Abstract
Muscular activity recording is of high basic science and clinical relevance and is typically achieved using electromyography (EMG). While providing detailed information about the state of a specific muscle, this technique has limitations such as the need for a priori assumptions about electrode placement and difficulty with recording muscular activity patterns from extended body areas at once. For head and face muscle activity, the present work aimed to overcome these restrictions by exploiting magnetoencephalography (MEG) as a whole head myographic recorder (head magnetomyography, hMMG). This is in contrast to common MEG studies, which treat muscular activity as artifact in electromagnetic brain activity. In a first proof‐of‐concept step, participants imitated emotional facial expressions performed by a model. Exploiting source projection algorithms, we were able to reconstruct muscular activity, showing spatial activation patterns in accord with the hypothesized muscular contractions. Going one step further, participants passively observed affective pictures with negative, neutral, or positive valence. Applying multivariate pattern analysis to the reconstructed hMMG signal, we were able to decode above chance the valence category of the presented pictures. Underlining the potential of hMMG, a searchlight analysis revealed that generally neglected neck muscles exhibit information on stimulus valence. Results confirm the utility of hMMG as a whole head electromyographic recorder to quantify muscular activation patterns including muscular regions that are typically not recorded with EMG. This key advantage beyond conventional EMG has substantial scientific and clinical potential.
Highlights
Our body allows for expression of a rich set of emotional states intrinsic to social interaction (Darwin, 1872; Nummenmaa, Glerean, Hari, & Hietanen, 2014; Nummenmaa, Hari, Hietanen, & Glerean, 2018)
Comparisons between “active emotions” (Fig. 4B) are in line with observations shown in figure 4A and highlight specific areas of muscular activation differences between emotion expressions. These results prove that head MagnetoMyography (hMMG) is suited for localizing muscular activity during facial expressions, but most importantly, they highlight the advantage of “whole-head” recordings against the classical “apriori” electrode selection, revealing that unexpected or overlooked muscles contributed to the expression patterns
4.4 Conclusions and Future Perspectives This study demonstrates that hMMG is a powerful method to monitor whole-head muscular activity, yielding some advantages over classical EMG
Summary
Our body allows for expression of a rich set of emotional states intrinsic to social interaction (Darwin, 1872; Nummenmaa, Glerean, Hari, & Hietanen, 2014; Nummenmaa, Hari, Hietanen, & Glerean, 2018). Studies in this field often exploit a technique of muscular recording called surface electromyography (EMG; Fridlund & Cacioppo, 1986; Larsen, Norris, & Cacioppo, 2003). When expressing a specific emotional state, specialized muscles in the face contract, resulting in differentiated activity patterns of facial muscles. While yielding signals at relatively high signal-to-noise levels for a specific muscle, a limitation is that, in order to record different muscles, many electrodes are needed. Some muscles are very difficult to record via surface EMG (e.g., inner neck) These issues limit the clinical use of the surface and (more invasive) needle EMG, since some muscles (such as Longus Colli in chronic neck pain syndromes, Falla, Jull, O’Leary, & Dall’Alba, 2006) are difficult to record with these techniques. The use of conventional techniques can be highly unpleasant in pain conditions such as allodynia or hyperalgesia (Coutaux, Adam, Willer, & Le Bars, 2005)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
