Preprints

* equal contribution

fMRI hyperscanning reveals widespread neural coupling during natural conversations

Mwilambwe-Tshilobo, L., Tsoi, L., Speer, S., Zada, Z., Burns, S. M., Falk, E. B., & Tamir, D. (2025).
PsyArXiv.

Brains and language models converge on a shared conceptual space across different languages

Zada, Z., Nastase, S., Li, J., & Hasson, U. (2025).
arXiv.

Cortical language areas are coupled via a soft hierarchy of model-based linguistic features

Samara, A., Zada, Z., Vanderwal, T., Hasson, U., & Nastase, S. (2025).
bioRxiv.

Information-making processes in the speaker's brain drive human conversations forward

Goldstein, A., Wang, H., Sheffer, T., Schain, M., Zada, Z., Niekerken, L., Aubrey, B., Nastase, S. A., Gazula, H., Casto, C., Doyle, W. K., Friedman, D., Devore, S., Dugan, P., Hassidim, A., Brenner, M., Matias, Y., Devinsky, O., Flinker, A., & Hasson, U. (2024).
bioRxiv.

Publications

2026

Context modulates brain state dynamics and behavioral responses during narrative comprehension

Chen, Y., Zada, Z., Nastase, S. A., Ashby, F. G., & Ghosh, S. S. (2026).
Imaging Neuroscience.

2025

Linguistic coupling between neural systems for speech production and comprehension during real-time dyadic conversations

Zada, Z., Nastase, S. A., Speer, S., Mwilambwe-Tshilobo, L., Tsoi, L., Burns, S. M., Falk, E., Hasson, U., & Tamir, D. I. (2025).
Neuron.

Temporal structure of natural language processing in the human brain corresponds to layered hierarchy of large language models

Goldstein, A.*, Ham, E.*, Schain, M., Nastase, S. A., Aubrey, B., Zada, Z., Grinstein-Dabush, A., Gazula, H., Feder, A., Doyle, W., Devore, S., Dugan, P., Friedman, D., Brenner, M., Hassidim, A., Matias, Y., Devinsky, O., Siegelman, N., Flinker, A., … Hasson, U. (2025).
Nature Communications, 16(1), 10529.

Aligning brains into a shared space improves their alignment with large language models

Bhattacharjee, A., Zada, Z., Wang, H., Aubrey, B., Doyle, W., Dugan, P., Friedman, D., Devinsky, O., Flinker, A., Ramadge, P. J., Hasson, U., Goldstein, A., & Nastase, S. A. (2025).
Nat Comput Sci.

Reading comprehension in L1 and L2 readers: Neurocomputational mechanisms revealed through large language models

Gu, C., Nastase, S. A., Zada, Z., & Li, P. (2025).
Npj Science of Learning, 10(1), 46.

The “Podcast” ECoG dataset for modeling neural activity during natural narrative comprehension

Zada, Z., Nastase, S. A., Aubrey, B., Jalon, I., Michelmann, S., Wang, H., Hasenfratz, L., Doyle, W., Friedman, D., Dugan, P., Melloni, L., Devore, S., Flinker, A., Devinsky, O., Goldstein, A., & Hasson, U. (2025).
Sci Data, 12(1), 1135.

A unified acoustic-to-speech-to-language embedding space captures the neural basis of natural language processing in everyday conversations

Goldstein, A., Wang, H.*, Niekerken, L.*, Schain, M.*, Zada, Z.*, Aubrey, B.*, Sheffer, T.*, Nastase, S. A.*, Gazula, H., Singh, A., Rao, A., Choe, G., Kim, C., Doyle, W., Friedman, D., Devore, S., Dugan, P., Hassidim, A., Brenner, M., … Hasson, U. (2025).
Nature Human Behavior, 9(5), 1041-1055.

In search of a neural mechanism for domain-general value comparison in decision making

Samara, A.*, & Zada, Z.* (2025).
The Journal of Neuroscience, 45(7), e2233242025.

2024

A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations

Zada, Z., Goldstein, A., 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., Nastase, S. A.*, & Hasson, U.* (2024).
Neuron, 112(18), 3211-3222.e5.

Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns

Goldstein, A., Grinstein-Dabush, A., Schain, M., Wang, H., Hong, Z., Aubrey, B., Schain, M., Nastase, S. A., Zada, Z., Ham, E., Feder, A., Gazula, H., Buchnik, E., Doyle, W., Devore, S., Dugan, P., Reichart, R., Friedman, D., Brenner, M., … Hasson, U. (2024).
Nature Communications, 15(1), 2768.

Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language

Hong, Z.*, Wang, H.*, Zada, Z., Gazula, H., Turner, D., Aubrey, B., Niekerken, L., Doyle, W., Devore, S., Dugan, P., Friedman, D., Devinsky, O., Flinker, A., Hasson, U., Nastase, S. A., & Goldstein, A. (2024).
eLife 13:RP101204.

2022

Shared computational principles for language processing in humans and deep language models

Goldstein, A., Zada, Z., Buchnik, E., Schain, M., Price, A., Aubrey, B., Nastase, S. A., Feder, A., Emanuel, D., Cohen, A., Jansen, A., Gazula, H., Choe, G., Rao, A., Kim, C., Casto, C., Fanda, L., Doyle, W., Friedman, D., … Hasson, U. (2022).
Nature Neuroscience, 25(3), 369-380.