Clinical correlates of quantitative EEG in Parkinson disease

Neurology ◽  
2018 ◽  
Vol 91 (19) ◽  
pp. 871-883 ◽  
Author(s):  
Victor J. Geraedts ◽  
Lennard I. Boon ◽  
Johan Marinus ◽  
Alida A. Gouw ◽  
Jacobus J. van Hilten ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Functional Connectivity ◽  
Parkinson Disease ◽  
Longitudinal Studies ◽  
Disease Severity ◽  
Quantitative Eeg ◽  
Dominant Frequency ◽  
Cognitive Deterioration ◽  
Individual Level ◽  
Network Analyses

ObjectiveTo assess the relevance of quantitative EEG (qEEG) measures as outcomes of disease severity and progression in Parkinson disease (PD).MethodsMain databases were systematically searched (January 2018) for studies of sufficient methodologic quality that examined correlations between clinical symptoms of idiopathic PD and cortical (surface) qEEG metrics.ResultsThirty-six out of 605 identified studied were included. Results were classified into 4 domains: cognition (23 studies), motor function (13 studies), responsiveness to interventions (7 studies), and other (10 studies). In cross-sectional studies, EEG slowing correlated with global cognitive impairment and with diffuse deterioration in other domains. In longitudinal studies, decreased dominant frequency and increased θ power, reflecting EEG slowing, were biomarkers of cognitive deterioration at an individual level. Results on motor dysfunction and treatment yielded contrasting findings. Studies on functional connectivity at an individual level and longitudinal studies on other domains or on connectivity measures were lacking.ConclusionqEEG measures reflecting EEG slowing, particularly decreased dominant frequency and increased θ power, correlate with cognitive impairment and predict future cognitive deterioration. qEEG could provide reliable and widely available biomarkers for nonmotor disease severity and progression in PD, potentially promoting early diagnosis of nonmotor symptoms and an objective monitoring of progression. More studies are needed to clarify the role of functional connectivity and network analyses.

scholarly journals Quantitative Eeg as a Biomarker in Mild Cognitive Impairment With Lewy Bodies

2020 ◽  
Author(s):  
Julia Schumacher ◽  
John-Paul Taylor ◽  
Calum A. Hamilton ◽  
Michael Firbank ◽  
Ruth A. Cromarty ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lewy Bodies ◽  
Quantitative Eeg ◽  
Dominant Frequency ◽  
Alpha Power ◽  
Healthy Controls ◽  
Operating Characteristics ◽  
Frequency Bands ◽  
Beta Power

Abstract Objectives:To investigate using quantitative EEG (1) differencesbetween patients with mild cognitive impairment with Lewy bodies (MCI-LB) and MCI with Alzheimer’s disease (MCI-AD) and (2) its utilityas a potential biomarker for early differential diagnosis.Methods:We analyzed eyes-closed, resting state, high-density EEG data from highly phenotyped participants (39 MCI-LB, 36 MCI-AD, and 31 healthy controls). EEG measures included spectral power in different frequency bands (delta, theta, pre-alpha, alpha, and beta), theta/alpha ratio, dominant frequency, and dominant frequency variability.Receiver operating characteristics (ROC) analyses were performed to assess diagnostic accuracy.Results:There was a shift in power from beta and alpha frequency bands towards slower frequencies in the pre-alpha and theta range in MCI-LB compared to healthy controls. Additionally, dominant frequency was slower in MCI-LB compared to controls. We found significantly increased pre-alpha power, decreased beta power, and slower dominant frequency in MCI-LB compared to MCI-AD. EEG abnormalities were more apparent in MCI-LB cases with more diagnostic features.There were no significant differences between MCI-AD and controls. In the ROC analysis, beta power and dominant frequency showed the highest area under the curve values of 0.71 and 0.70, respectively. While specificity was high for some measures (up to 0.97 for alpha power and 0.94 for theta/alpha ratio), sensitivity was generally much lower. Conclusions:Early EEG slowing is a specific feature of MCI-LB compared to MCI-AD.However, there is overlap between the two MCI groups which makes it difficult to distinguish between them based on EEG alone.

scholarly journals Cognitive correlates of cerebellar resting-state functional connectivity in Parkinson disease

Neurology ◽  
2019 ◽  
Vol 94 (4) ◽  
pp. e384-e396 ◽  
Author(s):  
Baijayanta Maiti ◽  
Jonathan M. Koller ◽  
Abraham Z. Snyder ◽  
Aaron B. Tanenbaum ◽  
Scott A. Norris ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Functional Connectivity ◽  
Parkinson Disease ◽  
Resting State ◽  
Cognitive Status ◽  
Association Cortex ◽  
Resting State Functional Connectivity ◽  
Clinical Dementia Rating ◽  
Cross Sectional ◽  
Global Cognition

ObjectiveTo investigate in a cross-sectional study the contributions of altered cerebellar resting-state functional connectivity (FC) to cognitive impairment in Parkinson disease (PD).MethodsWe conducted morphometric and resting-state FC-MRI analyses contrasting 81 participants with PD and 43 age-matched healthy controls using rigorous quality assurance measures. To investigate the relationship of cerebellar FC to cognitive status, we compared participants with PD without cognitive impairment (Clinical Dementia Rating [CDR] scale score 0, n = 47) to participants with PD with impaired cognition (CDR score ≥0.5, n = 34). Comprehensive measures of cognition across the 5 cognitive domains were assessed for behavioral correlations.ResultsThe participants with PD had significantly weaker FC between the vermis and peristriate visual association cortex compared to controls, and the strength of this FC correlated with visuospatial function and global cognition. In contrast, weaker FC between the vermis and dorsolateral prefrontal cortex was found in the cognitively impaired PD group compared to participants with PD without cognitive impairment. This effect correlated with deficits in attention, executive functions, and global cognition. No group differences in cerebellar lobular volumes or regional cortical thickness of the significant cortical clusters were observed.ConclusionThese results demonstrate a correlation between cerebellar vermal FC and cognitive impairment in PD. The absence of significant atrophy in cerebellum or relevant cortical areas suggests that this could be related to local pathophysiology such as neurotransmitter dysfunction.

scholarly journals 558 - Multimodal EEG-MRI in the diagnosis of mild cognitive impairment with lewybodies

2021 ◽  
Vol 33 (S1) ◽  
pp. 97-98
Author(s):  
Jerry Hai Kok Tan ◽  
Julia Schumacher ◽  
John-Paul Taylor ◽  
Alan Thomas
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Diagnostic Accuracy ◽  
Visual Assessment ◽  
Structural Mri ◽  
Quantitative Eeg ◽  
Dominant Frequency ◽  
Mri Features ◽  
Beta Power ◽  
Eeg Features

Background:Differentiating mild cognitive impairment with Lewy bodies (MCI-LB) from mild cognitive impairment due to Alzheimer’s disease (MCI-AD) is challenging due to an overlap of symptoms. Quantitative EEG analyses have shown varying levels of diagnostic accuracy, while visual assessment of EEG may be a promising diagnostic method. Additionally, a multimodal EEG-MRI approach may have greater diagnostic utility than individual modalities alone.Research Objective:To evaluate the utility of (1) a structured visual EEG assessment and (2) a machine learning multimodal EEG-MRI approach to differentiate MCI-LB from MCI-AD.Method:300 seconds of eyes-closed, resting-state EEG from 37 MCI-LB and 36 MCI-AD patients were analysed. EEGs were visually assessed for the presence of diffuse, focal, and epileptiform abnormalities, overall grade of abnormalities and focal rhythmic delta activity (FIRDA). Random forest classifiers to discriminate MCI-LB from MCI-AD were trained on combinations of visual EEG, quantitative EEG and structural MRI features. Quantitative EEG features (dominant frequency, dominant frequency variability, theta/alpha ratio and measures of spectral power in the delta, theta, prealpha, alpha and beta bands) and structural MRI features (hippocampal and insular volumes) were obtained from previous analyses of our dataset.Results:Most patients had abnormal EEGs on visual assessment (MCI-LB = 91.9%, MCI-AD = 77.8%). Overall grade (Χ2 (73, 2) = 4.416, p = 0.110), diffuse abnormalities Χ2(73,1) = 3.790, p = 0.052, focal abnormalities Χ2 (73,1) = 3.113, p = 0.077 and FIRDA Χ2(73,1) = 0.862, p = 0.353 did not differ between groups. All multimodal classifiers had similar diagnostic accuracy (area underthe curve, AUC = 0.681 - 0.686) to a classifier that used quantitative EEG features only (AUC =0.668). The feature ‘beta power’ had the highest predictive power in all classifiers.Conclusion:Visual EEG assessment was unable to discriminate between MCI-LB and MCI-AD. However, future work with a more sensitive visual assessment score may yield more promising results.A multimodal EEG-MRI approach does not enhance the diagnostic value of quantitative EEG alone in diagnosing MCI-LB.(326 words)

scholarly journals Quantitative EEG as a biomarker in mild cognitive impairment with Lewy bodies

2020 ◽  
Author(s):  
Julia Schumacher ◽  
John-Paul Taylor ◽  
Calum A. Hamilton ◽  
Michael Firbank ◽  
Ruth A. Cromarty ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lewy Bodies ◽  
Quantitative Eeg ◽  
Dominant Frequency ◽  
Alpha Power ◽  
Healthy Controls ◽  
Operating Characteristics ◽  
Frequency Bands ◽  
Beta Power

Abstract Objectives: To investigate using quantitative EEG (1) differences between patients with mild cognitive impairment with Lewy bodies (MCI-LB) and MCI with Alzheimer’s disease (MCI-AD) and (2) its utility as a potential biomarker for early differential diagnosis. Methods: We analyzed eyes-closed, resting state, high-density EEG data from highly phenotyped participants (39 MCI-LB, 36 MCI-AD, and 31 healthy controls). EEG measures included spectral power in different frequency bands (delta, theta, pre-alpha, alpha, and beta), theta/alpha ratio, dominant frequency, and dominant frequency variability. Receiver operating characteristics (ROC) analyses were performed to assess diagnostic accuracy. Results: There was a shift in power from beta and alpha frequency bands towards slower frequencies in the pre-alpha and theta range in MCI-LB compared to healthy controls. Additionally, dominant frequency was slower in MCI-LB compared to controls. We found significantly increased pre-alpha power, decreased beta power, and slower dominant frequency in MCI-LB compared to MCI-AD. EEG abnormalities were more apparent in MCI-LB cases with more diagnostic features. There were no significant differences between MCI-AD and controls. In the ROC analysis to distinguish MCI-LB from MCI-AD, beta power and dominant frequency showed the highest area under the curve values of 0.71 and 0.70, respectively. While specificity was high for some measures (up to 0.97 for alpha power and 0.94 for theta/alpha ratio), sensitivity was generally much lower. Conclusions: Early EEG slowing is a specific feature of MCI-LB compared to MCI-AD. However, there is overlap between the two MCI groups which makes it difficult to distinguish between them based on EEG alone.

scholarly journals Neuroimaging biomarkers differentiate Parkinson disease with and without cognitive impairment and dementia

2019 ◽  
Author(s):  
Conor Owens-Walton ◽  
David Jakabek ◽  
Brian D. Power ◽  
Mark Walterfang ◽  
Sara Hall ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Parkinson Disease ◽  
Seed Region ◽  
Subcortical Structures ◽  
Caudate Putamen ◽  
Mediodorsal Thalamus ◽  
Posterior Cingulate ◽  
Neuroimaging Biomarkers

AbstractMild cognitive impairment in Parkinson disease places a high burden on patients and is likely a precursor to Parkinson disease-related dementia. Studying the functional connectivity and morphology of subcortical structures within basal ganglia-thalamocortical circuits may uncover neuroimaging biomarkers of cognitive dysfunction in PD. We used an atlas-based seed region-of-interest approach to investigate resting-state functional connectivity of important subdivisions of the caudate nucleus, putamen and thalamus, between controls (n = 33), cognitively unimpaired Parkinson disease subjects (n = 33), Parkinson disease subjects with mild cognitive impairment (n = 22) and Parkinson disease subjects with dementia (n = 17). We then investigated how the morphology of the caudate, putamen and thalamus structures and differed between groups. Results indicate that cognitively unimpaired Parkinson disease subjects, compared to controls, display increased functional connectivity of the dorsal caudate, anterior putamen and mediodorsal thalamic subdivisions with areas across the frontal lobe, as well as reduced functional connectivity of the dorsal caudate with posterior cortical and cerebellar regions. Compared to cognitively unimpaired subjects, Parkinson disease subjects with mild cognitive impairment demonstrated reduced functional connectivity of the mediodorsal thalamus with midline nodes within the executive-control network. Compared to subjects with mild cognitive impairment, subjects with dementia demonstrated reduced functional connectivity of the mediodorsal thalamus with the posterior cingulate cortex, a key node within the default-mode network. Extensive volumetric and surface-based deflation was found in Parkinson disease subjects with dementia. Our research demonstrates how functional connectivity of the caudate, putamen and thalamus are implicated in the pathophysiology of cognitive impairment and dementia in Parkinson disease, with mild cognitive impairment and dementia in Parkinson disease associated with a breakdown in functional connectivity of the mediodorsal thalamus with para- and posterior cingulate regions of the brain.

scholarly journals Aberrant Functional Connectivity Architecture in Alzheimer’s Disease and Mild Cognitive Impairment: A Whole-Brain, Data-Driven Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Bo Zhou ◽  
Hongxiang Yao ◽  
Pan Wang ◽  
Zengqiang Zhang ◽  
Yafeng Zhan ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Disease Severity ◽  
Whole Brain ◽  
Functional Connectivity Strength ◽  
Brain Functional Connectivity ◽  
The Brain ◽  
Connectivity Strength

The purpose of our study was to investigate whether the whole-brain functional connectivity pattern exhibits disease severity-related alterations in patients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Resting-state functional magnetic resonance imaging data were acquired in 27 MCI subjects, 35 AD patients, and 27 age- and gender-matched subjects with normal cognition (NC). Interregional functional connectivity was assessed based on a predefined template which parcellated the brain into 90 regions. Altered whole-brain functional connectivity patterns were identified via connectivity comparisons between the AD and NC subjects. Finally, the relationship between functional connectivity strength and cognitive ability according to the mini-mental state examination (MMSE) was evaluated in the MCI and AD groups. Compared with the NC group, the AD group exhibited decreased functional connectivities throughout the brain. The most significantly affected regions included several important nodes of the default mode network and the temporal lobe. Moreover, changes in functional connectivity strength exhibited significant associations with disease severity-related alterations in the AD and MCI groups. The present study provides novel evidence and will facilitate meta-analysis of whole-brain analyses in AD and MCI, which will be critical to better understand the neural basis of AD.

The Anterior-posterior Functional Connectivity Disconnection in the Elderly with Subjective Memory Impairment and Amnestic Mild Cognitive Impairment

2020 ◽  
Vol 17 (4) ◽  
pp. 373-381
Author(s):  
Wuhai Tao ◽  
Jinping Sun ◽  
Xin Li ◽  
Wen Shao ◽  
Jing Pei ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Memory Impairment ◽  
Amnestic Mild Cognitive Impairment ◽  
Magnetic Resonance Imaging Scan ◽  
Subjective Memory ◽  
Long Distance ◽  
Whole Brain ◽  
Subjective Memory Impairment

Background: Subjective Memory Impairment (SMI) may tremendously increase the risk of Alzheimer’s Disease (AD). The full understanding of the neuromechanism of SMI will shed light on the early intervention of AD. Methods: In the current study, 23 Healthy Controls (HC), 22 SMI subjects and 24 amnestic Mild Cognitive Impairment (aMCI) subjects underwent the comprehensive neuropsychological assessment and the resting-state functional magnetic resonance imaging scan. The difference in the connectivity of the Default Mode Network (DMN) and Functional Connectivity (FC) from the Region of Interest (ROI) to the whole brain were compared, respectively. Results: The results showed that HC and SMI subjects had significantly higher connectivity in the region of the precuneus area compared to aMCI subjects. However, from this region to the whole brain, SMI and aMCI subjects had significant FC decrease in the right anterior cingulum, left superior frontal and left medial superior frontal gyrus compared to HC. In addition, this FC change was significantly correlated with the cognitive function decline in participants. Conclusion: Our study indicated that SMI subjects had relatively intact DMN connectivity but impaired FC between the anterior and posterior brain. The findings suggest that long-distance FC is more vulnerable than the short ones in the people with SMI.

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