EEG network connectivity changes in mild cognitive impairment — Preliminary results

Tóth, Brigitta; File, Bálint; Boha, Roland; Kardos, Zsófia; Hidasi, Zoltán; Gaál, Zsófia Anna; Csibri, Éva; Salacz, Pál; Stam, Cornelis J.; Molnár, Mihály

doi:10.1016/j.ijpsycho.2014.02.001

Cited by 62 publications

(57 citation statements)

References 38 publications

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“…In Babiloni's study, fronto-parietal connectivity decline was assumed to reflect the early deficits in attention-related neural network in patients with MCI [3]. In our study, the decreased frontoparietal functional coupling in old cognitively declined may reflect abnormal attention-related neural circuits associated with impaired brain function [21]. Furthermore, all the results of us demonstrated young and old adults had the distributed brain activation patterns.…”

Section: Youngsupporting

confidence: 58%

The function coupling in young adults, old controls and old cognitively declined adults

Wei

Cao

2014

2014 7th International Conference on Biomedical Engineering and Informatics

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This study explored the phase synchronization in young, old adults, and old cognitively declined adults using 2 minutes baseline resting EEG data. Sixteen young students recruited from shanghai university and eighteen elders recruited from a community in Shanghai, including nine old adults and nine old cognitively declined adults, participated in our experiment. The global phase synchrony index was calculated in each 1 second epoch and averaged for all EEG frequency band (delta, theta, alpha1, alpha2, beta, gamma1, gamma2). Then, we analyzed global phase synchronization, fronto-parietal functional coupling and frontal functional coupling at alpha2 band for three groups. The results revealed that old declined adults had decreased global phase synchronization at theta and alpha2 bands and lower frontal and fronto-parietal functional coupling at alpha2 band than old controls. Relative to young adults, the old controls had an active mechanism of compensation to maintain normal cognitive performance. In conclude the frontal and fronto-parietal functional coupling in alpha band may be helpful markers of cognitive decline associated with aging.

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Section: Youngsupporting

confidence: 58%

The function coupling in young adults, old controls and old cognitively declined adults

Wei

Cao

2014

2014 7th International Conference on Biomedical Engineering and Informatics

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“…Carriers of the APOE 4 allele have an increased risk for forming beta-amyloid plaques; during prion-like aggregation, damage to neurons is done by oxidative stress, resulting in brain atrophy. This loss significantly reduces the number of neurons available for connectivity such as that seen in mild cognitive impairment and Alzheimer's disease ( Jelic et al, 1997;Tóth et al, 2014), and may additionally result in the loss of integration in the MST network. Likewise, clusterin (CLU/APOJ) is involved in the clearance by binding to beta-amyloid resulting in variability in neurodegeneration (Desikan et al, 2014;Mengel-From et al, 2013) and could have similar effects on connectivity and connectivity patterns.…”

Section: Discussionmentioning

confidence: 99%

Life-Span Development of Brain Network Integration Assessed with Phase Lag Index Connectivity and Minimum Spanning Tree Graphs

et al. 2016

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Graph analysis of electroencephalography (EEG) has previously revealed developmental increases in connectivity between distant brain areas and a decrease in randomness and increased integration in the brain network with concurrent increased modularity. Comparisons of graph parameters across age groups, however, may be confounded with network degree distributions. In this study, we analyzed graph parameters from minimum spanning tree (MST) graphs and compared their developmental trajectories to those of graph parameters based on full graphs published previously. MST graphs are constructed by selecting only the strongest available connections avoiding loops, resulting in a backbone graph that is thought to reflect the major qualitative properties of the network, while allowing a better comparison across age groups by avoiding the degree of distribution confound. EEG was recorded in a large (n = 1500) population-based sample aged 5-71 years. Connectivity was assessed using phase lag index to reduce effects of volume conduction. Connectivity in the MST graph increased significantly from childhood to adolescence, continuing to grow nonsignificantly into adulthood, and decreasing significantly about 57 years of age. Leaf number, degree, degree correlation, and maximum centrality from the MST graph indicated a pattern of increased integration and decreased randomness from childhood into early adulthood. The observed development in network topology suggested that maturation at the neuronal level is aimed to increase connectivity as well as increase integration of the brain network. We confirm that brain network connectivity shows quantitative changes across the life span and additionally demonstrate parallel qualitative changes in the connectivity pattern.

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“…Carriers of the APOE \epsilon4 allele have an increased risk for forming beta-amyloid plaques; during prion-like aggregation, damage to neurons is done by oxidative stress, resulting in brain atrophy. This loss significantly reduces the number of neurons available for connectivity such as seen in MCI and AD (Jelic et al, 1997;Tóth et al, 2014), but may also result in the loss of integration in the MST network.…”

Section: Discussionmentioning

confidence: 99%

Life-span development of functional brain networks as assessed with minimum spanning tree analysis of resting state EEG.

Smit

Geus

Boersma

et al. 2015

Preprint

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The brain matures with large quantitative changes in anatomy and function. Graph analysis of EEG has previously revealed increased connectivity between distant brain areas and a decrease in randomness and increased integration in the brain network with concurrent increased modularity. Comparisons of graph parameters across age groups, however, may be confounded with network degree distributions.Here, we analyzed graph parameters from minimum spanning tree (MST) graphs.MST graphs are constructed by selecting only the strongest available connections avoiding loops resulting in a backbone graph that is thought reflect the major qualitative properties of connectivity while allowing a better comparison across age groups by avoiding the degree distribution confound. EEG was recorded in a large (N=1500) population-based sample aged 5 to 71 years. Connectivity was assessed using Phase Lag Index to reduce effects of volume conduction. As previously reported, connectivity increased from childhood to adolescence, continuing to grow nonsignificantly into adulthood decreasing only after ~30 years of age. Leaf number, degree, degree correlation, maximum centrality from the MST graph indicated a pattern of increased integration and decreased randomness from childhood into early adulthood. The observed development in network topology suggested that maturation at the neuronal level is aimed to increase connectivity as well as increase integration of the brain network. We confirm that brain network connectivity shows quantitative changes across the life span, and additionally demonstrate parallel qualitative changes in the connectivity pattern.

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EEG network connectivity changes in mild cognitive impairment — Preliminary results

Cited by 62 publications

References 38 publications

The function coupling in young adults, old controls and old cognitively declined adults

The function coupling in young adults, old controls and old cognitively declined adults

Life-Span Development of Brain Network Integration Assessed with Phase Lag Index Connectivity and Minimum Spanning Tree Graphs

Life-span development of functional brain networks as assessed with minimum spanning tree analysis of resting state EEG.

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