Advertisement

Power and phase coherence in sensorimotor mu and temporal lobe alpha components during covert and overt syllable production

  • Andrew BowersEmail author
  • Tim Saltuklaroglu
  • David Jenson
  • Ashley Harkrider
  • David Thornton
Research Article
  • 49 Downloads

Abstract

The sensorimotor dorsal stream is known to activate in both overt and covert speech production. However, overt production produces sensory consequences that are absent during covert production. Thus, the purpose of the current study is to investigate differences in dorsal stream activity between these two production conditions across the time course of utterances. Electroencephalography (EEG) was recorded from 68 channels while 23 participants overtly (Op) and covertly (Cp) produced orthographically cued bisyllabic targets. Sensorimotor mu and auditory alpha components (from anterior and posterior aspects of the dorsal stream) were identified using independent component analysis (ICA). Event-related spectral perturbation (ERSP) analyses identified changes in mu and alpha oscillatory power over time, while intercomponent phase coherence (IPC) measured anterior–posterior connectivity in the two conditions. Results showed greater beta (15–25 Hz) suppression during speech planning across left and right hemisphere sensorimotor and temporal ICs for Op relative to Cp. By contrast, greater intrahemispheric beta coherence was observed for Cp compared to Op during speech planning. During execution, greater beta suppression was observed along with greater low frequency (< 10 Hz) power enhancement and intrahemispheric phase coherence in Op compared to Cp. The findings implicate low frequency sensorimotor and posterior temporal phase coherence in the integration of somatosensory and acoustic feedback in overt relative to covert execution. Findings are consistent with early frontal–temporal forward models involved in planning and execution with modulations depending on whether the task goal is internal or overt syllable production.

Keywords

Neural oscillations Mu rhythm Auditory alpha rhythm Internal models 

References

  1. Assaneo MF, Poeppel D (2018) The coupling between auditory and motor cortices is rate-restricted: Evidence for an intrinsic speech-motor rhythm. Sci Adv 4:eaao3842.  https://doi.org/10.1126/sciadv.aao3842 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Behroozmand R, Sangtian S (2018) Neural bases of sensorimotor adaptation in the vocal motor system. Exp Brain Res 236:1881–1895CrossRefGoogle Scholar
  3. Behroozmand R, Ibrahim N, Korzyukov O et al (2015) Functional role of delta and theta band oscillations for auditory feedback processing during vocal pitch motor control. Front Neurosci 9:1–13.  https://doi.org/10.3389/fnins.2015.00109 CrossRefGoogle Scholar
  4. Behroozmand R, Oya H, Nourski K, Kawassaki H, Larson C, Brugge J, Howard M, Greenlee J (2016) Neural correlates of vocal production and motor control in human heschl’s gyrus. J Neuroscience 36:2302–2315CrossRefGoogle Scholar
  5. Blair C, Smith A (1986) EMG recording in human lip muscles: can single muscles be isolated? J Speech Hear Res 29:256–266CrossRefGoogle Scholar
  6. Bowers A, Saltuklaroglu T, Harkrider A, Cuellar M (2013) Suppression of the mu rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing. PloS One 8:e72024CrossRefGoogle Scholar
  7. Bowers AL, Saltuklaroglu T, Harkrider A et al (2014) Dynamic modulation of shared sensory and motor cortical rhythms mediates speech and non-speech discrimination performance. Front Psychol 5:366.  https://doi.org/10.3389/fpsyg.2014.00366 CrossRefPubMedPubMedCentralGoogle Scholar
  8. Bowers A, Bowers L, Hudock D, Ramsdell-Hudock R (2018) Phonological working memory in developmental stuttering: potential insights from the neurobiology of language and cognition. J Flu Dis 58:94–117CrossRefGoogle Scholar
  9. Buchsbaum B, Baldo J, Okada K, Berman K (2011) Conduction aphasia, sensory-motor integration, and phonological short-term memory–an aggregate analysis of lesion and fMRI data. Brain Lang 119:119–128CrossRefGoogle Scholar
  10. Buchman TJ, Miller EK (2007) Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science 315:1860–1861CrossRefGoogle Scholar
  11. Campos Viola F, Thorne J, Edmonds B et al (2009) Semi-automatic identification of independent components representing EEG artifact. Clin Neurophysiol 120:868–877.  https://doi.org/10.1016/j.clinph.2009.01.015 CrossRefGoogle Scholar
  12. Chang EF et al (2013) Human cortical sensorimotor network underlying feedback control of vocal pitch. Proc Natl Acad Sci USA 110:2653–2658CrossRefGoogle Scholar
  13. Chatrian GE, Lettich E, Nelson PL (1985) Ten percent electrode system for topographic studies of spontaneous and evoked EEG activity. Am J EEG Technol 25:83–92.  https://doi.org/10.1080/00029238.1985.11080163 CrossRefGoogle Scholar
  14. Chung JW, Ofori E, Misra G et al (2017) Beta-band activity and connectivity in sensorimotor and parietal cortex are important for accurate motor performance. Neuroimage 144:164–173.  https://doi.org/10.1016/j.neuroimage.2016.10.008 CrossRefPubMedGoogle Scholar
  15. Cogan G, Thesen T, Carlson C, Doyle W, Devinsky O, Pesaran B (2014) Sensory-motor transformations for speech occur bilaterally. Nature 507:94–97CrossRefGoogle Scholar
  16. Cuellar M, Harkrider AW, Jenson D et al (2016) Time–frequency analysis of the EEG mu rhythm as a measure of sensorimotor integration in the later stages of swallowing. Clin Neurophysiol 127:2625–2635.  https://doi.org/10.1016/j.clinph.2016.04.027 CrossRefPubMedGoogle Scholar
  17. Delorme A, Palmer J, Onton J et al (2012) Independent EEG sources are dipolar. PLoS One.  https://doi.org/10.1371/journal.pone.0030135 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Doelling K, Arnal L, Ghitza O, Poeppel D (2014) Speech comprehension by facilitating perceptual parsing. Neuroimage.  https://doi.org/10.1016/j.neuroimage.2013.06.035.Acoustic CrossRefPubMedGoogle Scholar
  19. Engel A, Fries P (2010) Beta band oscillations: signaling the status quo. Curr Opin Neurobiol 50:156–165CrossRefGoogle Scholar
  20. Franken MK, Eisner F, Acheson DJ, McQueen JM, Hagoort P, Schoffelen JM (2018) Self-monitoring in the cerebral cortex: neural responses to small pitch shifts in auditory feedback during speech production. Neuroimage 179:326–336CrossRefGoogle Scholar
  21. Fries P (2005) A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn Sci 9:474–479CrossRefGoogle Scholar
  22. Gehrig J, Wibral M, Arnold C, Kell CA (2012) Setting up the speech production network: how oscillations contribute to lateralized information routing. Front Psychol 3:169.  https://doi.org/10.3389/fpsyg.2012.00169 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Ghitza O (2012) On the role of theta-driven syllabic parsing in decoding speech: intelligibility of speech with a manipulated modulation spectrum. Front Psychol 3:238.  https://doi.org/10.3389/fpsyg.2012.00238 CrossRefPubMedPubMedCentralGoogle Scholar
  24. 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 CrossRefPubMedPubMedCentralGoogle Scholar
  25. Gracco VL (1988) Timing factors in the coordination of speech movements. J Neurosci 8:4628–4639CrossRefGoogle Scholar
  26. Gregoriou GG, Gotts SJ, Zhou H, Desimone R (2009) High-Frequency, long-range coupling between prefrontal and visual cortex during attention. Science 324:1207–1210.  https://doi.org/10.1126/science.1171402 CrossRefPubMedPubMedCentralGoogle Scholar
  27. Gross J, Schmitz F, Schnitzler I et al (2004) Modulation of long-range neural synchrony reflects temporal limitations of visual attention in humans. Proc Nat Acad Sci 101:13050–13055CrossRefGoogle Scholar
  28. Gross J, Hoogenboom N, Thut G et al (2013) Speech rhythms and multiplexed oscillatory sensory coding in the human brain. PLoS Biol 11:e1001752.  https://doi.org/10.1371/journal.pbio.1001752 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Guenther F, Hickok G (2015) Role of the auditory system in speech production. Handb Clin Neurol 129:161–175CrossRefGoogle Scholar
  30. Hari R (2006) Action–perception connection and the cortical mu rhythm. Prog Brain Res 159:253–260CrossRefGoogle Scholar
  31. Hickok G (2012) Computational neuroanatomy of speech production. Nat Rev Neurosci 13:135–145.  https://doi.org/10.1038/nrn3158 CrossRefPubMedPubMedCentralGoogle Scholar
  32. Hickok G, Poeppel D (2007) The cortical organization of speech processing. Nat Rev Neurosci 15:393–402CrossRefGoogle Scholar
  33. Hickok G, Buchsbaum B, Humphries H, Muftuler (2009) Auditory-motor interaction revealed by fmri: speech, music, and working memory in area Spt. J Cog Neuroci 15:673–682CrossRefGoogle Scholar
  34. Hickok G, Houde J, Rong F (2011) Sensorimotor integration in speech processing: computational basis and neural organization. Neuron 69:407–422CrossRefGoogle Scholar
  35. Hipp JF, Engel AK, Siegel M (2011) Oscillatory synchronization in large-scale cortical networks predicts perception. Neuron 69:387–396.  https://doi.org/10.1016/j.neuron.2010.12.027 CrossRefPubMedGoogle Scholar
  36. Hochberg Y, Benjamini Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 57:289–300.  https://doi.org/10.2307/2346101 CrossRefGoogle Scholar
  37. Houde JF, Nagarajan SS (2011) Speech production as state feedback control. Front Hum Neurosci 5:82.  https://doi.org/10.3389/fnhum.2011.00082 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Jenson D, Bowers AL, Harkrider AW et al (2014a) Temporal dynamics of sensorimotor integration in speech perception and production: independent component analysis of EEG data. Front Psychol 5:1–17.  https://doi.org/10.3389/fpsyg.2014.00656 CrossRefGoogle Scholar
  39. Jenson D, Harkrider AW, Thornton D et al (2015a) Auditory cortical deactivation during speech production and following speech perception: an EEG investigation of the temporal dynamics of the auditory alpha rhythm. Front Hum Neurosci.  https://doi.org/10.3389/fnhum.2015.00534 CrossRefPubMedPubMedCentralGoogle Scholar
  40. Jenson D, Reilly KJ, Harkrider AW, Thornton D, Saltuklaroglu T (2018) Trait related sensorimotor deficits in people who stutter: an EEG investigation of μ rhythm dynamics during spontaneous fluency. Neuroimage Clin 19:690–702CrossRefGoogle Scholar
  41. Kittilstved T, Reilly KJ, Harkrider AW, Casenhiser D, Thornton D, Jenson DE, Hedinger T, Bowers AL, Saltuklaroglu T (2018) The effects of fluency enhancing conditions on sensorimotor control of speech in typically fluent speakers: an EEG mu rhythm study. Front Hum Neurosci 12:126CrossRefGoogle Scholar
  42. Kingyon J, Behroozmand R, Kelley R, Oya H, Kawasaki H, Narayanan N, Greenlee J (2015) High-gamma band fronto-temporal coherence as a measure of functional connectivity in speech motor control. Neuroscience 305:15–25CrossRefGoogle Scholar
  43. Kort NS, Cuesta P, Houde JF, Nagarajan SS (2016) Bihemispheric network dynamics coordinating vocal feedback control. Hum Brain Mapp 37(4):1474–1485CrossRefGoogle Scholar
  44. Krippendorff K (2013) Content analysis: an introduction to its methodology. Sage, Thousand OaksGoogle Scholar
  45. Lee T, Girolami M, Sejnowski T (1999) Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural Comput 11:417–441CrossRefGoogle Scholar
  46. MacNeilage P (1998) The frame/content theory of evolution of speech production. Behav Brain Sci 21:499–546PubMedGoogle Scholar
  47. Makeig S, Debener S, Onton J, Delorme A (2004) Mining event-related brain dynamics. Trends Cognit Sci 8:204–210CrossRefGoogle Scholar
  48. Murakami T, Kell C, Restle J, Ugawa Y, Ziemann U (2015) Left dorsal speech stream components and their contribution to phonological processing. J Neurosci 35:1411–1422CrossRefGoogle Scholar
  49. Murphy K, Corfield DR, Guz A et al (1997) Cerebral areas associated with motor control of speech in humans. J Appl Physiol 83:1438–1447CrossRefGoogle Scholar
  50. Oldfield R (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9:97–113CrossRefGoogle Scholar
  51. Oostenveld TF, Oostendorp (2002) Validating the boundary element method for forward and inverse EEG computations in the presence of a hole in the skull. Hum Brain Map 17:179–192CrossRefGoogle Scholar
  52. Pei X, Barbour DL, Leuthardt EC, Schalk G (2011a) Decoding vowels and consonants in spoken and imagined words using electrocorticographic signals in humans. J Neural Eng 8:46028.  https://doi.org/10.1088/1741-2560/8/4/046028 CrossRefGoogle Scholar
  53. Pei X, Leuthardt EC, Gaona CM et al (2011b) Spatiotemporal dynamics of electrocorticographic high gamma activity during overt and covert word repetition. Neuroimage 54:2960–2972.  https://doi.org/10.1016/j.neuroimage.2010.10.029 CrossRefPubMedGoogle Scholar
  54. Pesaran B, Nelson MJ, Andersen RA (2008) Free choice activates a decision circuit between frontal and parietal cortex. Nature 453:406–409.  https://doi.org/10.1038/nature06849 CrossRefPubMedPubMedCentralGoogle Scholar
  55. Price CJ (2012) A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading. Neuroimage 62:816–847CrossRefGoogle Scholar
  56. Rauschecker J, Scott S (2009) Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing. Nature Neurosci 12:718CrossRefGoogle Scholar
  57. Saalmann Y, Pigarev I, Vidyasagar T (2007) Neural mechanisms of visual attention: how top-down feedback highlights relevant locations. Science 316:1612–1614CrossRefGoogle Scholar
  58. Saltuklaroglu T, Harkrider A, Thornton D, Jenson D (2017) EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adultsGoogle Scholar
  59. Sengupta R, Nasir SM (2015) Redistribution of neural phase coherence reflects establishment of feedforward map in speech motor adaptation. J Neurophysiol 113:2471–2479.  https://doi.org/10.1152/jn.00731.2014 CrossRefPubMedPubMedCentralGoogle Scholar
  60. Sengupta R, Nasir SM (2016) Anomaly in neural phase coherence accompanies reduced sensorimotor integration in adults who stutter. Neuropsychologia 93:242–250CrossRefGoogle Scholar
  61. Sengupta R, Shah S, Loucks T, Pelczarski K, Yaruss S, Gore K, Nasir S (2017) Cortical dynamics of disfluency in adults who stutter. Physiol Rep 5:e13194.  https://doi.org/10.1481/phy2.13194 CrossRefPubMedPubMedCentralGoogle Scholar
  62. Shuster LI, Lemieux SK (2005) An fMRI investigation of covertly and overtly produced mono- and multisyllabic words. Brain Lang 93:20–31.  https://doi.org/10.1016/j.bandl.2004.07.007 CrossRefPubMedGoogle Scholar
  63. Siegel M, Donner TH, Oostenveld R et al (2008) Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron 60:709–719.  https://doi.org/10.1016/j.neuron.2008.09.010 CrossRefPubMedGoogle Scholar
  64. Siegel M, Donner T, Engel AK (2012) Spectral fingerprints of large-scale neuronal interactions. Nat Rev Neuro 13:121–131CrossRefGoogle Scholar
  65. Simmonds A, Leech R, Colliins C, Redjep O, Wise RJ (2014) Sensory-motor integration during speech production localizes to both the left and right plana temporale. J Neuroci 34:12963–12972Google Scholar
  66. Stepp C (2012) Surface electromyography for speech and swallowing systems: measurement, analysis, and interpretation. J Speech Lang Hear Res 55:1232–1247.  https://doi.org/10.1044/1092-4388(2011/11-0214)a CrossRefPubMedGoogle Scholar
  67. Tian X, Poeppel D (2012) Mental imagery of speech: linking motor and perceptual systems through internal simulation and estimation. Front Hum Neurosci 6:314.  https://doi.org/10.3389/fnhum.2012.00314 CrossRefPubMedPubMedCentralGoogle Scholar
  68. Tremblay P, Small S (2011) On the context dependent nature of the contribution of the ventral premotor cortex to speech perception. Neuroimage 50:1561–1571CrossRefGoogle Scholar
  69. Viola F, Thorn J, Edmonds B et al (2009) Semi-automatic identification of independent components representing EEG artifact. Clin Neurophys 120:868–877CrossRefGoogle Scholar
  70. Wang J, Mathalon DH, Roach BJ et al (2014) Action planning and predictive coding when speaking. Neuroimage 91:91–98.  https://doi.org/10.1016/j.neuroimage.2014.01.003 CrossRefPubMedPubMedCentralGoogle Scholar
  71. Winkler I, Brandl S, Horn F et al (2014) Robust artifactual independent component classification for BCI practitioners. J Neural Eng 11:35013.  https://doi.org/10.1088/1741-2560/11/3/035013 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Communication Disorders, Epley Center for Health ProfessionsUniversity of ArkansasFayettevilleUSA
  2. 2.Department of Audiology and Speech-PathologyUniversity of Tennessee Health Science CenterKnoxvilleUSA
  3. 3.Department of Speech and Hearing Sciences, Elson S. Floyd College of MedicineWashington State UniversitySpokaneUSA
  4. 4.Department of Hearing, Speech, and Language SciencesGallaudet UniversityWashingtonUSA

Personalised recommendations