces. Neuroimage, 180, 188-202 

Naselaris, T, Kay, KN (2016) Resolving ambiguities of MVPA using explicit models of representation. Trends in Cognitive Sciences, 19, 551–554.

Pearson, J, Naselaris, T, Holmes, EA, Kosslyn, SM (2015) Mental Imagery: functional mechanisms and clinical applications. Trends in Cognitive Sciences, 19, 590–602.

Naselaris, T, Olman, CA, Stansbury, D, Ugurbil, K, Gallant, J (2015) A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes. NeuroImage, 105, 215-228.

Hanlon, CA, Dowdle, LT, Naselaris, T, Canterberry, M, Cortese, BM (2014) Visual cortex activation to drug cues: a meta-analysis of functional neuroimaging papers in addiction and substance abuse literature. Drug and Alcohol Dependence, 143, 206–212.

Dilgen, J, Tompa, T, Saggu, S, Naselaris, T, Lavin, A (2013) Optogentically evoked gamma oscillations are disturbed by cocaine administration. Frontiers in Cellular Neuroscience, 7, 213.