Global Efficiency of Structural Networks Mediates Cognitive Control in Mild Cognitive Impairment

Background: The early diagnosis of neurocognitive disorders before the symptoms’ onset is the ultimate goal of the scientific community. REMEDES for Alzheimer (R4Alz) is a battery, designed for assessing cognitive control abilities in people with minor and major neurocognitive disorders. Objective: To investigate whether the R4Alz battery’s tasks differentiate subjective cognitive decline (SCD) from cognitively healthy adults (CHA) and mild cognitive impairment (MCI). Methods: The R4Alz battery was administered to 175 Greek adults, categorized in five groups a) healthy young adults (HYA; n = 42), b) healthy middle-aged adults (HMaA; n = 33), c) healthy older adults (HOA; n = 14), d) community-dwelling older adults with SCD (n = 34), and e) people with MCI (n = 52). Results: Between the seven R4Alz subtasks, four showcased the best results for differentiating HOA from SCD: the working memory updating (WMCUT-S3), the inhibition and switching subtask (ICT/RST-S1&S2), the failure sets (FS) of the ICT/RST-S1&S2, and the cognitive flexibility subtask (ICT/RST-S3). The total score of the four R4Alz subtasks (R4AlzTot4) leads to an excellent discrimination among SCD and healthy adulthood, and to fare discrimination among SCD and MCI. Conclusion: The R4Alz battery is a novel approach regarding the neuropsychological assessment of people with SCD, since it can very well assist toward discriminating SCD from HOA. The R4Alz is able to measure decline of specific cognitive control abilities - namely of working memory updating, and complex executive functions - which seem to be the neuropsychological substrate of cognitive complaints in community dwelling adults of advancing age.

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Reversion From Mild Cognitive Impairment To Normal Cognition: False-Positive Error Or True Restoration Thanks To Cognitive Control Ability?

Neuropsychiatric Disease and Treatment ◽

10.2147/ndt.s223958 ◽

2019 ◽

Vol Volume 15 ◽

pp. 3021-3032

Author(s):

Ji-Yeon Chung ◽

Hyung-Jun Yoon ◽

Hu Won Kim ◽

Kyu Yeong Choi ◽

Jang Jae Lee ◽

...

Keyword(s):

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Control ◽

False Positive ◽

Positive Error ◽

False Positive Error ◽

Normal Cognition

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Editorial for “Diffusion Tensor Imaging Reveals Altered Topological Efficiency of Structural Networks in Type‐2 Diabetes Patients With and Without Mild Cognitive Impairment”

Journal of Magnetic Resonance Imaging ◽

10.1002/jmri.27899 ◽

2021 ◽

Author(s):

André M. Paschoal

Keyword(s):

Type 2 Diabetes ◽

Cognitive Impairment ◽

Diffusion Tensor Imaging ◽

Mild Cognitive Impairment ◽

Diffusion Tensor ◽

Structural Networks ◽

Topological Efficiency ◽

Diabetes Patients

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Small-World Properties in Mild Cognitive Impairment and Early Alzheimer’s Disease: A Cortical Thickness MRI Study

ISRN Geriatrics ◽

10.1155/2013/542080 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 23

Author(s):

Yongxia Zhou ◽

Yvonne W. Lui

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cortical Thickness ◽

Small World ◽

Small World Network ◽

Global Integration ◽

Global Efficiency ◽

Early Alzheimer’S Disease

Background. Small-world network consists of networks with local specialization and global integration. Our objective is to detect small-world properties alteration based on cortical thickness in mild cognitive impairment (MCI) including stables and converters, and early Alzheimer's disease (AD) compared to controls. Methods. MRI scans of 13 controls, 10 MCI, and 10 with early AD were retrospectively analyzed; 11 MCI converters, 11 MCI stables, and 10 controls from the ADNI website were also included. Results. There were significantly decreased local efficiencies in patients with MCI and AD compared to controls; and MCI patients showed increased global efficiency compared to AD and controls. The MCI converters experience the worst local efficiency during the converting period to AD; the stables, however, have highest local and global efficiency. Conclusions. The abnormal cortical thickness-based small-world properties in MCI and AD as well as the distinct patterns between two MCI subtypes suggest that small-world network analysis has the potential to better differentiate different stages of early dementia.

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Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2021.639795 ◽

2021 ◽

Vol 13 ◽

Author(s):

Zhanxiong Wu ◽

Yunyuan Gao ◽

Thomas Potter ◽

Julia Benoit ◽

Jian Shen ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Path Length ◽

Clustering Coefficient ◽

Network Efficiency ◽

Characteristic Path Length ◽

Structural Networks ◽

Structural Brain

Normative aging and Alzheimer’s disease (AD) propagation alter anatomical connections among brain parcels. However, the interaction between the trajectories of age- and AD-linked alterations in the topology of the structural brain network is not well understood. In this study, diffusion-weighted magnetic resonance imaging (MRI) datasets of 139 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used to document their structural brain networks. The 139 participants consist of 45 normal controls (NCs), 37 with early mild cognitive impairment (EMCI), 27 with late mild cognitive impairment (LMCI), and 30 AD patients. All subjects were further divided into three subgroups based on their age (56–65, 66–75, and 71–85 years). After the structural connectivity networks were built using anatomically-constrained deterministic tractography, their global and nodal topological properties were estimated, including network efficiency, characteristic path length, transitivity, modularity coefficient, clustering coefficient, and betweenness. Statistical analyses were then performed on these metrics using linear regression, and one- and two-way ANOVA testing to examine group differences and interactions between aging and AD propagation. No significant interactions were found between aging and AD propagation in the global topological metrics (network efficiency, characteristic path length, transitivity, and modularity coefficient). However, nodal metrics (clustering coefficient and betweenness centrality) of some cortical parcels exhibited significant interactions between aging and AD propagation, with affected parcels including left superior temporal, right pars triangularis, and right precentral. The results collectively confirm the age-related deterioration of structural networks in MCI and AD patients, providing novel insight into the cross effects of aging and AD disorder on brain structural networks. Some early symptoms of AD may also be due to age-associated anatomic vulnerability interacting with early anatomic changes associated with AD.

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P1-218: DISRUPTION OF WHITE MATTER STRUCTURAL NETWORKS AND COGNITIVE DECLINE IN MILD COGNITIVE IMPAIRMENT

Alzheimer s & Dementia ◽

10.1016/j.jalz.2014.05.457 ◽

2014 ◽

Vol 10 ◽

pp. P384-P384

Author(s):

Rok Berlot ◽

Claudia Metzler-Baddeley ◽

Nicola J. Ray ◽

Derek K. Jones ◽

John P. Aggleton ◽

...

Keyword(s):

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

White Matter ◽

Cognitive Decline ◽

Structural Networks

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Cingulum Microstructure Predicts Cognitive Control in Older Age and Mild Cognitive Impairment

Journal of Neuroscience ◽

10.1523/jneurosci.3299-12.2012 ◽

2012 ◽

Vol 32 (49) ◽

pp. 17612-17619 ◽

Cited By ~ 95

Author(s):

C. Metzler-Baddeley ◽

D. K. Jones ◽

J. Steventon ◽

L. Westacott ◽

J. P. Aggleton ◽

...

Keyword(s):

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Control ◽

Older Age

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Identifying Brain Connectivity Using Network-Based Statistics in Amnestic Mild Cognitive Impairment Stratified by β-Amyloid Positivity

American Journal of Alzheimer s Disease & Other Dementias® ◽

10.1177/1533317518813556 ◽

2018 ◽

Vol 34 (2) ◽

pp. 104-111 ◽

Cited By ~ 1

Author(s):

Ji Eun Kim ◽

Sung-Woo Kim ◽

Minsuk Choi ◽

Joon-Kyung Seong ◽

Jae-Hong Lee

Keyword(s):

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

White Matter ◽

Amnestic Mild Cognitive Impairment ◽

Control Group ◽

Whole Brain ◽

Brain White Matter ◽

Significant Difference ◽

Β Amyloid ◽

Structural Networks

Background: The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by β amyloid (Aβ) status and compare them using network-based statistics (NBS). Methods: Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [18F]-Florbetaben amyloid positron emission tomography. We performed the NBS analysis to compare the whole-brain white matter structural networks extracted from diffusion tensor images. Results: One hundred sixteen participants (Aβ− cognitively normal [CN], n = 35; Aβ− aMCI, n = 42; Aβ+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between Aβ+ aMCI and Aβ− aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, Aβ+ aMCI showed reduced connectivity mainly in the medial frontal regions, while Aβ− aMCI showed somewhat uniform disruption when compared to CN. Conclusion: Structural network analysis using network-based approach in aMCI may shed light on further understanding of white matter disruption in the prodromal stage of Alzheimer’s disease.

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