Lists with and without syntax: a new approach to measuring the neural processing of syntax
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Abstract
In the neurobiology of syntax, a methodological challenge is to vary syntax while holding semantics constant. Changes in syntactic structure usually correlate with changes in meaning. We approached this challenge from a new angle. We deployed word lists—typically, the unstructured control in studies of syntax—as both test and control stimuli. Three-noun lists (“lamps, dolls, guitars”) were embedded in sentences (“The eccentric man hoarded lamps, dolls, guitars…”) and in longer lists (“forks, pen, toilet, rodeo, lamps, dolls, guitars…”). This allowed us to minimize contributions from lexical semantics and local phrasal combinatorics: the same words occurred in both conditions, and in neither case did the list items locally compose into phrases (e.g., “lamps” and “dolls” do not form a phrase). Crucially, the list partakes in a syntactic tree in one case but not the other. Lists-in-sentences increased source-localized MEG activity at ∼250–300 ms from each of the list item onsets in the left inferior frontal cortex, at ∼300–350 ms in the left anterior temporal lobe and, most reliably, at ∼330–400 ms in left posterior temporal cortex. In contrast, the main effects of semantic association strength, which we also varied, localized in the left temporoparietal cortex, with high associations increasing activity at ∼400 ms. This dissociation offers a novel characterization of the structure versus word meaning contrast in the brain: the frontotemporal network that is familiar from studies of sentence processing can be driven by the sheer presence of global sentence structure, while associative semantics has a more posterior neural signature. SIGNIFICANCE STATEMENT Human languages all have a syntax, which both enables the infinitude of linguistic creativity and determines what is grammatical in a language. The neurobiology of syntactic processing has, however, been challenging to characterize despite decades of study. One reason is pure manipulations of syntax are difficult to design. The approach here offers a novel control of two variables that are notoriously hard to keep constant when syntax is manipulated: word meaning and phrasal combinatorics. The same noun lists occurred inside longer lists and sentences, while semantic associations also varied. Our MEG results show that classic frontotemporal language regions can be driven by sentence structure even when local semantic contributions are absent. In contrast, the left temporoparietal junction tracks associative relationships.
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The human language network is sensitive to abstract hierarchical rules across isolated phrases, naturalistic narratives, and syntactically well-formed but semantically empty stimuli.
“it is sensitive to abstract hierarchical rules in isolated phrases and sentences [31, 108, 109, 110], in naturalistic narratives [111, 112, 113, 114], and in syntactically well-formed but semantically empty (”
From Dissociating language and thought in large language models (2024) · cites this paper as [110]
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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835 · see citing works
Glove: Global Vectors for Word Representation
Pennington, J., Socher, R., & Manning, C. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1162 · Cited by 34,071 · see citing works
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324 · see citing works
Fitting Linear Mixed-Effects Models Using lme4Preprint
Bates, D. M., Maechler, M., Bolker, B. M., & Walker, S. (2014) · arXiv (Cornell University) · doi:10.3929/ethz-b-000105397 · Cited by 9,435 · see citing works
Nonparametric statistical testing of EEG- and MEG-data
Maris, E., & Oostenveld, R. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.03.024 · Cited by 8,496 · see citing works
SMITH, S., & NICHOLS, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.061 · Cited by 5,250 · see citing works
Thresholding of statistical maps in functional neuroimaging using the false discovery rate
Genovese, C. R., Lazar, N. A., & Nichols, T. (2002) · NeuroImage · doi:10.1006/nimg.2001.1037 · Cited by 4,923 · see citing works
Kutas, M., & Federmeier, K. D. (2011) · Annual Review of Psychology · doi:10.1146/annurev.psych.093008.131123 · Cited by 4,377 · see citing works
Brysbaert, M., & New, B. (2009) · Behavior Research Methods · doi:10.3758/brm.41.4.977 · Cited by 2,821 · see citing works
Spherical splines for scalp potential and current density mapping
Perrin, F., Pernier, J., Bertrand, O., & Echallier, J. F. (1989) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(89)90180-6 · Cited by 2,706 · see citing works
Using confidence intervals in within-subject designs
Loftus, G. R., & Masson, M. E. J. (1994) · Psychonomic Bulletin & Review · doi:10.3758/bf03210951 · Cited by 2,433 · see citing works
The brain basis of language processing: from structure to function.
Friederici, A. D. (2011) · Physiological Reviews · doi:10.1152/physrev.00006.2011 · Cited by 2,140 · see citing works
MNE software for processing MEG and EEG data
Gramfort, A., Luessi, M., Larson, E., Engemann, D. A., Strohmeier, D., Brodbeck, C. J., Parkkonen, L. T., & Hämäläinen, M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.10.027 · Cited by 1,924 · see citing works
Concreteness ratings for 40 thousand generally known English word lemmas
Brysbaert, M., Warriner, A. B., & Kuperman, V. (2014) · Behavior Research Methods · doi:10.3758/s13428-013-0403-5 · Cited by 1,821 · see citing works
Dynamic Statistical Parametric Mapping
Dale, A. M., Liu, A. K., Fischl, B. R., Buckner, R. L., Belliveau, J. W., Lewine, J. D., & Halgren, E. (2000) · Neuron · doi:10.1016/s0896-6273(00)81138-1 · Cited by 1,787 · see citing works
A cortical network for semantics: (de)constructing the N400
Lau, E. F., Phillips, C., & Poeppel, D. (2008) · Nature reviews. Neuroscience · doi:10.1038/nrn2532 · Cited by 1,688 · see citing works
Parsimonious Mixed ModelsPreprint
Bates, D. M., Kliegl, R. M., Vasishth, S., & Baayen, R. H. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.04967 · Cited by 1,455 · see citing works
A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex
Van Essen, D. C. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.058 · Cited by 1,151 · see citing works
What do we mean by prediction in language comprehension?
Kuperberg, G. R., & Jaeger, T. F. (2016) · Language, Cognition and Neuroscience · doi:10.1080/23273798.2015.1102299 · Cited by 1,087 · see citing works
The Now-or-Never bottleneck: A fundamental constraint on language
Christiansen, M. H., & Nick Chater, A. (2015) · Behavioral and Brain Sciences · doi:10.1017/s0140525x1500031x · Cited by 750 · see citing works
The Cortical Representation of Speech
Mazoyer, B. M., Tzourio‐Mazoyer, N., Frak, V., Syrota, A., Murayama, N., Levrier, O., Salamon, G., Dehaene, S., Cohen, L., & Mehler, J. (1993) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1993.5.4.467 · Cited by 712 · see citing works
The extended language network: A meta-analysis of neuroimaging studies on text comprehension
Ferstl, E. C., Neumann, J., Bogler, C., & von Cramon, D. Y. (2008) · Human Brain Mapping · doi:10.1002/hbm.20422 · Cited by 703 · see citing works
Cortical representation of the constituent structure of sentences
Pallier, C., Devauchelle, A.-D., & Dehaene, S. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018711108 · Cited by 691 · see citing works
Friederici, A. D., & Gierhan, S. M. E. (2012) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.10.002 · Cited by 673 · see citing works
When Peanuts Fall in Love: N400 Evidence for the Power of Discourse
Nieuwland, M. S., & Berkum, J. J. A. V. (2006) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2006.18.7.1098 · Cited by 588 · see citing works
Syntactic and Semantic Modulation of Neural Activity during Auditory Sentence Comprehension
Humphries, C., Binder, J. R., Medler, D. A., & Liebenthal, E. (2006) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2006.18.4.665 · Cited by 449 · see citing works
The Response of Left Temporal Cortex to Sentences
Vandenberghe, R. R., Nobre, A. C., & Price, C. J. (2002) · Journal of Cognitive Neuroscience · doi:10.1162/08989290260045800 · Cited by 431 · see citing works
The brain circuitry of syntactic comprehension
Kaan, E., & Swaab, T. Y. (2002) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(02)01947-2 · Cited by 428 · see citing works
The Cortical Organization of Syntax
Matchin, W., & Hickok, G. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhz180 · Cited by 370 · see citing works
Nodes and networks in the neural architecture for language: Broca's region and beyond
Peter Hagoort, A. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.07.013 · Cited by 330 · see citing works
Humphries, C., Love, T. E., Swinney, D., & Hickok, G. S. (2005) · Human Brain Mapping · doi:10.1002/hbm.20148 · Cited by 327 · see citing works
Working memory and binding in sentence recall
Baddeley, A., Hitch, G. J., & Allen, R. J. (2009) · Journal of Memory and Language · doi:10.1016/j.jml.2009.05.004 · Cited by 293 · see citing works
Bemis, D. K., & Liina Pylkkänen, A. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5003-10.2011 · Cited by 279 · see citing works
Snijders, T. M., Vosse, T., Kempen, G., Berkum, J. J. A. V., Petersson, K. M., & Peter Hagoort, A. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn187 · Cited by 249 · see citing works
The neural basis of combinatory syntax and semantics
Liina Pylkkänen, A. (2019) · Science · doi:10.1126/science.aax0050 · Cited by 237 · see citing works
Self-citationRogalsky, C., & Hickok, G. S. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn126 · Cited by 236 · see citing works
Friederici, A. D., & Chomsky, N. (2017) · The MIT Press eBooks · doi:10.7551/mitpress/11173.001.0001 · Cited by 231 · see citing works
Localizing components of a complex task
Stowe, L. A., Broere, C. A. J., Paans, A. M. J., Wijers, A. A., Mulder, G., Vaalburg, W., & Zwarts, F. (1998) · Neuroreport · doi:10.1097/00001756-199809140-00014 · Cited by 206 · see citing works
Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals
Engemann, D. A., & Gramfort, A. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.040 · Cited by 203 · see citing works
Neural correlate of the construction of sentence meaning
Fedorenko, E., Scott, T. L., Brunner, P., Coon, W. G., Pritchett, B., Schalk, G., & Kanwisher, N. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1612132113 · Cited by 199 · see citing works
Fedorenko, E. G., Nieto-Castañón, A., & Kanwisher, N. (2011) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.09.014 · Cited by 186 · see citing works
Seana Coulson, A., Federmeier, K. D., Petten, C. K. V., & Marta Kutas, A. (2005) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.31.1.129 · Cited by 185 · see citing works
Fronto-temporal brain systems supporting spoken language comprehension
Tyler, L. K., & Marslen-Wilson, W. (2008) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2007.2158 · Cited by 178 · see citing works
Matchin, W., Hammerly, C. M., & Lau, E. F. (2016) · Cortex · doi:10.1016/j.cortex.2016.12.010 · Cited by 166 · see citing works
Adachi, Y., Shimogawara, M., Higuchi, M., Haruta, Y., & Ochiai, M. (2001) · IEEE Transactions on Applied Superconductivity · doi:10.1109/77.919433 · Cited by 151 · see citing works
Rodd, J. M., Longe, O. A., Randall, B., & TYLER, L. K. (2009) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2009.12.035 · Cited by 142 · see citing works
The role of the left anterior temporal lobe in semantic composition vs. semantic memory
Westerlund, M., & Liina Pylkkänen, A. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2014.03.001 · Cited by 130 · see citing works
Language in Our Brain: The Origins of a Uniquely Human Capacity
Friederici, A. D. (2017) · Project Muse (Johns Hopkins University) · doi:10.7551/mitpress/11173.001.0001?locatt=mode:legacy · Cited by 128 · see citing works
The time-course and spatial distribution of brain activity associated with sentence processing
Brennan, J., & Liina Pylkkänen, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.030 · Cited by 124 · see citing works
Self-citationZaccarella, E., Schell, M., & Friederici, A. D. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.06.011 · Cited by 122 · see citing works
Griffiths, J. D., Marslen‐Wilson, W. D., Stamatakis, E. A., & TYLER, L. K. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr386 · Cited by 116 · see citing works
Composition is the Core Driver of the Language-selective Network
Mollica, F., Diachek, E., Mineroff, Z., Kean, H., Siegelman, M., Piantadosi, S. T., Futrell, R., Qian, P., & Fedorenko, E. G. (2020) · Neurobiology of Language · doi:10.1162/nol_a_00005 · Cited by 108 · see citing works
Evidence for conceptual combination in the left anterior temporal lobe
Baron, S. G., & Osherson, D. N. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.066 · Cited by 106 · see citing works
Matchin, W., Brodbeck, C. J., Hammerly, C. M., & Lau, E. F. (2018) · Human Brain Mapping · doi:10.1002/hbm.24403 · Cited by 88 · see citing works
Meyer, L., Obleser, J., Anwander, A., & Friederici, A. D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.05.052 · Cited by 86 · see citing works
Resolving sentence ambiguity with planning and working memory resources: Evidence from fMRI
Novais-Santos, S., Gee, J. C., Shah, M., Troiani, V., Work, M., & Grossman, M. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.077 · Cited by 85 · see citing works
Zhang, L., & Liina Pylkkänen, A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.028 · Cited by 85 · see citing works
Comprehension and Memory in Rapid Sequential Reading
Nickerson, R. S. (2014) · doi:10.4324/9781315802961-31 · Cited by 73 · see citing works
Rhodes, S., & Donaldson, D. (2007) · Psychophysiology · doi:10.1111/j.1469-8986.2007.00598.x · Cited by 66 · see citing works
Flick, G., & Liina Pylkkänen, A. (2020) · Cortex · doi:10.1016/j.cortex.2020.01.025 · Cited by 47 · see citing works
Self-citationIs the N400 effect a neurophysiological index of associative relationships?
Ortu, D., Allan, K., & Donaldson, D. I. (2013) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2013.05.003 · Cited by 43 · see citing works
TYLER, L. K., Cheung, T., Devereux, B. J., & Clarke, A. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00271 · Cited by 43 · see citing works
Same words, different structures: An fMRI investigation of argument relations and the angular gyrus
Matchin, W., Liao, C.-H., Gaston, P., & Lau, E. F. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.01.019 · Cited by 42 · see citing works
Whole report versus partial report in RSVP sentences
Potter, M. C., Nieuwenstein, M. R., & Strohminger, N. (2008) · Journal of Memory and Language · doi:10.1016/j.jml.2007.12.002 · Cited by 38 · see citing works
Coutanche, M. N., Solomon, S. H., & Thompson‐Schill, S. L. (2020) · The Cognitive Neurosciences · doi:10.7551/mitpress/11442.003.0091 · Cited by 11 · see citing works
The Neurobiology of Syntactic and Semantic Structure Building
Pylkkänen, L., & Brennan, J. (2020) · The Cognitive Neurosciences · doi:10.7551/mitpress/11442.003.0096 · Cited by 8 · see citing works
Self-citation
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- Kim S, Pylkkänen L (2020) Is semantic composition in the left anterior temporal lobe blind to syntax? Paper presented at 33rd Annual CUNY Human Sentence Processing Conference, Amherst, MA, March.
Cited by
Sorted by citations
Dissociating language and thought in large language models
Mahowald, K., Ivanova, A. A., Blank, I. A., Kanwisher, N., Tenenbaum, J. B., & Fedorenko, E. (2024) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.01.011 · Cited by 345 · see citing works
Minimal Phrase Composition Revealed by Intracranial Recordings
Murphy, E., Woolnough, O., Rollo, P. S., Roccaforte, Z. J., Segaert, K., Peter Hagoort, A., & Tandon, N. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.1575-21.2022 · Cited by 67 · see citing works
Left posterior temporal cortex is sensitive to syntax within conceptually matched Arabic expressions
Matar, S., Dirani, J., Marantz, A., & Liina Pylkkänen, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-86474-x · Cited by 39 · see citing works
Kapteijns, B., & Hintz, F. (2021) · PLoS ONE · doi:10.1371/journal.pone.0254546 · Cited by 22 · see citing works
Maran, M., Numssen, O., Hartwigsen, G., Friederici, A. D., & Zaccarella, E. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.968836 · Cited by 21 · see citing works
Language at a glance: How our brains grasp linguistic structure from parallel visual input
Fallon, J., & Liina Pylkkänen, A. (2024) · Science Advances · doi:10.1126/sciadv.adr9951 · Cited by 22 · see citing works
van der Burght, C. L., Friederici, A. D., Maran, M., Papitto, G., Pyatigorskaya, E., Schroën, J. A. M., Trettenbrein, P. C., & Zaccarella, E. (2023) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02058 · Cited by 16 · see citing works
Semantic and syntactic specialization during auditory sentence processing in 7-8-year-old children
Wang, J., Wagley, N., Rice, M. L., & Booth, J. R. (2021) · Cortex · doi:10.1016/j.cortex.2021.09.006 · Cited by 15 · see citing works
Semantic composition in experimental and naturalistic paradigms
Li, J., Lai, M. C.-H., & Liina Pylkkänen, A. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00072 · Cited by 22 · see citing works
Călinescu, L., Ramchand, G. C., & Baggio, G. (2023) · Frontiers in Language Sciences · doi:10.3389/flang.2023.1096110 · Cited by 16 · see citing works
Finding structure during incremental speech comprehension
Lyu, B., Marslen‐Wilson, W. D., Fang, Y., & TYLER, L. K. (2023) · eLife · doi:10.7554/elife.89311 · Cited by 12 · see citing works
Hauptman, M., Blanco-Elorrieta, E., & Liina Pylkkänen, A. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab309 · Cited by 10 · see citing works
Minimal Phrase Composition Revealed by Intracranial RecordingsPreprint
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Decoding the Neural Dynamics of Headed Syntactic Structure Building
赵隽元, J. Z., Gao, R., & Brennan, J. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.2126-24.2025 · Cited by 6 · see citing works
Yu, X., Mancha, S., Tian, X., & Lau, E. F. (2026) · Cognitive Science · doi:10.1111/cogs.70220 · Cited by 3 · see citing works
Finding structure during incremental speech comprehensionPreprint
Lyu, B., Marslen‐Wilson, W. D., Fang, Y., & TYLER, L. K. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.25.465687 · Cited by 3 · see citing works
Finding structure during incremental speech comprehension
Lyu, B., Marslen‐Wilson, W. D., Fang, Y., & TYLER, L. K. (2024) · eLife · doi:10.7554/elife.89311.3 · Cited by 2 · see citing works
MEG correlates of speech planning in simple vs. interactive picture naming in children and adults
Goldman, E., Dargham, S. B., Lai, M. C.-H., Guda, A., Fallon, J., Hauptman, M., Reinoso, A., Phillips, S. F., Abrams, E. B., Parrish, A., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0292316 · Cited by 2 · see citing works
Jiang, J., Guoyu, Z. H. A. O., Yingbo, M. A., Ding, G., & Lanfang, L. I. U. (2023) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2023.01002 · Cited by 3 · see citing works
Can we separate semantic representations from computations? A commentary on Calzavarini (2024)
Hauk, O., Magnabosco, F., & Law, R. (2023) · Language Cognition and Neuroscience · doi:10.1080/23273798.2023.2226269 · Cited by 2 · see citing works
Self-citationFinding structure during incremental speech comprehensionPreprint
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Flower, N., & Liina Pylkkänen, A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.17.688866 · Cited by 1 · see citing works
Finding structure during incremental speech comprehensionPreprint
Lyu, B., Marslen‐Wilson, W. D., Fang, Y., & TYLER, L. K. (2024) · eLife · doi:10.7554/elife.89311.2
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Liu, H., & Chen, H. (2024) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-50549-2_12
Syntactic development by trial and error
Ninio, A. (2025) · Oxford University Press eBooks · doi:10.1093/9780198907565.003.0006
The development of procedural syntax
Ninio, A. (2025) · Oxford University Press eBooks · doi:10.1093/9780198907565.003.0005
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Ninio, A. (2025) · Oxford University Press eBooks · doi:10.1093/9780198907565.003.0003
Ninio, A. (2025) · Oxford University Press eBooks · doi:10.1093/9780198907565.003.0002
Ninio, A. (2025) · Oxford University Press eBooks · doi:10.1093/9780198907565.003.0001
Ninio, A. (2025) · doi:10.1093/9780198907565.001.0001
Ninio, A. (2025) · Oxford University Press eBooks · doi:10.1093/9780198907565.003.0004
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Chen, H.-L., Yang, G., Qu, X., Li, D., Zhao, C., Junjie, W. U., Zeng, K., He, Y., Hartwigsen, G., Chen, R., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-8717654/v1
Flower, N., & Liina Pylkkänen, A. (2026) · Neurobiology of Language · doi:10.1162/nol.a.254 · Cited by 3 · see citing works
MEG investigation of adjective order preferences as a syntactic constraint
(李帛炫), B. L., & Liina Pylkkänen, A. (2026) · Cognition · doi:10.1016/j.cognition.2026.106536
Neural Coding of Multiple Linguistic Components During Reading Comprehension Across Development
Chen, J., Feng, X., Zhang, J. I.-X., Tang, C., Liu, L., Fan, S., Zhao, N., Lei, Y., Yang, X., Meng, X., et al. (2026) · Neurobiology of Language · doi:10.1162/nol.a.286
Wei, Y., Slevc, L. R., Brodbeck, C. J., & Yasmeen Faroqi-shah, A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.17.752155
- Authors
- Law, R., & Pylkkänen, L.
- Affiliations
- New York University Abu Dhabi (AE)
- Corresponding author
- Law, Ryan
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2021-01-26
- Volume
- 41
- Issue
- 10
- Pages
- 2186-2196
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC8018759
- OpenAlex
- W3123107951
- Cited by
- 37
- References
- 68
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 6 · 2023: 7 · 2022: 2 · 2021: 6
- FWCI
- 2.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Neuroscience (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Funders
- New York University Abu Dhabi Institute (Grant G1001)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Arts and Humanities › Language and Linguistics › Syntax, Semantics, Linguistic Variation
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Keywords
- syntactic processing, word lists, semantic association, left inferior frontal cortex, left anterior temporal lobe, temporoparietal junction, sentence structure, word meaning, magnetoencephalography
- MeSH terms
- Adult, Brain, Cognition, Female, Humans, Language, Linguistics, Male, Photic Stimulation, Semantics, Magnetoencephalography, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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