Subthalamic nucleus phase–amplitude coupling correlates with motor impairment in Parkinson’s disease

OBJECTIVEThe objective of this study was to investigate the correlation between the quantitative susceptibility mapping (QSM) signal gradient of the subthalamic nucleus (STN) and motor impairment in patients with Parkinson’s disease (PD).METHODSAll PD patients who had undergone QSM MRI for presurgical deep brain stimulation (DBS) planning were eligible for inclusion in this study. The entire STN and its three functional subdivisions, as well as the adjacent white matter (WM), were segmented and measured. The QSM value difference between the entire STN and adjacent WM (STN-WM), between the limbic and associative regions of the STN (L-A), and between the associative and motor regions of the STN (A-M) were obtained as measures of gradient and were input into an unsupervised k-means clustering algorithm to automatically categorize the overall boundary distinctness between the STN and adjacent WM and between STN subdivisions (gradient blur [GB] and gradient sharp [GS] groups). Statistical tests were performed to compare clinical and image measurements for discrimination between GB and GS groups.RESULTSOf the 39 study patients, 19 were categorized into the GB group and 20 into the GS group, based on quantitative cluster analysis. The GB group had a significantly higher presurgical off-medication Unified Parkinson’s Disease Rating Scale Part III score (51.289 ± 20.741) than the GS group (38.5 ± 16.028; p = 0.037). The GB group had significantly higher QSM values for the STN and its three subdivisions and adjacent WM than those for the GS group (p < 0.01). The GB group also demonstrated a significantly higher STN-WM gradient in the right STN (p = 0.01). The GB group demonstrated a significantly lower L-A gradient in both the left and the right STN (p < 0.02).CONCLUSIONSAdvancing PD with more severe motor impairment leads to more iron deposition in the STN and adjacent WM, as shown in the QSM signal. Loss of the STN inner QSM signal gradient should be considered as an image marker for more severe motor impairment in PD patients.

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Synchronised spiking activity underlies phase amplitude coupling in the subthalamic nucleus of Parkinson's disease patients

Neurobiology of Disease ◽

10.1016/j.nbd.2019.02.005 ◽

2019 ◽

Vol 127 ◽

pp. 101-113 ◽

Cited By ~ 18

Author(s):

Anders Christian Meidahl ◽

Christian K.E. Moll ◽

Bernadette C.M. van Wijk ◽

Alessandro Gulberti ◽

Gerd Tinkhauser ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Subthalamic Nucleus ◽

Phase Amplitude ◽

Spiking Activity

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Synchronised spiking activity underlies phase amplitude coupling in the subthalamic nucleus of Parkinson’s disease patients

10.1101/433334 ◽

2018 ◽

Cited By ~ 1

Author(s):

Anders Christian Meidahl ◽

Christian K.E. Moll ◽

Bernadette van Wijk ◽

Alessandro Gulberti ◽

Gerd Tinkhauser ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Subthalamic Nucleus ◽

Single Unit ◽

Closed Loop ◽

Beta Phase ◽

Frequency Range ◽

Phase Amplitude ◽

Deep Brain ◽

Spiking Activity

AbstractBoth phase-amplitude coupling (PAC) and beta-bursts in the subthalamic nucleus have been significantly linked to symptom severity in Parkinson’s disease (PD) in humans and emerged independently as competing biomarkers for closed-loop deep brain stimulation (DBS). However, the underlying nature of subthalamic PAC is poorly understood and its relationship with transient beta burst-events has not been investigated. To address this, we studied macro- and micro electrode recordings of local field potentials (LFPs) and single unit activity from 15 hemispheres in 10 PD patients undergoing DBS surgery. PAC between beta phase and high frequency oscillation (HFO) amplitude was compared to single unit firing rates, spike triggered averages, power spectral densities and phase-spike locking, and was studied in periods of beta-bursting. We found a significant synchronisation of spiking to HFOs and correlation of mean firing rates with HFO-amplitude when the latter was coupled to beta phase (i.e. in the presence of PAC). In the presence of PAC, single unit power spectra displayed peaks in the beta and HFO frequency range and the HFO frequency was correlated with that in the LFP. Finally, PAC significantly increased with beta burst-duration. Our findings offer new insight in the pathology of Parkinson’s disease by providing evidence that subthalamic PAC reflects the locking of spiking activity to network beta oscillations and that this coupling progressively increases with beta-burst duration. These findings suggest that beta-bursts capture periods of increased subthalamic input/output synchronisation in the beta frequency range and have important implications for therapeutic closed-loop DBS.Significance statementIdentifying biomarkers for closed-loop deep brain stimulation (DBS) has become an increasingly important issue in Parkinson’s Disease (PD) research. Two such biomarkers, phase–amplitude coupling (PAC) and beta-bursts, recorded from the implanted electrodes in subthalamic nucleus in PD patients, correlate with motor impairment. However, the physiological basis of PAC, and it relationship to beta bursts, is unclear. We provide multiple lines of evidence that PAC in the human STN reflects the locking of spiking activity to network beta oscillations and that this coupling progressively increases with the duration of beta-bursts. This suggests that beta-bursts capture increased subthalamic input/output synchronisation and provides new insights in PD pathology with direct implications for closed-loop DBS therapy strategies.

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Effect of levodopa on electroencephalographic biomarkers of the parkinsonian state

Journal of Neurophysiology ◽

10.1152/jn.00141.2019 ◽

2019 ◽

Vol 122 (1) ◽

pp. 290-299 ◽

Cited By ~ 3

Author(s):

Andrew M. Miller ◽

Svjetlana Miocinovic ◽

Nicole C. Swann ◽

Sheila S. Rajagopalan ◽

David M. Darevsky ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Voluntary Movement ◽

Motor Impairment ◽

Body Part ◽

Dopaminergic Therapy ◽

Scalp Eeg ◽

New Findings ◽

Phase Amplitude ◽

Motor Improvement

The objective of this study was to evaluate proposed electroencephalographic (EEG) biomarkers of Parkinson’s disease (PD) and test their correlation with motor impairment in a new, well-characterized cohort of PD patients and controls. Sixty-four-channel EEG was recorded from 14 patients with rigid-akinetic PD with minimal tremor and from 14 age-matched healthy controls at rest and during voluntary movement. Patients were tested off and on medication during a single session. Recordings were analyzed for phase-amplitude coupling over sensorimotor cortex and for pairwise coherence from all electrode pairs in the recording montage (distributed coherence). Phase-amplitude coupling and distributed coherence were found to be elevated Off compared with On levodopa, and their reduction was correlated with motor improvement. In the Off medication state, phase-amplitude coupling was greater in sensorimotor contacts contralateral to the most affected body part and reduced by voluntary movement. We conclude that phase-amplitude coupling and distributed coherence are cortical biomarkers of the parkinsonian state that are detectable noninvasively and may be useful as objective aids for management of dopaminergic therapy. Several analytic methods may be used for noninvasive measurement of abnormal brain synchronization in PD. Calculation of phase-amplitude coupling requires only a single electrode over motor cortex. NEW & NOTEWORTHY Several EEG biomarkers of the parkinsonian state have been proposed that are related to abnormal cortical synchronization. We report several new findings in this study: correlations of EEG markers of synchronization with specific motor signs of Parkinson’s disease (PD), and demonstration that one of the EEG markers, phase-amplitude coupling, is more elevated over the more clinically affected brain hemisphere. These findings underscore the potential utility of scalp EEG for objective, noninvasive monitoring of medication state in PD.

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Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson’s disease

10.1101/2020.04.27.064246 ◽

2020 ◽

Author(s):

Benoit Duchet ◽

Filippo Ghezzi ◽

Gihan Weerasinghe ◽

Gerd Tinkhauser ◽

Andrea A. Kühn ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Subthalamic Nucleus ◽

Motor Impairment ◽

Burst Duration ◽

Pathological State ◽

Motor Symptoms ◽

Biologically Inspired ◽

Beta Oscillations ◽

Healthy State

AbstractParkinson’s disease motor symptoms are associated with an increase in subthalamic nucleus beta band oscillatory power. But these oscillations are phasic, and there is a growing body of evidence suggesting that beta burst duration may be of critical importance to motor symptoms, making insights into the dynamics of beta bursting generation valuable. In this study, we ask the question “Can average burst duration reveal how dynamics change between the ON and OFF medication states?”. Our analysis of local field potentials from the subthalamic nucleus demonstrates using linear surrogates that the system generating beta oscillations acts in a more non-linear regime OFF medication and that the change in the degree of non-linearity is correlated with motor impairment. Further, we pinpoint specific dynamical changes responsible for changes in the temporal patterning of beta oscillations between medication states by fitting to data biologically inspired models, and simpler beta envelope models. Finally, we show that the non-linearity can be directly extracted from average burst duration profiles under the assumption of constant noise in envelope models. This reveals that average burst duration profiles provide a window into burst dynamics, which may underlie the success of burst duration as a biomarker. In summary, we demonstrate a relationship between average burst duration profiles, dynamics of the system generating beta oscillations, and motor impairment, which puts us in a better position to understand the pathology and improve therapies such as deep brain stimulation.Author summaryIn Parkinson’s disease, motor impairment is associated with abnormal oscillatory activity of neurons in deep motor regions of the brain. These oscillations come in the shape of bursts, and the duration of these bursts has recently been shown to be of importance to motor symptoms. To better understand the disease and refine therapies, we relate the duration of these bursts to properties of the system generating them in the pathological state and in a proxy of the healthy state. The data suggest that the system generating bursts is more complex in the pathological state, and we show that a measure of this complexity is associated with motor impairment. We propose biologically inspired models and simpler models that can generate the burst patterns observed in the pathological and healthy state. The models confirm what was observed in data, and tell us how burst generation mechanisms could differ in the disease. Finally, we identify a mathematical link allowing to infer properties of the burst generating system from burst duration. This sheds some light on the significance of burst duration as a marker of pathology.

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Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson’s disease

PLoS Computational Biology ◽

10.1371/journal.pcbi.1009116 ◽

2021 ◽

Vol 17 (7) ◽

pp. e1009116

Author(s):

Benoit Duchet ◽

Filippo Ghezzi ◽

Gihan Weerasinghe ◽

Gerd Tinkhauser ◽

Andrea A. Kühn ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Deep Brain Stimulation ◽

Subthalamic Nucleus ◽

Brain Stimulation ◽

Motor Impairment ◽

Burst Duration ◽

Motor Symptoms ◽

Beta Oscillations ◽

Deep Brain

Parkinson’s disease motor symptoms are associated with an increase in subthalamic nucleus beta band oscillatory power. However, these oscillations are phasic, and there is a growing body of evidence suggesting that beta burst duration may be of critical importance to motor symptoms. This makes insights into the dynamics of beta bursting generation valuable, in particular to refine closed-loop deep brain stimulation in Parkinson’s disease. In this study, we ask the question “Can average burst duration reveal how dynamics change between the ON and OFF medication states?”. Our analysis of local field potentials from the subthalamic nucleus demonstrates using linear surrogates that the system generating beta oscillations is more likely to act in a non-linear regime OFF medication and that the change in a non-linearity measure is correlated with motor impairment. In addition, we pinpoint the simplest dynamical changes that could be responsible for changes in the temporal patterning of beta oscillations between medication states by fitting to data biologically inspired models, and simpler beta envelope models. Finally, we show that the non-linearity can be directly extracted from average burst duration profiles under the assumption of constant noise in envelope models. This reveals that average burst duration profiles provide a window into burst dynamics, which may underlie the success of burst duration as a biomarker. In summary, we demonstrate a relationship between average burst duration profiles, dynamics of the system generating beta oscillations, and motor impairment, which puts us in a better position to understand the pathology and improve therapies such as deep brain stimulation.

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