Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in Parkinson's disease

Abstract

The disruption of pathologically enhanced beta oscillations is considered one of the key mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's disease. However, a specific modulation of other distinct physiological or pathological oscillatory activities could also play an important role in symptom control and motor function recovery during deep brain stimulation. Finely tuned gamma oscillations have been suggested to be prokinetic in nature, facilitating the preferential processing of physiological neural activity. In this study, we postulate that clinically effective high-frequency stimulation of the subthalamic nucleus imposes cross-frequency interactions with gamma oscillations in a cortico-subcortical network of interconnected regions and normalizes the balance between beta and gamma oscillations. To this end we acquired resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underwent deep brain stimulation to compare spectral power and power-to-power cross-frequency coupling using a beamformer algorithm for coherent sources. To show that modulations exclusively relate to stimulation frequencies that alleviate motor symptoms, two clinically ineffective frequencies were tested as control conditions. We observed a robust reduction of beta and increase of gamma power, attested in the regions of a cortical (motor cortex, supplementary motor area, premotor cortex) and subcortical network (subthalamic nucleus and cerebellum). Additionally, we found a clear cross-frequency coupling of narrowband gamma frequencies to the stimulation frequency in all of these nodes, which negatively correlated with motor impairment. No such dynamics were revealed within the control posterior parietal cortex region. Furthermore, deep brain stimulation at clinically ineffective frequencies did not alter the source power spectra or cross-frequency coupling in any region. These findings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differentially modifies different oscillatory activities in a widespread network of cortical and subcortical regions. Particularly the cross-frequency interactions between finely tuned gamma oscillations and the stimulation frequency may suggest an entrainment mechanism that could promote dynamic neural processing underlying motor symptom alleviation.

Keywords: cross-frequency coupling; deep brain stimulation; gamma oscillations; source analysis; volume of tissue activated.

Figure 1

Schematic of the analysis pipeline. (A) In a first step the VTA was calculated using lead-DBS (see also Fig. 2). (B) Utilizing the reconstructed source time series of voxels identified by VTA analysis as a reference for the clinical stimulation condition we identified six coherent sources that were used for further analyses [STN, CER, M1, premotor cortex (PMC), and supplementary motor area (SMA)]. Additionally, the PPC was included as a control region. PD = Parkinson’s disease.

Figure 2

Electrode location and VTA. (A) DBS electrode reconstruction for all subjects using lead-DBS. Red and white colours represent electrodes of patients stimulated with 130 Hz and 160 Hz, respectively. Subcortical structures are based on DISTAL atlas [orange: STN, green: internal globus pallidus (GPi), blue: external globus pallidus (GPe), and red: red nucleus] laid over a 7 T MRI ex vivo 100-μm thick human brain background template. Electrode contacts used for stimulation are shown in green (130 Hz) and magenta (160 Hz) and (B) VTA is shown in cyan (130 Hz) and magenta (160 Hz). (C) All electrodes locate to the sensorimotor region of the STN and VTA simulation shows that DBS primarily activates tissue in this area.

Figure 3

Stimulation induced beta- and gamma-band power changes. One-way repeated measures ANOVAs revealed that clinical stimulation significantly reduced beta-band and concurrently increased gamma-band power in M1, PMC, SMA, STN, CER, but not in PPC (Post hoc test with Bonferroni procedure, all P < 0.05). Stimulating with higher or lower frequencies (in comparison to clinical frequencies) exclusively reduced beta power in the STN.

Figure 4

Association between beta and gamma power. Correlation analysis demonstrated a significant negative correlation of beta and gamma power during the clinically effective stimulation condition (On-clinical) for M1 and STN. In addition, the difference between the On-clinical and Off condition of beta and gamma power was significantly negatively correlated. The coloured regions denote the 95% confidence intervals for the correlation. dBeta and dGamma refer to (On-clinical − Off) power estimates. The r² and P-values are included separately for each subplot.

Figure 5

Inter-regional CFC between the VTA reference signal and the regions of interest. CFC indices revealed clusters of narrowband gamma power coupled to the stimulation frequency (A) 130 Hz and (B) 160 Hz, respectively. The black line in the colour bars indicates the significance threshold based on surrogate analyses. See Supplementary Table 2 for ANOVA results and exact P-values.

Figure 6

Dynamics of CFC in M1. The temporal variation of CFC (power-to-power) in M1 for the entire 10 min divided into 10 epochs of 60 s. Stimulation was switched on at time point 0. The CFC is only significantly increased during On-clinical stimulation and takes ∼1 min to establish (A). This demonstrates that increased CFC does not relate to a stimulation artefact. If this was the case, increased CFC would be visible in non-clinical stimulation and would develop from the onset of the stimulation. (A) On-clinical 130 Hz (orange) and 160 Hz (blue); (B) On-low 110 (orange) and 140 Hz (blue); and (C) On-high 150 Hz (orange) and 180 Hz (blue). Statistical analyses between the epochs are shown with red lines: epoch 1 is significantly different to epochs 2 to 10, as shown by the black lines, but only for the On-clinical frequencies 130 Hz and 160 Hz (P < 0.0001). The bold line indicates the mean and the shaded region indicates the standard deviation over all subjects. Note the y-axis in A differs from that in B and C.

Figure 7

Association between gamma CFC and UPDRS III. Correlation analysis demonstrated a negative correlation of gamma CFC and UPDRS III On-clinical scores during clinically effective stimulation (r = −0.5266; P = 0.0023).