Decoding kinematic information from beta-band motor rhythms of speech motor cortex: a methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Ioanna Anastasopoulou; Douglas Owen Cheyne; Pascal van Lieshout; Blake Warren Johnson

doi:10.3389/fnhum.2024.1305058

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: a methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Front Hum Neurosci. 2024 Apr 5:18:1305058. doi: 10.3389/fnhum.2024.1305058. eCollection 2024.

Authors

Ioanna Anastasopoulou¹, Douglas Owen Cheyne^{2

3}, Pascal van Lieshout², Blake Warren Johnson¹

Affiliations

¹ School of Psychological Sciences, Macquarie University, Sydney, NSW, Australia.
² Department of Speech-Language Pathology, University of Toronto, Toronto, ON, Canada.
³ Hospital for Sick Children Research Institute, Toronto, ON, Canada.

Abstract

Introduction: Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been feasible to use both in the same experimental setup because of technical incompatibilities between the two methodologies.

Methods: Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), which is technically compatible with magnetoencephalography (MEG) brain scanning systems. In the present paper we describe our methodological and analytic approach for extracting brain motor activities related to key kinematic and coordination event parameters derived from time-registered MASK tracking measurements. Data were collected from 10 healthy adults with tracking coils on the tongue, lips, and jaw. Analyses targeted the gestural landmarks of reiterated utterances/ipa/ and /api/, produced at normal and faster rates.

Results: The results show that (1) Speech sensorimotor cortex can be reliably located in peri-rolandic regions of the left hemisphere; (2) mu (8-12 Hz) and beta band (13-30 Hz) neuromotor oscillations are present in the speech signals and contain information structures that are independent of those present in higher-frequency bands; and (3) hypotheses concerning the information content of speech motor rhythms can be systematically evaluated with multivariate pattern analytic techniques.

Discussion: These results show that MASK provides the capability, for deriving subject-specific articulatory parameters, based on well-established and robust motor control parameters, in the same experimental setup as the MEG brain recordings and in temporal and spatial co-register with the brain data. The analytic approach described here provides new capabilities for testing hypotheses concerning the types of kinematic information that are encoded and processed within specific components of the speech neuromotor system.

Keywords: decoding; magnetoencephalography; speech motor control; speech movement tracking; speech production.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by a Child Development Fund Research Grant (Ref. No. 2532-4758) and a Discovery Project Grant (DP170102407) from the Australian Research Council.