Neural synchronization analysis of electroencephalography coherence in patients with Parkinson’s disease-related mild cognitive impairment

Mano, Tomoo; Kinugawa, Kaoru; Ozaki, Maki; Kataoka, Hiroshi; Sugie, Kazuma

doi:10.1016/j.prdoa.2022.100140

Cited by 7 publications

(1 citation statement)

References 19 publications

(59 reference statements)

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“…4 ANOVA tests were performed on proportion of each dFC state. Significant differences were only found for Beta (13-30 Hz) state1, Gamma (30-50 Hz) state5 and state6 across HC, PD-off, and PD-on groups mainly to changes in the alpha frequency band [43,44], no significantly different FC states within alpha band were found from both data set 1 and data set 2. Otherwise, impaired channelwise dFC states (significant differences in the proportions of state5 and state6) in gamma band in PD were found for data set 1, in accordance with [12,45].…”

Section: Discussionmentioning

confidence: 80%

Dynamic channelwise functional-connectivity states extracted from resting-state EEG signals of patients with Parkinson’s disease

Ding,

Weng,

et al. 2024

Egypt J Neurol Psychiatry Neurosurg

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Background Parkinson’s disease (PD) is a progressive neurodegenerative disease that usually happens to elderly people, with a wide range of motor and dementia symptoms. An objective and convenient biomarker for PD detection is extremely valuable, especially one that could be acquired non-invasively and low-costly. To this end, this study used resting-state scalp electroencephalography (EEG) signals to explore dynamic functional-connectivity (dFC) states between each pair of EEG recording channels, without source localization. Methods dFC refers to synchronization patterns over time between each pair of EEG channels. First, five frequency bands were extracted from EEG signals with fourth-order Butterworth bandpass filter, including delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (8–30 Hz) and gamma (30–50 Hz). Then, after non-random joint fluctuation was measured with weighted symbolic mutual information (wSMI) algorithm, whole-brain dynamic channelwise dFC states were estimated, and classified with k-means clustering. At last, FC state occurrences were calculated, and ANOVA analyses were performed for each state. Two open-source resting-state EEG data sets (https://doi.org/10.18112/openneuro.ds002778.v1.0.4: 32 channels, 16 health controls and 15 PD subjects. https://doi.org/10.18112/openneuro.ds003490.v1.1.0: 64 channels, 25 health controls and 25 PD subjects) were used to test our methods. Results Significant changes in proportions of various dFC states within beta frequency-band were consistently observed in these both data sets (p value < 0.05). Conclusions Our findings suggest that channelwise dFC states within beta frequency-band directly extracted from resting-state scalp–EEG recordings could potentially serve as a biomarker of PD.

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Section: Discussionmentioning

confidence: 80%

Dynamic channelwise functional-connectivity states extracted from resting-state EEG signals of patients with Parkinson’s disease

Ding,

Weng,

et al. 2024

Egypt J Neurol Psychiatry Neurosurg

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Textural feature of EEG signals as a new biomarker of reward processing in Parkinson’s disease detection

Ezazi

Ghaderyan

2022

Biocybernetics and Biomedical Engineering

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Changes in brain functional connectivity between on and off states and their relationship with cognitive impairment in Parkinson’s disease

Kinugawa,

Mano,

Sugie

2024

Sci Rep

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Parkinson’s disease (PD) is characterized by motor and non-motor symptoms. Cognitive decline is crucial in disease progression and affect quality of life; however, their underlying mechanisms in PD remain unclear. We explored the relationship between cognitive impairment and functional connectivity (FC) using resting-state functional magnetic resonance imaging in 26 patients with sporadic PD, focusing on the changes in FC between on and off states. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) score. The correlation between MMSE scores and changes in FC values during on and off states was assessed using Pearson’s correlation coefficient. The correlation between changes in FC during the on and off periods and cognitive function differed for each cognitive function item. MMSE memory scores were positively correlated with FC between the brainstem and the left cerebral hemisphere. MMSE attention scores were positively correlated with FC between the bilateral thalamus and frontal lobes and negatively correlated with FC between the left cerebral hemispheres. These findings may facilitate our understanding of the neural correlates underlying cognitive impairment in PD and help develop treatment strategies to preserve cognitive function. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-78642-6.

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Neural synchronization analysis of electroencephalography coherence in patients with Parkinson’s disease-related mild cognitive impairment

Cited by 7 publications

References 19 publications

Dynamic channelwise functional-connectivity states extracted from resting-state EEG signals of patients with Parkinson’s disease

Dynamic channelwise functional-connectivity states extracted from resting-state EEG signals of patients with Parkinson’s disease

Textural feature of EEG signals as a new biomarker of reward processing in Parkinson’s disease detection

Changes in brain functional connectivity between on and off states and their relationship with cognitive impairment in Parkinson’s disease

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