Abstract

Sudden, unexpected stimuli can induce a transient inhibition of sympathetic vasoconstriction to skeletal muscle, indicating a link to defense reactions. This phenomenon is relatively stable within, but differs between, individuals. It correlates with blood pressure reactivity which is associated with cardiovascular risk. Inhibition of muscle sympathetic nerve activity (MSNA) is currently characterized through invasive microneurography in peripheral nerves. We recently reported that brain neural oscillatory power in the beta spectrum (beta rebound) recorded with magnetoencephalography (MEG) correlated closely with stimulus-induced MSNA inhibition. Aiming for a clinically more available surrogate variable reflecting MSNA inhibition, we investigated whether a similar approach with electroencephalography (EEG) can accurately gauge stimulus-induced beta rebound. We found that beta rebound shows similar tendencies to correlate with MSNA inhibition, but these EEG data lack the robustness of previous MEG results, although a correlation in the low beta band (13–20 Hz) to MSNA inhibition was found (p = 0.021). The predictive power is summarized in a receiver-operating-characteristics curve. The optimum threshold yielded sensitivity and false-positive rate of 0.74 and 0.33 respectively. A plausible confounder is myogenic noise. A more complicated experimental and/or analysis approach is required for differentiating MSNA-inhibitors from non-inhibitors based on EEG, as compared to MEG.

Details

Title
From MEG to clinical EEG: evaluating a promising non-invasive estimator of defense-related muscle sympathetic nerve inhibition
Author
Eskelin, John J. 1 ; Lundblad, Linda C. 2 ; Wallin, B. Gunnar 1 ; Karlsson, Tomas 1 ; Riaz, Bushra 1 ; Lundqvist, Daniel 3 ; Schneiderman, Justin F. 2 ; Elam, Mikael 2 

 Sahlgrenska Academy at University of Gothenburg, Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582) 
 Sahlgrenska Academy at University of Gothenburg, Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Department of Clinical Neurophysiology, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X) 
 Karolinska Institutet, NatMEG, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626) 
Pages
9507
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2825583834
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.