Complexity Analysis of Resting-State MEG Activity in Early-Stage Parkinson’s Disease Patients

Complexity Analysis of Resting-State MEG Activity in Early-Stage Parkinson’s Disease Patients

The aim of the present study was to analyze resting-state brain activity in patients with Parkinson’s disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage untreate...

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Veröffentlicht in:Annals of biomedical engineering 2011-12, Vol.39 (12), p.2935-2944
Hauptverfasser: Gómez, Carlos, Olde Dubbelink, Kim T. E., Stam, Cornelis J., Abásolo, Daniel, Berendse, Henk W., Hornero, Roberto
Format: Artikel
Sprache:eng
Schlagworte:
Accuracy
Aged
Biochemistry
Biological and Medical Physics
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Brain
Cerebral Cortex - physiopathology
Classical Mechanics
Classification
Complexity
Conversion
Discriminant Analysis
Female
Humans
Magnetoencephalography - methods
Male
Middle Aged
Parkinson Disease - classification
Parkinson Disease - physiopathology
Parkinson's disease
Patients
ROC Curve
Sensitivity and Specificity
Temporal logic
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Zusammenfassung:The aim of the present study was to analyze resting-state brain activity in patients with Parkinson’s disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage untreated PD patients and 20 age-matched control subjects. Artifact-free epochs of 4 s (1250 samples) were analyzed with Lempel–Ziv complexity ( LZC ), applying two- and three-symbol sequence conversion methods. The results showed that MEG signals from PD patients are less complex than control subjects’ recordings. We found significant group differences ( p -values
ISSN:0090-6964
1573-9686
DOI:10.1007/s10439-011-0416-0