Phase lag index and spectral power as QEEG features for identification of patients with mild cognitive impairment in Parkinson's disease

Chaturvedi, Menorca; Bogaarts, J.G.; Kozak, Vitalii V.; Hatz, Florian; Gschwandtner, Ute; Meyer, Antonia; Fuhr, Peter; Röth, Volker

doi:10.1016/j.clinph.2019.07.017

“…Notably, Nissim et al found that paired active-transcranial direct current stimulation (tDCS) over the left DLPFC together with cognitive training significantly increased working memory performance, as well as functional connectivity between the left DLPFC and right inferior parietal lobule in older adults ( Nissim et al, 2019 ), which may also indicate that the DLPFC connectivity pattern plays a crucial role in cognitive function. On the other hand, our results also corroborate previous studies of changed functional connectivity in patients with PD that is related to their cognitive impairments ( Bertrand et al, 2016 ; Hassan et al, 2017 ; Chaturvedi et al, 2019 ; Sanchez-Dinorin et al, 2021 ). Among them, Hassan et al demonstrated that lower edge-wise connectivity in the alpha1 and alpha2 frequencies was associated with lower cognitive state, particularly in the frontotemporal areas ( Hassan et al, 2017 ).…”

Section: Discussionsupporting

confidence: 92%

Identifying Mild Cognitive Impairment in Parkinson’s Disease With Electroencephalogram Functional Connectivity

Cai

¹

,

Ge

²

,

Su

³

et al. 2021

Front. Aging Neurosci.

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ObjectiveCognitive impairment occurs frequently in Parkinson’s disease (PD) and negatively impacts the patient’s quality of life. However, its pathophysiological mechanism remains unclear, hindering the development of new therapies. Changes in brain connectivity are related to cognitive impairment in patients with PD, with the dorsolateral prefrontal cortex (DLPFC) being considered the essential region related to PD cognitive impairment. Nevertheless, few studies have focused on the global connectivity responsible for communication with the DLPFC node, the posterior division of the middle frontal gyrus (PMFG) in patients with PD; this was the focus of this study.MethodsWe applied resting-state electroencephalography (EEG) and calculated a reliable functional connectivity measurement, the debiased weighted phase lag index (dWPLI), to examine inter-regional functional connectivity in 68 patients with PD who were classified into two groups according to their cognitive condition.ResultsWe observed that altered left and right PMFG-based functional connectivity associated with cognitive impairment in patients with PD in the theta frequency bands under the eyes closed condition (r = −0.426, p < 0.001 and r = −0.437, p < 0.001, respectively). Exploratory results based on the MoCA subdomains indicated that poorer visuospatial function was associated with higher right PMFG-based functional connectivity (r = −0.335, p = 0.005), and poorer attention function was associated with higher left and right PMFG-based functional connectivity (r = −0.380, p = 0.001 and r = −0.256, p = 0.035, respectively). Further analysis using logistic regression and receiver operating characteristic (ROC) curves found that this abnormal functional connectivity was an independent risk factor for cognitive impairment [odds ratio (OR): 2.949, 95% confidence interval (CI): 1.294–6.725, p = 0.01 for left PMFG; OR: 11.278, 95% CI: 2.578–49.335, p = 0.001 for right PMFG, per 0.1 U], and provided moderate classification power to discriminate between cognitive abilities in patients with PD [area under the ROC curve (AUC) = 0.770 for left PMFG; AUC = 0.809 for right PMFG].ConclusionThese preliminary findings indicate that abnormal PMFG-based functional connectivity patterns associated with cognitive impairment in the theta frequency bands under the eyes closed condition and altered functional connectivity patterns have the potential to act as reliable biomarkers for identifying cognitive impairment in patients with PD.

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“…The Theta and Gamma band are suggested as the pathways for brain region to interact [46,43] for encoding and reveal memory, in our result, most of the significant connections are in these two bands. Our finding by GDDC and dDTF confirm the result from [15] by using Phase Lag Index as another connectivity estimator, they provide evidence that memory is highly correlated to the theta frequency band.…”

Section: Discussionsupporting

confidence: 84%

Frequency-specific network effective connectivity: ERP analysis of recognition memory process by directed connectivity estimators

Bayazi

¹

,

Nasrabadi

²

,

Dubé

³

2021

Med Biol Eng Comput

3

0

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Various processes occur in memory retrieval in recognition memory and it is necessary to investigate memory brain function. Most of the research in past decades have focused on particular brain region function, but the interaction between these has a major role in human cognition. In this study, we used the memory retrieval task to investigate the underlying mechanism of recognition memory. The connectivity between brain regions is estimated from scalp electroencephalography signals that were recorded from twenty-three healthy subject participated in recognition memory task to correctly classify old/new words. Multivariate autoregressive models (MVAR) are used for the determination of Granger causality to estimate the effective connectivity in the time-frequency domain. We use GPDC and dDTF methods because they have almost resolved the previous problems in estimations. Results show that brain regions in the old condition have greater global connectivity in the theta and gamma band compared to the new words retrieval. Connectivity within and between the brain's hemisphere may be related to correct rejection. The left frontal has a crucial role in recollection. theta and gamma specific connectivity pattern between temporal, parietal and frontal cortex may disclose the retrieval mechanism. old/new comparison resulted in the different patterns of network connection. These results and other evidence emphasize the role of frequency of causal network interactions in the memory process.

show abstract

“…The Theta and Gamma band are suggested as the pathways for brain region to interact [46,43] for encoding and reveal memory, in our result, most of the significant connections are in these two bands. Our finding by GDDC and dDTF confirm the result from [15] by using Phase Lag Index as another connectivity estimator, they provide evidence that memory is highly correlated to the theta frequency band. Figure 7: Average Networks for old/new and their difference (connectivity old − connectivity new ) by using the dDTF estimator, the difference is normalized for visualization, the color of edges present this difference and colors limited between blue (-1)/(0) and red (+1) so in third column red color means the old condition have a stronger connection than new and blue shows new have stronger connection at that edge.…”

Section: Discussionsupporting

confidence: 84%

Frequency specific network effective connectivity: ERP analysis of recognition memory process by directed connectivity estimators

Bayazi

¹

,

Nasrabadi

²

,

Curran

³

2019

Preprint

0

View full text Add to dashboard Cite

Various processes occur in memory retrieval in recognition memory and it is necessary to investigate memory brain function. Most of the research in past decades have focused on particular brain region function, but the interaction between these has a major role in human cognition. In this study, we used the memory retrieval task to investigate the underlying mechanism of recognition memory. The connectivity between brain regions is estimated from scalp electroencephalography signals that were recorded from twenty-three healthy subject participated in recognition memory task to correctly classify old/new words. Multivariate autoregressive models (MVAR) are used for the determination of Granger causality to estimate the effective connectivity in the time-frequency domain. We use GPDC and dDTF methods because they have almost resolved the previous problems in estimations. Results show that brain regions in the old condition have greater global connectivity in the theta and gamma band compared to the new words retrieval. Connectivity within and between the brain's hemisphere may be related to correct rejection. The left frontal has a crucial role in recollection. theta and gamma specific connectivity pattern between temporal, parietal and frontal cortex may disclose the retrieval mechanism. old/new comparison resulted in the different patterns of network connection. These results and other evidence emphasize the role of frequency of causal network interactions in the memory process.

show abstract

Phase lag index and spectral power as QEEG features for identification of patients with mild cognitive impairment in Parkinson's disease

Cited by 33 publications

References 59 publications

Identifying Mild Cognitive Impairment in Parkinson’s Disease With Electroencephalogram Functional Connectivity

Identifying Mild Cognitive Impairment in Parkinson’s Disease With Electroencephalogram Functional Connectivity

Frequency-specific network effective connectivity: ERP analysis of recognition memory process by directed connectivity estimators

Frequency specific network effective connectivity: ERP analysis of recognition memory process by directed connectivity estimators

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