Phase Synchronicity of μ-Rhythm Determines Efficacy of Interhemispheric Communication Between Human Motor Cortices

Abstract

The theory of communication through coherence predicts that effective connectivity between nodes in a distributed oscillating neuronal network depends on their instantaneous excitability state and phase synchronicity (Fries, 2005). Here, we tested this prediction by using state-dependent millisecond-resolved real-time electroencephalography-triggered dual-coil transcranial magnetic stimulation (EEG-TMS) (Zrenner et al., 2018) to target the EEG-negative (high-excitability state) versus EEG-positive peak (low-excitability state) of the sensorimotor μ-rhythm in the left (conditioning) and right (test) motor cortex (M1) of 16 healthy human subjects (9 female, 7 male). Effective connectivity was tested by short-interval interhemispheric inhibition (SIHI); that is, the inhibitory effect of the conditioning TMS pulse given 10-12 ms before the test pulse on the test motor-evoked potential. We compared the four possible combinations of excitability states (negative peak, positive peak) and phase relations (in-phase, out-of-phase) of the μ-rhythm in the conditioning and test M1 and a random phase condition. Strongest SIHI was found when the two M1 were in phase for the high-excitability state (negative peak of the μ-rhythm), whereas the weakest SIHI occurred when they were out of phase and the conditioning M1 was in the low-excitability state (positive peak). Phase synchronicity contributed significantly to SIHI variation, with stronger SIHI in the in-phase than out-of-phase conditions. These findings are in exact accord with the predictions of the theory of communication through coherence. They open a translational route for highly effective modification of brain connections by repetitive stimulation at instants in time when nodes in the network are phase synchronized and excitable.SIGNIFICANCE STATEMENT The theory of communication through coherence predicts that effective connectivity between nodes in distributed oscillating brain networks depends on their instantaneous excitability and phase relation. We tested this hypothesis in healthy human subjects by real-time analysis of brain states by electroencephalography in combination with transcranial magnetic stimulation of left and right motor cortex. We found that short-interval interhemispheric inhibition, a marker of interhemispheric effective connectivity, was maximally expressed when the two motor cortices were in phase for a high-excitability state (the trough of the sensorimotor μ-rhythm). We conclude that findings are consistent with the theory of communication through coherence. They open a translational route to highly effectively modify brain connections by repetitive stimulation at instants in time of phase-synchronized high-excitability states.

Keywords: EEG-TMS; communication through coherence; effective cortico-cortical connectivity; human; interhemispheric communication; motor cortex.

Figure 1.

μ-oscillation triggered SIHI. a, b, Scalp EEG raw data derived from 5-point sum-of-difference operators centered on the C3 and C4 EEG electrodes (Hjorth-C3 and Hjorth-C4) over the left and right sensorimotor cortices are streamed to a real-time system with 3 ms latency (a), where a processing algorithm is computed at a rate of 500 Hz (b). The EEG-data are 8–12 Hz band-pass filtered forward and backward, edge artifacts are removed, and coefficients for an autoregressive model are calculated from the filtered data. c, d, The signal is forward predicted (blue shaded area in c), phase is estimated at time 0 (t = 0) using a Hilbert transform, and the two TMS stimulators (d) are triggered at 0 ms (CS to the hand area left motor cortex) and +10 ms or (in half of the subjects) +12 ms (test stimulus TS to the hand area right motor cortex) when the preselected one of the five predefined phase conditions (c) is met in the Hjorth-C3 (orange) and Hjorth-C4 (blue) EEG signals. These correspond to the four possible combinations of positive (pos) and negative (neg) peaks of the ongoing sensorimotor μ-rhythm in the conditioning (C) and the test (T) M1 (pos_C-pos_T, pos_C-neg_T, neg_C-pos_T, neg_C-neg_T) and a random phase condition as control (rand_C/T). d, Short-interval interhemispheric inhibition is reflected by attenuation of the conditioned MEP (continuous line) compared with the nonconditioned test MEP (dotted line) recorded by surface EMG from the left-hand target muscles (only EMG electrodes on APB are shown; electrodes on first dorsal interosseus are not shown).

Figure 2.

Frequency of occurrence of interhemispheric μ-phase conditions in nonstimulated resting-state EEG. a, Five seconds of scalp raw resting-state EEG recordings (gray traces, top: Hjorth-C3, bottom: Hjorth-C4) for one exemplary subject and corresponding μ-band (8–12 Hz) filtered signals (orange and blue traces, respectively). Vertical shaded gray bars highlight four events corresponding to the four combinations of positive (pos) and negative (neg) peak of the ongoing sensorimotor μ-rhythm in the conditioning (C) and the test (T) M1 (pos_C-pos_T, pos_C-neg_T, neg_C-pos_T, neg_C-neg_T) used for triggering of TMS pulses in the main experiment to determine effects of phase on short-interval interhemispheric inhibition. b, Enlargement of the events highlighted by the vertical gray bars in a. c, Group average (n = 16) empirical cumulative probability distributions of waiting time between the occurrence of an event and the next occurrence of the same event for the 4 phase combinations in 5 min of spontaneous resting-state EEG.

Figure 3.

SIHI curves. The SIHI curves of the individual subjects are represented with thin gray lines. SIHI (y-axis) is expressed as a percentage of the mean conditioned MEP over the mean unconditioned test MEP and plotted against CS intensity (x-axis, in %RMT). The CS preceded the test stimulus by 10 ms in 8/16 subjects and by 12 ms in 8/16 subjects. The red dots superimposed to the individual curves represent the CS intensity selected for the main experiment. For each subject, CS intensity was selected to induce on average ∼50% of maximum inhibition. The thick gray line represents the group mean SIHI curve of the studied sample.

Figure 4.

SIHI triggered on the instantaneous phase of sensorimotor μ-oscillation over left and right motor cortex. Top, Distribution of estimated phase angle at the time of the CS trigger for the conditioning motor cortex (left M1, left in each pair of rose plots) and TS trigger (10 or 12 ms later) for the test motor cortex (right M1, right) in triggered nonstimulated resting-state trials in the five different phase trigger conditions, indicated in the headers. Phase angles are binned (width, 18°) and frequencies are indicated (inner ring = 9%, outer ring = 20% for all phase-specific conditions, inner ring = 4%, outer ring = 8% for the random phase condition). Angular means ±1 SD are indicated in the phase distribution plots for all phase-specific conditions. Middle, Group mean CSD plots in the 20 ms preceding TMS. Amplitudes (in μV/m²) are indicated by the color bar. Bottom, Grand averages across all subjects and trials of raw sensorimotor Hjorth-C3 and Hjorth-C4 EEG signals preceding the TMS pulse at 0 ms. Shadings represent ±1 SD physiological shifts in μ-oscillation frequency across different trials and individuals are responsible for the declining oscillation amplitudes with distance to the TMS pulse.

Figure 5.

Effect of phase of μ-rhythm on unconditioned test MEP amplitude. a, Mean (n = 16) ±1 SEM unconditioned test MEP amplitudes (y-axis, mean MEP amplitudes in mV) evoked by the test stimulus alone applied to right test M1 in the 5 different phase conditions (x-axis). Data are pooled over the two target muscles (APB, FDI). b, Individual MEP data (in millivolts, logarithmic scale, y-axis). Data have been merged according to the phase in test M1. MEP amplitude is larger at the negative peak versus positive peak condition in all subjects, with intermediate MEP amplitudes in the random phase condition in 12/16 subjects. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 6.

Effect of phase of μ-rhythm on conditioning MEP amplitude. a, Mean (n = 16) ±1 SEM unconditioned test MEP amplitudes (y-axis, mean MEP amplitudes in mV) evoked by the conditioning stimulus applied to left M1 in the 5 different phase conditions (x-axis). Data are pooled over the two target muscles (APB, FDI). b, Individual MEP data (in millivolts, logarithmic scale, y-axis). Data have been merged according to the phase in conditioning M1. MEP amplitude is larger at the negative peak versus positive peak condition in 13/16 subjects. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 7.

Effect of phase of μ-rhythm on SIHI. a, Mean (n = 16) ±1 SEM SIHI (y-axis) expressed as a percentage of the mean conditioned MEP over the mean unconditioned test MEP and is shown for the five phase conditions (y-axis). Data are pooled over the two target muscles (APB, FDI). b, Individual SIHI data (as a percentage, y-axis). Data have been merged for in-phase (pos_C-pos_T, neg_C-neg_T) versus out-of-phase (pos_C-neg_T, neg_C-pos_T) conditions. SIHI is stronger in the in phase condition in 13/16 subjects. *p < 0.05.

Figure 8.

Time course of the PLV between the Hjorth-C3 and Hjorth-C4 signals before TMS for the 4 μ-phase trigger conditions (group average ±1 SEM, n = 16). The PLV shows a very similar pattern across conditions, ruling out the possibility that different durations of the pre-TMS synchronization between the trigger signals across the different μ-phase conditions may have played a role in the obtained SIHI results. For the time points close to TMS (up to ∼−40 ms), PLV estimation is distorted by the edge effect of the Hilbert transform used to estimate the phase of the μ-oscillation.