When does speech planning rely on motor routines? ERP comparison of speech and non-speech from childhood to adulthood

References

• Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412. https://doi.org/10.1016/j.jml.2007.12.005
   Web of Science ®Google Scholar
• Ballard, K. J., Robin, D. A., & Folkins, J. W. (2003). An integrative model of speech motor control: A response to Ziegler. Aphasiology, 17(1), 37–48. https://doi.org/10.1080/729254889
   Web of Science ®Google Scholar
• Basilakos, A., Smith, K. G., Fillmore, P., Fridriksson, J., & Fedorenko, E. (2017). Functional characterization of the human speech articulation network. Cerebral Cortex, 28(5), 1816–1830. https://doi.org/10.1093/cercor/bhx100
   Web of Science ®Google Scholar
• Bonilha, L., Moser, D., Rorden, C., Baylis, G. C., & Fridriksson, J. (2006). Speech apraxia without oral apraxia: Can normal brain function explain the physiopathology? Neuroreport, 17(10), 1027–1031. https://doi.org/10.1097/01.wnr.0000223388.28834.50
   PubMed Web of Science ®Google Scholar
• Brunet, D., Murray, M. M., & Michel, C. M. (2011). Spatiotemporal analysis of multichannel EEG: CARTOOL. Computational Intelligence and Neuroscience, 2011, 1. https://doi.org/10.1155/2011/813870
   PubMed Web of Science ®Google Scholar
• Chang, S.-E., Kenney, M. K., Loucks, T. M., Poletto, C. J., & Ludlow, C. L. (2009). Common neural substrates support speech and non-speech vocal tract gestures. Neuroimage, 47(1), 314–325. https://doi.org/10.1016/j.neuroimage.2009.03.032
   PubMed Web of Science ®Google Scholar
• Chauveau, N., Franceries, X., Doyon, B., Rigaud, B., Morucci, J. P., & Celsis, P. (2004). Effects of skull thickness, anisotropy, and inhomogeneity on forward EEG/ERP computations using a spherical three-dimensional resistor mesh model. Human Brain Mapping, 21(2), 86–97. https://doi.org/10.1002/hbm.10152
   PubMed Web of Science ®Google Scholar
• Cheng, H. Y., Murdoch, B. E., & Goozée, J. V. (2007). Temporal features of articulation from childhood to adolescence: An electropalatographic investigation. Clinical Linguistics & Phonetics, 21(6), 481–499. https://doi.org/10.1080/02699200701325043
   PubMed Web of Science ®Google Scholar
• Frossard, J., & Renaud, O. (2021). permuco4brain: Massively Univariate Tests on Several Signals in Space [R package version 0.2.0]. https://github.com/jaromilfrossard/permuco4brain
   Google Scholar
• Frossard, J., & Renaud, O. (2022). The cluster depth tests: Toward point-wise strong control of the family-wise error rate in massively univariate tests with application to M/EEG. Neuroimage, 247, 118824. https://doi.org/10.1016/j.neuroimage.2021.118824
   PubMed Web of Science ®Google Scholar
• Green, J. R., Moore, C. A., Higashikawa, M., & Steeve, R. W. (2000). The physiologic development of speech motor control: Lip and jaw coordination. Journal of Speech, Language, and Hearing Research, 43(1), 239–255. https://doi.org/10.1044/jslhr.4301.239
   PubMed Web of Science ®Google Scholar
• Guenther, F. H. (2016). Neural control of speech. Mit Press.
   Google Scholar
• Halle, M., Hughes, G. W., & Radley, J. P. (1957). Acoustic properties of stop consonants. The Journal of the Acoustical Society of America, 29(1), 107–116. https://doi.org/10.1121/1.1908634
   Web of Science ®Google Scholar
• Horwitz, B., Amunts, K., Bhattacharyya, R., Patkin, D., Jeffries, K., Zilles, K., & Braun, A. R. (2003). Activation of Broca’s area during the production of spoken and signed language: A combined cytoarchitectonic mapping and PET analysis. Neuropsychologia, 41(14), 1868–1876. https://doi.org/10.1016/S0028-3932(03)00125-8
   PubMed Web of Science ®Google Scholar
• Jaeger, T. F. (2008). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59(4), 434–446. https://doi.org/10.1016/j.jml.2007.11.007
   PubMed Web of Science ®Google Scholar
• Jouen, A.-L., Lancheros, M., & Laganaro, M. (2021). Microstate ERP analyses to pinpoint the articulatory onset in speech production. Brain Topography, 34(1), 29–40. https://doi.org/10.1007/s10548-020-00803-3
   PubMed Web of Science ®Google Scholar
• Kawamoto, A. H., Liu, Q., Mura, K., & Sanchez, A. (2008). Articulatory preparation in the delayed naming task. Journal of Memory and Language, 58(2), 347–365. https://doi.org/10.1016/j.jml.2007.06.002
   Web of Science ®Google Scholar
• Kent, R. D. (2015). Nonspeech oral movements and oral motor disorders: A narrative review. American Journal of Speech-Language Pathology, 24(4), 763–789. https://doi.org/10.1044/2015_AJSLP-14-0179
   PubMed Web of Science ®Google Scholar
• Koenig, T., Kottlow, M., Stein, M., & Melie-García, L. (2011). Ragu: A free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics. Computational Intelligence and Neuroscience, 2011, 1. https://doi.org/10.1155/2011/938925
   PubMed Web of Science ®Google Scholar
• Koenig, T., & Melie-García, L. (2010). A method to determine the presence of averaged event-related fields using randomization tests. Brain Topography, 23(3), 233–242. https://doi.org/10.1007/s10548-010-0142-1
   PubMed Web of Science ®Google Scholar
• Koenig, T., Stein, M., Grieder, M., & Kottlow, M. (2014). A tutorial on data-driven methods for statistically assessing ERP topographies. Brain Topography, 27(1), 72–83. https://doi.org/10.1007/s10548-013-0310-1
   PubMed Web of Science ®Google Scholar
• Kröger, B. J., Kannampuzha, J., & Neuschaefer-Rube, C. (2009). Towards a neurocomputational model of speech production and perception. Speech Communication, 51(9), 793–809. https://doi.org/10.1016/j.specom.2008.08.002
   Web of Science ®Google Scholar
• Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. (2017). Lmertest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. https://doi.org/10.18637/jss.v082.i13
   Web of Science ®Google Scholar
• Laganaro, M., & Alario, F.-X. (2006). On the locus of the syllable frequency effect in speech production. Journal of Memory and Language, 55(2), 178–196. https://doi.org/10.1016/j.jml.2006.05.001
   Web of Science ®Google Scholar
• Lancheros, M., Jouen, A., & Laganaro, M. (2020). Neural dynamics of speech and non-speech motor planning. Brain and Language, 203, 104742. https://doi.org/10.1016/j.bandl.2020.104742
   PubMed Web of Science ®Google Scholar
• Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 159–174. https://doi.org/10.2307/2529310
   PubMed Web of Science ®Google Scholar
• Levelt, W. J. (1993). Speaking: From intention to articulation (Vol. 1). MIT press.
   Google Scholar
• McLeod, S., & Crowe, K. (2018). Children's consonant acquisition in 27 languages: A cross-linguistic review. American Journal of Speech-Language Pathology, 27(4), 1546–1571. https://doi.org/10.1044/2018_AJSLP-17-0100
   PubMed Web of Science ®Google Scholar
• Mock, J. R., Foundas, A. L., & Golob, E. J. (2011). Modulation of sensory and motor cortex activity during speech preparation. European Journal of Neuroscience, 33(5), 1001–1011. https://doi.org/10.1111/j.1460-9568.2010.07585.x
   PubMed Web of Science ®Google Scholar
• Moser, D., Fridriksson, J., Bonilha, L., Healy, E. W., Baylis, G., Baker, J. M., & Rorden, C. (2009). Neural recruitment for the production of native and novel speech sounds. Neuroimage, 46(2), 549–557. https://doi.org/10.1016/j.neuroimage.2009.01.015
   PubMed Web of Science ®Google Scholar
• Namasivayam, A. K., Coleman, D., O’Dwyer, A., & Van Lieshout, P. (2020). Speech sound disorders in children: An articulatory phonology perspective. Frontiers in Psychology, 10. https://doi.org/10.3389/fpsyg.2019.02998
   PubMed Web of Science ®Google Scholar
• Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9(1), 97–113. https://doi.org/10.1016/0028-3932(71)90067-4
   PubMed Web of Science ®Google Scholar
• Parrell, B., Ramanarayanan, V., Nagarajan, S., & Houde, J. (2019). The FACTS model of speech motor control: Fusing state estimation and task-based control. PLoS Computational Biology, 15(9), e1007321. https://doi.org/10.1371/journal.pcbi.1007321
   PubMed Web of Science ®Google Scholar
• Perrin, F., Pernier, J., Bertnard, O., Giard, M., & Echallier, J. (1987). Mapping of scalp potentials by surface spline interpolation. Electroencephalography and Clinical Neurophysiology, 66(1), 75–81. https://doi.org/10.1016/0013-4694(87)90141-6
   PubMedGoogle Scholar
• Picton, T. W., & Taylor, M. J. (2007). Electrophysiological evaluation of human brain development. Developmental Neuropsychology, 31(3), 249–278. https://doi.org/10.1080/87565640701228732
   PubMed Web of Science ®Google Scholar
• Protopapas, A. (2007). Check vocal: A program to facilitate checking the accuracy and response time of vocal responses from DMDX. Behavior Research Methods, 39(4), 859–862. https://doi.org/10.3758/BF03192979
   PubMed Web of Science ®Google Scholar
• Qu, Y., Tan, M., & Kutner, M. H. (1996). Random effects models in latent class analysis for evaluating accuracy of diagnostic tests. Biometrics, 797–810. https://doi.org/10.2307/2533043
   PubMed Web of Science ®Google Scholar
• R Development Core Team. (2013). R: A language and environment for statistical computing.
   Google Scholar
• Sanders, E. (1972). When are speech sounds learned. Journal of Speech and Hearing Disorders, 37(1), 55–63. In. https://doi.org/10.1044/jshd.3701.55
   PubMedGoogle Scholar
• Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82(4), 225. https://doi.org/10.1037/h0076770
   Web of Science ®Google Scholar
• Schmidt, R. A. (1976). The schema as a solution to some persistent problems in motor learning theory. In R. A. Schmidt (Ed.), Motor control (pp. 41–65). Elsevier.
   Google Scholar
• Schneider, W., Eschman, A., & Zuccolotto, A. (2002). E-Prime: User's guide. Psychology Software Incorporated.
   Google Scholar
• Segawa, J. A., Tourville, J. A., Beal, D. S., & Guenther, F. H. (2015). The neural correlates of speech motor sequence learning. Journal of Cognitive Neuroscience, 27(4), 819–831. https://doi.org/10.1162/jocn_a_00737
   PubMed Web of Science ®Google Scholar
• Smith, A. (2006). Speech motor development: Integrating muscles, movements, and linguistic units. Journal of Communication Disorders, 39(5), 331–349. https://doi.org/10.1016/j.jcomdis.2006.06.017
   PubMed Web of Science ®Google Scholar
• Smith, A., & Goffman, L. (1998). Stability and patterning of speech movement sequences in children and adults. Journal of Speech, Language, and Hearing Research, 41(1), 18–30. https://doi.org/10.1044/jslhr.4101.18
   PubMed Web of Science ®Google Scholar
• Smith, A., & Zelaznik, H. N. (2004). Development of functional synergies for speech motor coordination in childhood and adolescence. Developmental Psychobiology, 45(1), 22–33. https://doi.org/10.1002/dev.20009
   PubMed Web of Science ®Google Scholar
• Smith, S. M., & Nichols, T. E. (2009). Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage, 44(1), 83–98. https://doi.org/10.1016/j.neuroimage.2008.03.061
   PubMed Web of Science ®Google Scholar
• Tilsen, S., Spincemaille, P., Xu, B., Doerschuk, P., Luh, W.-M., Feldman, E., & Wang, Y. (2016). Anticipatory posturing of the vocal tract reveals dissociation of speech movement plans from linguistic units. PloS one, 11(1), e0146813. https://doi.org/10.1371/journal.pone.0146813
   PubMed Web of Science ®Google Scholar
• Walsh, B., & Smith, A. (2002). Articulatory movements in adolescents.
   Google Scholar
• Wilks, S. S. (1963). Multivariate statistical outliers. Sankhyā: The Indian Journal of Statistics, Series A (1961-2002), 25(4), 407–426. http://www.jstor.org/stable/25049292
   Google Scholar
• Wirth, M., Horn, H., Koenig, T., Razafimandimby, A., Stein, M., Mueller, T., Federspiel, A., Meier, B., Dierks, T., & Strik, W. (2008). The early context effect reflects activity in the temporo-prefrontal semantic system: Evidence from electrical neuroimaging of abstract and concrete word reading. Neuroimage, 42(1), 423–436. https://doi.org/10.1016/j.neuroimage.2008.03.045
   PubMed Web of Science ®Google Scholar
• Ziegler, W. (2003). To speak or not to speak: Distinctions between speech and nonspeech motor control. Aphasiology, 17(2), 99–105. https://doi.org/10.1080/729255218
   Web of Science ®Google Scholar