Beta-gamma phase-amplitude coupling as non-invasive biomarker of Parkinson's disease
Exploration of the spatial and pathological origins of abnormal beta-gamma phase-amplitude coupling and the impact of dopamine deficiency on brain activity during both resting state and voluntary motor activity of Parkinson patients compared with healthy subjects.
Parkinson disease (PD) is a neurodegenerative disorder resulting from the loss of dopaminergic neurons in the substantia nigra pars compacta. Currently, therapy is largely based on dopamine replacement medication, or deep brain stimulation (DBS), when patients become progressively resistant to drugs after some years. Although DBS has been demonstrated to have effects on a wide range of Parkinson motor symptoms, it remains limited in terms of surgical safety, service lifetime, and strict selection criteria. Therefore, non-invasive brain stimulation (NIBS) has been proposed as a prospective technique for treating PD . This has motivated recent efforts to focus on the temporal dimension of PD related brain activity, in particular brain oscillations, as targets for NIBS intervention . Enhanced phase-amplitude coupling (PAC) between beta (13-30Hz) and broadband gamma (50-150Hz) oscillations has been suggested as a biomarker of PD . Such activity can even be measured with non-invasive scalp EEG . However, its spatial origin and biophysical mechanism are still obscure, limiting its possible use for understanding and treating PD.
This project explores the spatial and pathological origins of abnormal PAC and the impact of dopamine deficiency on brain activity during both resting state and voluntary motor activity of Parkinson patients (recruited from the outpatient clinic of the Department of Neurology University of Leipzig Medical Center) compared with healthy subjects (recruited from MPI CBS). It provides experimental evidence to computational modeling of the pathological basal ganglia thalamocortical pathways, and is ultimately expected to lead to a promising alternative way for the use of NIBS in the clinical therapy of motor impairments under PD.
We establish the spatial basis of resting state PAC using a combination of a least-square minimum variance beamformer and independent component analysis (ICA). In order to gain insight into the anatomical basis and the neuronal mechanisms of PAC, we study for each brain region, whether PAC is different between patients and controls, to what extent PAC correlates with clinical scores, whether the coupled beta and gamma rhythms stem from the same or different brain areas, and if the PAC coupled rhythms also bear a fixed phase relationship (Fig. 1).
Furthermore, we also study transient PAC dynamics in different voluntary movement conditions. The performance of repetitive finger movements is used to assess the severity, progression, and treatment efficacy of PD and related disorders. The schematic diagram of the device for measuring the performance of the finger tapping is presented in Fig. 2. Our hypothesis is that PAC is not stable during voluntary movement but dynamically changes with different movement states and movement patterns. The changes may be related to the performance of PD patients. To test this hypothesis, we investigate the PAC in small time windows along with the progress of the voluntary movement and compare these transient PAC values with the performance state.
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