| Shared computational principles for language processing in humans and deep language models A Goldstein, Z Zada, E Buchnik, M Schain, A Price, B Aubrey, SA Nastase, ... Nature neuroscience 25 (3), 369-380, 2022 | 425* | 2022 |
| Correspondence between the layered structure of deep language models and temporal structure of natural language processing in the human brain A Goldstein, E Ham, SA Nastase, Z Zada, A Grinstein-Dabus, B Aubrey, ... BioRxiv, 2022.07. 11.499562, 2022 | 32 | 2022 |
| Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns A Goldstein, A Grinstein-Dabush, M Schain, H Wang, Z Hong, B Aubrey, ... Nature communications 15 (1), 2768, 2024 | 20 | 2024 |
| A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations Z Zada, A Goldstein, S Michelmann, E Simony, A Price, L Hasenfratz, ... Neuron 112 (18), 3211-3222. e5, 2024 | 14 | 2024 |
| Deep speech-to-text models capture the neural basis of spontaneous speech in everyday conversations A Goldstein, H Wang, L Niekerken, Z Zada, B Aubrey, T Sheffer, ... bioRxiv, 2023.06. 26.546557, 2023 | 12 | 2023 |
| A shared linguistic space for transmitting our thoughts from brain to brain in natural conversations Z Zada, A Goldstein, S Michelmann, E Simony, A Price, L Hasenfratz, ... bioRxiv, 2023 | 11 | 2023 |
| Brain embeddings with shared geometry to artificial contextual embeddings, as a code for representing language in the human brain A Goldstein, A Dabush, B Aubrey, M Schain, SA Nastase, Z Zada, E Ham, ... BioRxiv, 2022.03. 01.482586, 2022 | 10 | 2022 |
| Thinking ahead: prediction in context as a keystone of language in humans and machines. bioRxiv A Goldstein, Z Zada, E Buchnik, M Schain, A Price, B Aubrey, SA Nastase, ... | 8 | 2021 |
| The temporal structure of language processing in the human brain corresponds to the layered hierarchy of deep language models A Goldstein, E Ham, M Schain, S Nastase, Z Zada, A Dabush, B Aubrey, ... arXiv preprint arXiv:2310.07106, 2023 | 4 | 2023 |
| Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language Z Hong, H Wang, Z Zada, H Gazula, D Turner, B Aubrey, L Niekerken, ... bioRxiv, 2024 | 2 | 2024 |
| Aligning Brains into a Shared Space Improves their Alignment to Large Language Models A Bhattacharjee, Z Zada, H Wang, B Aubrey, W Doyle, P Dugan, ... bioRxiv, 2024.06. 04.597448, 2024 | 1 | 2024 |
| Brain-to-brain linguistic coupling in natural conversations Z Zada, S Nastase, A Goldstein, U Hasson 2022 Conference on Cognitive Computational Neuroscience, 2022 | 1 | 2022 |
| In Search of a Neural Mechanism for Domain-General Value Comparison in Decision Making A Samara, Z Zada Journal of Neuroscience 45 (7), 2025 | | 2025 |
| The" Podcast" ECoG dataset for modeling neural activity during natural language comprehension Z Zada, SA Nastase, B Aubrey, I Jalon, S Michelmann, H Wang, ... bioRxiv, 2025.02. 14.638352, 2025 | | 2025 |
| Linguistic coupling between neural systems for speech production and comprehension during real-time dyadic conversations Z Zada, SA Nastase, S Speer, L Mwilambwe-Tshilobo, L Tsoi, S Burns, ... bioRxiv, 2025.02. 14.638276, 2025 | | 2025 |
| Author Correction: Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns A Goldstein, A Grinstein-Dabush, M Schain, H Wang, Z Hong, B Aubrey, ... nature communications 15, 8500, 2024 | | 2024 |
| Information-making processes in the speaker’s brain drive human conversations forward A Goldstein, H Wang, T Sheffer, M Schain, Z Zada, L Niekerken, B Aubrey, ... bioRxiv, 2024.08. 27.609946, 2024 | | 2024 |
| Larger Language Models Better Predict Neural Activity During Natural Language Processing Z Hong, H Wang, Z Zada, H Gazula, B Aubrey, W Doyle, S Devore, ... | | |
