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  • Perspective
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What neural oscillations can and cannot do for syntactic structure building

Abstract

Understanding what someone says requires relating words in a sentence to one another as instructed by the grammatical rules of a language. In recent years, the neurophysiological basis for this process has become a prominent topic of discussion in cognitive neuroscience. Current proposals about the neural mechanisms of syntactic structure building converge on a key role for neural oscillations in this process, but they differ in terms of the exact function that is assigned to them. In this Perspective, we discuss two proposed functions for neural oscillations — chunking and multiscale information integration — and evaluate their merits and limitations taking into account a fundamentally hierarchical nature of syntactic representations in natural languages. We highlight insights that provide a tangible starting point for a neurocognitive model of syntactic structure building.

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Fig. 1: Neural oscillations chunk linguistic input into syntactic phrases.
Fig. 2: Binding and symbolic propositions in DORA.
Fig. 3: Representation of a sentence with a single subject–verb dependency and multiple subject–verb dependencies in VS-BIND.

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References

  1. Chomsky, N. Syntactic Structures (Mouton, 1957).

  2. Adger, D. Language Unlimited: The Science Behind Our Most Creative Power (Oxford Univ. Press, 2019).

  3. Jackendoff, R. Foundations of Language (Oxford Univ. Press, 2002).

  4. Adger, D. Syntax. WIREs Cogn. Sci. 6, 131–147 (2015).

    Article  Google Scholar 

  5. Crocker, M. W. Computational Psycholinguistics: An Interdisciplinary Approach to the Study of Language (Kluwer Academic, 1996).

  6. Hale, J. T. What a rational parser would do. Cogn. Sci. 35, 399–443 (2011).

    Article  Google Scholar 

  7. Hale, J. T. Automaton Theories of Human Sentence Comprehension (CSLI, 2014).

  8. Ding, N., Melloni, L., Zhang, H., Tian, X. & Poeppel, D. Cortical tracking of hierarchical linguistic structures in connected speech. Nat. Neurosci. 19, 158–164 (2016).

    Article  CAS  PubMed  Google Scholar 

  9. Ghitza, O. Acoustic-driven delta rhythms as prosodic markers. Lang. Cogn. Neurosci. 32, 545–561 (2017).

    Article  Google Scholar 

  10. Kaufeld, G. et al. Linguistic structure and meaning organize neural oscillations into a content-specific hierarchy. J. Neurosci. 40, 9467–9475 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Keitel, A., Gross, J. & Kayser, C. Perceptually relevant speech tracking in auditory and motor cortex reflects distinct linguistic features. PLoS Biol. 16, e2004473 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Meyer, L. The neural oscillations of speech processing and language comprehension: state of the art and emerging mechanisms. Eur. J. Neurosci. 48, 2609–2621 (2017).

    Article  PubMed  Google Scholar 

  13. Meyer, L., Sun, Y. & Martin, A. E. Synchronous, but not entrained: exogenous and endogenous cortical rhythms of speech and language processing. Lang. Cogn. Neurosci. 35, 1089–1099 (2019).

    Article  Google Scholar 

  14. Benítez-Burraco, A. & Murphy, E. Why brain oscillations are improving our understanding of language. Front. Behav. Neurosci. 13, 190 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Murphy, E. The brain dynamics of linguistic computation. Front. Psychol. 6, 1515 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Murphy, E. The Oscillatory Nature of Language (Cambridge Univ. Press, 2020).

  17. Calmus, R., Wilson, B., Kikuchi, Y. & Petkov, C. I. Structured sequence processing and combinatorial binding: neurobiologically and computationally informed hypotheses. Philos. Trans. R. Soc. Lond. B Biol. Sci. 375, 20190304 (2020).

    Article  PubMed  Google Scholar 

  18. Martin, A. E. & Doumas, L. A. A mechanism for the cortical computation of hierarchical linguistic structure. PLoS Biol. 15, e2000663 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Martin, A. E. & Doumas, L. A. Predicate learning in neural systems: using oscillations to discover latent structure. Curr. Opin. Behav. Sci. 29, 77–83 (2019).

    Article  Google Scholar 

  20. Boeckx, C. & Theofanopoulou, C. in Language, Syntax, and the Natural Sciences (eds Gallego, A. J. & Martin, R.) 295–315 (Cambridge Univ. Press, 2018).

  21. Giraud, A. L. Oscillations for all ¯\_(ツ)_/¯? A commentary on Meyer, Sun & Martin (2020). Lang. Cogn. Neurosci. 35, 1106–1113 (2020).

    Article  Google Scholar 

  22. Doelling, K. B. & Assaneo, F. M. Neural oscillations are a start toward understanding brain activity rather than the end. PLoS Biol. 19, e3001234 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Obleser, J., Henry, M. J. & Lakatos, P. What do we talk about when we talk about rhythm? PLoS Biol. 15, e2002794 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lakatos, P., Karmos, G., Mehta, A. D., Ulbert, I. & Schroeder, C. E. Entrainment of neuronal oscillations as a mechanism of attentional selection. Science 320, 110–113 (2008).

    Article  CAS  PubMed  Google Scholar 

  25. Lakatos, P., Gross, J. & Thut, G. A new unifying account of the roles of neuronal entrainment. Curr. Biol. 29, R890–R905 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Schroeder, C. E. & Lakatos, P. Low-frequency neuronal oscillations as instruments of sensory selection. Trends Neurosci. 32, 9–18 (2009).

    Article  CAS  PubMed  Google Scholar 

  27. Giraud, A. L. & Poeppel, D. Cortical oscillations and speech processing: emerging computational principles and operations. Nat. Neurosci. 15, 511–517 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ghitza, O. Linking speech perception and neurophysiology: speech decoding guided by cascaded oscillators locked to the input rhythm. Front. Psychol. 2, 130 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Ding, N. et al. Temporal modulations in speech and music. Neurosci. Biobehav. Rev. 81, 181–187 (2017).

    Article  PubMed  Google Scholar 

  30. Pellegrino, F., Coupé, C. & Marsico, E. Across-language perspective on speech information rate. Language 87, 539–558 (2011).

    Article  Google Scholar 

  31. Norcia, A. M., Appelbaum, L. G. G., Ales, J. M. J. M., Cottereau, B. R. B. R. & Rossion, B. The steady-state visual evoked potential in vision research: a review. J. Vis. 15, 1–46 (2015).

    Article  Google Scholar 

  32. Glushko, A., Poeppel, D. & Steinhauer, K. Overt and implicit prosody contribute to neurophysiological responses previously attributed to grammatical processing. Sci. Rep. 12, 1459 (2022).

    Article  Google Scholar 

  33. Kalenkovich, E., Shestakova, A. & Kazanina, N. Frequency tagging of syntactic structure or lexical properties; a registered MEG study. Cortex 146, 24–38 (2022).

    Article  PubMed  Google Scholar 

  34. Burroughs, A., Kazanina, N. & Houghton, C. Grammatical category and the neural processing of phrases. Sci. Rep. 11, 2446 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Makov, S. et al. Sleep disrupts high-level speech parsing despite significant basic auditory processing. J. Neurosci. 37, 7772–7781 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ding, N. et al. Characterizing neural entrainment to hierarchical linguistic units using electroencephalography (EEG). Front. Hum. Neurosci. 11, 481 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Marcus, M. P., Santorini, B. & Marcinkiewicz, M. A. Building a large annotated corpus of English: the Penn Treebank. Comput. Linguist. 19, 313–330 (1993).

    Google Scholar 

  38. Bird, S., Klein, E. & Loper, E. Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit (O’Reilly Media, 2009).

  39. Gwilliams, L. Hierarchical oscillators in speech comprehension: a commentary on Meyer, Sun, and Martin (2019). Lang. Cogn. Neurosci. 35, 1114–1118 (2020).

    Article  Google Scholar 

  40. Ghitza, O. & Greenberg, S. On the possible role of brain rhythms in speech perception: intelligibility of time-compressed speech with periodic and aperiodic insertions of silence. Phonetica 66, 113–126 (2009).

    Article  PubMed  Google Scholar 

  41. Ghitza, O. “Acoustic-driven oscillators as cortical pacemaker”: a commentary on Meyer, Sun & Martin (2019). Lang. Cogn. Neurosci. 35, 1100–1105 (2020).

    Article  Google Scholar 

  42. Honey, C. J. et al. Slow cortical dynamics and the accumulation of information over long timescales. Neuron 76, 423–434 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Hasson, U., Yang, E., Vallines, I., Heeger, D. J. & Rubin, N. A hierarchy of temporal receptive windows in human cortex. J. Neurosci. 28, 2539–2550 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Meyer, L., Sun, Y. & Martin, A. E. “Entraining” to speech, generating language? Lang. Cogn. Neurosci. 35, 1138–1148 (2020).

    Article  Google Scholar 

  45. Crocker, M. W. in Perspectives on Sentence Processing (eds Clifton, C., Frazier, L. & Rayner, K.) 245–266 (L. Erlbaum Associates, 1994).

  46. Sturt, P. & Lombardo, V. Processing coordinated structures: incrementality and connectedness. Cogn. Sci. 29, 291–305 (2005).

    Article  PubMed  Google Scholar 

  47. Sturt, P. & Crocker, M. W. Monotonic syntactic processing: a cross-linguistic study of attachment and reanalysis. Lang. Cogn. Process. 11, 449–494 (1996).

    Article  Google Scholar 

  48. Schroeder, C. E., Wilson, D. A., Radman, T., Scharfman, H. & Lakatos, P. Dynamics of active sensing and perceptual selection. Curr. Opin. Neurobiol. 20, 172–176 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Morillon, B., Arnal, L. H., Schroeder, C. E. & Keitel, A. Prominence of delta oscillatory rhythms in the motor cortex and their relevance for auditory and speech perception. Neurosci. Biobehav. Rev. 107, 136–142 (2019).

    Article  PubMed  Google Scholar 

  50. Morillon, B. & Baillet, S. Motor origin of temporal predictions in auditory attention. Proc. Natl Acad. Sci. USA 114, E8913–E8921 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Zalta, A., Petkoski, S. & Morillon, B. Natural rhythms of periodic temporal attention. Nat. Commun. 11, 1051 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Wilson, M. & Wilson, T. P. An oscillator model of the timing of turn-taking. Psychon. Bull. Rev. 12, 957–968 (2005).

    Article  PubMed  Google Scholar 

  53. Scott, S. K., McGettigan, C. & Eisner, F. A little more conversation, a little less action—candidate roles for the motor cortex in speech perception. Nat. Rev. Neurosci. 10, 295–302 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Keitel, A., Ince, R. A. A., Gross, J. & Kayser, C. Auditory cortical delta-entrainment interacts with oscillatory power in multiple fronto-parietal networks. Neuroimage 147, 32–42 (2017).

    Article  PubMed  Google Scholar 

  55. Park, H., Ince, R. A. A., Schyns, P. G., Thut, G. & Gross, J. Frontal top-down signals increase coupling of auditory low-frequency oscillations to continuous speech in human listeners. Curr. Biol. 25, 1649–1653 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Kimball, J. Seven principles of surface structure parsing in natural language. Cognition 2, 15–47 (1973).

    Article  Google Scholar 

  57. Frazier, L. & Clifton Jr, C. Construal (MIT Press, 1996).

  58. Frazier, L. & Fodor, J. D. The sausage machine: a new two-stage parsing model. Cognition 6, 291–325 (1978).

    Article  Google Scholar 

  59. Fodor, J. D. Learning to parse? J. Psycholinguist. Res. 27, 285–319 (1998).

    Article  Google Scholar 

  60. Milner, P. M. A model for visual shape recognition. Psychol. Rev. 81, 521–535 (1974).

    Article  CAS  PubMed  Google Scholar 

  61. von der Malsburg, C. Nervous structures with dynamical links. Ber. Bunsenges. 89, 703–710 (1985).

    Article  Google Scholar 

  62. von der Malsburg, C. The Correlation Theory of Brain Function. Internal report 81–82 (Max Planck Institute for Biophysical Chemistry, 1981).

  63. Gray, C. M. & Singer, W. Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc. Natl Acad. Sci. USA 86, 1698–1702 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Gray, C. M., König, P., Engel, A. K. & Singer, W. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334–337 (1989).

    Article  CAS  PubMed  Google Scholar 

  65. Singer, W. Binding by synchrony. Scholarpedia 2, 1657 (2007).

    Article  Google Scholar 

  66. Perez-Orive, J. et al. Oscillations and sparsening of odor representations in the mushroom body. Science 297, 359–365 (2002).

    Article  CAS  PubMed  Google Scholar 

  67. Busch, N. A. & VanRullen, R. Spontaneous EEG oscillations reveal periodic sampling of visual attention. Proc. Natl Acad. Sci. USA 107, 16048–16053 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Dugué, L., McLelland, D., Lajous, M. & VanRullen, R. Attention searches nonuniformly in space and in time. Proc. Natl Acad. Sci. USA 112, 15214–15219 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Fries, P. A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn. Sci. 9, 474–480 (2005).

    Article  PubMed  Google Scholar 

  70. Fries, P., Nikolić, D. & Singer, W. The gamma cycle. Trends Neurosci. 30, 309–316 (2007).

    Article  CAS  PubMed  Google Scholar 

  71. O’Keefe, J. & Dostrovsky, J. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res. 34, 171–175 (1971).

    Article  PubMed  Google Scholar 

  72. O’Keefe, J. & Recce, M. Phase relationship between hippocampal place units and the EEG theta rhythm. Hippocampus 3, 317–330 (1993).

    Article  PubMed  Google Scholar 

  73. Bose, A. & Recce, M. Phase precession and phase-locking of hippocampal pyramidal cells. Hippocampus 11, 204–215 (2001).

    Article  CAS  PubMed  Google Scholar 

  74. Skaggs, W. E., McNaughton, B. L., Wilson, M. A. & Barnes, C. A. Theta phase precession in hippocampal neuronal populations and the compression of temporal sequences. Hippocampus 6, 149–172 (1996).

    Article  CAS  PubMed  Google Scholar 

  75. Drieu, C. & Zugaro, M. Hippocampal sequences during exploration: mechanisms and functions. Front. Cell Neurosci. 13, 1–22 (2019).

    Article  Google Scholar 

  76. Gupta, A. S., van der Meer, M. A. A., Touretzky, D. S. & Redish, A. D. Segmentation of spatial experience by hippocampal theta sequences. Nat. Neurosci. 15, 1032–1039 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Jensen, O. & Lisman, J. E. Hippocampal sequence-encoding driven by a cortical multi-item working memory buffer. Trends Neurosci. 28, 67–72 (2005).

    Article  CAS  PubMed  Google Scholar 

  78. Friederici, A. D. & Singer, W. Grounding language processing on basic neurophysiological principles. Trends Cogn. Sci. 19, 329–338 (2015).

    Article  PubMed  Google Scholar 

  79. King, C., Recce, M. & O’keefe, J. The rhythmicity of cells of the medial septum/diagonal band of Broca in the awake freely moving rat: relationships with behaviour and hippocampal theta. Eur. J. Neurosci. 10, 464–477 (1998).

    Article  CAS  PubMed  Google Scholar 

  80. Heusser, A. C., Poeppel, D., Ezzyat, Y. & Davachi, L. Episodic sequence memory is supported by a theta-gamma phase code. Nat. Neurosci. 19, 1374–1380 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Lisman, J. E. & Jensen, O. The theta-gamma neural code. Neuron 77, 1002–1016 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Boeckx, C. & Benítez-Burraco, A. The shape of the human language-ready brain. Front. Psychol. 5, 1–23 (2014).

    Article  Google Scholar 

  83. Murphy, E. in The Talking Species: Perspectives on the Evolutionary, Neuronal and Cultural Foundations of Language (eds Luef, E. & Manuela, M.) 251–269 (Unipress Graz, 2018).

  84. Doumas, L. A. A., Hummel, J. E. & Sandhofer, C. M. A theory of the discovery and predication of relational concepts. Psychol. Rev. 115, 1–43 (2008).

    Article  PubMed  Google Scholar 

  85. Hummel, J. E. & Holyoak, K. J. Distributed representations of structure: a theory of analogical access and mapping. Psychol. Rev. 104, 427–466 (1997).

    Article  Google Scholar 

  86. Martin, A. E. A compositional neural architecture for language. J. Cogn. Neurosci. 32, 1407–1427 (2020).

    Article  PubMed  Google Scholar 

  87. Chomsky, N. Lectures on Government and Binding: The Pisa Lectures (Foris, 1981).

  88. Chomsky, N. Aspects of the Theory of Syntax (MIT Press, 1965).

  89. Joshi, A. K., Levy, L. S. & Takahashi, M. Tree adjunct grammars. J. Comput. Syst. Sci. 10, 136–163 (1975).

    Article  Google Scholar 

  90. Shieber, S. M. An Introduction to Unification-Based Approaches to Grammar (Microtome, 2003).

  91. Chomsky, N. The Minimalist Program (MIT Press, 1995).

  92. Plate, T. A. Holographic reduced representations. IEEE Trans. Neural Netw. 6, 623–641 (1995).

    Article  CAS  PubMed  Google Scholar 

  93. Carpenter, A. F., Baud-Bovy, G., Georgopoulos, A. P. & Pellizzer, G. Encoding of serial order in working memory: neuronal activity in motor, premotor, and prefrontal cortex during a memory scanning task. J. Neurosci. 38, 4912–4933 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Petrides, M. Functional specialization within the dorsolateral frontal cortex for serial order memory. Proc. R. Soc. Lond. B Biol. Sci. 246, 299–306 (1991).

    Article  CAS  Google Scholar 

  95. Long, N. M. & Kahana, M. J. Hippocampal contributions to serial-order memory. Hippocampus 29, 252–259 (2019).

    Article  PubMed  Google Scholar 

  96. Friederici, A. D., Fiebach, C. J., Schlesewsky, M., Bornkessel, I. D. & von Cramon, D. Y. Processing linguistic complexity and grammaticality in the left frontal cortex. Cereb. Cortex 16, 1709–1717 (2006).

    Article  PubMed  Google Scholar 

  97. Lisman, J. E. & Idiart, M. A. P. Storage of 7±2 short-term memories in oscillatory subcycles. Science 267, 1512–1515 (1995).

    Article  CAS  PubMed  Google Scholar 

  98. Bader, M. & Lasser, I. in Perspectives on Sentence Processing (eds Clifton, C., Frazier, L. & Reiner, K.) 225–242 (L. Erlbaum Associates, 1994).

  99. Inoue, A. & Fodor, J. D. in Japanese Sentence Processing (eds Mazuka, R & Nagai, N.) 9–63 (L. Erlbaum Associates, 1995).

  100. Mazuka, R. & Itoh, K. In Japanese Sentence Processing (eds Mazuka, R. & Nagai, N.) 295–329 (L. Erlbaum Associates, 1995).

  101. Miyamoto, E. T. Case markers as clause boundary inducers in Japanese. J. Psycholinguist. Res. 31, 307–347 (2002).

    Article  PubMed  Google Scholar 

  102. Tabor, W., Galantucci, B. & Richardson, D. Effects of merely local syntactic coherence on sentence processing. J. Mem. Lang. 50, 355–370 (2004).

    Article  Google Scholar 

  103. Altmann, G. T. M. & Mirković, J. Incrementality and prediction in human sentence processing. Cogn. Sci. 33, 583–609 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Bransford, J. D. & Johnson, M. K. Contextual prerequisites for understanding: some investigations of comprehension and recall. J. Verbal Learn. Verbal Behav. 11, 717–726 (1972).

    Article  Google Scholar 

  105. Nelson, M. J. et al. Neurophysiological dynamics of phrase-structure building during sentence processing. Proc. Natl Acad. Sci. USA 114, E3669–E3678 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Uddén, J., de Jesus Dias Martins, M., Zuidema, W. & Tecumseh Fitch, W. Hierarchical structure in sequence processing: how to measure it and determine its neural implementation. Top. Cogn. Sci. 12, 910–924 (2020).

    Article  PubMed  Google Scholar 

  107. Carnie, A. Syntax: A Generative Introduction (Blackwell, 2002).

  108. Berger, H. Über das Elektroenkephalogramm des Menschen. Arch. Psychiatr. Nervenkr. 87, 527–570 (1929).

    Article  Google Scholar 

  109. Nunez, P. L. & Srinivasan, R. Electroencephalogram. Scholarpedia 2, 1348 (2007).

    Article  Google Scholar 

  110. Rodin, E. & Funke, M. Cerebral electromagnetic activity in the subdelta range. J. Clin. Neurophysiol. 23, 238–244 (2006).

    Article  PubMed  Google Scholar 

  111. Buzsaki, G. & Watson, B. O. Brain rhythms and neural syntax: implications for efficient coding of cognitive content and neuropsychiatric disease. Dialogues Clin. Neurosci. 14, 345–367 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Klimesch, W. The frequency architecture of brain and brain body oscillations: an analysis. Eur. J. Neurosci. 48, 2431–2453 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  113. Breska, A. & Deouell, L. Y. Neural mechanisms of rhythm-based temporal prediction: delta phase-locking reflects temporal predictability but not rhythmic entrainment. PLoS Biol. 15, e2001665 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  114. Pikovsky, A., Kurths, J., Rosenblum, M. & Kurths, J. Synchronization: A Universal Concept in Nonlinear Sciences (Cambridge Univ. Press, 2003).

  115. Strogatz, S. H. Nonlinear Dynamics and Chaos with Student Solutions Manual: With Applications to Physics, Biology, Chemistry, and Engineering (CRC, 2018).

  116. Kopell, N., Ermentrout, G. B., Whittington, M. A. & Traub, R. D. Gamma rhythms and beta rhythms have different synchronization properties. Proc. Natl Acad. Sci. USA 97, 1867–1872 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Buzsáki, G. & Draguhn, A. Neuronal oscillations in cortical networks. Science 304, 1926–1929 (2004).

    Article  PubMed  Google Scholar 

  118. Herreras, O. Local field potentials: myths and misunderstandings. Front. Neural Circuits 10, 101 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  119. Buzsáki, G., Anastassiou, C. A. & Koch, C. The origin of extracellular fields and currents-EEG, ECoG, LFP and spikes. Nat. Rev. Neurosci. 13, 407–420 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  120. Doelling, K. B., Florencia Assaneo, M., Bevilacqua, D., Pesaran, B. & Poeppel, D. An oscillator model better predicts cortical entrainment to music. Proc. Natl Acad. Sci. USA 116, 10113–10121 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Helfrich, R. F., Breska, A. & Knight, R. T. Neural entrainment and network resonance in support of top-down guided attention. Curr. Opin. Psychol. 29, 82–89 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  122. Obleser, J., Herrmann, B. & Henry, M. J. Neural oscillations in speech: don’t be enslaved by the envelope. Front. Hum. Neurosci. 6, 2008–2011 (2012).

    Article  Google Scholar 

  123. Doelling, K. B., Arnal, L. H., Ghitza, O. & Poeppel, D. Acoustic landmarks drive delta-theta oscillations to enable speech comprehension by facilitating perceptual parsing. Neuroimage 85, 761–768 (2014).

    Article  CAS  PubMed  Google Scholar 

  124. van Rullen, R. Perceptual cycles. Trends Cogn. Sci. 20, 723–735 (2016).

    Article  Google Scholar 

  125. Shamma, S. A., Elhilali, M. & Micheyl, C. Temporal coherence and attention in auditory scene analysis. Trends Neurosci. 34, 114–123 (2011).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors are very grateful to E. Lau and M. Yoshida for their vast input and feedback. They also thank J. Mitchell for help with corpus data, J. Bowers for his comments and S. Brendecke for help with illustrations. N.K. acknowledges the support of the International Laboratory of Social Neurobiology, Institute for Cognitive Neuroscience, Higher School of Economics, Russian Federation (grant 075-15-2022-1037). A.T. acknowledges the support of the Max Planck Society.

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Kazanina, N., Tavano, A. What neural oscillations can and cannot do for syntactic structure building. Nat Rev Neurosci 24, 113–128 (2023). https://doi.org/10.1038/s41583-022-00659-5

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