Gamma Oscillations in the Hyperkinetic State Detected with Chronic Human Brain Recordings in Parkinson's Disease

Abstract

Hyperkinetic states are common in human movement disorders, but their neural basis remains uncertain. One such condition is dyskinesia, a serious adverse effect of medical and surgical treatment for Parkinson's disease (PD). To study this, we used a novel, totally implanted, bidirectional neural interface to obtain multisite long-term recordings. We focus our analysis on two patients with PD who experienced frequent dyskinesia and studied them both at rest and during voluntary movement. We show that dyskinesia is associated with a narrowband gamma oscillation in motor cortex between 60 and 90 Hz, a similar, though weaker, oscillation in subthalamic nucleus, and strong phase coherence between the two. Dyskinesia-related oscillations are minimally affected by voluntary movement. When dyskinesia persists during therapeutic deep brain stimulation (DBS), the peak frequency of this signal shifts to half the stimulation frequency. These findings suggest a circuit-level mechanism for the generation of dyskinesia as well as a promising control signal for closed-loop DBS.

Significance statement: Oscillations in brain networks link functionally related brain areas to accomplish thought and action, but this mechanism may be altered or exaggerated by disease states. Invasive recording using implanted electrodes provides a degree of spatial and temporal resolution that is ideal for analysis of network oscillations. Here we used a novel, totally implanted, bidirectional neural interface for chronic multisite brain recordings in humans with Parkinson's disease. We characterized an oscillation between cortex and subcortical modulators that is associated with a serious adverse effect of therapy for Parkinson's disease: dyskinesia. The work shows how a perturbation in oscillatory dynamics might lead to a state of excessive movement and also suggests a possible biomarker for feedback-controlled neurostimulation to treat hyperkinetic disorders.

Keywords: Parkinson's disease; deep brain stimulation; dyskinesia; electrocorticography; local field potentials; motor cortex.

Copyright © 2016 the authors 0270-6474/16/366445-14$15.00/0.

Figures

Figure 1.

Electrode locations, raw signals, and signal stability over time. A, Schematic of the Activa PC+S. B, Electrode locations (indicated in red) for Patients 1 and 2 over cortex (top) and in STN (bottom). Locations are derived from the preoperative MRI merged with the intraoperative CT. C, Raw signals from STN and Motor cortex. D, Root mean square voltage off DBS for motor cortex ECoG potentials and STN LFP for each patient, recorded over 12 months. Signals are relatively stable over time.

Figure 2.

Gamma oscillations distinguish the dyskinetic and nondyskinetic states. A, Example of motor cortex log PSD, STN log PSD, coherence, and phase coherence from Patient 2 at rest (all on medications). The PSD scale is 10 * log10(μV2/Hz). B, Schematic of PSD height and width calculation. Original PSDs (panel 1) were flattened and normalized (panel 2; see Materials and Methods) to identify the peak frequency in the 62–83 Hz range (red dot). The height of this peak was calculated by subtracting the original log PSD value at this frequency (red dot) from the average of the PSDs 5 Hz above and below the peak frequency (black dots, average indicated with green line). The height is indicated with the vertical black line (panel 3). The width of the peak at half the height was also calculated (red line, panel 4). For coherence, the maximum coherence in the 62–83 Hz range was used as the height. C, Group analysis for peak gamma amplitude. There was significantly higher gamma power during dyskinesia for each measure (Table 2). Data are displayed as boxplots, where center is median, box top and bottom are 25th and 75th percentiles, and whiskers reflect range of data excluding outliers. Outliers are denoted with plus signs. ** indicates p < 0.001. D, Receiver operating characteristic curves for each measure showing the false positive and true positive rates derived from fitting the data to a general linear model and examining rates for different classification threshold values for each biomarker.

Figure 3.

A, B, Grouped data from Figure 2C segregated by patient (Patient 1, A; Patient 2, B) for each measure examined (motor cortex and STN PSD, coherence, and phase coherence). p values are reported in Table 2. Data are displayed with boxplots as in Figure 2C. ** indicates p < 0.001.

Figure 4.

Grouped data from Figure 2C for recording off DBS only. Values are significantly higher during dyskinesia for all measures, demonstrating that our findings are not driven by a stimulation artifact. p values reported in Table 3. Data are displayed with boxplots as in Figure 2C. ** indicates p < 0.001.

Figure 5.

The gamma oscillation as a function of medication state. The oscillation is a relatively poor marker for medication state. The figure is similar to Figure 2D, except here recordings are segregated based on medication state rather than presence or absence of dyskinesia. All home recordings were considered “on medication” unless patients indicated that they were off medications overnight, since patients were maintaining their regular medication regimen.

Figure 6.

STN–motor cortex phase differences at the narrowband gamma frequency. A, Instantaneous phase differences between STN and motor cortex grouped for all recordings (on and off DBS) with and without dyskinesia. The number of sample points per bin is different for each plot due to differing amounts of data included for each. For the “dyskinesia” recordings, the outermost marker indicates 300,000 sample points, and the second outermost indicates 200,000. For the “no dyskinesia” recordings, the outermost marker indicates 400,000 sample points, and the second outermost indicates 300,000. B, Instantaneous phase differences between STN and motor cortex grouped for all recordings off DBS, with and without dyskinesia. For the “dyskinesia” recordings, the outermost marker indicates 200,000 sample points, and the second outermost indicates 150,000. For the “no dyskinesia” recordings, the outermost marker indicates 250,000 sample points, and the second outermost indicates 125,000.

Figure 7.

Correlation between dyskinesia severity and gamma oscillation amplitude. There is a correlation between dyskinesia severity (measured with dyskinesia rating scale; see Materials and Methods) and peak height of gamma oscillation in motor cortex (r = 0.63, p = 3.58 × 10−13, Spearman correlation, indicated with red regression line). However, this effect was mostly driven by the presence or absence of dyskinesia (when recordings with no dyskinesia were excluded, r = 0.41, p = 0.016, Spearman correlation, indicated with black regression line). This observation is consistent with a bimodal or sigmoidal relationship between dyskinesia severity and gamma oscillation height (Halje et al., 2012). Only in-clinic recordings were included in this analysis (where the dyskinesia rating scale was available, 107 recordings total). The sum of dyskinesia severity from all effectors measured with the dyskinesia rating scale (arms, legs, trunk, neck, and face) was derived to quantify dyskinesia severity. Average value for recordings without dyskinesia is indicated with the large yellow circle.

Figure 8.

Beta oscillations in the dyskinetic and nondyskinetic states. The figure shows a grouped analysis analogous to that shown in Figure 2C, except focusing on the beta range (13–30 Hz). This analysis includes only recordings with DBS off, to avoid artifacts caused by DBS subharmonics in the beta range. There are no significant differences except for decreased phase coherence between motor cortex and STN during dyskinesia (p = 7.24 × 10−4). Data are displayed with boxplots as in Figure 2C. ** indicates p < 0.001. n.s., Not significant.

Figure 9.

Characterization of peak frequency of the gamma oscillation. A, Frequencies at which the gamma oscillation occurred off DBS for Patients 1 and 2. There does not appear to be a “characteristic frequency” within the gamma range for each patient. B, Correlation between frequency of gamma oscillation in motor cortex versus STN for stimulation off files (Pearson's r = 0.597, p = 0.0016). The y = x line is shown in red.

Figure 10.

Example recordings from patients not included in the grouped statistical analysis. A, B, Examples from Patients 3 (A) and 4 (B) during episodes of dyskinesia versus no dyskinesia (or minimal dyskinesia). Both recordings are on DBS (160 Hz for A, 130 Hz for B). Note that in A, the data were recorded at 422 Hz during a montage recording. In B, data were recorded at 800 Hz as usual. The PSD scale is 10 * log10(μV2/Hz).

Figure 11.

Amplitudes of dyskinesia biomarkers related to the gamma oscillation are minimally affected by voluntary movement. Biomarker amplitudes associated with each recording were segregated both by presence or absence of dyskinesia and presence or absence of voluntary movement (i.e., “walking” or “iPad” recordings compared to other recordings). There were 20 or more recordings included in the analysis for each condition. The data set is the same as that used in Figure 2C. Except for coherence in the nondyskinetic state (p = 0.0063), the movement condition had no effect on biomarker amplitude. n.s., Not significant. Data are displayed with boxplots as in Figure 2C. * indicates p < 0.01.

Figure 12.

Broadband gamma versus gamma oscillation. A, B, Example of broadband gamma increase during movement when Patient 2 was not dyskinetic (A) and when he was dyskinetic (B). Note that in B, the gamma oscillation is also apparent, and distinguishable from the broadband increase. Plots are derived from 20 trials of the iPad reaching task (analysis contains 2 s of movement, 2 s of rest for each trial). In A, the patient was off medications, and in B they were on medications. In both examples they were off DBS. The PSD scale is 10 * log10(μV2/Hz).

Figure 13.

Optimal recording location for cortical gamma oscillations. A, Set of recordings from all contact pairs recorded sequentially (over a time period of 3 min) from Patient 2 during dyskinesia. This recording was obtained with a sampling rate of 422 Hz (required to obtain a rapid sequential “montage recording” across all possible contact pairs) with DBS off. The peak is most strongly observed in contact pairs that include contact 11. The PSD scale is 10 * log10(μV2/Hz). B, Fusion of intraoperative CT with preoperative MRI, showing contact locations with respect to gyral anatomy. Contact 11 (white arrow) is located over the anterior portion of the precentral gyrus as well as precentral sulcus.

Figure 14.

DBS entrains the gamma oscillation at half the stimulation frequency. A, Example from Patient 1 during dyskinesia that was present on DBS (160 Hz) and absent off DBS. The PSD scale is 10 * log10(μV2/Hz). B, Example from Patient 2 with and without dyskinesia on DBS (130 Hz). Note that the gamma oscillation is not present in the recording without dyskinesia, despite a similar stimulation artifact, arguing against the artifact driving the effect. C, When DBS frequency is changed (from 130 to 150 Hz), the gamma oscillation also changes (from 65 to75 Hz). An example from Patient 2 is shown. D, Instantaneous phase difference between STN and motor cortex for a file recorded during DBS while the patient was experiencing dyskinesia. The gamma oscillation has a similar distribution and phase angle as the off stimulation recordings (compare Fig. 6B). In contrast, the same measures at the stimulation frequency (130 Hz) or a folded subharmonic (116 Hz) have a more narrow distribution, consistent with an artifactual source. Example from Patient 2. E, The frequency of the gamma oscillation during DBS wash-in moves from ∼75 Hz to half the stimulation frequency (65 Hz, at 130 Hz stimulation). F, During washout, the gamma oscillation moves back to ∼75–80 Hz. Both E and F are from Patient 2.