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Combining MEG with Real-time Measures of Articulation during Speech: The MASK system
Poster D52 in Poster Session D, Wednesday, October 25, 4:45 - 6:30 pm CEST, Espace Vieux-Port
Douglas Cheyne1,2,4, Ioanna Anastasopoulou3, Cecilia Jobst1, Narges Moein1,2, Tom Chau4, Pascal van Lieshout2, Blake Johnson3; 1Program in Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Canada, 2Dept. of Speech-Language Pathology, University of Toronto, Toronto, Canada, 3School of Psychological Sciences, Macquarie University, Sydney, Australia, 4Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
MEG recordings of movement-related brain activity provide an ideal method for the study of the cortical control of movement. However, MEG measurements associated with overt speech is limited due to the challenge of tracking speech movements in the MEG environment, particularly for small movements of the tongue which requires non-line-of-sight methods. We have developed an MEG-compatible motion tracking system to monitor brain activity in parallel with ongoing orofacial and speech movements. This technology, dubbed MASK (Magneto-articulography for the Assessment of Speech Kinematics), can be integrated into existing MEG recording systems to acquire 3-dimensional kinematic data simultaneously with neuromagnetic brain activity [1]. This system has been shown to measure speech kinematics comparable to conventional articulography measurement systems [2]. Methods: 10 healthy adults performed a repetitive speech task (10 second trials x 10 repetitions) involving reiterated disyllabic non-words (/ipa/, /api/), non-speech mouth opening-closing, and a simple manual motor task (left and right button press). Speech gestures and non-speech mouth movements were tracked in real time along with brain measures using a 275-channel MEG (CTF Systems, Vancouver) by affixing MASK sensors on the upper and lower lip (bilabial closure) and tongue body (tongue movements associated with vowel formation /a/ versus /i/) in addition to the acoustic speech signal. Results: Source analysis of MEG data showed suppression of beta band (15-30Hz) oscillations during speech localized to regions of the precentral gyrus ventral to the hand motor area activated during button press. Beta suppression during reiterative speech was strongly left lateralized in contrast to non-speech movements which were associated with bilateral beta suppression in lateral motor cortex, similar to that observed during a simple CV repetition task time locked to speech onset [3]. Conclusions: Preliminary results demonstrate the ability to measure time-locked brain responses and speech kinematics during speech tasks using a novel MEG compatible motion-tracking system. Differences in patterns of brain activation between non-speech movements and speech tasks involving articulatory control demonstrate the importance of both task design and the ability to measure complex speech gestures concurrently with functional brain imaging to understand the underlying mechanisms of speech motor control. This technology provides new avenues for both basic research on articulatory control and speech sound disorders. References: [1] Alves, N., Jobst, C., Hotze, F., Ferrari, P., Lalancette, M., Chau, T., van Lieshout, P. & Cheyne, D. (2016). An MEG-compatible electromagnetic-tracking system for monitoring orofacial kinematics. IEEE Trans. Biomed. Eng., 63, 1709–1717. [2] Anastasopoulou, I., van Lieshout, P., Cheyne, D. & Johnson, B. W. (2022), Speech kinematics and coordination measured with an MEG-compatible speech tracking system. Front. Neurology, 13: [3] De Nil L., Isabella S., Jobst C., Kwon S., Mollaei F. & Cheyne D. (2021) Complexity-dependent modulations of beta oscillations for verbal and nonverbal movements. J. Speech Lang. Hear. Res. 64: 2248-2260. Acknowledgements: Supported Australian Research Council (DP170102407) and Natural Sciences and Engineering Research of Canada (CPG-104310) and the Waterloo Foundation, UK.
Topic Areas: Speech Motor Control, Methods