Low-Frequency MEG Activity and MRI Evaluation in Parkinson's Disease

Kotini, A; Anninos, P. A.; Adamopoulos, Adam; Prassopoulos, Panos

doi:10.1007/s10548-005-7901-4

Cited by 26 publications

(18 citation statements)

References 20 publications

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“…Finally, MEG studies also showed that PD is associated with a slowing of resting state oscillatory brain activity. 3,20,35 Stoffers et al 35 not only confirmed previously reported slowing, but for the first time made clear that these changes already occurred in the first clinical stages of PD in untreated patients. As an alternative to spectral analyses, some research studies have focused on the application of linear connectivity measures to explore the functional interactions between brain regions.…”

Section: Introductionsupporting

confidence: 54%

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

et al. 2011

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Abstract-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 <0.01) for the 10 major cortical areas analyzed (e.g., bilateral frontal, central, temporal, parietal, and occipital regions). In addition, using receiver-operating characteristic curves with a leave-one-out cross-validation procedure, a classification accuracy of 81.58% was obtained. In order to investigate the best combination of LZC results for classification purposes, a forward stepwise linear discriminant analysis with leave-one out cross-validation was employed. LZC results (threesymbol sequence conversion) from right parietal and temporal brain regions were automatically selected by the model. With this procedure, an accuracy of 84.21% (77.78% sensitivity, 90.0% specificity) was achieved. Our findings demonstrate the usefulness of LZC to detect an abnormal type of dynamics associated with PD.

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Section: Introductionsupporting

confidence: 54%

“…The most common alteration in PD is generalized slowing of brain activity. 3,20,29,34,35 PD patients showed a power decrease at the EEG beta band and an increase at the theta band. 34 In another study, 29 the patients presented diffuse slowing of their quantitative EEG (qEEG) when compared with age-matched controls.…”

Section: Introductionmentioning

confidence: 97%

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

et al. 2011

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“…In a similar sense, both EEG and MEG slowing have also been reported in other neurodegenerative diseases like mild cognitive impairment [13,36], vascular dementia [28,35,54], Lewy body dementia [18,31], major depression [34,55,56], dementia associated with Parkinson's disease [31,57,58], Pick's disease [59], Huntington's chorea [60] and progressive supranuclear palsy [31]. To extract accurate markers of AD, further studies should analyze differences in the slowing of EEG/MEG rhythms when comparing AD and the aforementioned diseases.…”

Section: Discussionmentioning

confidence: 62%

Extraction of spectral based measures from MEG background oscillations in Alzheimer's disease

Poza

Hornero

Abásolo

et al. 2007

Medical Engineering & Physics

104

160

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“…Recent studies using EEG or MEG have noted that there was stronger increase of power in demented as compared to non-demented PD patients (Caviness et al 2007;Neufeld et al 1994;Soikkeli et al 1991), and the latter showed the increase of power in low frequency domain (Bosboom et al 2006;Kotini et al 2005;Serizawa et al 2008;Moazami-Goudarzi et al 2008), or even in all frequency bands (Tanaka et al 2000) in comparison with controls. For example, Soikkeli et al (1991) reported an increase of h activity and a decrease of b power in demented PD patients using FFT analysis of EEG data obtained with a single occipital electrode, and Neufeld et al (1994) also suggested consistent trend of increase in the d-and h-band and a significant decrease in the a-band for demented PD patients, but both of them did not obtain similar results in non-demented patients relative to controls.…”

Section: Discussionmentioning

confidence: 98%

Investigation of EEG abnormalities in the early stage of Parkinson’s disease

et al. 2013

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The objective of the present study was to investigate brain activity abnormalities in the early stage of Parkinson's disease (PD). To achieve this goal, eyes-closed resting state electroencephalography (EEG) signals were recorded from 15 early-stage PD patients and 15 agematched healthy controls. The AR Burg method and the wavelet packet entropy (WPE) method were used to characterize EEG signals in different frequency bands between the groups, respectively. In the case of the AR Burg method, an increase of relative powers in the d-and h-band, and a decrease of relative powers in the a-and b-band were observed for patients compared with controls. For the WPE method, EEG signals from patients showed significant higher entropy over the global frequency domain. Furthermore, WPE in the c-band of patients was higher than that of controls, while WPE in the d-, h-, a-and b-band were all lower. All of these changes in EEG dynamics may represent early signs of cortical dysfunction, which have potential use as biomarkers of PD in the early stage. Our findings may be further used for early intervention and early diagnosis of PD.

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Low-Frequency MEG Activity and MRI Evaluation in Parkinson's Disease

Abstract: It is suggested that the MEG could be a complementary method in the diagnostic evaluation of PD using spatial distribution of the raw data in the frequency domain.

Cited by 26 publications

References 20 publications

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

Extraction of spectral based measures from MEG background oscillations in Alzheimer's disease

Investigation of EEG abnormalities in the early stage of Parkinson’s disease

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