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Neurocomputational Properties of Speech Sound Perception and Production

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Language Electrified

Part of the book series: Neuromethods ((NM,volume 202))

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Abstract

Speakers acquire, comprehend, and produce speech effortlessly, notwithstanding its complexity, variability, and dynamicity. This is possible thanks to sophisticated neuronal connections evolved to jointly control auditory and motor areas, together with specialized memory processes. Recent interdisciplinary research has begun to reveal the neurocomputational properties of speech sounds perception and production. Discussing neurophysiological evidence coming from different methodologies and research approaches, we will try to interconnect well-established linguistic primitives with neurophysiological ones assumed to be at the core of the computation and representation of speech sounds. In this way, we will explore how auditory and motor areas control bottom-up and top-down processes to categorize and produce speech sounds. Event-related potentials, event-related magnetic fields, oscillatory rhythms, transcranial magnetic stimulation, and functional magnetic resonance imaging evidence will show us if distinctive features or articulatory gestures are the better candidate to epistemologically link linguistic models with neural models of speech processing. Finally, we will delineate a preliminary theoretic proposal that integrates the linguistic and the neurobiological perspectives.

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Notes

  1. 1.

    For what concerns the discussion about the traditional notions of “phonetics” and “phonology,” cf. [12, 13].

References

  1. Kuhl PK, Miller JD (1978) Speech perception by the chinchilla: identification functions for synthetic VOT stimuli. J Acoust Soc Am 63:905–917

    Article  CAS  PubMed  Google Scholar 

  2. Ohl FW, Scheich H (2005) Learning-induced plasticity in animal and human auditory cortex. Curr Opin Neurobiol 15:470–477

    Article  CAS  PubMed  Google Scholar 

  3. Lu T, Liang L, Wang X (2001) Temporal and rate representations of time-varying signals in the auditory cortex of awake primates. Nat Neurosci 4:1131–1138

    Article  CAS  PubMed  Google Scholar 

  4. Mesgarani N, David SV, Fritz, et. Al. (2008) Phoneme representation and classification in primary auditory cortex. J Acoust Soc Am 123(2):899–909

    Article  PubMed  Google Scholar 

  5. Zoloth SR, Petersen MR, Beecher MD et al (1979) Species-specific perceptual processing of vocal sounds by monkeys. Science 204:870–872

    Article  CAS  PubMed  Google Scholar 

  6. Nelson DA, Marler P (1989) Categorical perception of a natural stimulus continuum: birdsong. Science 244:976–978

    Article  CAS  PubMed  Google Scholar 

  7. Fitch WT (2010) The evolution of language. Cambridge University Press, New York

    Book  Google Scholar 

  8. Carterette EC, Shipley C, Buchwald JS (1984) On synthesizing animal speech: the case of the cat. In: Bristow G (ed) Electronic speech synthesis: techniques, technology, and applications. McGraw-Hill, New York, pp 292–302

    Google Scholar 

  9. Kuhl PK, Stevens E, Hayashi A et al (2006) Infants show a facilitation effect for native language phonetic perception between 6 and 12 months. Dev Sci 9(2):13–21

    Article  Google Scholar 

  10. Edelman GM, Tononi G (2000) A universe of consciousness. How matter becomes imagination. Basic Books, New York

    Google Scholar 

  11. Phillips C (2000) Levels of representation in the electrophysiology of speech perception. Cogn Sci 25:711–731

    Article  Google Scholar 

  12. Durand J, Laks B (2002) Phonology, phonetics and cognition. In: Durand J, Bernard L (eds) Phonetics, phonology and cognition. Oxford University Press, Oxford, pp 10–50

    Google Scholar 

  13. van der Hulst HG (2013) The discoverers of the phoneme. In: Allen K (ed) Oxford handbook of the history of linguistics. Oxford University Press, Oxford, pp 167–191

    Google Scholar 

  14. Grimaldi M (2012) Toward a neural theory of language: old issues and new perspectives. J Neuroling 25(5):304–327

    Article  Google Scholar 

  15. Embick D, Poeppel D (2015) Towards a computational(ist) neurobiology of language: correlational, integrated, and explanatory neurolinguistics. Lang Cogn Neurosci 30(4):357–366. https://doi.org/10.1080/23273798.2014.980750

    Article  PubMed  Google Scholar 

  16. Feynman RP (1965) The character of physical low. The M.I.T Press, Cambridge, MA

    Google Scholar 

  17. Halle M, Stevens KN (1962) Speech recognition: a model and a program for research. IRE Trans PGIT IT-8:155–159

    Google Scholar 

  18. Stevens KN (2002) Toward a model for lexical access based on acoustic landmarks and distinctive features. J Acoust Soc Am 111:1872–1891

    Article  PubMed  Google Scholar 

  19. Jakobson R, Fant G, Halle M (1952) Preliminaries to speech analysis. The MIT Press, Cambridge, MA

    Google Scholar 

  20. Chomsky N, Morris H (1968) The sound patterns of English. Harper & Row, New York

    Google Scholar 

  21. Halle M (2002) From memory to speech and back: papers on phonetics and phonology 1954–2002. Mouton de Gruyter, Berlin

    Google Scholar 

  22. Manca AD, Grimaldi M (2016) Vowels and consonants in the brain: evidence from magnetoencephalographic studies on the N1m in normal-hearing listeners. Front Psychol 7:1413. https://doi.org/10.3389/fpsyg.2016.01413

    Article  PubMed  PubMed Central  Google Scholar 

  23. Teuber H-L (1967) Lacunae and research approaches to them: I. In: Millikan CH, Darley FL (eds) Brain mechanisms underlying speech and language. New MIT Press, York, pp 204–216

    Google Scholar 

  24. Liberman AM, Mattingly IG (1985) The motor theory of speech perception revised. Cognition 21(1):1–36

    Article  CAS  PubMed  Google Scholar 

  25. Liberman AM, Whalen DH (2000) On the relation of speech to language. Trends Cogn Sci 4(5):187–196

    Article  CAS  PubMed  Google Scholar 

  26. Partanen E, Kujala T, Näätänen R et al (2013) Learning-induced neural plasticity of speech processing before birth. PNAS 110(37):15145–15150

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Kuhl PK (2004) Early language acquisition: cracking the speech code. Nat Rev Neurosci 5(11):831–843

    Article  CAS  PubMed  Google Scholar 

  28. Werker JF, Richiard TC (1984) Cross-language speech perception: evidence for perceptual reorganization during the first year of life. Infant Behav Dev 7:49–63

    Article  Google Scholar 

  29. Romani GL, Williamson SJ, Kaufman L (1982) Tonotopic organization of the human auditory cortex. Science 216:1339–1340. https://doi.org/10.1016/j.neuroimage.2010.01.046

    Article  CAS  PubMed  Google Scholar 

  30. Scott SK, Johnsrude IS (2003) The neuroanatomical and functional organization of speech perception. Trends Neurosci 26:100–107

    Article  CAS  PubMed  Google Scholar 

  31. Moerel M, De Martino F, Formisano E (2014) An anatomical and functional topography of human auditory cortical areas. Front Human Neurosci 8. https://doi.org/10.3389/fnins.2014.00225

  32. Roberts TP, Ferrari P, Stufflebeam S et al (2000) Latency of the auditory evoked neuromagnetic field components: stimulus dependence and insights toward perception. J Clin Neurophysiol 17:114–129

    Article  CAS  PubMed  Google Scholar 

  33. Wang X (2007) Neural coding strategies in auditory cortex. Hear Res 229:81–93

    Article  PubMed  Google Scholar 

  34. Boemio A, Fromm S, Braun A et al (2005) Hierarchical and asymmetric temporal sensitivity in human auditory cortices. Nat Neurosci 8:389–395

    Article  CAS  PubMed  Google Scholar 

  35. Näätänen R, Picton T (1987) The N1 wave of the human electric and magnetic response to sound: a review and an analysis of the component structure. Psychophysiol 24:375–425

    Article  Google Scholar 

  36. Woods DL (1995) The component structure of the N1 wave of the human auditory evoked potential. Electroencephalogr Clin Neurophysiol 44:102–109

    CAS  Google Scholar 

  37. Ahlfors SP, Han J, Belliveau JW et al (2010) Sensitivity of MEG and EEG to source orientation. Brain Topog 23:227–232

    Article  Google Scholar 

  38. Baillet S (2017) Magnetoencephalography for brain electrophysiology and imaging. Nat Neurosci 20:327–339

    Article  CAS  PubMed  Google Scholar 

  39. Eulitz C, Diesch E, Pantev C et al (1995) Magnetic and electric brain activity evoked by the processing of tone and vowel stimuli. J Neurosci 1:2748–2755

    Article  Google Scholar 

  40. Diesch E, Eulitz C, Scott H et al (1996) The neurotopography of vowels as mirrored by evoked magnetic field measurements. Brain Lang 53:143–168

    Article  CAS  PubMed  Google Scholar 

  41. Poeppel D, Phillips C, Yellin E et al (1997) Processing of vowels in supratemporal auditory cortex. Neurosci Lett 221:145–148. https://doi.org/10.1016/S0304-3940(97)13325-0

    Article  CAS  PubMed  Google Scholar 

  42. Swink S, Stuart A (2012) Auditory long latency responses to tonal and speech stimuli. J Speech Lang Hear Res 55(2):447–459

    Article  PubMed  Google Scholar 

  43. Ohl FW, Scheich H (1997) Orderly cortical representation of vowels based on formant interaction. PNAS 94:9440–9444

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Shamma SA (1985) Speech processing in the auditory system I: the representation of speech sounds in the responses of the auditory nerve. J Acoust Soc Am 78(5):1612–1621

    Article  CAS  PubMed  Google Scholar 

  45. Shamma SA (1985) Speech processing in the auditory system II: the representation of speech sounds in the responses of the auditory nerve. J Acoust Soc Am 78(5):1622–1632

    Article  CAS  PubMed  Google Scholar 

  46. Scharinger M, Idsardi W, J., Poe, S. (2011) A comprehensive three-dimensional cortical map of vowel space. J Cogn Neursci 23:3972–3982

    Article  Google Scholar 

  47. Gage N, Roberts TPL, Hickok G (2006) Temporal resolution properties of human auditory cortex: reflections in the neuromagnetic auditory evoked M100 component. Brain Res 1069(1):166–171

    Article  CAS  PubMed  Google Scholar 

  48. Obleser J, Skott S, Eulitz K (2006) Now you hear it, now you don’t: transient traces of consonants and their nonspeech analogues in the human brain. Cereb Cortex 16:1069–1076

    Article  PubMed  Google Scholar 

  49. Obleser J, Elbert T, Lahiri A et al (2003) Cortical representation of vowels reflects acoustic dissimilarity determined by formant frequencies. Cogn Brain Res 15:207–213

    Article  Google Scholar 

  50. Obleser J, Elbert T, Eulitz C (2004) Attentional influences on functional mapping of speech sounds in human auditory cortex. BMC Neurosci 5:24. https://doi.org/10.1186/1471-2202-5-24

    Article  PubMed  PubMed Central  Google Scholar 

  51. Obleser J, Lahiri A, Eulitz C (2004) Magnetic brain response mirrors extraction of phonological features from spoken vowels. J Cogn Neurosci 16:31–39. https://doi.org/10.1162/089892904322755539

    Article  PubMed  Google Scholar 

  52. Grimaldi M, Manca AD, Sigona F et al (2016) Electroencephalographic evidence of vowels computation and representation in human auditory cortex. In: Di Sciullo AM (ed) Biolinguistics investigations on the language faculty. Benjamins, Amsterdam/Philadelphia, pp 79–100

    Chapter  Google Scholar 

  53. Obleser J, Lahiri A, Eulitz C (2003) Auditory-evoked magnetic field codes place of articulation in timing and topography around 100 milliseconds post syllable onset. NeuroImage 20:1839–1847

    Article  PubMed  Google Scholar 

  54. Luck SJ (2005) An introduction to the event-related potential technique. The MIT Press, Cambridge MA

    Google Scholar 

  55. Mäkelä A, Mari AP, Tiitinen H (2003) The auditory N1m reveals the left-hemispheric representation of vowel identity in humans. Neurosci Lett 353:111–114

    Article  PubMed  Google Scholar 

  56. Shestakova A, Brattico E, Soloviev A et al (2004) Orderly cortical representation of vowel categories presented by multiple exemplars. Brain Cogn Res 21:342–350

    Article  Google Scholar 

  57. Diesch E, Luce T (1997) Magnetic fields elicited by tones and vowel formants reveal tonotopy and nonlinear summation of cortical activation. Psychophysiology 34:501–510. https://doi.org/10.1111/j.1469-8986.1997.tb01736.x

    Article  CAS  PubMed  Google Scholar 

  58. Scharinger M, Monahan PJ, Idsardi WJ (2012) Asymmetries in the processing of vowel height. J Speech Lang Hear Res 55(3):903–918

    Article  PubMed  Google Scholar 

  59. Kuriki S, Okita Y, Hirata Y (1995) Source analysis of magnetic field responses from the human auditory cortex elicited by short speech sounds. Exp Brain Res 104(1):144–152

    Article  CAS  PubMed  Google Scholar 

  60. Scharinger M, Merickel J, Riley J et al (2011) Neuromagnetic evidence for a featural distinction of English consonants: sensor-and source-space data. Brain Lang 116(2):71–82

    Article  PubMed  Google Scholar 

  61. Hari R, Aittoniemi K, Järvinen et al (1980) Auditory evoked transient and sustained magnetic fields of the human brain localization of neural generators. Exp Brain Res 40(2):237–240

    Article  CAS  PubMed  Google Scholar 

  62. Wood CC, Wolpaw JR (1982) Scalp distribution of human auditory evoked potentials. II. Evidence for multiple sources and involvement of auditory cortex. Electroencephalogr Clin Neurophysiol 54:25–38

    Article  CAS  PubMed  Google Scholar 

  63. Inui K, Okamoto H, Miki K et al (2006) Serial and parallel processing in the human auditory cortex: a magnetoencephalographic study. Cereb Cortex 16:18–30

    Article  PubMed  Google Scholar 

  64. Eulitz C, Obleser J, Lahiri A (2004) Intra-subject replication of brain magnetic activity during the processing of speech sounds. Cogn Brain Res 19:82–91

    Article  Google Scholar 

  65. Malmivuo J, Suihko V, Eskola H (1997) Sensitivity distributions of EEG and MEG measurements. Biom Eng IEEE Trans 44:196–208

    Article  CAS  Google Scholar 

  66. Liu AK, Dale AM, Belliveau JW (2002) Monte Carlo simulation studies of EEG and MEG localization accuracy. Human Brain Map 16:47–62

    Article  CAS  Google Scholar 

  67. Cohen D, Halgren E (2003) Magnetoencephalography (Neuromagnetism). In: Encyclopedia of neuroscience. Elsevier, Amsterdam, pp 615–622

    Google Scholar 

  68. Lütkenhöner B, Krumbholz K, Seither-Preisler A (2003) Studies of tonotopy based on wave N100 of the auditory evoked field are problematic. Neuroimage 19:935–949

    Article  PubMed  Google Scholar 

  69. Manca AD, Di Russo F, Sigona F et al (2019) Electrophysiological evidence of phonemotopic representations of vowels in the primary and secondary auditory cortex. Cortex 121:385–398. https://doi.org/10.1016/j.cortex.2019.09.016

    Article  PubMed  Google Scholar 

  70. de Boer B (2001) The origins of vowel systems. Oxford University Press, Oxford

    Google Scholar 

  71. Teder-Sälejärvi WA, Di Russo F, McDonald et al (2005) Effects of spatial congruity on audio-visual multimodal integration. J Cogn Neurosci 17:1396–1409

    Article  PubMed  Google Scholar 

  72. Weise A, Schröger E, Horváth J (2018) The detection of higher order acoustic transitions is reflected in the N1 ERP. Psychophysiology 55(7):e13063. https://doi.org/10.1111/psyp.13063

    Article  PubMed  Google Scholar 

  73. Skipper JI, Devlin JT, Lametti RD (2017) The hearing ear is always found close to the speaking tongue: review of the role of the motor system in speech perception. Brain Lang 164:77–105

    Article  PubMed  Google Scholar 

  74. Hamilton LS, Oganian Y, Hall J et al (2021) Parallel and distributed encoding of speech across human auditory cortex. Cell 184:1–14. https://doi.org/10.1016/j.cell.2021.07.019

    Article  CAS  Google Scholar 

  75. Weinberger NM (2015) New perspective in the auditory cortex: learning and memory. In: Hickok G, Celesia GC (eds) Handbook of clinical neurology, vol 129. Elsevier, Amsterdam, pp 117–147

    Google Scholar 

  76. Bernal B, Ardila A (2016) From hearing sounds to recognizing phonemes: primary auditory cortex is a truly perceptual language area. AIMS Neurosci 3(4):454–473. https://doi.org/10.3934/Neuroscience.2016.4.454

    Article  Google Scholar 

  77. Brody RM, Nicholas BD, Wolf MJ et al (2013) Cortical deafness: a case report and review of the literature. Otol Neurotol 34:1226–1229

    Article  PubMed  Google Scholar 

  78. Näätänen R (2001) The perception of speech sounds by the human brain as reflected by the mismatch negativity (MMN) and its magnetic equivalent (MMNm). Psychophysiology 38:1–21

    Article  PubMed  Google Scholar 

  79. Näätänen R, Lehtokoski A, Lennes M et al (1997) Language-specific phoneme representations revealed by electric and magnetic brain responses. Nature 385:432–434

    Article  PubMed  Google Scholar 

  80. Winkler IKT, Alku P, Näätänen R (2003) Language context and phonetic change detection. Cogn Brain Res 17:833–844. https://doi.org/10.1016/S0926-6410(03)00205-2

    Article  Google Scholar 

  81. Nenonen S, Shestakova A, Huotilainen M et al (2003) Linguistic relevance of duration within the native language determines the accuracy of speech-sound duration processing. Cogn Brain Res 16:492–495. https://doi.org/10.1016/S0926-6410(03)00055-7

    Article  Google Scholar 

  82. Ylinen S, Shestakova A, Huotilainen M et al (2006) Mismatch negativity (MMN) elicited by changes in phoneme length: a cross-linguistic study. Br Res 1072:175–185. https://doi.org/10.1016/j.brainres.2005.12.004

    Article  CAS  Google Scholar 

  83. Yu YH, Shafer VL, Sussman ES (2017) Neurophysiological and behavioral responses of mandarin lexical tone processing. Front Hum Neurosci 11:95. https://doi.org/10.3389/fnins.2017.00095

    Article  Google Scholar 

  84. Sharma A, Dorman MF (1999) Cortical auditory evoked potential correlates of categorical perception of voice-onset time. J Acoust Soc Am 106(2):1078–1083

    Article  CAS  PubMed  Google Scholar 

  85. Sharma A, Dorman MF (2000) Neurophysiologic correlates of cross-language phonetic perception. J Acoust Soc Am 107(5):2697–2703

    Article  CAS  PubMed  Google Scholar 

  86. Fournier R, Gussenhoven C, Jensen et al (2010) Lateralization of tonal and intonational pitch processing: an MEG study. Brain Res 1328:7 9–8 8

    Article  Google Scholar 

  87. Sato Y, Utsugi A, Yamane N et al (2013) Dialectal differences in hemispheric specialization for Japanese lexical pitch accent. Brain Lang 127:475–483

    Article  PubMed  Google Scholar 

  88. Scharinger M, Monahan PJ, Idsardi WJ (2011) You had me at “Hello”: rapid extraction of dialect information from spoken words. Neuroimage 56(4):2329–2338

    Article  PubMed  Google Scholar 

  89. Conrey B, Potts P, Niedzielski NA (2005) Effects of dialect on merger perception: ERP and behavioral correlates. Brain Lang 95:435–449

    Article  PubMed  Google Scholar 

  90. Ying W, Xiaotao G, Ya Gao ZW et al (2019) Meaning enhances discrimination of merged phonemes: a mismatch negativity study. Brain Res 1724:146433. https://doi.org/10.1016/j.brainres.2019.146433

    Article  CAS  Google Scholar 

  91. Brunellière A, Dufour S, Nguyen N et al (2009) Behavioral and electrophysiological evidence for the impact of regional variation on phoneme perception. Cognition 111:390–396

    Article  PubMed  Google Scholar 

  92. Brunellière A, Dufour S, Nguyen N (2011) Regional differences in the listener’s phonemic inventory affect semantic processing: a mismatch negativity (MMN) study. Brain Lang 117:45–51

    Article  PubMed  Google Scholar 

  93. Dufour S, Brunellière A, Nguyen N (2013) To what extent do we hear phonemic contrasts in a non-native regional variety? Tracking the dynamics of perceptual processing with EEG. J Psycholin Res 42:161–173

    Article  Google Scholar 

  94. Lanwermeyer M, Henrich K, Rocholl M et al (2016) Dialect variation influences the phonological and lexical-semantic word processing in sentences. Electrophysiological evidence from a cross-dialectal comprehension. Front Psychol 7:739. https://doi.org/10.3389/fpsyg.2016.00739

    Article  PubMed  PubMed Central  Google Scholar 

  95. Bühler JC, Waßmann F, Buser D et al (2017) Neural processes associated with vocabulary and vowel-length differences in a dialect: an ERP study in pre-literate children. Brain Topogr 30:610–628

    Article  PubMed  Google Scholar 

  96. Kenstowicz M (1994) Phonology in generative grammar. Balckwell, Oxford

    Google Scholar 

  97. Kazanina N, Phillips C, Idsardi WJ (2006) The influence of meaning on the perception of speech sounds. PNAS 103(30):1138–1186

    Article  Google Scholar 

  98. Miglietta S, Grimaldi M, Calabrese A (2013) Conditioned allophony in speech perception: an ERP study. Brain Lang 126:285–290

    Article  PubMed  Google Scholar 

  99. Calabrese A (2012) Auditory representations and phonological illusions: a linguist’s perspective on the neurophysiological bases of speech perception. J Neuroling 25(5):355–381

    Article  Google Scholar 

  100. Grimaldi M (2018) Dialects and neuroscience: a first critical review. In: Grimaldi M, Lai R, Franco L et al (eds) Structuring variation in romance linguistics and beyond. Benjamins, Amsterdam/Philadelphia, pp 351–364

    Chapter  Google Scholar 

  101. Bühler JC, Schmid S, Maurer U (2017) Influence of dialect use on speech perception: a mismatch negativity study. Lang Cogn Neurosci 32(6):757–775

    Article  Google Scholar 

  102. Archangeli D, Pulleyblank D (1994) Grounded phonology. MIT Press, Cambridge, MA

    Google Scholar 

  103. Lahiri A, Reetz H (2010) Distinctive features: phonological underspecification in representation and processing. J Phon 38:44–59. https://doi.org/10.1016/j.wocn.2010.01.002

    Article  Google Scholar 

  104. Eulitz C, Lahiri A (2004) Neurobiological evidence for abstract phonological representations in the mental lexicon during speech recognition. J Cogn Neurosci 16:577–583. https://doi.org/10.1162/089892904323057308

    Article  PubMed  Google Scholar 

  105. Lipski SC, Lahiri A, Eulitz C (2007) Differential height specification in front vowels for German speakers and Turkish-German bilinguals: an electroencephalographic study. ICPhS, 16th, 809–812, Saarbrücken

    Google Scholar 

  106. De Jonge MJ, Boersma P (2015) French high-mid vowels are underspecified for height. Proc 18th ICPhS, Glasgow

    Google Scholar 

  107. Hestvik A, Durvasula K (2016) Neurobiological evidence for voicing underspecification in English. Brain Lang 152:28–43

    Article  PubMed  Google Scholar 

  108. Schluter K, Politzer-Ahles S, Almeida D (2016) No place for /h/: an ERP investigation of English fricative place features. Lang Cogn Neurosci 31:728–740

    Article  PubMed  PubMed Central  Google Scholar 

  109. Schluter K, Politzer-Ahles S, Kaabi AM et al (2017) Laryngeal features are phonetically abstract: mismatch negativity evidence from Arabic, English, and Russian. Front Psychol 8:746

    Article  PubMed  PubMed Central  Google Scholar 

  110. Cummings AE, Madden J, Hefta K (2017) Converging evidence for [coronal] underspecification in English-speaking adults. J Neuroling 44:147–162. https://doi.org/10.1016/j.jneuroling.2017.05.003

    Article  Google Scholar 

  111. Cummings AE, Ogiela DA, Wu YC (2020) Evidence for [coronal] Underspecification in typical and atypical phonological development. Front Hum Neurosci 14:580697. https://doi.org/10.3389/fnhum.2020.580697

    Article  PubMed  PubMed Central  Google Scholar 

  112. Højlund A, Gebauer L, McGregor WB et al (2019) Context and perceptual asymmetry effects on the mismatch negativity (MMNm) to speech sounds: an MEG study. Lang Cogn Neurosci 34:545–560. https://doi.org/10.1080/23273798.2019.1572204

    Article  Google Scholar 

  113. Hestvik A, Shinohara Y, Durvasula K et al (2020) Abstractness of human speech sound representations. Brain Res 1732:146664. https://doi.org/10.1016/j.brainres.2020.146664

    Article  CAS  PubMed  Google Scholar 

  114. Fu Z, Monahan PJ (2021) Extracting phonetic features from natural classes: a mismatch negativity study of mandarin Chinese retroflex consonants. Front Human Neursci 15:609898. https://doi.org/10.3389/fnhum.2021.609898

    Article  Google Scholar 

  115. Yu YH, Shafer VL (2021) Neural representation of the English vowel feature [high]: evidence from /ε/ vs./ɪ/. Front Human Neursci 15:629517. https://doi.org/10.3389/fnhum.2021.629517

    Article  Google Scholar 

  116. Cummings AE, Wu YC, Ogiela DA (2021) Phonological Underspecification: an explanation for how a rake can become awake. Front Hum Neurosci 15:585817. https://doi.org/10.3389/fnhum.2021.585817

    Article  PubMed  PubMed Central  Google Scholar 

  117. Politzer-Ahles S, Schluter K, Wu K et al (2016) Asymmetries in the perception of mandarin tones: evidence from mismatch negativity. J Exp Psychol Hum Perc Perf 42:1547–1570. https://doi.org/10.1037/xhp0000242

    Article  Google Scholar 

  118. Friedrich CK, Lahiri A, Eulitz C (2008) Neurophysiological evidence for underspecified lexical representations: asymmetries with word initial variations. J Exp Psy Hum Perc Perf 34:1545–1559. https://doi.org/10.1037/a0012481

    Article  Google Scholar 

  119. Cornell SA, Lahiri A, Eulitz C (2013) Inequality across consonantal contrasts in speech perception: evidence from mismatch negativity. J Exp Psy Hum Perc Perf 39:757–772. https://doi.org/10.1037/a0030862

    Article  Google Scholar 

  120. Lawyer LA, Corina DP (2018) Putting underspecification in context: ERP evidence for sparse representations in morphophonological alternations. Lang Cogn Neursci 33:50–64. https://doi.org/10.1080/23273798.2017.1359635

    Article  Google Scholar 

  121. Riedinger M, Nagels A, Werth A et al (2021) Asymmetries in accessing vowel representations are driven by phonological and acoustic properties: neural and behavioral evidence from natural German minimal pairs. Front Human Neurosci 15:612345. https://doi.org/10.3389/fnhum.2021.612345

    Article  Google Scholar 

  122. Mitterer H (2023) Understanding gardem bench: Studies on the perception of assimilation word forms. Degree Dissertation, Universiteit Maastricht, Maastricht,The Netherlands.

    Google Scholar 

  123. Bonte ML, Mitterer H, Zellagui N et al (2005) Auditory cortical tuning to statistical regularities in phonology. Clin Neurophisol 116:2765–2774

    Article  Google Scholar 

  124. Nduga N, Urbanec J, Oceláková Z et al (2021) Neural processing of spectral and durational changes in speech and non-speech stimuli: an MMN study with Czech adults. Front Human Neurosci 15:643655. https://doi.org/10.3389/fnhum.2021.643655

    Article  Google Scholar 

  125. Polka L, Bohn OS (2011) Natural Referent Vowel (NRV) framework: an emerging view of early phonetic development. J Phon 39:467–478. https://doi.org/10.1016/j.wocn.2010.08.007

    Article  Google Scholar 

  126. Masapollo M, Polka L, Ménard L (2017) A universal bias in adult vowel perception – by ear or by eye. Cognition 166:358–370. https://doi.org/10.1016/j.cognition.2017.06.001

    Article  PubMed  Google Scholar 

  127. Masapollo M, Polka L, Ménard L et al (2018) Asymmetries in unimodal visual vowel perception: the roles of oral-facial kinematics, orientation and configuration. J Exp Psychol Hum Percept Perform 44:1103–1118. https://doi.org/10.1037/xhp0000518

    Article  PubMed  PubMed Central  Google Scholar 

  128. Masapollo M, Guenther FH (2019) Engaging the articulators enhances perception of concordant visible speech movements. J Speech Lang Hear Sci 62:3679–3688. https://doi.org/10.1044/2019_jslhr-s-19-0167

    Article  Google Scholar 

  129. Best CT, Tyler MD (2007) Nonnative and second-language speech perception: commonalities and complementarities. In: Munroand MJ, Bohn O-S (eds) Second language speech learning: the role of language experience in speech perception and production. Benjamins, Amsterdam, pp 13–34

    Chapter  Google Scholar 

  130. Winkler I, Kujala T, Tiitinen H et al (1999) Brain responses reveal the learning of foreign language phonemes. Psychophysiology 36:638–642

    Article  CAS  PubMed  Google Scholar 

  131. Rinker T, Alku P, Brosch S et al (2010) Discrimination of native and nonnative vowel contrasts in bilingual Turkish–German and monolingual German children: insight from the mismatch negativity ERP component. Brain Lang 113:90–95

    Article  PubMed  Google Scholar 

  132. Peltola MS, Kujala T, Tuomainen J et al (2003) Native and foreign vowel discrimination as indexed by the mismatch negativity (MMN) response. Neurosci Lett 352:25–28

    Article  CAS  PubMed  Google Scholar 

  133. Cheour M, Shestakova A, Alku P et al (2002) Mismatch negativity (MMN) shows that 3-6-years-old children can learn to discriminate nonnative speech sounds within two months. Neurosci Lett 325:187–190

    Article  CAS  PubMed  Google Scholar 

  134. Shestakova A, Huotilainen M, Čeponiené R et al (2003) Event-related potentials associated with second language learning in children. Clin Neurophisol 114(8):1507–1512

    Article  Google Scholar 

  135. Peltola MS, Kuntola M, Tamminen H (2005) Early exposure to a nonnative language alters preattentive vowel discrimination. Neurosci Lett 388:121–125

    Article  CAS  PubMed  Google Scholar 

  136. Peltola MS, Tuomainen O, Aaltonen O (2007) The effect of language immersion education on the preattentive perception of native and nonnative vowel contrasts. J Psycholin Res 36:15–23

    Article  Google Scholar 

  137. Bomba MD, Choly D, Pang EW (2011) Phoneme discrimination and mismatch negativity in English and Japanese speakers. Neuroreport 13, 22(10):479–483

    Article  Google Scholar 

  138. Grimaldi M, Sisinni B, Gili FB et al (2014) Assimilation of L2 vowels to L1 phonemes governs L2 learning in adulthood – a behavioral and ERP study. Front Human Neurosci 8:279. https://doi.org/10.3389/fnhum.2014.00279

    Article  Google Scholar 

  139. Jost LB, Eberhard-Moscicka AK, Pleisch G, Heusser et al (2015) Native and non-native speech sound processing and the neural mismatch responses: a longitudinal study on classroom-based foreign language learning. Neuropsychologia 72:94–104

    Article  PubMed  Google Scholar 

  140. Hisagi M, Shafer VL, Miyagawa S (2016) Second-language learning effects on automaticity of speech processing of Japanese phonetic contrasts: an MEG study. Brain Res 1652:111–118

    Article  CAS  PubMed  Google Scholar 

  141. Wottawa J, Adda-Decker M, Isel F (2021) Neurophysiology of non-native sound discrimination: evidence from German vowels and consonants in successive French–German bilinguals using an MMN oddball paradigm. Bilin Lang Cogn 1–11. https://doi.org/10.1017/S1366728921000468

  142. Sakai M, Moorman C (2018) Can perception training improve the production of second language phonemes? A meta-analytic review of 25 years of perception training research. Appl Psycholinguis 39(1):187–224. https://doi.org/10.1017/S0142716417000418

    Article  Google Scholar 

  143. Varela F, Lachaux JP, Rodriguez E et al (2001) The brain web: phase synchronization and large-scale integration. Nat Rev Neurosci 2:229–239. https://doi.org/10.1038/35067550

    Article  CAS  PubMed  Google Scholar 

  144. Başar E, Başar-Erogluc C, Karakaş S et al (2001) Gamma, alpha, delta, and theta oscillations govern cognitive processes. Int J Psychophysiol 39:241–248

    Article  PubMed  Google Scholar 

  145. Buzsáki G (2006) Rhythms of the brain. Oxford University Press, Oxford

    Book  Google Scholar 

  146. Sauseng P, Klimesch W, Gruber WR et al (2007) Are event-related potential components generated by phase resetting of brain oscillations? A critical discussion. Neuroscience 146(4):1435–1444

    Article  CAS  PubMed  Google Scholar 

  147. Penny WD, Kiebel SJ, Kilner J et al (2002) Event-related brain dynamics. Trends Neurosci 25:387–389

    Article  CAS  PubMed  Google Scholar 

  148. Klimesch W, Schack B, Schabus M et al (2004) Phase-locked alpha and theta oscillations generate the P1-N1 complex and are related to memory performance. Cogn Brain Res 19:302–316

    Article  Google Scholar 

  149. Zoefel B, VanRullen R (2015) The role of high-level processes for oscillatory phase entrainment to speech sound. Front Human Neurosci 9:651. https://doi.org/10.3389/fnhum.2015.00651

    Article  Google Scholar 

  150. Ghitza O (2011) Linking speech perception and neurophysiology: speech decoding guided by cascaded oscillators locked to the input rhythm. Front Psychol 2:130. https://doi.org/10.3389/fpsyg.2011.00130

    Article  PubMed  PubMed Central  Google Scholar 

  151. Giraud A-L, Poeppel D (2012) Cortical oscillations and speech processing: emerging computational principles and operations. Nat Neurosci 15:511–517. https://doi.org/10.1038/nn.3063

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Kösem A, van Wassenhove V (2017) Distinct contributions of low- and high-frequency neural oscillations to speech comprehension. Lang Cogn Neurosci 32(5):536–544. https://doi.org/10.1080/23273798.2016.1238495

    Article  Google Scholar 

  153. Coffey EBJ, Arseneau-Bruneau I, Zhang X et al (2021) Oscillatory entrainment of the frequency-following response in auditory cortical and subcortical structures. J Neurosci 41(18):4073–4087. https://doi.org/10.1523/JNEUROSCI.2313-20.2021

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Pasley BN, Stephen DV, Mesgarani N et al (2012) Reconstructing speech from human auditory cortex. PLoS Biol 10(1):e1001251. https://doi.org/10.1371/journal.pbio.1001251

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Mesgarani N, Cheung C, Keith J et al (2014) Phonetic feature encoding in human superior temporal Gyrus. Science 343:1006–1010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Kösem A, Basira A, Azizi L et al (2016) High frequency neural activity predicts word parsing in ambiguous speech streams. J Neurophysiol 116:2497–2512. https://doi.org/10.1152/jn.00074

    Article  PubMed  PubMed Central  Google Scholar 

  157. Ding N, Melloni L, Zhang H et al (2016) Cortical tracking of hierarchical linguistic structures in connected speech. Nat Neurosci 19(1):158–164. https://doi.org/10.1038/nn.4186

    Article  CAS  PubMed  Google Scholar 

  158. Di Liberto GM, O’sullivan JA, Lalor EC (2015) Low-frequency cortical entrainment to speech reflects phoneme level processing. Curr Biol 25(19):2457–2465. https://doi.org/10.1016/j.cub.2015.08.030

    Article  CAS  PubMed  Google Scholar 

  159. Nora A, Faisal A, Seol J et al (2020) Dynamic time-locking mechanism in the cortical representation of spoken words. eNeuro 7(4). https://doi.org/10.1523/ENEURO.0475-19.2020

  160. Lizarazu M, Lallier M, Bourguignon M et al (2021) Impaired neural response to speech edges in dyslexia. Cortex 135:207–218

    Article  PubMed  Google Scholar 

  161. Daube C, Ince RAA, Gross J (2019) Simple acoustic features can explain phoneme-based predictions of cortical responses to speech. Curr Biol 29:1924–1937. https://doi.org/10.1016/j.cub.2019.04.067

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Riecke L, Vanbussel M, Hausfeld L et al (2012) Hearing an illusory vowel in noise: suppression of auditory cortical activity. J Neurosci 32(23):8024–8034. https://doi.org/10.1523/JNEUROSCI.0440-12.2012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Sunami K, Ishii A, Takano S, Yamamoto H et al (2013) Neural mechanisms of phonemic restoration for speech comprehension revealed by magnetoencephalography. Brain Res 1537:164–173. https://doi.org/10.1016/j.brainres.2013.09.010

    Article  CAS  PubMed  Google Scholar 

  164. Strauß A, Kotz SA, Scharinger M et al (2014) Alpha and theta brain oscillations index dissociable processes in spoken word recognition. Neuroimage 97:387–395. https://doi.org/10.1016/j.neuroimage.2014.04.005

    Article  PubMed  Google Scholar 

  165. Buiatti M, Peña M, Dehaene-Lambertz G (2009) Investigating the neural correlates of continuous speech computation with frequency-tagged neuroelectric responses. Neuroimage 44:509–519. https://doi.org/10.1016/j.neuroimage.2008.09.015pmid:18929668

    Article  PubMed  Google Scholar 

  166. Murphy E (2016) A theta-gamma neural code for feature set composition with phase-entrained delta nestings. UCLWPL:1–22

    Google Scholar 

  167. Ou J, Sam-Po L (2018) Induced gamma oscillations index individual differences in speech sound perception and production. Neuropsychologia 121:28–36

    Article  PubMed  Google Scholar 

  168. Bouchard KE, Mesgarani N, Johnson K et al (2012) Functional organization of human sensorimotor cortex for speech articulation. Nature 495:327–332. https://doi.org/10.1038/nature11911

    Article  CAS  Google Scholar 

  169. Lotte F, Brumberg JS, Brunner P et al (2015) Electrocorticographic representations of segmental features in continuous speech. Front Human Neuro 9:97. https://doi.org/10.3389/fnhum.2015.00097

    Article  Google Scholar 

  170. Giraud A-L, Kleinschmidt A, Poeppel D et al (2007) Endogenous cortical rhythms determine cerebral specialization for speech perception and production. Neuron 56(6):1127–1134. https://doi.org/10.1016/j.neuron.2007.09.038

    Article  CAS  PubMed  Google Scholar 

  171. Cogan G, Thesen T, Carlson C et al (2014) Sensory–motor transformations for speech occur bilaterally. Nature 507:94–98. https://doi.org/10.1038/nature12935

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Khoshkhoo S, Leonard MK, Mesgarani N et al (2018) Neural correlates of sine-wave speech intelligibility in human frontal and temporal cortex. Brain Lang 187:83–91

    Article  PubMed  PubMed Central  Google Scholar 

  173. Cheung C, Liberty SH, Johnson K et al (2016) The auditory representation of speech sounds in human motor cortex. elife 5:e12577. https://doi.org/10.7554/eLife.12577

    Article  PubMed  PubMed Central  Google Scholar 

  174. Barnaud M-L, Bessière P, Diard J et al (2018) Reanalyzing neurocognitive data on the role of the motor system in speech perception within COSMO, a Bayesian perceptuo-motor model of speech communication. Brain Lang 187:19–32. https://doi.org/10.1016/j.bandl.2017.12.003

    Article  PubMed  PubMed Central  Google Scholar 

  175. Chartier J, Gopala KA, Johnson K et al (2018) Encoding of articulatory kinematic trajectories in human speech sensorimotor cortex. Neuron 98:1042–1054. https://doi.org/10.1016/j.neuron.2018.04.031

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. Mugler EM, Matthew CT, Karen L et al (2018) Differential representation of articulatory gestures and phonemes in precentral and inferior frontal gyri. J Neurosci 38(46):9803–9813. https://doi.org/10.1523/JNEUROSCI.1206-18.2018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Mukherjee S, Badino L, Hilt PM et al (2019) The neural oscillatory markers of phonetic convergence during verbal interaction. Hum Brain Mapp 40:187–201. https://doi.org/10.1002/hbm.24364

    Article  PubMed  Google Scholar 

  178. Magrassi L, Giuseppe A, Alessandro C et al (2015) Sound representation in higher language areas during language generation. PNAS 112(6):1868–1873

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Watanabe H, Hiroki T, Sakriani S et al (2020) Synchronization between overt speech envelope and EEG oscillations during imagined speech. Neurosci Res 153:48–55. https://doi.org/10.1016/j.neures.2019.04.004

    Article  PubMed  Google Scholar 

  180. Pasley BN, Stephen VD, Nima M et al (2012) Reconstructing speech from human auditory cortex. PLoS Biol 10(1):e1001251. https://doi.org/10.1371/journal.pbio.1001251

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  181. Fadiga L, Craighero L, Buccino G et al (2002) Speech listening specifically modulates the excitability of tongue muscles: a TMS study. Eur J Neurosci 15(2):399–402. https://doi.org/10.1046/j.0953-816x.2001.01874.x

    Article  PubMed  Google Scholar 

  182. Roy AC, Craighero L, Fabbri-Destro M et al (2008) Phonological and lexical motor facilitation during speech listening: a transcranial magnetic stimulation study. J Phys 102(1–3):101–105

    Google Scholar 

  183. Rizzolatti G, Craighero L (2004) The mirror neuron system. Ann Rev Neurosci 27:169–192

    Article  CAS  PubMed  Google Scholar 

  184. Meister IG, Wilson SM, Deblieck C et al (2007) The essential role of premotor cortex in speech perception. Curr Biol 17(19):1692–1696. https://doi.org/10.1016/j.cub.2007.08.064

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Möttönen R, van de Ven GM, Watkins KE (2014) Attention fine-tunes auditory-motor processing of speech sounds. J Neurosci 34(11):4064–4069. https://doi.org/10.1523/JNEUROSCI.2214-13.2014

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  186. D’Ausilio A, Pulvermuüller F, Salmas P et al (2009) The motor somatotopy of speech perception. Curr Biol 19(5):381–385. https://doi.org/10.1016/j.cub.2009.01.017

    Article  CAS  PubMed  Google Scholar 

  187. D’Ausilio A, Bufalari I, Salmas P et al (2011) Vocal pitch discrimination in the motor system. Brain Lang 118(1–2):9–14. https://doi.org/10.1016/j.bandl.2011.02.007

    Article  PubMed  Google Scholar 

  188. Sato M, Tremblay P, Gracco VL (2009) A mediating role of the premotor cortex in phoneme segmentation. Brain Lang 111(1):1–7

    Article  PubMed  Google Scholar 

  189. Romero L, Walsh V, Papagno C (2006) The neural correlates of phonological short-term memory: a repetitive transcranial magnetic stimulation study. J Cogn Neurosci 18(7):1147–1155

    Article  CAS  PubMed  Google Scholar 

  190. Hickok G, Poeppel D (2007) The cortical organization of speech processing. Nat Neurosci 8:393–402

    Article  CAS  Google Scholar 

  191. Smalle EHM, Rogers J, Möttönen R (2015) Dissociating contributions of the motor cortex to speech perception and response bias by using transcranial magnetic stimulation. Cereb Cortex 25(10):3690–3698

    Article  PubMed  Google Scholar 

  192. Schomers MR, Pulvermüller F (2016) Is the sensorimotor cortex relevant for speech perception and understanding? An integrative review. Front Human Neuro 10:435

    Google Scholar 

  193. Murakami T, Kell CA, Restle J et al (2015) Left dorsal speech stream components and their contribution to phonological processing. J Neurosci 35(4):1411–1422. https://doi.org/10.1523/JNEUROSCI.0246-14.2015

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  194. Lametti DR, Oostwoud W, Bonaiuto L et al (2016) Cerebellar tDCS dissociates the timing of perceptual decisions from perceptual change in speech. J Neurophysiol 116(5):2023–2232. https://doi.org/10.1152/jn.00433.2016

    Article  PubMed  PubMed Central  Google Scholar 

  195. Osnes B, Hugdahl K, Specht K (2011) Effective connectivity analysis demonstrates involvement of premotor cortex during speech perception. Neuroimage 54(3):2437–2445

    Article  PubMed  Google Scholar 

  196. Alho J, Barannon MG, May PJC et al (2016) Early-latency categorical speech sound representations in the left inferior frontal gyrus. Neuroimage 129:214–223. https://doi.org/10.1016/j.neuroimage.2016.01.016

    Article  PubMed  Google Scholar 

  197. Hickok G (2012) The cortical organization of speech processing: feedback control and predictive coding the context of a dual-stream model. J Com Diss 45(6):393–402

    Article  Google Scholar 

  198. Rimmele JM, Zion GE, Schröger E et al (2015) The effects of selective attention and speech acoustics on neural speech-tracking in a multitalker scene. Cortex 68:144–154

    Article  PubMed  PubMed Central  Google Scholar 

  199. Klimovich-Gray A, Tyler LK, Randal B et al (2019) Balancing prediction and sensory input in speech comprehension: the spatiotemporal dynamics of word recognition in context. J Neurosci 39:519–527. https://doi.org/10.1523/JNEUROSCI.3573-17.2018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  200. Donhauser PW, Baillet S (2019) Two distinct neural timescales for predictive speech processing. Neuron 105(2):385–393. https://doi.org/10.1016/j.neuron.2019.10.019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  201. Yi HG, Leonard MK, Chang EF (2019) The encoding of speech sounds in the superior temporal gyrus. Neuron 102(6):1096–1110. https://doi.org/10.1016/j.neuron.2019.04.023

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  202. Friston K (2005) A theory of cortical responses. Phil Trans R Soc 360:815–815

    Article  Google Scholar 

  203. Friston K, Kiebel S (2009) Predictive coding under the free-energy principle. Phil Trans R Soc 364:1211–1221

    Article  Google Scholar 

  204. Knill DC, Pouget A (2004) The Bayesian brain: the role of uncertainty in neural coding and computation. Trends Neurosci 27(12):712–719. https://doi.org/10.1016/j.tins.2004.10.007

    Article  CAS  PubMed  Google Scholar 

  205. Fontolan L, Morillon B, Liegeois-Chauvel C et al (2014) The contribution of frequency-specific activity to hierarchical information processing in the human auditory cortex. Nat Commun 5:4694

    Article  CAS  PubMed  Google Scholar 

  206. Park H, Ince RA, Schyns A et al (2015) Frontal top-down signals increase coupling of auditory low-frequency oscillations to continuous speech in human listeners. Curr Biol 25:1649–1653

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  207. Lewis AG, Schoffelen JM, Schriefers H et al (2016) A predictive coding perspective on beta oscillations during sentence-level language comprehension. Front Human Neurosci 10:85

    Article  Google Scholar 

  208. Sedley W, Gander PE, Sukhbinder K et al (2016) Neural signatures of perceptual inference. elife 5:e11476. https://doi.org/10.7554/eLife.11476.001

    Article  PubMed  PubMed Central  Google Scholar 

  209. Pefkou M, Arnal LH, Fontolan L, Giraud AL (2017) Θ-Band and Β-band neural activity reflects independent syllable tracking and comprehension of time-compressed speech. J Neurosci 37:7930–7938

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  210. Chao ZC, Takaura K, Wang L, Fujii N, Dehaene S (2018) Large-scale cortical networks for hierarchical prediction and prediction error in the primate brain. Neuron 100:1252–1266.e3

    Article  CAS  PubMed  Google Scholar 

  211. Monsalve IF, Bourguignon M, Molinaro N (2018) Theta oscillations mediate pre-activation of highly expected word initial phonemes. Sci Rep 8:9503. https://doi.org/10.1038/s41598-018-27898-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  212. Hovsepyan S, Olasagasti I, Giraud AL (2020) Combining predictive coding and neural oscillations enables online syllable recognition in natural speech. Nat Commun 11:3117. https://doi.org/10.1038/s41467-020-16956-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  213. Kuhl PK, Ramírez RR, Bosseler A et al (2014) Infants’ brain responses to speech suggest analysis by synthesis. PNAS 5, 111(31):11238–11245

    Article  Google Scholar 

  214. Arnal L, Poeppel D, Giraud A-L (2016) A neurophysiological perspective on speech processing. In: Hickok G, Small (eds) Neurobiology of language. Elsevier, Amsterdam, pp 463–478

    Chapter  Google Scholar 

  215. Obleser J, Herrmann B, Henry MJ (2012) Neural oscillations in speech: don’t be enslaved by the envelope. Front Human Neurosci 6:250. https://doi.org/10.3389/fnhum.2012.00250

    Article  Google Scholar 

  216. Petersen C, Malenka RC, Nicoll R et al (1998) All-or-none potentiation of ca3-ca1 synapses. PNAS 95:4732–4737

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  217. O’Connor DH, Wittenberg GM, Wang Samuel S-H (2005) Graded bidirectional synaptic plasticity is composed of switch-like unitary events. PNAS 102:9679–9684

    Article  PubMed  PubMed Central  Google Scholar 

  218. Tanaka J, Horiike Y, Matsuzaki M et al (2008) Protein synthesis and neurotrophin-dependent structural plasticity of single dendritic spines. Science 319:1683–1687

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  219. Chaudhuri R, Fiete I (2016) Computational principles of memory. Nat Neurosci 19:394–403. https://doi.org/10.1038/nn.4237

    Article  CAS  PubMed  Google Scholar 

  220. Markram H, Gerstner W, Sjöström PJ (2012) Spike-timing-dependent plasticity: a comprehensive overview. Front Syn Neurosci 4/2. https://doi.org/10.3389/fnsyn.2012.00002

  221. Rieke F, Bialek W, de Ruyter van Steveninck R (1999) Spikes: exploring the neural code. MIT Press, Cambridge, MA

    Google Scholar 

  222. Shu Y, Hasenstaub A, Duque A et al (2006) Modulation of intracortical synaptic potentials by presynaptic somatic membrane potential. Nature 441:761–765. https://doi.org/10.1038/nature04720

    Article  CAS  PubMed  Google Scholar 

  223. Mochizuki Y, Shinomoto S (2014) Analog and digital codes in the brain. Phys Rev E 89(2):022705

    Article  Google Scholar 

  224. Schroeder CE, Lakatos P (2009) Low-frequency neuronal oscillations as instruments of sensory selection. Trends Neurosci 32:9–18

    Article  CAS  PubMed  Google Scholar 

  225. Borgers C, Epstein S, Kopell NJ (2005) Background gamma rhythmicity and attention in cortical local circuits: a computational study. PNAS 102:7002–7007

    Article  PubMed  PubMed Central  Google Scholar 

  226. Shamir M, Ghitza O, Epstein S et al (2009) Representation of time-varying stimuli by a network exhibiting oscillations on a faster time scale. PLoS Comput Biol 5(5):e1000370. https://doi.org/10.1371/journal.pcbi.1000370

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  227. Grimaldi M (2020) From brain noise to syntactic structures: a formal proposal within the oscillatory rhythms perspective. In: Franco L, Lorusso P (eds) Linguistic variation: structure and interpretation. Mouton de Gruyter, Berlin-New York, pp 293–216

    Google Scholar 

  228. Saenz M, Langers DRM (2014) Tonotopic mapping of human auditory cortex. Hear Res 307:42–52

    Article  PubMed  Google Scholar 

  229. Bartlett EL (2013) The organization and physiology of the auditory thalamus and its role in processing acoustic features important for speech perception. Brain Lang 126:29–48

    Article  PubMed  PubMed Central  Google Scholar 

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Grimaldi, M. (2023). Neurocomputational Properties of Speech Sound Perception and Production. In: Grimaldi, M., Brattico, E., Shtyrov, Y. (eds) Language Electrified. Neuromethods, vol 202. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3263-5_13

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