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Abstract
Parkinson’s disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients’ disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.
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1 Karolinska Institutet, NatMEG, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Copenhagen University Hospital - Amager and Hvidovre, Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen, Denmark (GRID:grid.4973.9) (ISNI:0000 0004 0646 7373)
2 Karolinska Institutet, NatMEG, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Karolinska Institutet, Section of Neurology, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); University Hospital Marburg, Department of Neurology, Marburg, Germany (GRID:grid.411067.5) (ISNI:0000 0000 8584 9230)
3 Karolinska Institutet, NatMEG, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Uppsala University, Department of Women’s and Children’s Health, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457)
4 Karolinska Institutet, NatMEG, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Nanyang Technological University, Cognitive Neuroimaging Centre, Lee Kong Chien School of Medicine, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361); Massachusetts Institute of Technology, McGovern Institute of Brain Research, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786)
5 Karolinska Institutet, Division of Clinical Geriatrics, Center for Alzheimer’s Research, Department of Neurobiology, Care Sciences, and Society, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Mayo Clinic, Department of Radiology, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X); Las Palmas de Gran, Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Canaria, España (GRID:grid.512367.4) (ISNI:0000 0004 5912 3515)
6 Karolinska Institutet, NatMEG, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
7 Karolinska Institutet, Section of Neurology, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)