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Updated: Jul 13, 2026

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation
Published on: August 20, 2019
Muscle responses to transcranial stimulation in man depend on background oscillatory activity
W Kyle Mitchell1, Mark R Baker, Stuart N Baker
1Department of Anatomy, Cambridge University, Cambridge CB2 3DY, UK.
Abstract:
Muscle responses to transcranial stimulation show high sweep-to-sweep variability, which may reflect an underlying noise process in the motor system. We examined whether response amplitude correlated with the level of prestimulus background EMG, and network oscillations. Transcranial magnetic or electrical stimulation was delivered to primary motor cortex whilst human subjects performed a precision grip task known to promote beta-band ( approximately 20 Hz) cortical oscillations. Responses were recorded from two intrinsic hand muscles. Response magnitude correlated significantly with the level of background EMG (mean r(2) = 0.20). Using a novel wavelet method, we quantified the amplitude and phase of oscillations in prestimulus sensorimotor EEG. Surprisingly, response magnitude showed no significant correlation with EEG oscillations at any frequency. However, oscillations in the prestimulus EMG were significantly correlated with response size; the correlation coefficient had peaks around 20 Hz. When oscillations in one muscle were used to predict response amplitude in a different muscle, correlations were substantially smaller. Finally, for each recording, we calculated the best possible prediction of response size obtainable from up to 20 measures of prestimulus EEG and EMG oscillations. Such optimal predictions had low correlation coefficients (mean r(2) = 0.2; 76% were below 0.3). We conclude that prestimulus oscillations, mainly in the beta-band, do explain some of the variability in responses to transcranial stimulation. Oscillations may likewise increase the noise of natural motor processing, explaining why this form of network activity is usually suppressed prior to dynamic movements. However, the majority of the variation is determined by other factors, which are not accessible by noninvasive recordings.
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