Publications

Lab members are noted in bold


2024


Wolfman, M., Dunagan, D., Brennan, J. R., & Hale, J. (2024). Hierarchical syntactic structure in human-like language models. Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics. [link]

Momenian, M., Ma, Z., Wu, S., Wang, C., Brennan, J. R., Hale, J., Meyer, L, & Li, J. (2024).
Le Petit Prince Hong Kong (LPPHK): Naturalistic fMRI and EEG data from older Cantonese
speakers. Scientific Data. [data]

Cho, J.-H., Pires, A. & Brennan, J. R. (2024). How large are root and affix priming effects
in visual word recognition? Estimation from original data and a Bayesian meta-analysis.
Language, Cognition & Neuroscience. [link] [code]

Tatar, C., Brennan, J. R., Krivokapic, J. & Keshet, E. (2024). Examining melodiousness in
sarcasm: Wiggliness, spaciousness, and contour clustering. Proceedings of Speech Prosody
2024
. [link]

Cho, J.-H., & Brennan, J. R. (2024). Neural decoding of words and morphosyntactic features
within and across languages. Proceedings of COGSCI 2024 [link]

He, L., Chen, P., Nie, E., Li, Y., & Brennan, J. R. (2024). Decoding Probing: Revealing Internal Linguistic Structures in Neural Language Models using Minimal Pairs. Proceedings of LREC-COLING 2024. COLING2024. [link]

Sugimoto, Y., Yoshida, R., Jeong, H., Koizumi, M., Brennan, J. R., & Oseki, Y. (2024).
Localizing Syntactic Composition with Left-Corner Recurrent Neural Network Grammars.
Neurobiology of Language [link]


2023


Tung, T.-Y., & Brennan, J. R. (2023). Expectations modulate retrieval interference during ellipsis resolution. Neuropsychologia [link]

Stanojević, M.*, Brennan. J. R.*, Dunagan, D., Steedman, M., & Hale, J. T. (2023). Modeling structure-building in the brain with CCG parsing and large language models. Cognitive Science 47(7) [link] [data] [analysis]
(* denotes co-first authorship)

Dunagan, D., Stanojević, M., Coavoux, M., , Zhang, S., Bhattasali, S., Li, J., Brennan, J. R., & Hale, J (2023). Long-distance linguistic dependencies in Chinese and English brains. Neurobiology of Language [link] [data]

Brennan, J. R. (2023). Syntax. in Johnsrude, I. (ed.) Oxford Research Encyclopedia for Psychology. [link] [preprint]

Brennan, J. R., (2023). Hemodynamic methods. in Sprouse, J. (ed.) The Oxford Handbook of Experimental Syntax. [preprint]


2022


Li, J., Bhattasali, S., Zhang, S., Franzluebbers, B., Luh, W., Spreng, R. N., Brennan, J. R., Yang, Y., Pallier, C., & Hale, J. (2022). Le Petit Prince: A multilingual fMRI corpus using ecological stimuli. Scientific Data 9 530. [link] [data

Lo, C.-W., Tung, T.-Y., Ke, H., & Brennan, J. R. (2022). Hierarchy, not lexical regularity, modulates low-frequency neural synchrony during language comprehension. Neurobiology of Language. [link]

Cho, J.-H., & Brennan, J. R. (2022). Word-final orthographic priming as a function of word frequency, prime duration, and morphological status. Proceedings of the Annual Meeting of the Cognitive Science Society. [link]

Brennan, J. R. (2022) Language and the brain: A slim guide to neurolinguistics. Oxford, UK: Oxford University Press. [link]

Hale, J. T., Campenelli, L., Li, J., Bhattasali, S., Pallier, C. & Brennan, J. R. (2022). Neuro-computational models of language processing. Annual Review of Linguistics, 8: 427-446. [link]


2021


Stanojević, M., Bhattasali, S., Dunagan, D., Campanelli, L., Steedman, M., Brennan, J., & Hale, J. (2021). Modeling Incremental Language Comprehension in the Brain with Combinatory Categorial Grammar. Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, 23–38. [link]

Lo, C.-W. & Brennan, J. R. (2021). EEG correlates of long-distance dependency formation in mandarin wh-questions. Frontiers in Human Neuroscience, 15:23. [link]


2020


Wagley, N., Kovelman, I., Lajiness-O’Neill, R., Hay, J. S. F., Ugolini, M., Bowyer, S. M., & Brennan, J. R. (2020). Predictive processing during a naturalistic statistical learning task in ASD. eNeuro [link]

Brennan, J. R., Kuncoro, A., Dyer, C., & Hale, J. T. (2020) Localizing syntactic predictions using recurrent neural network grammars. Neuropsychologia 146: 1074–1079 [link]

Stehwien, S., Henke, L., Hale, J. T., Brennan, J. R., & Meyer, L. (2020). The Little Prince in 26 Languages: Towards a Multilingual Neuro-Cognitive Corpus. Proceedings of the Workshop on Linguistic and Neurocognitive Resources (LiNCr2020) pp. 43–49

Pylkkänen, L. & Brennan, J. R. (2020). The Neurobiology of Syntactic and Semantic Structure Building In Poeppel, Mangun & Gazzaniga (eds.) The Cognitive Neurosciences, 6th ed.  [preprint]

Bhattasali, S., Brennan, J. R., Luh, W.-M., Franzluebbers, B., & Hale, J. T., (2020).The Alice Datasets: fMRI & EEG Observations of Natural Language Comprehension. Proceedings of Linguistic Resources and Evaluation (LREC) [link] [fMRI data] [EEG data]

Weissler, R. E. & Brennan, J. R. (2020). How do listeners form grammatical expectations to African American Language?. University of Pennsylvania Working Papers in Linguistics. 25(2) [link]


2019


Brennan, J. R. & Martin, A. E. (2019). Phase synchronization varies systematically with linguistic structure composition. Philosophical Transactions of the Royal Society B 375. [link] [data]

Hale, J. T., Kuncoro, A., Hall, K. B., Dyer, C., & Brennan, J. R., (2019). Text Genre and Training Data Size in Human-Like Parsing. Proceedings of Empirical Methods in Natural Language Processing. [preprint] raw data]

Brennan, J. R., & Hale, J. T. (2019). Hierarchical structure guides rapid linguistic predictions during naturalistic listening. PLoSONE 14(1): e0207741 [link] [raw data & stimuli]


2018


Brennan, J. R., Lajiness-O’Neill, R., Bowyer, S., Kovelman, I., & Hale, J. T. (2018). Predictive sentence comprehension during story-listening in Autism Spectrum Disorder. Language, Cognition & Neuroscience, 34(4): 428-439. [link]

Brennan, J. R., (2018). Mapping meanings. Trends in Neurosciences, 41(11): 770-772 [link]

Bhattasali, S., Fabre, M., Luh, W.-M., Al Saied, H., Constant, M., Pallier, C., Brennan, J. R., & Hale, J. T. (2018). Localising memory retrieval and syntactic composition: an fMRI study of naturalistic language comprehension. Language, Cognition and Neuroscience, 34(4): 491-510. [link]

Wei, H., Boland, J. E., Brennan, J., Yuan, F., Wang, M., & Zhang, C. (2018). Lexicalized structural priming in second language online sentence comprehension. Second Language Research, 34(3): 395-416 [link]

Hale, J., Dyer, C., Kuncoro, A., & Brennan, J. R. (2018). Finding syntax in human encephalography with beam search. Proceedings of the Association for Computational Linguistics. [link] [raw data & stimuli] 🏆 Best Paper Award

Lajiness-O’Neill, R., Brennan, J., Flores, A., Swick, C., Goodcase, R., Anderson, T., McFarlane, K., Rusiniak, K., Kovelman, I., Wagley, N.Ugolini, M., Richard, A. E. Albright, J., Moran, J. E., & Bowyer, S. M. (2018). Patterns of Altered Neural Synchrony in the Default Mode Network in Autism Spectrum Disorder Revealed with Magnetoencephalography (MEG): Relationship to Clinical Symptomatology. Autism Research, 11: 434-449 [link]

Bhattasali, S., Hale, J.T., Pallier, C., Brennan, J.R., Luh, W.-M., & Spreng, R.N. (2018). Differentiating Phrase Structure Parsing and Memory Retrieval in the Brain. Proceedings of the Society for Computation in Linguistics. [link]


2017 


Brennan, J. R. & Pylkkänen, L (2017) MEG evidence for incremental sentence composition in the anterior temporal lobe. Cognitive Science, 41(S6): 1515-1531[link]


2016


Li, J., Hale, J. T., Mahar, A.,& Brennan, J. R. (2016). Temporal Lobes as Combinatory Engines for both Form and Meaning. Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), COLING2016. [Proceedings PDF]

Brennan, J., Wagley, N., Kovelman, I., Bowyer, S. M., Richard, A. E., and Lajiness-O’Neill, R., (2016). MEG reveals atypical sensitivity to linguistic sound sequences in Autism Spectrum Disorder. NeuroReport, 27(13): 982-986 [link]

Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7): 299–313 [link]

Brennan, J., Stabler, E. P. Jr., Van Wagenen, S. E., Luh, W.-M., & Hale, J. (2016). Abstract Linguistic Structure Correlates with Temporal Activity during Naturalistic Comprehension. Brain and Language, 157-158: 81-84.  [link] [stimulus & data]

Levinson, L. & Brennan, J. (2016). Silent causativity in verbs: Behavioral and neural correlates. Morphological Metatheory eds. D. Siddiqi and H. Harley, pp. 163-198. John Benjamins [link]


2015


Hale, J. T., Lutz, D., Luh, W.-M., & Brennan, J. (2015). Modeling fMRI time courses with linguistic structure at various grain sizes. Proceedings of the 6th Workshop on Cognitive Modeling and Computational Linguistics, pp. 89–97 [PDF]

Kovelman, I, Wagley, N., Hay, J. S. F., Ugolini, M., Bowyer, S., Lajiness-O’Neill, R., & Brennan, J. (2015) Multi-modal imaging of temporal processing in typical and atypical language development. Annals of the New York Academy of Sciences, 1337: 7–15 [link]

Brennan, J. (2015) Neurolinguistic processing of psychological verbs. in Wright, J. D. (Ed.) International Encyclopedia of Social and Behavioral Sciences, 2nd ed. [link]


2014


VanWagenen, S., Brennan, J., and Stabler, E. P. (2014) Quantifying parsing complexity as a function of grammar complexity. In Stockall, L., and Shutze, C. (Eds.) UCLA Working Papers in Linguistics, no. 18, Connectedness: A Festshrift for Sarah VanWagenen [link]

Brennan, J., Lignos, Constantine, Embick, D. & Roberts, T. P. L. (2014). Spectro-temporal correlates of lexical access during auditory lexical decision. Brain & Language. 133:39–46. [link]