CoChat
Sign Up
Cited by 72Neurobiology of Language and BilingualismReading and Literacy DevelopmentLanguage Development and Disorders

Incremental Language Comprehension Difficulty Predicts Activity in the Language Network but Not the Multiple Demand Network

Open access
Wehbe, Leila, Blank, Idan Asher, Shain, Cory, Futrell, Richard, Levy, Roger, von der Malsburg, Titus, Smith, Nathaniel, Gibson, Edward +1 more·2021·Cerebral Cortex
DOI 10.1093/cercor/bhab065PMC PMC8328211

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

What role do domain-general executive functions play in human language comprehension? To address this question, we examine the relationship between behavioral measures of comprehension and neural activity in the domain-general “multiple demand” (MD) network, which has been linked to constructs like attention, working memory, inhibitory control, and selection, and implicated in diverse goal-directed behaviors. Specifically, functional magnetic resonance imaging data collected during naturalistic story listening are compared with theory-neutral measures of online comprehension difficulty and incremental processing load (reading times and eye-fixation durations). Critically, to ensure that variance in these measures is driven by features of the linguistic stimulus rather than reflecting participant- or trial-level variability, the neuroimaging and behavioral datasets were collected in nonoverlapping samples. We find no behavioral-neural link in functionally localized MD regions; instead, this link is found in the domain-specific, fronto-temporal “core language network,” in both left-hemispheric areas and their right hemispheric homotopic areas. These results argue against strong involvement of domain-general executive circuits in language comprehension.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/cercor/bhab065

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Speech comprehension requires attention, particularly for higher-level processes such as syntactic integration and reanalysis and drawing inferences.

    “Similarly, many studies have shown that speech comprehension requires attention. This holds in particular for higher-level processes, such as syntactic integration and reanalysis and drawing inferences”

    From Timing in Conversation (2023) · cites this paper as Wehbe et al., 2021

    The opening discussion (indexed under Abstract; page unavailable) lists syntactic dependencies and pragmatic inferences among comprehension processes and says psycholinguists have invoked focal attention in accounts of dependency formation. It does not establish that speech comprehension requires attention, particularly for syntactic reanalysis or drawing inferences. The Discussion instead reports little involvement of domain-general executive mechanisms during naturalistic comprehension. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 143

  1. Aaronson, D., & Scarborough, H. S. (1977). Performance theories for sentence coding: Some quantitative models. Journal of Verbal Learning and Verbal Behavior, 16(3), 277-303. https://doi.org/10.1016/S0022-5371(77)80052-2 · DOI
  2. Abney, S. P., & Johnson, M. (1991). Memory requirements and local ambiguities of parsing strategies. Journal of Psycholinguistic Research, 20(3), 233-250.
  3. Anderson, M. L. (2010). Neural reuse: A fundamental organizational principle of the brain. Behavioral and Brain Sciences. https://doi.org/10.1017/S0140525X10000853 · DOI · Paper page
  4. Bautista, A., & Wilson, S. M. (2016). Neural responses to grammatically and lexically degraded speech. Language, Cognition and Neuroscience, 31(4), 567-574.
  5. Bhattasali, S., Hale, J., 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 (SCiL) 2018, Salt Lake City, Utah, January 4-7, 2018, (2012), 74-80. https://doi.org/10.7275/R5FF3QJ2 · DOI
  6. Bilenko, N. Y., Grindrod, C. M., Myers, E. B., & Blumstein, S. E. (2008). Neural correlates of semantic competition during processing of ambiguous words. Journal of Cognitive Neuroscience, 21(5), 960-975.
  7. Blanco-Elorrieta, E., & Pylkkänen, L. (2017). Bilingual Language Switching in the Laboratory versus in the Wild: The Spatiotemporal Dynamics of Adaptive Language Control. Journal of Neuroscience, 37(37), 9022-9036. https://doi.org/10.1523/JNEUROSCI.0553-17.2017 · DOI
  8. Blank, I., & Fedorenko, E. (2017). Domain-general brain regions do not track linguistic input as closely as language-selective regions. The Journal of Neuroscience, 3642-16. https://doi.org/10.1523/JNEUROSCI.3642-16.2017 · DOI
  9. Blumstein, S. E., & Amso, D. (2013). Dynamic Functional Organization of Language: Insights From Functional Neuroimaging. Perspectives on Psychological Science. https://doi.org/10.1177/1745691612469021 · DOI
  10. Braga, R. M., DiNicola, L. M., & Buckner, R. L. (2019). Situating the Left-Lateralized Language Network in the Broader Organization of Multiple Specialized Large-Scale Distributed Networks. BioRxiv. https://doi.org/10.1101/2019.12.11.873174 · DOI
  11. Braze, D., Mencl, W. E., Tabor, W., Pugh, K. R., Constable, R. T., Fulbright, R. K., … Shankweiler, D. P. (2011). Unification of sentence processing via ear and eye: An fMRI study. Cortex, 47(4), 416-431.
  12. Brennan, J. R., Stabler, E. P., Van Wagenen, S. E., Luh, W. M., & Hale, J. T. (2016). Abstract linguistic structure correlates with temporal activity during naturalistic comprehension. Brain and Language, 157-158, 81-94. https://doi.org/10.1016/j.bandl.2016.04.008 · DOI
  13. Brennan, J, Nir, Y., Hasson, U., Malach, R., Heeger, D. J., Pylkkänen, L., … Structures, T. (2010). Syntactic structure building in the anterior temporal lobe during natural story listening. Brain and Language, 6(2), 247-253. https://doi.org/10.1111/j.1743- 6109.2008.01122.x.Endothelial · DOI
  14. Brennan, Jonathan, & Pylkkänen, L. (2012). The time-course and spatial distribution of brain activity associated with sentence processing. NeuroImage, 1-10. https://doi.org/10.1016/j.neuroimage.2012.01.030 · DOI
  15. Broca, P. P. (1861). Remarks on the seat of the faculty of articulated language, following an observation of aphemia (loss of speech). Bulletin de La Société Anatomique.
  16. Campbell, K. L., & Tyler, L. K. (2018). Language-related domain-specific and domain-general systems in the human brain. Current Opinion in Behavioral Sciences. https://doi.org/10.1016/j.cobeha.2018.04.008 · DOI
  17. Clifton, C., & Frazier, L. (1989). Comprehending Sentences with Long-Distance Dependencies BT -Linguistic Structure in Language Processing. In G. N. Carlson & M. K. Tanenhaus (Eds.) (pp. 273-317). Dordrecht: Springer Netherlands. https://doi.org/10.1007/978-94-009-2729-2_8 · DOI
  18. Cohen, A. L. (2013). Software for the automatic correction of recorded eye fixation locations in reading experiments. Behavior Research Methods, 45(3), 679-683.
  19. D'Esposito, M., & Postle, B. R. (2015). The Cognitive Neuroscience of Working Memory. Annual Review of Psychology. https://doi.org/10.1146/annurev-psych-010814-015031 · DOI · Paper page
  20. de Heer, W. A., Huth, A. G., Griffiths, T. L., Gallant, J. L., & Theunissen, F. E. (2017). The Hierarchical Cortical Organization of Human Speech Processing. The Journal of Neuroscience, 37(27), 6539-6557. https://doi.org/10.1523/JNEUROSCI.3267-16.2017 · DOI
  21. Dehghani, M., Boghrati, R., Man, K., Hoover, J., Gimbel, S. I., Vaswani, A., … Kaplan, J. T. (2017). Decoding the neural representation of story meanings across languages. Human Brain Mapping, 38(12), 6096-6106. https://doi.org/10.1002/hbm.23814 · DOI
  22. Demberg, V., & Keller, F. (2008). Data from eye-tracking corpora as evidence for theories of syntactic processing complexity. Cognition, 109(2), 193-210.
  23. Deniz, F., Nunez-Elizalde, A. O., Huth, A. G., & Gallant, J. L. (2019). The Representation of Semantic Information Across Human Cerebral Cortex During Listening Versus Reading Is Invariant to Stimulus Modality. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience. https://doi.org/10.1523/JNEUROSCI.0675-19.2019 · DOI · Paper page
  24. Desai, R. H., Choi, W., Lai, V. T., & Henderson, J. M. (2016). Toward Semantics in the Wild: Activation to Manipulable Nouns in Naturalistic Reading. Journal of Neuroscience, 36(14), 4050-4055. https://doi.org/10.1523/JNEUROSCI.1480-15.2016 · DOI
  25. Diachek, E., Blank, I., Siegelman, M., Affourtit, J., & Fedorenko, E. (in press). The domain- general multiple demand (MD) network does not support core aspects of language comprehension: a large-scale fMRI investigation. https://doi.org/10.1101/744094 · DOI
  26. Duncan, J. (2010). The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends in Cognitive Sciences, 14(4), 172-179. https://doi.org/10.1016/j.tics.2010.01.004 · DOI · Paper page
  27. Eklund, A., Andersson, M., Josephson, C., Johannesson, M., & Knutsson, H. (2012). Does parametric fMRI analysis with SPM yield valid results?-An empirical study of 1484 rest datasets. NeuroImage. https://doi.org/10.1016/j.neuroimage.2012.03.093 · DOI
  28. Fedorenko, E., Behr, M. K., & Kanwisher, N. (2011). Functional specificity for high-level linguistic processing in the human brain. Proceedings of the National Academy of Sciences, 108(39), 16428-16433. https://doi.org/10.1073/pnas.1112937108 · DOI · Paper page
  29. Fedorenko, E, Hsieh, P.-J., Nieto-Castanon, A., Whitfield-Gabrieli, S., & Kanwisher, N. (2010). New method for f{MRI} investigations of language: Defining {ROI}s functionally in individual subjects. Journal of Neurophysiology, 104(2), 1177-1194.
  30. Fedorenko, E, Nieto-Castanon, A., & Kanwisher, N. (2012). Lexical and syntactic representations in the brain: An f{MRI} investigation with multi-voxel pattern analyses. Neuropsychologia, 50(4), 499-513.
  31. Fedorenko, E. (in press). The brain network that supports high-level language processing. In
  32. Gazzaniga, Ivry, Mangun (Ed.), Cognitive Neuroscience: The Biology of the Mind (5th Edition).
  33. Fedorenko, E, & Blank, I. A. (2020). Broca's Area Is Not a Natural Kind. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2020.01.001 · DOI
  34. Fedorenko, E, Blank, I., Siegelman, M., & Mineroff, Z. (2020). Lack of selectivity for syntax relative to word meanings throughout the language network. BioRxiv, 477851.
  35. Fedorenko, E, Gibson, E., & Rohde, D. (2006). The nature of working memory capacity in sentence comprehension: Evidence against domain-specific working memory resources. Journal of Memory and Language. https://doi.org/10.1016/j.jml.2005.12.006 · DOI
  36. Fedorenko, E, Gibson, E., & Rohde, D. (2007). The nature of working memory in linguistic, arithmetic and spatial integration processes. Journal of Memory and Language. https://doi.org/10.1016/j.jml.2006.06.007 · DOI
  37. Fedorenko, E, Hsieh, P.-J., Nieto-Castanon, A., Whitfield-Gabrieli, S., & Kanwisher, N. (2010). New Method for fMRI Investigations of Language: Defining ROIs Functionally in Individual Subjects. Journal of Neurophysiology, 104(2), 1177-1194. https://doi.org/10.1152/jn.00032.2010 · DOI · Paper page
  38. Fedorenko, E, Mineroff, Z., Siegelman, M., & Blank, I. (2018). Word meanings and sentence structure recruit the same set of fronto-temporal regions during comprehension. BioRxiv, 477851.
  39. Fedorenko, E, Scott, T. L., Brunner, P., Coon, W. G., Pritchett, B., Schalk, G., & Kanwisher, N. (2016). Neural correlate of the construction of sentence meaning. Proceedings of the National Academy of Sciences, 113(41), E6256--E6262. https://doi.org/10.1073/pnas.1612132113 · DOI · Paper page
  40. Fedorenko, E, & Thompson-Schill, S. L. (2014). Reworking the language network. Trends in Cognitive Sciences, 18(3), 120-127. https://doi.org/10.1016/j.tics.2013.12.006 · DOI · Paper page
  41. Fedorenko, E, & Varley, R. (2016). Language and thought are not the same thing: Evidence from neuroimaging and neurological patients. Annals of the New York Academy of Sciences. https://doi.org/10.1111/nyas.13046 · DOI · Paper page
  42. Fiebach, C. J., Vos, S. H., & Friederici, A. D. (2004). Neural correlates of syntactic ambiguity in sentence comprehension for low and high span readers. Journal of Cognitive Neuroscience, 16(9), 1562-1575.
  43. Fitch, W. T., & Martins, M. D. (2014). Hierarchical processing in music, language, and action: Lashley revisited. Annals of the New York Academy of Sciences. https://doi.org/10.1111/nyas.12406 · DOI
  44. Frazier, L., & Rayner, K. (1987). Resolution of syntactic category ambiguities: Eye movements in parsing lexically ambiguous sentences. Journal of Memory and Language, 26(5), 505-526.
  45. Friederici, A. D., Rüschemeyer, S.-A., Hahne, A., & Fiebach, C. J. (2003). The role of left inferior frontal and superior temporal cortex in sentence comprehension: localizing syntactic and semantic processes. Cerebral Cortex (New York, N.Y. : 1991), 13(2), 170-177. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12507948
  46. Friedrich, R., & Friederici, A. D. (2009). Mathematical logic in the human brain: Syntax. PLoS ONE. https://doi.org/10.1371/journal.pone.0005599 · DOI
  47. Frost, M. A., & Goebel, R. (2012). Measuring structural-functional correspondence: Spatial variability of specialised brain regions after macro-anatomical alignment. NeuroImage. https://doi.org/10.1016/j.neuroimage.2011.08.035 · DOI
  48. Futrell, R., Gibson, E., Tily, H. J. H., Blank, I., Vishnevetsky, A., Piantadosi, S. T., & Fedorenko, E. (2018). The Natural Stories Corpus. In Proceedings of the 11th Language Resources and Evaluation Conference (pp. 1-16). Miyazaki, Japan: European Language Resource Association. Retrieved from http://arxiv.org/abs/1708.05763 · arXiv
  49. Gernsbacher, M. A. (1993). Less Skilled Readers Have Less Efficient Suppression Mechanisms. Psychological Science. https://doi.org/10.1111/j.1467-9280.1993.tb00567.x · DOI
  50. Geschwind, N. (1970). The organization of language and the brain. Science. https://doi.org/10.1126/science.170.3961.940 · DOI
  51. Gibson, E. (1998). Linguistic complexity: locality of syntactic dependencies. Cognition, 68(1), 1-76. https://doi.org/10.1016/S0010-0277(98)00034-1 · DOI · Paper page
  52. Gordon, P. C., Hendrick, R., & Levine, W. H. (2002). Memory-load interference in syntactic processing. Psychological Science. https://doi.org/10.1111/1467-9280.00475 · DOI
  53. Grodner, D., Gibson, E., & Tunstall, S. (2002). Syntactic Complexity in Ambiguity Resolution. Journal of Memory and Language, 46(2), 267-295. https://doi.org/10.1006/jmla.2001.2808 · DOI
  54. Hale, J. T., Lutz, D. E., Luh, W., Brennan, J. R., & Arbor, A. (2015). Modeling fMRI time courses with linguistic structure at various grain sizes. Proceedings of CMCL, 89-97.
  55. Handwerker, D. A., Ollinger, J. M., & D'Esposito, M. (2004). Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses. NeuroImage. https://doi.org/10.1016/j.neuroimage.2003.11.029 · DOI
  56. Hasson, U., & Honey, C. J. (2012). Future trends in {N}euroimaging: {N}eural processes as expressed within real-life contexts. NeuroImage, 62(2), 1272-1278.
  57. Hasson, U., Yang, E., Vallines, I., Heeger, D. J., & Rubin, N. (2008). A hierarchy of temporal receptive windows in human cortex. Journal of Neuroscience, 28(10), 2539-2550.
  58. Heim, S., Eickhoff, S. B., & Amunts, K. (2008). Specialisation in Broca's region for semantic, phonological, and syntactic fluency? NeuroImage. https://doi.org/10.1016/j.neuroimage.2008.01.009 · DOI
  59. Henderson, J. M., Choi, W., Lowder, M. W., & Ferreira, F. (2016). Language structure in the brain: A fixation-related fMRI study of syntactic surprisal in reading. NeuroImage, 132, 293- 300. https://doi.org/10.1016/j.neuroimage.2016.02.050 · DOI
  60. Henderson, J. M., Choi, W., Luke, S. G., & Desai, R. H. (2015). Neural correlates of fixation duration in natural reading: evidence from fixation-related fMRI. NeuroImage, 119, 390-397. https://doi.org/10.1016/j.neuroimage.2015.06.072 · DOI
  61. Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics.
  62. Hsu, A., Borst, A., & Theunissen, F. (2004). Quantifying variability in neural responses and its application for the validation of model predictions. Network: Computation in Neural Systems. https://doi.org/10.1088/0954-898x/15/2/002 · DOI
  63. Hsu, N. S., & Novick, J. M. (2016). Dynamic Engagement of Cognitive Control Modulates Recovery From Misinterpretation During Real-Time Language Processing. Psychological Science. https://doi.org/10.1177/0956797615625223 · DOI
  64. Humphries, C., Binder, J. R., Medler, D. A., & Liebenthal, E. (2006). Syntactic and semantic modulation of neural activity during auditory sentence comprehension. Journal of Cognitive Neuroscience. https://doi.org/10.1162/jocn.2006.18.4.665 · DOI
  65. Huth, A. G., de Heer, W. A., Griffiths, T. L., Theunissen, F. E., Gallant, J. L., Heer, W. a De, … Gallant, J. L. (2016). Natural speech reveals the semantic maps that tile human cerebral cortex. Nature, 532(7600), 453-458. https://doi.org/10.1038/nature17637.Natural · DOI
  66. January, D., Trueswell, J. C., & Thompson-schill, S. L. (2009). NIH Public Access, 21(12), 2434-2444. https://doi.org/10.1162/jocn.2008.21179.Co-localization January, D., Trueswell, J. C., & Thompson-Schill, S. L. (2009). Co-localization of Stroop and Syntactic Ambiguity Resolution in Broca's Area: Implications for the Neural Basis of Sentence Processing. Journal of Cognitive Neuroscience, 21(12), 2434-2444. https://doi.org/10.1162/jocn.2008.21179 · DOI · Paper page
  67. Johnson-Laird, P. N. (1983). Mental models: Towards a cognitive science of language, inference, and consciousness. Harvard University Press.
  68. Julian, J. B., Fedorenko, E., Webster, J., & Kanwisher, N. (2012). An algorithmic method for functionally defining regions of interest in the ventral visual pathway. Neuroimage, 60(4), 2357-2364.
  69. Jung-Beeman, M. (2005). Bilateral brain processes for comprehending natural language. Trends in Cognitive Sciences, 9(11), 512-518.
  70. Just, M. A., & Carpenter, P. A. (1980). A theory of reading: From eye fixations to comprehension. Psychological Review. https://doi.org/10.1037/0033-295X.87.4.329 · DOI
  71. Just, M. a, Carpenter, P. a, & Woolley, J. D. (1982). Paradigms and processes in reading comprehension. Journal of Experimental Psychology. General, 111(2), 228-238. https://doi.org/10.1037/0096-3445.111.2.228 · DOI
  72. Kaakinen, J. K., & Hyönä, J. (2010). Task Effects on Eye Movements During Reading. Journal of Experimental Psychology: Learning Memory and Cognition. https://doi.org/10.1037/a0020693 · DOI
  73. Kaan, E., & Swaab, T. Y. (2002). The brain circuitry of syntactic comprehension. Trends in Cognitive Sciences. https://doi.org/10.1016/S1364-6613(02)01947-2 · DOI
  74. Kennedy, A. (2000). Parafoveal processing in word recognition. Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology. https://doi.org/10.1080/713755901 · DOI
  75. King, J., & Just, M. A. (1991). Individual differences in syntactic processing: The role of working memory. Journal of Memory and Language, 30(5), 580-602.
  76. Klein, R., & Farrell, M. (1989). Search performance without eye movements. Perception & Psychophysics. https://doi.org/10.3758/BF03210863 · DOI
  77. Kuperberg, G. R., Holcomb, P. J., Sitnikova, T., Greve, D., Dale, A. M., & Caplan, D. (2003). Distinct patterns of neural modulation during the processing of conceptual and syntactic anomalies. Journal of Cognitive Neuroscience, 15(2), 272-293. https://doi.org/10.1162/089892903321208204 · DOI
  78. Kuperberg, G. R., Sitnikova, T., & Lakshmanan, B. M. (2008). Neuroanatomical distinctions within the semantic system during sentence comprehension: evidence from functional magnetic resonance imaging. Neuroimage, 40(1), 367-388.
  79. Lescroart, M. D., & Gallant, J. L. (2019). Human Scene-Selective Areas Represent 3D Configurations of Surfaces. Neuron. https://doi.org/10.1016/j.neuron.2018.11.004 · DOI
  80. Lescroart, M. D., Stansbury, D. E., & Gallant, J. L. (2015). Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas. Frontiers in Computational Neuroscience, 9, 135. https://doi.org/10.3389/fncom.2015.00135 · DOI
  81. Levy, R. (2008). Expectation-based syntactic comprehension. Cognition, 106(3), 1126-1177. https://doi.org/10.1016/j.cognition.2007.05.006 · DOI
  82. Lewis, R. L., & Vasishth, S. (2005). An activation-based model of sentence processing as skilled memory retrieval. Cognitive Science. https://doi.org/10.1207/s15516709cog0000_25 · DOI
  83. Lewis, R. L., Vasishth, S., & Van Dyke, J. A. (2006). Computational principles of working memory in sentence comprehension. Trends in Cognitive Sciences, 10(10), 447-454. https://doi.org/10.1016/j.tics.2006.08.007 · DOI
  84. Lopopolo, A., Frank, S. L., Van Den Bosch, A., & Willems, R. M. (2017). Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain. PLoS ONE, 12(5), 1-18. https://doi.org/10.1371/journal.pone.0177794 · DOI
  85. Mahowald, K., & Fedorenko, E. (2016). Reliable individual-level neural markers of high-level language processing: A necessary precursor for relating neural variability to behavioral and genetic variability. NeuroImage. https://doi.org/10.1016/j.neuroimage.2016.05.073 · DOI
  86. Mazoyer, B. M., Tzourio, N., Frak, V., Syrota, A., Murayama, N., Levrier, O., … Mehler, J. (1993). The cortical representation of speech. Journal of Cognitive Neuroscience, 5(4), 467- 479. https://doi.org/10.1162/jocn.1993.5.4.467 · DOI
  87. McElree, B. (2000). Sentence comprehension is mediated by content-addressable memory structures. Journal of Psycholinguistic Research. https://doi.org/10.1023/A:1005184709695 · DOI
  88. McElree, B. (2001). Working Memory and Focal Attention. Journal of Experimental Psychology: Learning Memory and Cognition. https://doi.org/10.1037/0278-7393.27.3.817 · DOI
  89. McMillan, C. T., Clark, R., Gunawardena, D., Ryant, N., & Grossman, M. (2012). FMRI evidence for strategic decision-making during resolution of pronoun reference. Neuropsychologia. https://doi.org/10.1016/j.neuropsychologia.2012.01.004 · DOI
  90. McMillan, C. T., Coleman, D., Clark, R., Liang, T. W., Gross, R. G., & Grossman, M. (2013). Converging evidence for the processing costs associated with ambiguous quantifier comprehension. Frontiers in Psychology, 4(APR), 1-10. https://doi.org/10.3389/fpsyg.2013.00153 · DOI
  91. Menke, J., & Martinez, T. R. (2004). Using permutations instead of student's t distribution for p- values in paired-difference algorithm comparisons. In 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No. 04CH37541) (Vol. 2, pp. 1331-1335).
  92. Mesulam, M. M. (1998). From sensation to cognition. Brain. https://doi.org/10.1093/brain/121.6.1013 · DOI · Paper page
  93. Miller, E. K., & Cohen, J. D. (2001). An Integrative Theory of Prefrontal Cortex Function. Annual Review of Neuroscience. https://doi.org/10.1146/annurev.neuro.24.1.167 · DOI · Paper page
  94. Mollica, F., Siegelman, M., Diachek, E., Piantadosi, S. T., Mineroff, Z., Futrell, R., … Fedorenko, E. (2020). Composition is the core driver of the language-selective network. Neurobiology of Language. https://doi.org/10.1162/nol_a_00005 · DOI
  95. Murphy, B., Hale, J., & Brennan, J. (2016). Grammatical Relations in the Listening Brain. Poster at PRNI 2016, Pattern Recognition and Neuroimaging Conference.
  96. Naselaris, T., Kay, K. N., Nishimoto, S., & Gallant, J. L. (2011). Encoding and decoding in fMRI. NeuroImage, 56(2), 400-410. https://doi.org/10.1016/j.neuroimage.2010.07.073 · DOI
  97. Nieuwland, M. S., Martin, A. E., & Carreiras, M. (2012). Brain regions that process case: Evidence from basque. Human Brain Mapping, 33(11), 2509-2520. https://doi.org/10.1002/hbm.21377 · DOI
  98. Novais-Santos, S., Gee, J., Shah, M., Troiani, V., Work, M., & Grossman, M. (2007). Resolving sentence ambiguity with planning and working memory resources: Evidence from fMRI. NeuroImage, 37(1), 361-378. https://doi.org/10.1016/j.neuroimage.2007.03.077 · DOI
  99. Novick, J. M., Kan, I. P., Trueswell, J. C., & Thompson-Schill, S. L. (2009). A case for conflict across multiple domains: Memory and language impairments following damage to ventrolateral prefrontal cortex. Cognitive Neuropsychology. https://doi.org/10.1080/02643290903519367 · DOI
  100. Pallier, C., Devauchelle, A. D., & Dehaene, S. (2011). Cortical representation of the constituent structure of sentences. Proceedings of the National Academy of Sciences, 108(6), 2522-2527.
  101. Patel, A. D. (2003). Language, music, syntax and the brain. Nature Neuroscience. https://doi.org/10.1038/nn1082 · DOI
  102. Patel, A. D. (2012). Music, Language, and the Brain. Music, Language, and the Brain. https://doi.org/10.1093/acprof:oso/9780195123753.001.0001 · DOI
  103. Paunov, A. M., Blank, I. A., & Fedorenko, E. (2019). Functionally distinct language and Theory 29 of Mind networks are synchronized at rest and during language comprehension. Journal of Neurophysiology, 121(4), 1244-1265.
  104. Peelle, J. E., Troiani, V., Wingfield, A., & Grossman, M. (2010). Neural processing during older adults' comprehension of spoken sentences: Age differences in resource allocation and connectivity. Cerebral Cortex, 20(4), 773-782. https://doi.org/10.1093/cercor/bhp142 · DOI · Paper page
  105. Posner, M. I. (1980). Orienting of attention. The Quarterly Journal of Experimental Psychology. https://doi.org/10.1080/00335558008248231 · DOI · Paper page
  106. Posner, Michael I. (2016). Orienting of attention: Then and now. Quarterly Journal of Experimental Psychology. https://doi.org/10.1080/17470218.2014.937446 · DOI
  107. Rasmussen, N. E., & Schuler, W. (2018). Left-Corner Parsing With Distributed Associative Memory Produces Surprisal and Locality Effects. Cognitive Science. https://doi.org/10.1111/cogs.12511 · DOI
  108. Rayner, K. (1977). Visual attention in reading: Eye movements reflect cognitive processes. Memory & Cognition. https://doi.org/10.3758/BF03197383 · DOI
  109. Rayner, K. (1978). Eye movements in reading and information processing. Psychological Bulletin. https://doi.org/10.1037/0033-2909.85.3.618 · DOI
  110. Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124(3), 372. https://doi.org/10.1037/0033-2909.124.3.372 · DOI · Paper page
  111. Remington, R. W. (1980). Attention and saccadic eye movements. Journal of Experimental Psychology: Human Perception and Performance. https://doi.org/10.1037/0096-1523.6.4.726 · DOI
  112. Resnik, P. (1992). Left-corner parsing and psychological plausibility. https://doi.org/10.3115/992066.992098 · DOI
  113. Rodd, J. M., Davis, M. H., & Johnsrude, I. S. (2005). The neural mechanisms of speech comprehension: fMRI studies of semantic ambiguity. Cerebral Cortex, 15(8), 1261-1269. https://doi.org/10.1093/cercor/bhi009 · DOI
  114. Rodd, J. M., Johnsrude, I. S., & Davis, M. H. (2010). The role of domain-general frontal systems in language comprehension: Evidence from dual-task interference and semantic ambiguity. Brain and Language. https://doi.org/10.1016/j.bandl.2010.07.005 · DOI
  115. Rodriguez, A., & Granger, R. (2016). The grammar of mammalian brain capacity. Theoretical Computer Science. https://doi.org/10.1016/j.tcs.2016.03.021 · DOI
  116. Rogalsky, C., & Hickok, G. (2011). The role of Broca's area in sentence comprehension. Journal of Cognitive Neuroscience. https://doi.org/10.1162/jocn.2010.21530 · DOI
  117. Schotter, E. R., Tran, R., & Rayner, K. (2014). Don't believe what you read (Only Once): Comprehension is supported by regressions during reading. Psychological Science. https://doi.org/10.1177/0956797614531148 · DOI
  118. Schuler, W., AbdelRahman, S., Miller, T., & Schwartz, L. (2010). Broad-coverage parsing using human-like memory constraints. Computational Linguistics. https://doi.org/10.1162/coli.2010.36.1.36100 · DOI
  119. Scott, T. L., Gallée, J., & Fedorenko, E. (2017). A new fun and robust version of an fMRI localizer for the frontotemporal language system. Cognitive Neuroscience, 8(3), 167-176.
  120. Shain, C., Blank, I. A., van Schijndel, M., Schuler, W., & Fedorenko, E. (2020). fMRI reveals language-specific predictive coding during naturalistic sentence comprehension. Neuropsychologia. https://doi.org/10.1016/j.neuropsychologia.2019.107307 · DOI · Paper page
  121. Slevc, L. R., Rosenberg, J. C., & Patel, A. D. (2009). Making psycholinguistics musical: Self- paced reading time evidence for shared processing of linguistic and musical syntax. Psychonomic Bulletin and Review. https://doi.org/10.3758/16.2.374 · DOI
  122. Smith, N. J., & Levy, R. (2013). The effect of word predictability on reading time is logarithmic. Cognition, 128(3), 302-319. https://doi.org/10.1016/j.cognition.2013.02.013 · DOI · Paper page
  123. Snijders, T. M., Vosse, T., Kempen, G., Van Berkum, J. J. A., Petersson, K. M., & Hagoort, P. (2009). Retrieval and unification of syntactic structure in sentence comprehension: An fMRI study using word-category ambiguity. Cerebral Cortex, 19(7), 1493-1503. https://doi.org/10.1093/cercor/bhn187 · DOI
  124. Speer, Nicole K, Reynolds, J. R., Swallow, K. M., & Zacks, J. M. (2009). Reading stories activates neural representations of visual and motor experiences. Psychological Science, 20(8), 989-999. https://doi.org/10.1111/j.1467-9280.2009.02397.x.Reading · DOI
  125. Sreenivasan, K. K., Curtis, C. E., & D'Esposito, M. (2014). Revisiting the role of persistent neural activity during working memory. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2013.12.001 · DOI
  126. Stowe, L. A., Broere, C. A. J., Paans, A. M. J., Wijers, A. A., Mulder, G., Vaalburg, W., & Zwarts, F. (1998). Localizing components of a complex task: Sentence processing and working memory. NeuroReport. https://doi.org/10.1097/00001756-199809140-00014 · DOI
  127. Tahmasebi, A. M., Davis, M. H., Wild, C. J., Rodd, J. M., Hakyemez, H., Abolmaesumi, P., & Johnsrude, I. S. (2012). Is the link between anatomical structure and function equally strong at all cognitive levels of processing? Cerebral Cortex. https://doi.org/10.1093/cercor/bhr205 · DOI
  128. Taylor, J. S. H., Rastle, K., & Davis, M. H. (2014). Interpreting response time effects in functional imaging studies. NeuroImage. https://doi.org/10.1016/j.neuroimage.2014.05.073 · DOI
  129. Tettamanti, M., & Weniger, D. (2006). Broca's area: A supramodal hierarchical processor? Cortex. https://doi.org/10.1016/S0010-9452(08)70384-8 · DOI
  130. Thesen, S., Heid, O., Mueller, E., & Schad, L. R. (2000). Prospective Acquisition Correction for head motion with image-based tracking for real-time fMRI. Magnetic Resonance in Medicine, 44(3), 457-465. https://doi.org/10.1002/1522-2594(200009)44:3<457::AID- MRM17>3.0.CO;2-R Thompson-Schill, S. L., Bedny, M., & Goldberg, R. F. (2005). The frontal lobes and the regulation of mental activity. Current Opinion in Neurobiology. https://doi.org/10.1016/j.conb.2005.03.006 · DOI · Paper page
  131. Vagharchakian, L., Dehaene-Lambertz, G., Pallier, C., & Dehaene, S. (2012). A temporal bottleneck in the language comprehension network. Journal of Neuroscience, 32(26), 9089- 9102.
  132. van Schijndel, M., Exley, A., & Schuler, W. (2013). A Model of Language Processing as Hierarchic Sequential Prediction. Topics in Cognitive Science. https://doi.org/10.1111/tops.12034 · DOI
  133. Vandenberghe, R., Nobre, A. C., & Price, C. J. (2002). The response of left temporal cortex to sentences. Journal of Cognitive Neuroscience. https://doi.org/10.1162/08989290260045800 · DOI
  134. Vasishth, S., von der Malsburg, T., & Engelmann, F. (2013). What eye movements can tell us about sentence comprehension. Wiley Interdisciplinary Reviews: Cognitive Science, 4(2), 125- 134.
  135. Vázquez-Rodríguez, B., Suárez, L. E., Markello, R. D., Shafiei, G., Paquola, C., Hagmann, P., … Misic, B. (2019). Gradients of structure-function tethering across neocortex. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.1903403116 · DOI
  136. Vergauwe, E., Barrouillet, P., & Camos, V. (2010). Do mental processes share a domain-general resource? Psychological Science. https://doi.org/10.1177/0956797610361340 · DOI
  137. Waters, G. S., & Caplan, D. (1996). The Measurement of Verbal Working Memory Capacity and Its Relation to Reading Comprehension. Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology. https://doi.org/10.1080/713755607 · DOI
  138. Wehbe, L., Murphy, B., Talukdar, P., Fyshe, A., Ramdas, A., & Mitchell, T. (2014). Simultaneously uncovering the patterns of brain regions involved in different story reading Subprocesses. PloS One, 9(11), e112575. https://doi.org/10.1371/journal.pone.0112575 · DOI
  139. Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2012). Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity, 2(3), 125-141.
  140. Whitney, C., Huber, W., Klann, J., Weis, S., Krach, S., & Kircher, T. (2009). Neural correlates of narrative shifts during auditory story comprehension. NeuroImage, 47(1), 360-366. https://doi.org/10.1016/j.neuroimage.2009.04.037 · DOI · Paper page
  141. Wild, C. J., Yusuf, A., Wilson, D. E., Peelle, J. E., Davis, M. H., & Johnsrude, I. S. (2012). Effortful listening: The processing of degraded speech depends critically on attention. Journal of Neuroscience. https://doi.org/10.1523/JNEUROSCI.1528-12.2012 · DOI
  142. Wright, P., Randall, B., Marslen-Wilson, W. D., & Tyler, L. K. (2011). Dissociating linguistic and task-related activity in the left inferior frontal gyrus. Journal of Cognitive Neuroscience, 23(2), 404-413.
  143. Yarkoni, T., Barch, D. M., Gray, J. R., Conturo, T. E., & Braver, T. S. (2009). BOLD correlates of trial-by-trial reaction time variability in gray and white matter: A multi-study fMRI analysis. PLoS ONE, 4(1). https://doi.org/10.1371/journal.pone.0004257 · DOI · Paper page

Cited by

Sorted by citations

Authors
Wehbe, L., Blank, I. A., Shain, C., Futrell, R., Levy, R., von der Malsburg, T., Smith, N., Gibson, E., & Fedorenko, E.
Affiliations
  • Carnegie Mellon University (US)
  • University of California, Los Angeles (US)
  • The Ohio State University (US)
  • University of California, Irvine (US)
  • Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences MA 02139, USA
  • University of California San Diego (US)
  • Massachusetts Institute of Technology (US)
  • McGovern Institute for Brain Research (US)
Corresponding author
  • Wehbe, Leila
  • Fedorenko, Evelina
ORCID
Venue
Cerebral Cortex
Publisher
Oxford University Press (OUP)
Published
2021-04-24
Volume
31
Issue
9
Pages
4006-4023
ISSN
  • 1047-3211 (ISSN-L)
  • 1460-2199
DOI
10.1093/cercor/bhab065
PMC
PMC8328211
OpenAlex
W3159391327
Cited by
72
References
18
Citations by year
2026: 8 · 2025: 10 · 2024: 9 · 2023: 18 · 2022: 13 · 2021: 11 · 2020: 3
FWCI
6.70
Type
journal article
Language
en
Open access
Licence
academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor, 1 d)
Locations
  • Cerebral Cortex (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • NIH (DC016950, DC016607, HD057522, HD065829)
  • NSF (1551543)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
  • Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
Keywords
language comprehension, multiple-demand network, executive function, reading time, fixation duration, story listening, hemispheric lateralization
MeSH terms
Adult, Attention, Brain, Female, Fixation, Ocular, Humans, Language, Language Tests, Functional Laterality, Magnetic Resonance Imaging, Male, Memory, Short-Term, Nerve Net, Psycholinguistics, Psychomotor Performance, Reading, Comprehension, Young Adult, Executive Function

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 ›

Are you an author, or do you see a problem with this page? Request a review