Stanford
Laboratory of Speech Neuroscience

Papers

Preprints

Roll, N., Kries, J., Jin, F., Wang, C., Finley, AM., Sumner, M., Shain, C. & Gwilliams, L. (submitted). The Text Aphasia Battery (TAB): A Clinically-Grounded Benchmark for Aphasia Like Deficits in Language Models. https://arxiv.org/abs/2511.20507 [pdf]

de Heer Kloots, M., Kazemian, A., Turner, W., Parvizi, J., Gwilliams, L. (submitted). Distinct yet neighboring neural populations encode past, future, and surrounding speech context in the human temporal lobe. bioRxiv. https://doi.org/10.64898/2026.05.13.724774 [pdf] 

Roll, N., Kries, J., Gwilliams, L., Shain, C. (submitted). Artificial Aphasias in Lesioned Language Models. https://arxiv.org/abs/2605.16222v1 [pdf]

Journal Publications

Ergin, I., Kries, J., Gupta, S., Papworth Barrel & Gwilliams, L. (2026). Measuring Naturalistic Speech Comprehension in Real Time. Behavior Research Methods, 58(4), 93. https://doi.org/10.3758/s13428-026-02941-1 [pdf]

Zhang, Y., Leonard, M.K., Bhaya-Grossman, I., Gwilliams, L., Chang, E.F., (2026). Human cortical dynamics of auditory word form encoding. Neuron 114, 167-180.e6. https://doi.org/10.1016/j.neuron.2025.10.011 [pdf]

Kries, J., *Vandermosten, M., & *Gwilliams, L. (2025). The spatio-temporal dynamics of phoneme encoding in aging and aphasia. Journal of Neuroscience, e1001252025. https://doi.org/10.1523/JNEUROSCI.1001-25.2025 [pdf]

Gwilliams, L., Marantz, A., Poeppel, D., & King, J. R. (2025). Hierarchical dynamic coding coordinates speech comprehension in the brain. Proc. Natl. Acad. Sci. U.S.A. 122 (42) e2422097122. https://doi.org/10.1073/pnas.2422097122 [pdf]

Abrams, E. B., Marantz, A., Krementsov, I., & Gwilliams, L. (2025). Dynamics of pitch perception in the auditory cortex. Journal of Neuroscience, e1111242025. https://doi.org/10.1523/JNEUROSCI.1111-24.2025 [pdf]

Bhaya-Grossman, I., Leonard, M.K., Zhang, Y., Gwilliams, L., Johnson, K., Lu, J., Chang, E.F., (2025). Shared and language-specific phonological processing in the human temporal lobe. Nature. https://doi.org/10.1038/s41586-025-09748-8 [pdf] 

Gwilliams, L., Bhaya-Grossman, I., Zhang, Y., Scott, T., Harper, S., & Levy, D. (2025). Computational Architecture of Speech Comprehension in the Human Brain. Annual Review of Linguistics, 11. https://doi.org/10.1146/annurev-linguistics-031120-111245 [pdf]

Reilly, J., Shain, C., Borghesani, V., Kuhnke, P., Vigliocco, G., Peelle, J. E., ... & Vinson, D. (2024). What we mean when we say semantic: Toward a multidisciplinary semantic glossary. Psychonomic bulletin & review, 1-38.https://doi.org/10.3758/s13423-024-02556-7 [pdf]

Degano, G., Donhauser, P. W., Gwilliams, L., Merlo, P., & Golestani, N. (2024). Speech prosody enhances the neural processing of syntax. Communications Biology, 7(1), 1-10. https://doi.org/10.1038/s42003-024-06444-7 [pdf]

Zuanazzi, A., Ripollés, P., Lin, W. M., Gwilliams, L., King, J. R., & Poeppel, D. (2024). Negation mitigates rather than inverts the neural representations of adjectives. Plos Biology, 22(5), e3002622.https://doi.org/10.1371/journal.pbio.3002622 [pdf]

*Gwilliams, L., *Leonard, M. K., Sellers, K. K., Chung, J. E., Xu, D., Mischler, G., ... & Chang, E. F. (2024). Large-scale single-neuron speech sound encoding across the depth of human cortex. Nature, 626(7999), 593-602.https://doi.org/10.1038/s41586-023-06839-2 [pdf]

Gwilliams, L., Flick, G., Marantz, A., Pylkkänen, L., Poeppel, D., & King, J. R. (2023). Introducing MEG-MASC a high-quality magneto-encephalography dataset for evaluating natural speech processing. Scientific data, 10(1), 862. https://doi.org/10.1038/s41597-023-02752-5 [pdf]

Gwilliams, L., Marantz, A., Poeppel, D., & King, J. R. (2023). Top-down information shapes lexical processing when listening to continuous speech. Language, Cognition and Neuroscience, 39(8), 1045-1058. https://doi.org/10.1080/23273798.2023.2171072 [pdf]

*Chung, J. E., *Sellers, K. K., Leonard, M. K., Gwilliams, L., Xu, D., Dougherty, M. E., ... & Chang, E. F. (2022). High-density single-unit human cortical recordings using the Neuropixels probe. Neuron, 110(15), 2409-2421. https://doi.org/10.1016/j.neuron.2022.05.007 [pdf]

Gwilliams, L., King, J. R., Marantz, A., & Poeppel, D. (2022). Neural dynamics of phoneme sequences reveal position-invariant code for content and order. Nature communications, 13(1), 6606. https://doi.org/10.1038/s41467-022-34326-1 [pdf]

Iemi, L., Gwilliams, L., Samaha, J., Auksztulewicz, R., Cycowicz, Y. M., King, J. R., ... & Haegens, S. (2022). Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability. NeuroImage, 247, 118746. https://doi.org/10.1016/j.neuroimage.2021.118746 [pdf]

*Gwilliams, L., *Blanco-Elorrieta, E., Marantz, A., & Pylkkänen, L. (2021). Adaptation to mis-pronounced speech: evidence for a prefrontal-cortex repair mechanism. Scientific reports, 11(1), 97. https://doi.org/10.1038/s41598-020-79640-0 [pdf]

Gwilliams, L., & King, J. R. (2020). Recurrent processes support a cascade of hierarchical decisions. Elife, 9, e56603. https://doi.org/10.7554/eLife.56603 [pdf]

Dikker, S., Assaneo, M. F., Gwilliams, L., Wang, L., & Kösem, A. (2020). Magnetoencephalography and language. Neuroimaging Clinics, 30(2), 229-238. https://doi.org/10.1016/j.nic.2020.01.004

Gwilliams, L. (2020). Hierarchical oscillators in speech comprehension: A commentary on Meyer, Sun, and Martin (2019). Language, Cognition and Neuroscience, 35(9), 1114-1118. https://doi.org/10.1080/23273798.2020.1740749 [pdf]

Gwilliams, L. (2020). How the brain composes morphemes into meaning. Philosophical Transactions of the Royal Society B, 375(1791), 20190311. https://doi.org/10.1098/rstb.2019.0311 [pdf]

Stockall, L., Manouilidou, C., Gwilliams, L., Neophytou, K., & Marantz, A. (2019). Prefix stripping re-re-revisited: MEG investigations of morphological decomposition and recomposition. Frontiers in Psychology, 10, 1964. https://doi.org/10.3389/fpsyg.2019.01964 [pdf]

Gwilliams, L., Poeppel, D., Marantz, A., & Linzen, T. (2018). Phonological (un) certainty weights lexical activation. In 8th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2018 (pp. 29-34). Association for Computational Linguistics (ACL). [pdf]

Gwilliams, L., Linzen, T., Poeppel, D., & Marantz, A. (2018). In spoken word recognition, the future predicts the past. Journal of Neuroscience, 38(35), 7585-7599. https://doi.org/10.1523/JNEUROSCI.0065-18.2018 [pdf]

Gwilliams, L., & Marantz, A. (2018). Morphological representations are extrapolated from morpho-syntactic rules. Neuropsychologia, 114, 77-87. https://doi.org/10.1016/j.neuropsychologia.2018.04.015 [pdf]

Brodbeck, C., Gwilliams, L., & Pylkkänen, L. (2016). Language in context: MEG evidence for modality-general and-specific responses to reference resolution. ENeuro, 3(6). https://doi.org/10.1523/ENEURO.0145-16.2016 [pdf]

Gwilliams, L., Lewis, G. A., & Marantz, A. (2016). Functional characterisation of letter-specific responses in time, space and current polarity using magnetoencephalography. Neuroimage, 132, 320-333. https://doi.org/10.1016/j.neuroimage.2016.02.057 [pdf]

Brodbeck, C., Gwilliams, L., & Pylkkänen, L. (2015). EEG can track the time course of successful reference resolution in small visual worlds. Frontiers in psychology, 6, 1787. https://doi.org/10.3389/fpsyg.2015.01787 [pdf]

Gwilliams, L., & Marantz, A. (2015). Non-linear processing of a linear speech stream: The influence of morphological structure on the recognition of spoken Arabic words. Brain and language, 147, 1-13. https://doi.org/10.1016/j.bandl.2015.04.006 [pdf]

Gwilliams, L. E., Monahan, P. J., & Samuel, A. G. (2015). Sensitivity to morphological composition in spoken word recognition: Evidence from grammatical and lexical identification tasks. Journal of experimental psychology: Learning, memory, and cognition, 41(6), 1663. https://doi.org/10.1037/xlm0000130 [pdf]

Gwilliams, L., & Fontaine, L. (2015). Indeterminacy in process type classification. Functional Linguistics, 2, 1-19. https://doi.org/10.1186/s40554-015-0021-x [pdf]

Politzer-Ahles, S., & Gwilliams, L. (2015). Involvement of prefrontal cortex in scalar implicatures: evidence from magnetoencephalography. Language, Cognition and Neuroscience, 30(7), 853-866. https://doi.org/10.1080/23273798.2015.1027235 [pdf]

Book Chapters

Gwilliams, L., & Marantz, A. (2023). Neural Processing of Morphological Structure in Speech Production, Listening, and Reading. In Linguistic Morphology in the Mind and Brain (pp. 137-151). Routledge.

Stockall, L. & Gwilliams, L. (2023). Distributed morphology and neurolinguistics. In The Cambridge Handbook of Distributed Morphology.

Dikker, S., Mech, E. N., Gwilliams, L., West, T., Dumas, G., & Federmeier, K. D. (2022). Exploring age-related changes in inter-brain synchrony during verbal communication. In Psychology of Learning and Motivation (Vol. 77, pp. 29-68). Academic Press. https://doi.org/10.1016/bs.plm.2022.08.003

Gwilliams, L., Davis, M.H. (2022). Extracting Language Content from Speech Sounds: The Information Theoretic Approach. In: Holt, L.L., Peelle, J.E., Coffin, A.B., Popper, A.N., Fay, R.R. (eds) Speech Perception. Springer Handbook of Auditory Research, vol 74. Springer, Cham. https://doi.org/10.1007/978-3-030-81542-4_5

King, JR., Gwilliams, L., Holdgraf, C., Sassenhagen, J., Barachant, A., Engemann, D., Larson, E. & Gramfort, A. (2020). Encoding and Decoding Framework to Uncover the Algorithms of Cognition. In The Cognitive Neurosciences.