Concurrent tACS-fMRI Reveals Causal Influence of Power Synchronized Neural Activity on Resting State fMRI Connectivity

Abstract

Resting state fMRI (rs-fMRI) is commonly used to study the brain's intrinsic neural coupling, which reveals specific spatiotemporal patterns in the form of resting state networks (RSNs). It has been hypothesized that slow rs-fMRI oscillations (<0.1 Hz) are driven by underlying electrophysiological rhythms that typically occur at much faster timescales (>5 Hz); however, causal evidence for this relationship is currently lacking. Here we measured rs-fMRI in humans while applying transcranial alternating current stimulation (tACS) to entrain brain rhythms in left and right sensorimotor cortices. The two driving tACS signals were tailored to the individual's α rhythm (8-12 Hz) and fluctuated in amplitude according to a 1 Hz power envelope. We entrained the left versus right hemisphere in accordance to two different coupling modes where either α oscillations were synchronized between hemispheres (phase-synchronized tACS) or the slower oscillating power envelopes (power-synchronized tACS). Power-synchronized tACS significantly increased rs-fMRI connectivity within the stimulated RSN compared with phase-synchronized or no tACS. This effect outlasted the stimulation period and tended to be more effective in individuals who exhibited a naturally weak interhemispheric coupling. Using this novel approach, our data provide causal evidence that synchronized power fluctuations contribute to the formation of fMRI-based RSNs. Moreover, our findings demonstrate that the brain's intrinsic coupling at rest can be selectively modulated by choosing appropriate tACS signals, which could lead to new interventions for patients with altered rs-fMRI connectivity.SIGNIFICANCE STATEMENT Resting state fMRI (rs-fMRI) has become an important tool to estimate brain connectivity. However, relatively little is known about how slow hemodynamic oscillations measured with fMRI relate to electrophysiological processes. It was suggested that slowly fluctuating power envelopes of electrophysiological signals synchronize across brain areas and that the topography of this activity is spatially correlated to resting state networks derived from rs-fMRI. Here we take a novel approach to address this problem and establish a causal link between the power fluctuations of electrophysiological signals and rs-fMRI via a new neuromodulation paradigm, which exploits these power synchronization mechanisms. These novel mechanistic insights bridge different scientific domains and are of broad interest to researchers in the fields of Medical Imaging, Neuroscience, Physiology, and Psychology.

Keywords: EEG; electrical stimulation; mechanism; neuronal oscillations; simultaneous tACS/fMRI.

Figure 1.

EEG-based stimulation signals during fMRI. A, For each subject, the individual α peak and IAF band (IAF = α peak ± 2 Hz) was determined from electrodes C3/C4 during rest (eyes-open). Right, Exemplary frequency spectrum. Left, Mean and 95% CI (shaded area) of the EEG frequency spectrum normalized to the IAF ±5 Hz of the left and the right hemisphere, indicating a clear peak. B, Correlational analysis showing an anticorrelated relationship between electrodes C3/C4 for the signal within IAF (red) and a positive correlation for the envelope modulation of IAF (blue). C, Histogram of relative phase difference between C3 and C4 of IAF signal (red) and envelope (blue) across subjects. Arrows indicate average phase difference across subjects. D, Based on the subject's IAF, two kinds of stimulation signals were applied via a 3-electrode setup during rs-fMRI. Power-synchronized tACS mimics the in-phase relationship of the IAF power envelopes between C3/C4 (while the IAF signal was anticorrelated; blue-green) and phase-synchronized tACS (control) with the opposite correlational properties (antiphase power fluctuations, synchronized IAF signal). A total of 35 min of resting state fMRI was recorded, split into 5 runs of 7 min from the same 20 subjects as in the EEG experiment (see Materials and Methods). During runs 2 and 4, power-synchronized and phase-synchronized tACS was applied via 2 active electrodes placed on the left and right motor cortex (red); run 1 served as baseline for further analysis, and runs 3 and 5 measured potential aftereffects. E, Post-fMRI analysis of the EEG data confirms that the IAF is clearly detectable in source space (i.e., in left and right sensorimotor cortex). F, G, Correlational and instantaneous phase properties in source space. The IAF envelope exhibits robust synchronization (i.e., 0 degrees relative phase) between hemispheres, whereas the IAF signals exhibit large intersubject variability.

Figure 2.

Simulations of the electric field during power-synchronized (left side) and phase-synchronized tACS (right side). A, Top, Externally applied signals over left and right sensorimotor cortex. B, The electric field distribution estimated for four different time points of the envelope amplitude of the right hemisphere (indicted by black vertical lines) is shown on a surface view and an axial slice through the sensorimotor system (z = 66). The highlighted aspect shows the sensorimotor RSN. C, Simulated signals showing effective modulation within left and right sensorimotor cortex extracted from MNI coordinates +/−18, −40, 66 (i.e., the maximum of the simulated electric field during power-synchronized stimulation) and the visual cortex (MNI 2, −88, 22; i.e., approximately under the return electrode). During power-synchronized tACS (B,C, left), both hemispheres oscillate synchronously between strong and weak stimulation. By contrast, during phase-synchronized tACS (B,C, right), one hemisphere is always more strongly activated than the other. Also, the maximum modulation depth of the envelope reached similar levels in the sensorimotor cortex for both stimulation conditions (0.25 V/m for power-synchronized tACS and 0.21 V/m for phase-synchronized tACS).

Figure 3.

RSNs of interest. Based on the MELODIC group-ICA, eight RSNs were selected for further analyses: a sensorimotor network (blue), a premotor network (blue-green), a more lateral motor network (light green), the default-mode network split into a frontal (dark red) and parietal part (light red), the striatum (light blue, bottom), a visual network (yellow), and a superior parietal network (light blue, top).

Figure 4.

Increase of network strength of the sensorimotor network during power-synchronized tACS compared with baseline and phase-synchronized tACS (control). Left, Averaged normalized scores of network strength identified by dual regression during and after power-synchronized (blue-green) and phase-synchronized tACS (dark red) revealing an increase of 25% in network strength during power-synchronized tACS compared with baseline and a significant increase (20%; p = 0.037) compared with phase-synchronized tACS (control). The increase was still significant when comparing the two aftereffects (POST power-synchronized and POST phase-synchronized, p = 0.010). *p < 0.05. Error bars indicate mean ± SEM. Right, Corresponding voxelwise contrasts revealing an increase of network strength around the central sulcus in between the active electrodes during and after power-synchronized tACS compared with baseline and phase-synchronized tACS, and a general increase during and after power-synchronized tACS compared with baseline (all images: p_{tfce-corrected} < 0.05).

Figure 5.

Results of other RSNs of interest. We did not find a main effect of stimulation type for any RSN other than the sensorimotor network. However, there was a similar trend (i.e., power-synchronized tACS increasing network connectivity vs phase-synchronized tACS not increasing network connectivity) observable in the striatum, the premotor network, the lateral motor network, and the superior parietal network. Although the effect did not reach statistical significance, the general trend fits the observed changes in the sensorimotor network because all of these networks are either associated with motor functions, and are therefore connected to the sensorimotor network (premotor network, striatum), or in between/under the stimulation electrodes (superior parietal network, lateral motor network). By contrast, we observed no difference between stimulation paradigms for the default-mode network (parietal and frontal) and the visual network, which rules out that the above described effects are purely driven by current injection itself or current related artifacts. p_{Stimulation Type} given for normalized data. Error bars indicate mean ± SEM.

Figure 6.

tACS induced changes in network strength relative to the previous condition. Only power-synchronized stimulation signals cause a relative increase of connectivity strength, whereas phase-synchronized stimulation (i.e., power envelopes are in antiphase) has only a minor effect on connectivity. Error bars indicate mean ± SEM. *p < 0.05. ^†p < 0.1.

Figure 7.

Effects of power-synchronized (left) and phase-synchronized stimulation (right) on network connectivity strength when participants were split depending on stimulation order. The data are normalized to the rest period immediately before stimulation. Power-synchronized stimulation has a synchronizing effect on the sensorimotor network regardless of whether it followed the baseline condition or was applied on top of the aftereffects caused by the phase-synchronized stimulation. Phase-synchronized stimulation has a slight synchronizing effect when applied immediately after baseline, but a desynchronizing effect when the network state had already been modulated by power-synchronized tACS. Error bars indicate mean ± SEM.

Figure 8.

Individual subject data. Left, Normalized network strength of the sensorimotor network during power-synchronized compared with phase-synchronized tACS. Right, Normalized network strength of the sensorimotor network during POST power-synchronized and POST phase-synchronized for each subject revealing large intersubject variability. Gray represents subjects who do not follow the general trend (power-synchronized tACS > phase-synchronized tACS).

Figure 9.

Correlations between EEG signal properties and percentage increase of network strength during power-synchronized and phase-synchronized tACS. A, Correlation between increase of network strength during power-synchronized tACS and IAF envelope correlation between electrode C3 and C4 (r_Envelope) revealing a negative association between the IAF envelope over sensorimotor cortex in the sensor space and efficacy of tACS stimulation (ρ = −0.48, p = 0.03). B, Positive correlation of increase of network strength during power-synchronized tACS and IAF signal correlation between electrode C3 and C4 (r_Signal) (ρ = 0.42, p = 0.06). C, D, No such relationship was visible between the change in network strength during phase-synchronized tACS and IAF envelope or signal between C3 and C4 (IAF envelope: ρ = −0.19, p = 0.43; IAF signal: ρ = −0.07, p = 0.78). EEG and fMRI measurements were performed in two separate sessions.