Developing and Applying a QEEG-Informed Transcranial Electrical Stimulation Protocol to Remediate Stuttering in Adults Who Stutter

Authors

  • Masoumeh Bayat Geriatric Mental Health Research Center, School of Behavioral Sciences and Mental Health, Iran University of Medical Sciences, Tehran, Iran
  • Reza Boostani Head of Biomedical Engineering Group, Faculty of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
  • Mohammadreza Pirmoradi Department of Clinical Psychology, School of Behavioral Sciences and Mental Health, Iran University of Medical Sciences, Tehran, Iran
  • Malihe Sabeti Department of Computer Engineering, Islamic Azad University, North-Tehran Branch, Tehran, Iran
  • Fariba Yadegari Department of Speech and Language Pathology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
  • Niloofar Fallahinia Research Center for Bhavioral and Cognitive Sciences, Tehran University of Medical Sciences
  • Mohammad Nami Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran

DOI:

https://doi.org/10.15540/nr.13.1.20

Keywords:

QEEG, stuttering, individualized tDCS, power spectrum, phase coherence

Abstract

Introduction. This study investigated whether personalized transcranial direct current stimulation (tDCS) protocols informed by quantitative EEG (qEEG) patterns could enhance treatment outcomes in adults who stutter (AWS), addressing individual variability in neural activity. Methods. Twenty male AWS participated in a double-blind, randomized controlled trial. EEG signals were recorded during speech tasks to differentiate neural substrates of fluent and stuttered speech. Over 10 days, participants received 10 sessions of speech therapy combined with tDCS. The experimental group received personalized tDCS (2 mA for 25 min per session) targeting regions identified through qEEG, while the control group received standard stimulation over FC5. Behavioral outcomes (SSI-4 scores) and EEG metrics were compared pretreatment, posttreatment, and at 3-month follow-up using repeated-measures ANOVA. Results. Both groups exhibited significant reductions in stuttering severity posttreatment. However, the study group maintained greater fluency at follow-up (p < .001). EEG analysis revealed that the study group demonstrated enhanced delta power in the FC5, reduced phase coherence in motor-auditory-somatosensory networks, and greater suppression of high-frequency bands in the personalized group. Conclusion. Personalized, qEEG-informed tDCS protocols yielded more sustainable fluency improvements than conventional tDCS, highlighting the potential of individualized neuromodulation strategies for treating stuttering.

References

Ackermann, H. (2008). Cerebellar contributions to speech production and speech perception: Psycholinguistic and neurobiological perspectives. Trends in Neurosciences, 31(6), 265–272. https://doi.org/10.1016/j.tins.2008.02.011

Al-Fahoum, A. S., & Al-Fraihat, A. A. (2014). Methods of EEG signal features extraction using linear analysis in frequency and time-frequency domains. International Scholarly Research Notices, 2014(1), Article 730218. https://doi.org /10.1155/2014/730218

Bakhtiar, M., Wong, M. N., Shum, H. Y., & Lam, C. K. (2023). The effect of transcranial direct current stimulation on stuttering: A preliminary report. Brain Stimulation, 16(1), Article P227. https://doi.org/10.1016/j.brs.2023.01.332

Bartolo, R., Prado, L., & Merchant, H. (2014). Information processing in the primate basal ganglia during sensory-guided and internally driven rhythmic tapping. The Journal of Neuroscience, 34(11), 3910–3923. https://doi.org/10.1523 /jneurosci.2679-13.2014

Bashir, N., & Howell, P. (2015). tDCS and stuttering. Brain Stimulation, 8(2), Article P429. https://doi.org/10.1016 /j.brs.2015.01.369

Bastos, A. M., & Schoffelen, J.-M. (2016). A tutorial review of functional connectivity analysis methods and their interpretational pitfalls. Frontiers in Systems Neuroscience, 9, Article 175. https://doi.org/10.3389/fnsys.2015.00175

Bayat, M., Boostani, R., Sabeti, M., Yadegari, F., Pirmoradi, M., Rao, K., & Nami, M. (2024). Source localization and spectrum analyzing of EEG in stuttering state upon dysfluent utterances. Clinical EEG and Neuroscience, 55(3), 371–383. https://doi.org/10.1177/15500594221150638

Bayat, M., Boostani, R., Sabeti, M., Yadegari, F., Taghavi, M., Pirmoradi, M., Chakrabarti, P., & Nami, M. (2023). Speech related anxiety in adults who stutter. Journal of Psychophysiology, 37(1), 25–38. https://doi.org/10.1027 /0269-8803/a000305

Bell, A. J., & Sejnowski, T. J. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7(6), 1129–1159. https://doi.org/10.1162 /neco.1995.7.6.1129

Belyk, M., Kraft, S. J., & Brown, S. (2015). Stuttering as a trait or state–An ALE meta‐analysis of neuroimaging studies. European Journal of Neuroscience, 41(2), 275–284. https://doi.org/10.1111/ejn.12765

Bjekić, J., Živanović, M., Paunović, D., Vulić, K., Konstantinović, U., & Filipović, S. R. (2022). Personalized frequency modulated transcranial electrical stimulation for associative memory enhancement. Brain Sciences, 12(4), Article 472. https://doi.org/10.3390/brainsci12040472

Block, S., Onslow, M., Packman, A., & Dacakis, G. (2006). Connecting stuttering management and measurement: IV. Predictors of outcome for a behavioural treatment for stuttering. International Journal of Language & Communication Disorders, 41(4), 395–406. https://doi.org /10.1080/13682820600623853

Blomgren, M. (2013). Behavioral treatments for children and adults who stutter: A review. Psychology Research and Behavior Management, 6, 9–19. https://doi.org/10.2147 /PRBM.S31450

Bowers, A., Saltuklaroglu, T., Jenson, D., Harkrider, A., & Thornton, D. (2019). Power and phase coherence in sensorimotor mu and temporal lobe alpha components during covert and overt syllable production. Experimental Brain Research, 237(3), 705–721. https://doi.org/10.1007/s00221-018-5447-4

Brignell, A., Krahe, M., Downes, M., Kefalianos, E., Reilly, S., & Morgan, A. T. (2020). A systematic review of interventions for adults who stutter. Journal of Fluency Disorders, 64, Article 105766. https://doi.org/10.1016/j.jfludis.2020.105766

Busan, P., Moret, B., Masina, F., Del Ben, G., & Campana, G. (2021). Speech fluency improvement in developmental stuttering using non-invasive brain stimulation: Insights from available evidence. Frontiers in Human Neuroscience, 15, Article 662016. https://doi.org/10.3389/fnhum.2021.662016

Cai, H., Dong, J., Mei, L., Feng, G., Li, L., Wang, G., & Yan, H. (2024). Functional and structural abnormalities of the speech disorders: a multimodal activation likelihood estimation meta-analysis. Cerebral Cortex, 34(3), Article bhae075. https://doi.org/10.1093/cercor/bhae075

Cannon, R. L., Baldwin, D. R., Shaw, T. L., Diloreto, D. J., Phillips, S. M., Scruggs, A. M., & Riehl, T. C. (2012). Reliability of quantitative EEG (qEEG) measures and LORETA current source density at 30 days. Neuroscience Letters, 518(1), 27–31. https://doi.org/10.1016 /j.neulet.2012.04.035

Chang, S.-E., & Guenther, F. H. (2020). Involvement of the cortico-basal ganglia-thalamocortical loop in developmental stuttering. Frontiers in Psychology, 10, Article 3088. https://doi.org/10.3389/fpsyg.2019.03088

Chesters, J., Möttönen, R., & Watkins, K. E. (2018). Transcranial direct current stimulation over left inferior frontal cortex improves speech fluency in adults who stutter. Brain, 141(4), 1161–1171. https://doi.org/10.1093/brain/awy011

Chesters, J., Möttönen, R., & Watkins, K. E. (2021). Neural changes after training with transcranial direct current stimulation to increase speech fluency in adults who stutter. https://doi.org/10.31219/osf.io/8st3j

Chesters, J., Watkins, K. E., & Möttönen, R. (2017). Investigating the feasibility of using transcranial direct current stimulation to enhance fluency in people who stutter. Brain and Language, 164, 68–76. https://doi.org/10.1016/j.bandl.2016.10.003

Craig, A., Blumgart, E., & Tran, Y. (2009). The impact of stuttering on the quality of life in adults who stutter. Journal of Fluency Disorders, 34(2), 61–71. https://doi.org/10.1016 /j.jfludis.2009.05.002

Craig, A., Hancock, K., & Cobbin, D. (2002). Managing adolescents who relapse following treatment for stuttering. Asia Pacific Journal of Speech, Language and Hearing, 7(2), 79–91. https://doi.org/10.1179/136132802805576490

Cream, A., O'Brian, S., Onslow, M., Packman, A., & Menzies, R. (2009). Self‐modelling as a relapse intervention following speech‐restructuring treatment for stuttering. International Journal of Language & Communication Disorders, 44(5), 587–599. https://doi.org/10.1080/13682820802256973

Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. https://doi.org/10.1016 /j.jneumeth.2003.10.009

Diedrichsen, J., Ivry, R. B., & Pressing, J. (2003). Cerebellar and basal ganglia contributions to interval timing. In W. H. Meck (Ed.), Functional and neural mechanisms of interval timing (pp. 457–481). CRC Press.

DiLollo, A., Neimeyer, R. A., & Manning, W. H. (2002). A personal construct psychology view of relapse: Indications for a narrative therapy component to stuttering treatment. Journal of Fluency Disorders, 27(1), 19–42. https://doi.org/10.1016 /S0094-730X(01)00109-7

Ding, Y., Ou, Y., Su, Q., Pan, P., Shan, X., Chen, J., Liu, F., Zhang, Z., Zhao, J., & Guo, W. (2019). Enhanced global-brain functional connectivity in the left superior frontal gyrus as a possible endophenotype for schizophrenia. Frontiers in Neuroscience, 13, Article 145. https://doi.org/10.3389 /fnins.2019.00145

Etchell, A., Johnson, B., & Sowman, P. (2014a). Behavioral and multimodal neuroimaging evidence for a deficit in brain timing networks in stuttering: A hypothesis and theory. Frontiers in Human Neuroscience, 8, Article 467. https://doi.org/10.3389 /fnhum.2014.00467

Etchell, A. C., Civier, O., Ballard, K. J., & Sowman, P. F. (2017). A systematic literature review of neuroimaging research on developmental stuttering between 1995 and 2016. Journal of Fluency Disorders, 55, 6–45. https://doi.org/10.1016 /j.jfludis.2017.03.007

Etchell, A. C., Johnson, B. W., & Sowman, P. F. (2014b). Beta oscillations, timing, and stuttering. Frontiers in Human Neuroscience, 8, Article 1036. https://doi.org/10.3389 /fnhum.2014.01036

Farrahi, H., Gharraee, B., Oghabian, M. A., Pirmoradi, M. R., Najibi, S. M., & Batouli, S. A. H. (2021). Psychometric properties of the persian version of the Overall Anxiety Severity and Impairment Scale (OASIS). Iranian Journal of Psychiatry and Behavioral Sciences, 14(4), Article e100674. https://doi.org/10.5812/ijpbs.100674

Garnett, E. O. D., Chow, H. M., Choo, A. L., & Chang, S.-E. (2019). Stuttering severity modulates effects of non-invasive brain stimulation in adults who stutter. Frontiers in Human Neuroscience, 13, Article 411. https://doi.org/10.3389 /fnhum.2019.00411

Gaudet, I., Hüsser, A., Vannasing, P., & Gallagher, A. (2020). Functional brain connectivity of language functions in children revealed by EEG and MEG: A systematic review. Frontiers in Human Neuroscience, 14, Article 62. https://doi.org /10.3389/fnhum.2020.00062

Ghaderi, A. H., Andevari, M. N., & Sowman, P. F. (2018). Evidence for a resting state network abnormality in adults who stutter. Frontiers in Integrative Neuroscience, 12, Article 16. https://doi.org/10.3389/fnint.2018.00016

Giacometti, P., Perdue, K. L., & Diamond, S. G. (2014). Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain. Journal of Neuroscience Methods, 229, 84–96. https://doi.org/10.1016/j.jneumeth.2014.04.020

Giménez, M., Pujol, J., Ortiz, H., Soriano-Mas, C., López-Solà, M., Farré, M., Deus, J., Merlo-Pich, E., & Martín-Santos, R. (2012). Altered brain functional connectivity in relation to perception of scrutiny in social anxiety disorder. Psychiatry Research: Neuroimaging, 202(3), 214–223. https://doi.org /10.1016/j.pscychresns.2011.10.008

Ingham, R. J., Fox, P. T., Costello Ingham, J., & Zamarripa, F. (2000). Is overt stuttered speech a prerequisite for the neural activations associated with chronic developmental stuttering? Brain and Language, 75(2), 163–194. https://doi.org/10.1006 /brln.2000.2351

Jenson, D., Bowers, A. L., Harkrider, A. W., Thornton, D., Cuellar, M., & Saltuklaroglu, T. (2014). Temporal dynamics of sensorimotor integration in speech perception and production: Independent component analysis of EEG data. Frontiers in Psychology, 5, Article 656. https://doi.org/10.3389 /fpsyg.2014.00656

Jenson, D., Bowers, A. L., Hudock, D., & Saltuklaroglu, T. (2020). The application of EEG mu rhythm measures to neurophysiological research in stuttering. Frontiers in Human Neuroscience, 13, Article 458. https://doi.org/10.3389 /fnhum.2019.00458

Jenson, D., Reilly, K. J., Harkrider, A. W., Thornton, D., & Saltuklaroglu, T. (2018). Trait related sensorimotor deficits in people who stutter: An EEG investigation of μ rhythm dynamics during spontaneous fluency. NeuroImage: Clinical, 19, 690–702. https://doi.org/10.1016/j.nicl.2018.05.026

Jiang, J., Lu, C., Peng, D., Zhu, C., & Howell, P. (2012). Classification of types of stuttering symptoms based on brain activity. PLoS ONE, 7(6), Article e39747. https://doi.org/10.1371/journal.pone.0039747

Kaiser, D. A. (2007). What is quantitative EEG? Journal of Neurotherapy, 10(4), 37–52. https://doi.org/10.1300 /J184v10n04_05

Karsan, Ç., Özdemir, R. S., Bulut, T., & Hanoğlu, L. (2022). The effects of single-session cathodal and bihemispheric tDCS on fluency in stuttering. Journal of Neurolinguistics, 63, Article 101064. https://doi.org/10.1016/j.jneuroling.2022.101064

Keizer, A. W. (2019). Standardization and personalized medicine using quantitative EEG in clinical settings. Clinical EEG and Neuroscience, 52(2), 82–89. https://doi.org/10.1177 /1550059419874945

Kell, C. A., Neumann, K., Behrens, M., von Gudenberg, A. W., & Giraud, A.-L. (2018). Speaking-related changes in cortical functional connectivity associated with assisted and spontaneous recovery from developmental stuttering. Journal of Fluency Disorders, 55, 135–144. https://doi.org/10.1016 /j.jfludis.2017.02.001

Korzeczek, A., Neef, N. E., Steinmann, I., Paulus, W., & Sommer, M. (2022). Stuttering severity relates to frontotemporal low-beta synchronization during pre-speech preparation. Clinical Neurophysiology, 138, 84–96. https://doi.org/10.1016 /j.clinph.2022.03.010

Korzeczek, A., Primaßin, A., Wolff von Gudenberg, A., Dechent, P., Paulus, W., Sommer, M., & Neef, N. E. (2021). Fluency shaping increases integration of the command-to-execution and the auditory-to-motor pathways in persistent developmental stuttering. NeuroImage, 245, Article 118736. https://doi.org/10.1016/j.neuroimage.2021.118736

Kuremoto, T., Baba, Y., Obayashi, M., Mabu, S., & Kobayashi, K. (2018). Enhancing EEG signals recognition using roc curve. Journal of Robotics, Networking and Artificial Life, 4(4), 283–286. https://doi.org/10.2991/jrnal.2018.4.4.5

Kuremoto, T., Baba, Y., Obayashi, M., Mabu, S., & KobayashiI, K. (2017). A method of feature extraction for EEG signals recognition using ROC curve. Spectrum, 22(1), 654–657. https://doi.org/10.5954/ICAROB.2017.OS12-2

Lu, C., Chen, C., Ning, N., Ding, G., Guo, T., Peng, D., Yang, Y., Li, K., & Lin, C. (2010). The neural substrates for atypical planning and execution of word production in stuttering. Experimental Neurology, 221(1), 146–156. https://doi.org /10.1016/j.expneurol.2009.10.016

Lu, C., Zheng, L., Long, Y., Yan, Q., Ding, G., Liu, L., Peng, D., & Howell, P. (2017). Reorganization of brain function after a short-term behavioral intervention for stuttering. Brain and Language, 168, 12–22. https://doi.org/10.1016 /j.bandl.2017.01.001

Ma, Y., Gong, A., Nan, W., Ding, P., Wang, F., & Fu, Y. (2023). Personalized brain–computer interface and its applications. Journal of Personalized Medicine, 13(1), Article 46. https://doi.org/10.3390/jpm13010046

Mastakouri, A.-A., Weichwald, S., Özdenizci, O., Meyer, T., Schölkopf, B., & Grosse-Wentrup, M. (2017). Personalized brain-computer interface models for motor rehabilitation. IEEE international conference on systems, man, and cybernetics. https://doi.org/10.48550/arXiv.1705.03259

Mersov, A., Cheyne, D., Jobst, C., & De Nil, L. (2018). A preliminary study on the neural oscillatory characteristics of motor preparation prior to dysfluent and fluent utterances in adults who stutter. Journal of Fluency Disorders, 55, 145–155. https://doi.org/10.1016/j.jfludis.2017.05.003

Mersov, A.-M., Jobst, C., Cheyne, D. O., & De Nil, L. (2016). Sensorimotor oscillations prior to speech onset reflect altered motor networks in adults who stutter. Frontiers in Human Neuroscience, 10, Article 443. https://doi.org/10.3389 /fnhum.2016.00443

Miller, B., & Guitar, B. (2009). Long-term outcome of the lidcombe program for early stuttering intervention. American Journal of Speech-Language Pathology, 18(1), 42–49. https://doi.org /10.1044/1058-0360(2008/06-0069)

Mizuno, A., Villalobos, M. E., Davies, M. M., Dahl, B. C., & Müller, R.-A. (2006). Partially enhanced thalamocortical functional connectivity in autism. Brain Research, 1104(1), 160–174. https://doi.org/10.1016/j.brainres.2006.05.064

Mock, J. R., Foundas, A. L., & Golob, E. J. (2016). Cortical activity during cued picture naming predicts individual differences in stuttering frequency. Clinical Neurophysiology, 127(9), 3093–3101. https://doi.org/10.1016/j.clinph.2016.06.005

Moein, N., Mohamadi, R., Rostami, R., Nitsche, M., Zomorrodi, R., & Ostadi, A. (2022). Investigation of the effect of delayed auditory feedback and transcranial direct current stimulation (DAF-tDCS) treatment for the enhancement of speech fluency in adults who stutter: A randomized controlled trial. Journal of Fluency Disorders, 72, Article 105907. https://doi.org/10.1016 /j.jfludis.2022.105907

Mognon, A., Jovicich, J., Bruzzone, L., & Buiatti, M. (2011). ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features. Psychophysiology, 48(2), 229–240. https://doi.org/10.1111/j.1469-8986.2010.01061.x

Neumann, K., Euler, H. A., Kob, M., Wolff von Gudenberg, A., Giraud, A.-L., Weissgerber, T., & Kell, C. A. (2018). Assisted and unassisted recession of functional anomalies associated with dysprosody in adults who stutter. Journal of Fluency Disorders, 55, 120–134. https://doi.org/10.1016 /j.jfludis.2017.09.003

Olbrich, S., Jödicke, J., Sander, C., Himmerich, H., & Hegerl, U. (2011). ICA-based muscle artefact correction of EEG data: What is muscle and what is brain?: Comment on McMenamin et al. NeuroImage, 54(1), 1–3. https://doi.org/10.1016 /j.neuroimage.2010.04.256

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

Onslow, M., Costa, L., Andrews, C., Harrison, E., & Packman, A. (1996). Speech outcomes of a prolonged-speech treatment for stuttering. Journal of Speech, Language, and Hearing Research, 39(4), 734–749. https://doi.org/10.1044 /jshr.3904.734

Paik, N.-J. (2015). Applications of neuromodulation in neurology and neurorehabilitation. In Textbook of neuromodulation (pp. 211–245). Springer.

Paulus, W., Peterchev, A. V., & Ridding, M. (2013). Chapter 27 - Transcranial electric and magnetic stimulation: Technique and paradigms. In A. M. Lozano & M. Hallett (Eds.), Handbook of clinical neurology (Vol. 116, pp. 329–342). Elsevier.

Piai, V., & Zheng, X. (2019). Chapter Eight - Speaking waves: Neuronal oscillations in language production. In K. D. Federmeier (Ed.), Psychology of learning and motivation (Vol. 71, pp. 265–302). Academic Press.

Popa, L. L., Dragos, H., Pantelemon, C., Rosu, O. V., & Strilciuc, S. (2020). The role of quantitative EEG in the diagnosis of neuropsychiatric disorders. Journal of Medicine and Life, 13(1), 8–15. https://doi.org/10.25122/jml-2019-0085

Riley, G. D., & Bakker, K. (2009). Stuttering severity instrument: SSI-4. Pro-Ed.

Rimmele, J. M., Gross, J., Molholm, S., & Keitel, A. (2018). Editorial: Brain oscillations in human communication. Frontiers in Human Neuroscience, 12, Article 39. https://doi.org/10.3389/fnhum.2018.00039

Saltuklaroglu, T., Harkrider, A. W., Thornton, D., Jenson, D., & Kittilstved, T. (2017). EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults. NeuroImage, 153, 232–245. https://doi.org/10.1016 /j.neuroimage.2017.04.022

Sengupta, R., & Nasir, S. M. (2016). The predictive roles of neural oscillations in speech motor adaptability. Journal of Neurophysiology, 115(5), 2519–2528. https://doi.org/10.1152 /jn.00043.2016

Sengupta, R., Shah, S., Loucks, T. M. J., Pelczarski, K., Scott Yaruss, J., Gore, K., & Nasir, S. M. (2017). Cortical dynamics of disfluency in adults who stutter. Physiological Reports, 5(9), Article e13194. https://doi.org/10.14814/phy2.13194

Smith, A., & Weber, C. (2016). Childhood stuttering: Where are we and where are we going? Seminars in Speech and Language, 37(4), 291–297. https://doi.org/10.1055/s-0036-1587703

Taherifard, M., Saeidmanesh, M., & Azizi, M. (2021). The effectiveness of transcranial direct current stimulation (tDCS) on the anxiety and severity of stuttering in adolescents aged 15 to 18. Journal of Research in Rehabilitation Sciences, 16, 224–231. https://doi.org/10.22122/JRRS.V16I0.3605

Tahmasebi, N., Shafie, B., Karimi, H., & Mazaheri, M. (2018). A Persian-version of the stuttering severity instrument-version four (SSI-4): How the new additions to SSI-4 complement its stuttering severity score? Journal of Communication Disorders, 74, 1–9. https://doi.org/10.1016 /j.jcomdis.2018.04.005

Tezel-Bayraktaroglu, O., Bayraktaroglu, Z., Demirtas-Tatlidede, A., Demiralp, T., & Oge, A. E. (2020). Neuronavigated rTMS inhibition of right pars triangularis anterior in stuttering: Differential effects on reading and speaking. Brain and Language, 210, Article 104862. https://doi.org/10.1016 /j.bandl.2020.104862

Tian, X., & Poeppel, D. (2010). Mental imagery of speech and movement implicates the dynamics of internal forward models. Frontiers in Psychology, 1, Article 166. http://dx.doi.org/10.3389/fpsyg.2010.00166

Tian, X., & Poeppel, D. (2012). Mental imagery of speech: Linking motor and perceptual systems through internal simulation and estimation. Frontiers in Human Neuroscience, 6, Article 314. http://dx.doi.org/10.3389/fnhum.2012.00314

Vanhoutte, S., Cosyns, M., van Mierlo, P., Batens, K., Corthals, P., De Letter, M., Van Borsel, J., & Santens, P. (2016). When will a stuttering moment occur? The determining role of speech motor preparation. Neuropsychologia, 86, 93–102. https://doi.org/10.1016/j.neuropsychologia.2016.04.018

Wells, B. G., & Moore, W. H., Jr. (1990). EEG alpha asymmetries in stutterers and non-stutterers: Effects of linguistic variables on hemispheric processing and fluency. Neuropsychologia, 28(12), 1295–1305. https://doi.org/10.1016/0028-3932(90)90045-p

Woods, A. J., Antal, A., Bikson, M., Boggio, P. S., Brunoni, A. R., Celnik, P., Cohen, L. G., Fregni, F., Herrmann, C. S., Kappenman, E. S., Knotkova, H., Liebetanz, D., Miniussi, C., Miranda, P. C., Paulus, W., Priori, A., Reato, D., Stagg, C., Wenderoth, N., & Nitsche, M. A. (2016). A technical guide to tDCS, and related non-invasive brain stimulation tools. Clinical Neurophysiology, 127(2), 1031–1048. https://doi.org /10.1016/j.clinph.2015.11.012

Wymbs, N. F., Ingham, R. J., Ingham, J. C., Paolini, K. E., & Grafton, S. T. (2013). Individual differences in neural regions unctionally related to real and imagined stuttering. Brain and Language, 124(2), 153–164. https://doi.org/10.1016 /j.bandl.2012.11.013

Yada, Y., Tomisato, S., & Hashimoto, R.-i. (2019). Online cathodal transcranial direct current stimulation to the right homologue of Broca's area improves speech fluency in people who stutter. Psychiatry and Clinical Neurosciences, 73(2), 63–69. https://doi.org/10.1111/pcn.12796

Yairi, E., & Carrico, D. M. (1992). Early childhood stuttering. American Journal of Speech-Language Pathology, 1(3), 54–62. https://doi.org/10.1044/1058-0360.0103.54

Yaruss, J. S. (2010). Assessing quality of life in stuttering treatment outcomes research. Journal of Fluency Disorders, 35(3), 190–202. https://doi.org/10.1016/j.jfludis.2010.05.010

Yordanova, J., Falkenstein, M., Hohnsbein, J., & Kolev, V. (2004). Parallel systems of error processing in the brain. NeuroImage, 22(2), 590–602. https://doi.org/10.1016 /j.neuroimage.2004.01.040

Yordanova, J., Falkenstein, M., & Kolev, V. (2024). Motor oscillations reveal new correlates of error processing in the human brain. Scientific Reports, 14, Article 5624. https://doi.org/10.1038/s41598-024-56223-x

Zhang, N., Yin, Y., Jiang, Y., & Huang, C. (2022). Reinvestigating the neural bases involved in speech production of stutterers: An ALE meta-analysis. Brain Sciences, 12(8), Article 1030. https://doi.org/10.3390/brainsci12081030

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2026-03-31

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