UDC

612.821+612.789

DOI

10.37482/2542-1298-Z001

Authors

Oleg M. Bakhtin* ORCID: 0000-0003-2164-7885
Elena M. Krivko** ORCID: 0000-0001-9003-4690
Valeriy N. Kiroy* ORCID: 0000-0003-3560-9935
*Research Technological Centre for Neurotechnology, Southern Federal University (Rostov-on-Don, Russian Federation)
**Academy of Biology and Biotechnology, Southern Federal University (Rostov-on-Don, Russian Federation)
Corresponding author: Elena Krivko, address: prosp. Stachki 194/1, Rostov-on-Don, 344090, Russian Federation; e-mail: ele5484@mail.ru

Abstract

As is known, inner speech is accompanied by involuntary activation of articulatory muscles, which can produce artifacts recorded in electroencephalogram (EEG). The latter is important to consider when developing communication and control systems based on brain-computer interface and EEG technology. In order to study electromyographic (EMG) correlates of inner speech, multichannel EEG was investigated within the framework of methodological approaches developed earlier (Kamavuako E.N. et al., 2018; Kiroy V.N. et al., 2015). The presence and severity of EMG artifacts in parallel EEG recordings were assessed using the correlation and cross-correlation analysis methods. It is shown that the correlation of EMG and EEG activity is higher in inner speech (compared to overt speech), which is indicated by greater correlation coefficients and maxima of cross-correlation functions / correlation and crosscorrelation coefficients. At the same time, in all cases the correlation stays in the region of low and very low values, without significantly affecting the characteristics of EEG patterns associated with the mechanisms of overt and covert speech. We believe that these differences are not particularly important for the identification and analysis of specific patterns of activity associated with perceptual or cognitive processes in the brain. However, they seem to be useful in practical terms to assess, at least, the presence / absence of inner speech, as well as indicate the existence of a deeper connection between the peripheral electromyographic manifestations of the inner (covert) speech and purely cerebral processes.
For citation: Bakhtin O.M., Krivko E.M., Kiroy V.N. Electromyographic Components Associated with Inner Speech. Journal of Medical and Biological Research, 2020, vol. 8, no. 2, pp. 111–120. DOI: 10.37482/2542-1298-Z001

Keywords

EEG activity, EMG activity, gamma range, correlation analysis, cross-correlation analysis, inner speech

References

1. Kiroi V.N., Vladimirskii B.M., Aslanyan E.V., Bakhtin O.M., Minyaeva N.R. Electrographic Correlates of Actual and Imagined Movements: Spectral Analysis. Neurosci. Behav. Physiol., 2012, vol. 42, no. 1, pp. 21–27.
2. Pasley B.N., David S.V., Mesgarani N., Flinker A., Shamma S.A., Crone N.E., Knight R.T., Chang E.F. Reconstructing Speech from Human Auditory Cortex. PLoS Biol., 2012, vol. 10, no. 1. Art. no. e1001251.
3. Kamavuako E.N., Sheikh U.A., Gilani S.O., Jamil M., Niazi I.K. Classification of Overt and Covert Speech for Near-Infrared Spectroscopy-Based Brain Computer Interface. Sensors (Basel), 2018, vol. 18, no. 9. Art. no. 2989. DOI: 10.3390/s18092989
4. Cooney C., Folli R., Coyle D. Mel Frequency Cepstral Coefficients Enhance Imagined Speech Decoding Accuracy from EEG. 2018 29th Irish Signals and Systems Conference. Belfast, 2018, pp. 1–7. DOI: 10.1109/ISSC.2018.8585291
5. Cooney C., Folli R., Coyle D. Neurolinguistics Research Advancing Development of a Direct-Speech BrainComputer Interface. iScience, 2018, vol. 8, pp. 103–125.
6. Brigham K., Kumar B.V.K. Imagined Speech Classification with EEG Signals for Silent Communication: A Preliminary Investigation into Synthetic Telepathy. IEEE, 2010, pp. 1–4. Available at: http://ieeexplore.ieee.org/lpdocs/ epic03/wrapper.htm?arnumber=5515807 (accessed: 12 May 2019).
7. Kiroy V.N., Bakhtin O.M., Minyaeva N.R., Lazurenko D.M., Aslanyan E.V., Kiroy R.I. Elektrograficheskie korrelyaty vnutrenney rechi [Electrographic Correlations of Inner Speech]. Zhurnal vysshey nervnoy deyatel’nosti, 2015, vol. 65, no. 5, pp. 616–625.
8. Martin S., Brunner P., Iturrate I., Millán J.R., Schalk G., Knight R.T., Pasley B.N. Word Pair Classification During Imagined Speech Using Direct Brain Recordings. Sci. Rep., 2016, vol. 6. Art. no. 25803.
9. Herff C., de Pesters A., Heger D., Brunner P., Schalk G., Schultz T. Towards Continuous Speech Recognition for BCI. Guger C., Allison B., Ushiba J. (eds.). Brain-Computer Interface Research: A State-of-the-Art Summary 5. Springer International Publishing, 2017, pp. 1–9.
10. Chen X., Wang Y., Nakanishi M., Gao X., Jung T.-P., Gao S. High-Speed Spelling with a Noninvasive Brain–Computer Interface. Proc. Natl. Acad. Sci. USA, 2015, vol. 112, no. 44, pp. E6058–E6067.
11. Iljina O., Derix J., Schirrmeister R.T., Schulze-Bonhage A., Auer P., Aertsen A., Ball T. Neurolinguistic and Machine-Learning Perspectives on Direct Speech BCIs for Restoration of Naturalistic Communication. Brain-Comput. Interfaces, 2017, vol. 4, no. 3, pp. 186–199.
12. Towle V.L., Yoon H.A., Castelle M., Edgar J.C., Biassou N.M., Frim D.M., Spire J.P., Kohrman M.H. ECoG Gamma Activity During a Language Task: Differentiating Expressive and Receptive Speech Areas. Brain, 2008, vol. 131, pt. 8, pp. 2013–2027.
13. Llorens A., Trébuchon A., Liégeois-Chauvel C., Alario F.-X. Intra-Cranial Recordings of Brain Activity During Language Production. Front. Psychol., 2011, vol. 2. Art. no. 375. DOI: 10.3389/fpsyg.2011.00375
14. Pei X., Leuthardt E.C., Gaona C.M., Brunner P., Wolpaw J.R., Schalk G. Spatiotemporal Dynamics of Electrocorticographic High Gamma Activity During Overt and Covert Word Repetition. NeuroImage, 2011, vol. 54, no. 4, pp. 2960–2972.
15. Pei X., Barbour D.L., Leuthardt E.C., Schalk G. Decoding Vowels and Consonants in Spoken and Imagined Words Using Electrocorticographic Signals in Humans. J. Neural Eng., 2011, vol. 8, no. 4. Art. no. 046028. DOI: 10.1088/1741-2560/8/4/046028
16. Sinai A., Bowers C.W., Crainiceanu C.M., Boatman D., Gordon B., Lesser R.P., Lenz F.A., Crone N.E. Electrocorticographic High Gamma Activity Versus Electrical Cortical Stimulation Mapping of Naming. Brain, 2005, vol. 128, pt. 7, pp. 1556–1570.
17. Cervenka M.C., Corines J., Boatman-Reich D.F., Eloyan A., Sheng X., Franaszczuk P.J., Crone N.E. Electrocorticographic Functional Mapping Identifies Human Cortex Critical for Auditory and Visual Naming. NeuroImage, 2013, vol. 69, pp. 267–276.
18. Crone N.E., Sinai A., Korzeniewska A. High Frequency Gamma Oscillations and Human Brain Mapping with Electrocorticography. Prog. Brain Res., 2006, vol. 159, pp. 275–295.
19. Crone N.E., Hao L., Hart J. Jr., Boatman D., Lesser R.P., Irizarry R., Gordon B. Electrocorticographic Gamma Activity During Word Production in Spoken and Sign Language. Neurology, 2001, vol. 57, no. 11, pp. 2045–2053.
20. Demandt E., Mehring C., Vogt K., Schulze-Bonhage A., Aertsen A., Ball T. Reaching Movement Onset- and End-Related Characteristics of EEG Spectral Power Modulations. Front. Neurosci., 2012, vol. 6. Art. no. 65. DOI: 10.3389/fnins.2012.00065
21. Muthukumaraswamy S.D. High-Frequency Brain Activity and Muscle Artifacts in MEG/EEG: A Review and Recommendations. Front. Hum. Neurosci., 2013, vol. 7. Art. no. 138. DOI: 10.3389/fnhum.2013.00138
22. Petersen S.E., Fox P.T., Posner M.I., Mintun M., Raichle M.E. Positron Emission Tomographic Studies of the Processing of Single Words. J. Cogn. Neurosci., 1989, vol. 1, no. 2, pp. 153–170.
23. Price C.J. A Review and Synthesis of the First 20 Years of PET and fMRI Studies of Heard Speech, Spoken Language and Reading. NeuroImage, 2012, vol. 62, no. 2, pp. 816–847.
24. Berwick R.C., Friederici A.D., Chomsky N., Bolhuis J.J. Evolution, Brain, and the Nature of Language. Trends Cogn. Sci., 2013, vol. 17, no. 2, pp. 89–98.
25. Gelfand S.A. Hearing: An Introduction to Psychological and Physiological Acoustics. New York, 1981. 392 p. (Russ. ed.: Gel’fand S.A. Slukh. Vvedenie v psikhologicheskuyu i fiziologicheskuyu akustiku. Moscow, 1984. 350 p.).
26. Criswell E. (ed.). Cram’s Introduction to Surface Electromyography. London, 2011. 412 p.