Key result
EEG-derived lower beta band (13-20 Hz) oscillatory power correlated significantly with MSNA inhibition (r = 0.38, p = 0.021), but lacked the robustness of MEG for differentiating inhibitors from non-inhibitors.
Why the study?
Muscle sympathetic nerve activity inhibition is currently characterized through invasive microneurography, prompting investigation into whether more clinically available electroencephalography can gauge stimulus-induced beta rebound as a surrogate variable.
Does electroencephalography (EEG) accurately gauge stimulus-induced MSNA inhibition compared to invasive microneurography in young healthy males?
Observational (n=49)
Does electroencephalography (EEG) accurately gauge stimulus-induced MSNA inhibition compared to invasive microneurography in young healthy males?
EEG shows a weak correlation with MSNA inhibition in the low beta band, but lacks the robustness of MEG, likely due to myogenic noise, limiting its current clinical utility as a non-invasive surrogate measure.
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.
No takes yet. Share an insight, caveat, or question.
Eskelin et al. (2023) conducted an observational in Healthy (n=49). Electroencephalography (EEG) beta rebound measurement vs. Invasive microneurography was evaluated on Correlation between individual MSNA inhibition and average lower beta oscillatory power (13-20 Hz) (r = 0.38, p=0.021). EEG-derived lower beta band (13-20 Hz) oscillatory power correlated significantly with MSNA inhibition (r = 0.38, p = 0.021), but lacked the robustness of MEG for differentiating inhibitors from non-inhibitors.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: