Subthalamic nucleus phase-amplitude coupling correlates with motor impairment in Parkinson's disease.
- Authors
- van Wijk, Bernadette C M; Beudel, Martijn; Jha, Ashwani; Oswal, Ashwini; Foltynie, Tom; Hariz, Marwan I; Limousin, Patricia; Zrinzo, Ludvic; Aziz, Tipu Z; Green, Alexander L; Brown, Peter; Litvak, Vladimir
- Year
- 2016
- Journal
- Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
- PMID
- 26971483
- DOI
- 10.1016/j.clinph.2016.01.015
- PMCID
- PMC4803022
OBJECTIVE: High-amplitude beta band oscillations within the subthalamic nucleus are frequently associated with Parkinson's disease but it is unclear how they might lead to motor impairments. Here we investigate a likely pathological coupling between the phase of beta band oscillations and the amplitude of high-frequency oscillations around 300 Hz. METHODS: We analysed an extensive data set comprising resting-state recordings obtained from deep brain stimulation electrodes in 33 patients before and/or after taking dopaminergic medication. We correlated mean values of spectral power and phase-amplitude coupling with severity of hemibody bradykinesia/rigidity. In addition, we used simultaneously recorded magnetoencephalography to look at functional interactions between the subthalamic nucleus and ipsilateral motor cortex. RESULTS: Beta band power and phase-amplitude coupling within the subthalamic nucleus correlated positively with severity of motor impairment. This effect was more pronounced within the low-beta range, whilst coherence between subthalamic nucleus and motor cortex was dominant in the high-beta range. CONCLUSIONS: We speculate that the beta band might impede pro-kinetic high-frequency activity patterns when phase-amplitude coupling is prominent. Furthermore, results provide evidence for a functional subdivision of the beta band into low and high frequencies. SIGNIFICANCE: Our findings contribute to the interpretation of oscillatory activity within the cortico-basal ganglia circuit.
Grand-average PAC and power spectral densities separated by OFF and ON dopaminergic states. (A) Higher PAC values were observed in the OFF state, which were centred around frequencies in the lower beta and HFO range. (B) Percentage of cases with significant PAC (p < .05) for all beta and HFO frequency combinations in the spectrum. (C) PAC averaged across all HFO frequencies (left) or across all beta frequencies (right) was significantly higher for lower beta band frequencies in the OFF (blue) compared to ON (purple) medication state, and showed a shift in peak frequency within the HFO range. Yellow patches indicate for which 1 Hz frequency bins significant differences were detected between OFF and ON as determined with independent samples t-tests (p < .05). (D) The grand-average power spectral densities expressed similar modulations as PAC. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Histogram of peak frequencies within the spectral beta band. All spectral peaks and sub-peaks within the beta band were included for all subjects, conditions, and STN channels. This revealed a clear bimodal pattern. Overlaid in red is the optimal fit of a mixture of two normal distributions. The first distribution had its mean at 16.6 Hz and a standard deviation of 1.99 Hz, the second distribution at 24.79 Hz and a standard deviation of 2.81 Hz. The lowest point between distributions (20.36 Hz) was taken as the cut-off frequency between low- and high-beta ranges. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Distribution of peak frequencies and phase angles within the low- and high-beta range. (A) Histograms show the distance between peak frequencies for PAC and corresponding power spectral densities within individual channels. Bins represent 0.5 Hz intervals. The observed number of cases for each bin was compared against 1000 surrogate histograms obtained by randomly reshuffling the PAC peak frequencies within the low- or high-beta ranges. Spectral peak frequencies were left at their observed values. Bins exceeding the .05 or .95 percentiles are indicated with an asterisk. For the low-beta range (left), a significantly large proportion of samples were found to have PAC and spectral peaks within 0.5 Hz proximity. For visualisation, a histogram is plotted for the pair-wise distance between a large number of uniformly distributed frequencies within the low-beta range (middle). The high-beta range did not show an exceedingly large proportion of samples with peaks in close proximity (right). (B) Distribution of phase angles computed for the beta–HFO frequency combinations for which PAC was maximal. Only one channel per STN site was taken into account, resulting in 101 samples considered. A significant non-uniform distribution was found only for the low-beta range: mean angle = 8.8° (p = .022).
Regression analyses between hemibody bradykinesia/rigidity UPDRS scores and mean beta/HFO power and PAC separately. Samples taken from the OFF medication state are depicted in blue, samples from the ON state in purple. Note that OFF and ON states were combined in the computation of the regression coefficients. Correlation coefficients and p-values are indicated for each plot with significant relations in bold. (A) Low-beta range; (B) High-beta range; (C) HFO. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Correlations between UDPRS scores and PAC/power across different frequency ranges. Pair-wise correlations were performed between hemibody bradykinesia/rigidity UPDRS scores and either PAC or spectral power using a moving frequency window with 4 Hz width and centred on frequencies from 7 to 33 Hz with 1 Hz steps. Correlation coefficients r were highest and p-values lowest for centre-frequencies in the lower-beta range. Correlations ceased to be significant towards the theta/alpha range, as well as the higher beta band.
Distinct beta frequency ranges for STN activity and STN-motor cortex interactions. (A) Grand-average PAC between HFO in the STN and beta band activity in the motor cortex. Spectra are averaged across OFF and ON medication states and left/right STN channels in 11 subjects, comprising a total of 128 recordings. Unlike beta–HFO PAC in the STN, PAC between STN and motor cortex (STN-M) was found to be weaker and large clusters of significant beta/HFO frequency combinations were rarely detected. (B) Differential effects in PAC and coherence within the low- and high-beta range. Beta–HFO PAC within STN was mainly strong for low beta band frequencies, whereas beta band coherence between STN and motor cortex centred around high beta frequencies. This might explain why no distinct PAC was found between the phase of beta band cortical activity and HFO amplitude in the STN. The strongest modulations in spectral power with dopaminergic treatment were also found in the lower beta frequency range within the STN.
| # | Section | Preview |
|---|---|---|
| 40 | Discussion — Finding biomarkers of Parkinson’s disease | Correlation coefficients with motor impairment were relatively low (maximum value was found to be… |
| 41 | Discussion — Finding biomarkers of Parkinson’s disease | low coefficients may indicate that constraining effects of the low-beta rhythm on HFO activity… |
| 42 | Discussion — Finding biomarkers of Parkinson’s disease | The magnitude of PAC and spectral power detected in our recorded signals might have depended on the… |
| 43 | Discussion — Finding biomarkers of Parkinson’s disease | The identification of biomarkers for Parkinson’s disease is crucial for understanding its… |
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