Oscillatory activity within sensorimotor networks is characterized by time-varying changes in phase and power. The influence of interactions between sensorimotor oscillatory phase and power on human motor function, like corticospinal output, is unknown. We addressed this gap in knowledge by delivering transcranial magnetic stimulation (TMS) to the human motor cortex during electroencephalography recordings in 20 healthy participants. Motor evoked potentials, a measure of corticospinal excitability, were categorized offline based on the mu (8–12 Hz) and beta (13–30 Hz) oscillatory phase and power at the time of TMS. Phase-dependency of corticospinal excitability was evaluated across a continuous range of power levels using trial-by-trial linear mixed-effects models. For mu, there was no effect of PHASE or POWER (P > 0.51), but a significant PHASE × POWER interaction (P = 0.002). The direction of phase-dependency reversed with changing mu power levels: corticospinal output was higher during mu troughs versus peaks when mu power was high while the opposite was true when mu power was low. A similar PHASE × POWER interaction was not present for beta oscillations (P > 0.11). We conclude that the interaction between sensorimotor oscillatory phase and power gates human corticospinal output to an extent unexplained by sensorimotor oscillatory phase or power alone.
Background: Neural oscillations reflect rapidly changing brain excitability states. We have demonstrated previously with EEG-triggered transcranial magnetic stimulation (TMS) of human motor cortex that the positive vs. negative peak of the sensorimotor m-oscillation reflect corticospinal low-vs. high-excitability states. In vitro experiments showed that induction of long-term depression (LTD) by low-frequency stimulation depends on the postsynaptic excitability state. Objective/Hypothesis: We tested the hypothesis that induction of LTD-like corticospinal plasticity in humans by 1 Hz repetitive TMS (rTMS) is enhanced when rTMS is synchronized with the low-excitability state, but decreased or even shifted towards long-term (LTP)-like plasticity when synchronized with the high-excitability state. Methods: We applied real-time EEG-triggered 1-Hz-rTMS (900 pulses) to the hand area of motor cortex in healthy subjects. In a randomized double-blind three-condition crossover design, pulses were synchronized to either the positive or negative peak of the sensorimotor m-oscillation, or were applied at random phase (control). The amplitude of motor evoked potentials was recorded as an index of corticospinal excitability before and after 1-Hz-rTMS. Results: 1-Hz-rTMS at random phase resulted in a trend towards LTD-like corticospinal plasticity. RTMS in the positive peak condition (i.e., the low-excitability state) induced significant LTD-like plasticity. RTMS in the negative peak condition (i.e., the high-excitability state) showed a trend towards LTP-like plasticity, which was significantly different from the other two conditions. Conclusion: The level of corticospinal depolarization reflected by phase of the m-oscillation determines the degree of corticospinal plasticity induced by low-frequency rTMS, a finding that may guide future personalized therapeutic stimulation.
The ability to interpret transcranial magnetic stimulation (TMS)-evoked electroencephalography (EEG) potentials (TEPs) is limited by artifacts, such as auditory evoked responses produced by discharge of the TMS coil. TEPs generated from direct cortical stimulation should vary in their topographical activity pattern according to stimulation site and differ from responses to sham stimulation. Responses that do not show these effects are likely to be artifactual. In 20 healthy volunteers, we delivered active and sham TMS to the right prefrontal, left primary motor, and left posterior parietal cortex and compared the waveform similarity of TEPs between stimulation sites and active and sham TMS using a cosine similaritybased analysis method. We identified epochs after the stimulus when the spatial pattern of TMS-evoked activation showed greater than random similarity between stimulation sites and sham vs. active TMS, indicating the presence of a dominant artifact. To do this, we binarized the derivatives of the TEPs recorded from 30 EEG channels and calculated cosine similarity between conditions at each time point with millisecond resolution. Only TEP components occurring before approximately 80 ms differed across stimulation sites and between active and sham, indicating site and condition-specific responses. We therefore conclude that, in the absence of noise masking or other measures to decrease neural artifact, TEP components before about 80 ms can be safely interpreted as stimulation locationspecific responses to TMS, but components beyond this latency should be interpreted with caution due to high similarity in their topographical activity pattern.
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