Brain Network Mechanisms Underlying Motor Enhancement by Transcranial Entrainment of Gamma Oscillations

Abstract

Gamma and beta oscillations are routinely observed in motor-related brain circuits during movement preparation and execution. Entrainment of gamma or beta oscillations via transcranial alternating current stimulation (tACS) over primary motor cortex (M1) has opposite effects on motor performance, suggesting a causal role of these brain rhythms for motor control. However, it is largely unknown which brain mechanisms characterize these changes in motor performance brought about by tACS. In particular, it is unclear whether these effects result from brain activity changes only in the targeted areas or within functionally connected brain circuits. Here we investigated this issue by applying gamma-band and beta-band tACS over M1 in healthy humans during a visuomotor task and concurrent functional magnetic resonance imaging (fMRI). Gamma tACS indeed improved both the velocity and acceleration of visually triggered movements, compared with both beta tACS and sham stimulation. Beta tACS induced a numerical decrease in velocity compared with sham stimulation, but this was not statistically significant. Crucially, gamma tACS induced motor performance enhancements correlated with changed BOLD activity in the stimulated M1. Moreover, we found frequency- and task-specific neural compensatory activity modulations in the dorsomedial prefrontal cortex (dmPFC), suggesting a key regulatory role of this region in motor performance. Connectivity analyses revealed that the dmPFC interacted functionally with M1 and with regions within the executive motor system. These results suggest a role of the dmPFC for motor control and show that tACS-induced behavioral changes not only result from activity modulations underneath the stimulation electrode but also reflect compensatory modulation within connected and functionally related brain networks. More generally, our results illustrate how combined tACS-fMRI can be used to resolve the causal link between cortical rhythms, brain systems, and behavior.

Significance statement: Recent research has suggested a causal role for gamma oscillations during movement preparation and execution. Here we combine transcranial alternating current stimulation (tACS) with functional magnetic resonance imaging (fMRI) to identify the neural mechanisms that accompany motor performance enhancements triggered by gamma tACS over the primary motor cortex. We show that the tACS-induced motor performance enhancements correlate with changed neural activity in the stimulated area and modulate, in a frequency- and task-specific manner, the neural activity in the dorsomedial prefrontal cortex. This suggests a regulatory role of this region for motor control. More generally, we show that combined tACS-fMRI can elucidate the causal link between brain oscillations, neural systems, and behavior.

Keywords: concurrent tACS and fMRI; fMRI; gamma-band oscillations; gamma-tACS entrainment; motor enhancement; tACS.

Copyright © 2016 the authors 0270-6474/16/3612053-13$15.00/0.

Figures

Figure 1.

Quality and safety tests. A, Quality tests performed with a watermelon. Parameter estimates (left) and statistical maps (right) thresholded at p = 0.05 uncorrected for the parametric analysis (upper row; parametric modulator: regressor values were set to 6, 10, 20, 40, 60, and 80 for the blocks where the stimulation frequency was 6, 10, 20, 40, 60, and 80 Hz respectively, and 0 for the baseline blocks with no stimulation), for stimulation ON versus OFF (middle row; regressor contrast weights were set to 1 for all stimulation blocks, regardless of the stimulation frequency, and 0 for baseline) and for the control analysis (bottom row; same regressor contrast weights as for the stimulation ON versus OFF analysis, but for the control fMRI dataset, where the electrodes were attached to the melon and connected to the stimulator, but with the stimulator switched off). B, SfNR images for two conditions: during 70 Hz tACS stimulation and during the control condition, where the electrodes were attached to the melon and connected to the stimulator, but with the stimulator switched off. Low SfNR values indicate a high temporal variability of the EPI signal, hinting toward an undesired impact of the tACS stimulation on the EPI quality. Here no additional temporal EPI signal fluctuation was induced by the tACS stimulation compared with the control measurement. A comparable SfNR map was observed for 20 Hz tACS. C, Temperature measurement during 70 Hz tACS: the temperature under the active electrodes increased with <1°C over the 30 min stimulation. Critically, there was no difference in the temperature increase under the active electrodes and the increase in temperature in the control sensor, which was ≥6 cm away from any of the two active electrodes. Similar temperature increases were observed also during 20 Hz tACS.

Figure 2.

A, Schematic diagram of the motor task. During the movement-initiation task, a new force level was displayed at a frequency of 1 Hz and the subjects updated their grip force accordingly. The designated grip level was displayed as a white horizontal bar while any dynamic change in the grip force was displayed as a gray vertical bar (left). The grip-control task required the subjects to keep the grip force at a constant level of 5% of the maximum voluntary contraction (middle). During the resting blocks, subjects passively viewed the display without performing any movements (right). B, Schematic diagram of the experimental design. The top row shows the timing of one block lasting 18 s. The tACS stimulation was ramped up and down over the first and last 2 s (left, top row). During the sham condition, the current was ramped up to 0.5 mA over 2 s and immediately ramped down over 2 s (right, top row). Each run presented four repetitions of each condition of the 3 × 3 factorial block design [tACS type (beta tACS, gamma tACS, or sham) crossed with motor state (movement initiation, grip control, or rest) (bottom row). C, Behavioral results of the multiple-regression analyses for movement-initiation task velocity (left figure) and acceleration (right figure). The error bars represent the SEs of the regression coefficient estimates (see Materials and Methods). n.s., Not significant; *, significant at p < 0.05; a.u., arbitrary units).

Figure 3.

Task main effects (MNI space; p < 0.05 FWE cluster corrected, cluster-forming threshold T(19) > 2.6). A, Movement initiation and grip control versus rest. B, Movement initiation versus grip control.

Figure 4.

Correlation analyses between behavior and brain activity for gamma tACS versus beta tACS during the movement-initiation task. A, Correlation analysis between velocity change during gamma tACS versus beta tACS and BOLD-imaging contrast movement initiation during gamma tACS versus beta tACS (p < 0.05 FWE cluster corrected, cluster-forming threshold T(19) > 2.6). B, Standard left M1 region of interest (ROI) generated by a meta-analysis of 303 motor studies (Neurosynth database dated Jan. 21, 2015; http://neurosynth.org/). C, D, Overlap between the standard left M1 ROI and the brain regions showing a significant correlation with the velocity difference (C) and acceleration difference (D) for gamma-tACS versus beta tACS during movement initiation. The right panels of C and D show the velocity difference (C) and acceleration difference (D) for gamma-tACS M1 versus beta-tACS M1 as a function of BOLD signal parameter estimates (PE; proportional to BOLD signal changes). The BOLD PEs were first averaged across all voxels in the overlay M1 ROI displayed in the left panels of C and D. For each single subject, the averaged PE for movement initiation during beta tACS was subtracted from the averaged PE for movement initiation during gamma tACS. S1, Somatosensory cortex; MI, movement-initiation task.

Figure 5.

A, Interaction between motor task (movement initiation versus grip control) and tACS frequency (beta tACS vs gamma tACS). B, Interaction between motor task (movement initiation vs grip control) and tACS condition (sham stimulation vs gamma tACS). The left panels of A and B show thresholded (p < 0.05 FWE cluster corrected, cluster-forming threshold T(19) > 2.6) SPMs projected onto sagittal brain slices in MNI space, whereas the right panels illustrate the effects with parameter estimates (PE; proportional to BOLD signal changes) extracted from the dmPFC region activated by the interaction contrasts. The error bars represent +/−SEM across subjects. C, The position of the tACS electrode (size, 5 × 7 cm; area, 35 cm2) over left M1 used for the main experiment and for the electric field simulation. The other electrode (size, 10 × 10 cm; area, 100 cm2) was placed over the left shoulder. D, The normalized predicted electric field distribution projected onto MNI space is minimal in the dmPFC region that exhibits a significant interaction between motor tasks (movement initiation vs grip control) and tACS frequency (beta tACS vs gamma tACS). The yellow circles indicate the position of the dmPFC region. The electric field is strongest under and in the vicinity of the active electrode placed over left M1 (left and middle transversal views), while the electric field is minimal in the dmPFC region (middle transversal and right sagittal views). The yellow circle in the middle transversal view is centered on the maximum activation in the dmPFC [peak coordinates (MNI): x = 15, y = 32, z = 40; Table 2]. The right sagittal view is the same sagittal view as in A. This projection consolidates the notion that the dmPFC effects are not directly triggered by the stimulation but instead reflect compensatory modulations in response to tACS over M1.

Figure 6.

Task-dependent changes in the functional coupling between the dmPFC seed region and other brain areas, assessed using PPI analysis. A, dmPFC seed region for the PPI analysis generated as the overlay of the two interactions shown in Figure 5A, B. B, Brain areas that exhibit increased functional coupling with the seed region during movement initiation (p < 0.05 FWE cluster corrected, cluster-forming threshold T(19) > 2.6). C, Standard motor system regions of interest [ROIs; left M1, supplementary motor area (SMA), thalamus, and left putamen] generated by a meta-analysis of 303 motor studies (Neurosynth database dated Jan. 21, 2015; http://neurosynth.org/). To generate these ROIs, the standard motor network activation map was first corrected for multiple comparisons using an expected false discovery rate of 0.01, while the height of the threshold was set to T > 6.5 for generating the left M1 and SMA ROIs and to T > 5 for generating the putamen and thalamus ROIs. We used different thresholds for different ROIs to be able to distinguish the ROIs from neighboring brain areas (e.g., left M1 from left dorsal premotor area). D, Overlay between the standard motor system ROIs shown in C and the PPI analysis shown in B.