Complex network analysis of MCI-AD EEG signals under cognitive and resting state

Das, Surya Sarathi; Puthankattil, Subha D.

doi:10.1016/j.brainres.2020.146743

Cited by 39 publications

(32 citation statements)

References 62 publications

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“…Our results suggest that brain networks of MCI patients show a transient shift to a more centralized, star-like topology to compensate for the initial impairments in accordance with the "hub overload" stage, and complement former EEG studies, which reported the deviation of the network topology from the optimal small-world architecture to a more random type configuration (Wei et al, 2015) and the shifting of the MST toward a more decentralized, line-like structure of AD patients in the "hub failure" stage during resting state (Yu et al, 2016;Peraza et al, 2018;Das and Puthankattil, 2020) and cognitive tasks (Das and Puthankattil, 2020).…”

Section: Discussionsupporting

confidence: 82%

“…Regarding the overall network structure, previous studies observed a progressive derangement of brain organization during the disease course causing a deviation from the optimal smallworld architecture to a more random type configuration leading to a less efficient information transfer during resting state (de Haan et al, 2009;Stam et al, 2009;Stam, 2014;Wei et al, 2015;Miraglia et al, 2017), and cognitive tasks (Wei et al, 2015;Das and Puthankattil, 2020), firstly affecting alpha-band networks in MCI (Miraglia et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance

Fodor

Horváth

Hidasi

et al. 2021

Front. Aging Neurosci.

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Background: While decreased alpha and beta-band functional connectivity (FC) and changes in network topology have been reported in Alzheimer’s disease, it is not yet entirely known whether these differences can mark cognitive decline in the early stages of the disease. Our study aimed to analyze electroencephalography (EEG) FC and network differences in the alpha and beta frequency band during visuospatial memory maintenance between Mild Cognitive Impairment (MCI) patients and healthy elderly with subjective memory complaints.Methods: Functional connectivity and network structure of 17 MCI patients and 20 control participants were studied with 128-channel EEG during a visuospatial memory task with varying memory load. FC between EEG channels was measured by amplitude envelope correlation with leakage correction (AEC-c), while network analysis was performed by applying the Minimum Spanning Tree (MST) approach, which reconstructs the critical backbone of the original network.Results: Memory load (increasing number of to-be-learned items) enhanced the mean AEC-c in the control group in both frequency bands. In contrast to that, after an initial increase, the MCI group showed significantly (p < 0.05) diminished FC in the alpha band in the highest memory load condition, while in the beta band this modulation was absent. Moreover, mean alpha and beta AEC-c correlated significantly with the size of medial temporal lobe structures in the entire sample. The network analysis revealed increased maximum degree, betweenness centrality, and degree divergence, and decreased diameter and eccentricity in the MCI group compared to the control group in both frequency bands independently of the memory load. This suggests a rerouted network in the MCI group with a more centralized topology and a more unequal traffic load distribution.Conclusion: Alpha- and beta-band FC measured by AEC-c correlates with cognitive load-related modulation, with subtle medial temporal lobe atrophy, and with the disruption of hippocampal fiber integrity in the earliest stages of cognitive decline. The more integrated network topology of the MCI group is in line with the “hub overload and failure” framework and might be part of a compensatory mechanism or a consequence of neural disinhibition.

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Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance

Fodor

Horváth

Hidasi

et al. 2021

Front. Aging Neurosci.

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“…The previous study has been found that a new method called a correlation-based label consistent K-SVD can diagnose patients with MCI (Kashefpoor et al, 2019). Brain functional connectivity has been analyzed the changes from MCI to AD based on resting and cognitive task conditions (Surya and Puthankattil, 2020). To diagnose patients with MCI, the permutation entropy neuromarker was proposed based on EEG signals (Eker et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Brain Function State During Mild Cognitive Impairment Based on Weighted Multiple Multiscale Entropy

Liu

et al. 2021

Front. Aging Neurosci.

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The mild cognitive impairment (MCI) stage plays an essential role in preventing the progression of older adults to Alzheimer's disease. In this study, neurofeedback training (NFT) is applied to improve MCI brain cognitive function. To assess the improvement effect, a novel algorithm called Weighted Multiple Multiscale Entropy (WMMSE) is proposed to extract and analyze the electroencephalogram (EEG) features of patients with MCI. To overcome the information loss problem of traditional multiscale entropy (MSE), WMMSE fully considered the correlation of the sequence and the contribution of each sequence to the total entropy. The experimental group composed of 39 patients with MCI was subjected to NFT for 10 days during two sessions. The control group included 21 patients with MCI without any intervention. The Lempel-Ziv complexity (LZC) was used for primary assessment, and WMMSE was used to accurately analyze the effect of NFT. The results show that the WMMSE values of F4, C3, C4, O1, and T5 channels post-NFT are higher compared with pre-NFT and significant differences (P < 0.05). Moreover, the cognitive subscale of the Montreal Cognitive Assessment (MoCA) results shows that the post-NFT score is higher than the pre-NFT in the vast majority of the patients with MCI and significant differences (P < 0.05). When compared with the control group, the WMMSE values of the experimental group increased in each channel. Therefore, the NFT intervention method contributes to brain cognitive functional recovery, and WMMSE can be used as a biomarker to evaluate the state of MCI brain cognitive function.

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“…Studies have also found that the abnormal rate of EEG is higher in AD patients, which is manifested by the significantly increased power of low-frequency slowwave θ and δ waves, and decreased power of the fast wave, especially in the frontotemporal area (16,17). Patients with mild to moderate AD also show atrophy of the frontal and temporal lobes (18) where a large number of 5-HTR1A receptors are located.…”

Section: Discussionmentioning

confidence: 99%

EEG power spectral analysis reveals tandospirone improves anxiety symptoms in patients with Alzheimer’s disease: a prospective cohort study

Liao¹,

Zhao²,

Li³

et al. 2021

Ann Transl Med

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Background: To study the efficacy of tandospirone citrate in treating Alzheimer's disease (AD) patients with anxiety.Methods: Thirty mild-to-moderate AD patients with anxiety symptoms were randomly divided into a monotherapy group (donepezil) and a combination therapy group (donepezil and tandospirone). The treatment lasted for 12 weeks. Drug efficacy was regularly assessed using psychological assessment scales and quantitative pharmaco-electroencephalogram (QPEEG) power spectral analysis.Results: After 12 weeks of treatment, the mean Hamilton Anxiety Scale (HAMA) score and mean Neuropsychiatric Inventory (NPI) score of the combination therapy group were 5.13±4.18 and 4.2±5.0, respectively, which was significantly lower compared to baseline and the monotherapy group (all P<0.05).The mean attention score on the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) was 0.07±0.26 for the combination group, which was significantly lower than that of the monotherapy group (P<0.05). QPEEG revealed that the power values of the δ wave in the right prefrontal lobe, left middle temporal lobe and right posterior temporal lobe decreased in the combination therapy group but not in the monotherapy group. Similarly, the power values of the α2 wave in the right parietal, right posterior temporal and left middle temporal lobes, and the β1 wave power values of left middle temporal and left posterior temporal lobes were also significantly decreased in the combination therapy group, but not in the monotherapy group.Conclusions: Tandospirone citrate can significantly improve anxiety symptoms and attention in patients with mild to moderate AD. QPEEG examination might provide a objective way for the efficacy of the tandospirone in anxiety symptoms of the patients with Alzheimer's disease.

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Complex network analysis of MCI-AD EEG signals under cognitive and resting state

Cited by 39 publications

References 62 publications

EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance

EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance

Evaluation of the Brain Function State During Mild Cognitive Impairment Based on Weighted Multiple Multiscale Entropy

EEG power spectral analysis reveals tandospirone improves anxiety symptoms in patients with Alzheimer’s disease: a prospective cohort study

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