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Samuel Nastase

Assistant Professor of Psychology
Samuel Nastase
Pronouns He / Him / His Email snastase@usc.edu Office SGM 1016

Biography

The core questions driving my research are “What is shared between individual brains?” and “How do we share our thoughts with one another?”—using language and other coordinated actions. My research combines naturalistic neuroimaging paradigms (fMRI, ECoG) and deep neural networks to better answer these questions in real-world contexts. In current work, we leverage large language models to better understand how humans use language to transmit complex thoughts from one brain to another.

I’ll be recruiting PhD students this year to start in Fall 2026!

Education

  • Ph.D. Cognitive Neuroscience, Dartmouth College, 2017
  • M.S. Cognitive Neuroscience, University of Trento, Italy, 2012
  • B.A. Cognitive Science, Philosophy, Johns Hopkins University, 2010
    • Research Scholar, Lecturer, Princeton University, 2018 – 2025

  • Journal Article

    • Zada, Z., Goldstein, A. Y., Michelmann, S., Simony, E., Price, A., Hasenfratz, L., Barham, E., Zadbood, A., Doyle, W., Friedman, D., Dugan, P., Melloni, L., Devore, S., Flinker, A., Devinsky, O., Hasson, U., Nastase, S. A. (2024). A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations. Neuron. Vol. 112 (18), pp. 3211–3222. DOI
    • Kumar, S., Sumers, T. R., Yamakoshi, T., Goldstein, A., Hasson, U., Norman, K. A., Griffiths, T. L., Hawkins, R. D., Nastase, S. A. (2024). Shared functional specialization in transformer-based language models and the human brain. Nature Communications. Vol. 15, pp. 5523. DOI
    • Goldstein, A., Nastase, S. A., Zada, Z., Buchnik, E., Schain, M., Price, A., Aubrey, B., Feder, A., Emanual, D., Cohen, A., Jensen, A., Gazula, H., Choe, G., Rao, A., Kim, C., Casto, C., Lora, F., Flinker, A., Devore, S., Doyle, W., Dugan, P., Friedman, D., Hassidim, A., Brenner, M., Matias, Y., Norman, K. A., Devinsky, O. (2022). Shared computational principles for language processing in humans and deep language models. Nature Neuroscience. Vol. 25, pp. 369–380. DOI
    • Nastase, S. A., Liu, Y., Hillman, H., Zadbood, A., Hasenfratz, L., Keshavarzian, N., Chen, J., Honey, C. J., Yeshurun, Y., Regev, M., Nguyen, M., Chang, C. H., Baldassano, C., Lositsky, O., Simony, E., Chow, M. A., Leong, Y. C., Brooks, P. P., Micciche, E., Choe, G., Goldstein, A., Vanderwal, T., Halchenko, Y. O., Norman, K. A., Hasson, U. (2021). The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension. Scientific Data. Vol. 8, pp. 250. DOI
    • Nastase, S. A., Goldstein, A., Hasson, U. (2020). Keep it real: rethinking the primacy of experimental control in cognitive neuroscience. NeuroImage. Vol. 222, pp. 117254. DOI
    • Nastase, S. A., Liu, Y., Hillman, H., Norman, K. A., Hasson, U. (2020). Leveraging shared connectivity to aggregate heterogeneous datasets into a common response space. NeuroImage. Vol. 217, pp. 116865. DOI
    • Haxby, J. V., Guntupalli, J. S., Nastase, S. A., Feilong, M. (2020). Hyperalignment: modeling shared information encoded in idiosyncratic cortical topographies. eLife. Vol. 9, pp. e56601. DOI
    • Hasson, U., Nastase, S. A., Goldstein, A. (2020). Direct fit to nature: an evolutionary perspective on biological and artificial neural networks. Neuron. Vol. 105 (3), pp. 416–434. DOI
    • Nastase, S. A., Gazzola, V., Hasson, U., Keysers, C. (2019). Measuring shared responses across subjects using intersubject correlation. Social Cognitive and Affective Neuroscience. Vol. 14 (6), pp. 667–685. DOI
    • Nastase, S. A., Connolly, A. C., Oosterhof, N. N., Halchenko, Y. O., Guntupalli, J. S., Visconti di Oleggio Castello, M., Gors, J., Gobbini, M. I., Haxby, J. V. (2017). Attention selectively reshapes the geometry of distributed semantic representation. Cerebral Cortex. Vol. 27 (8), pp. 4277–4291. DOI
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