Directed Functional Networks in Alzheimer's Disease: Disruption of Global and Local Connectivity Measures

Several studies of Alzheimer’s disease (AD) reveal an impaired capacity to integrate visual elements into global pictures, leading to a deficit in global processing of visual information. The aim of this paper was to explore global and local processing in people with AD at non-advanced stage. The Global and Local Attention Test (AGL; from the original Spanish: AGL-Atención global y local) was administered to a group of 100 participants with a mean age of 75.36 years. Fifty of them were AD patients at a mild or moderate stage, while the remainder comprised healthy elders. The AGL provides two scores that indicate speed and accuracy in analyzing global and local figures. Participants had to indicate the figures where the target appeared at either global or local levels in a divided attention task. The results showed lower accuracy in the AD group compared with controls. Also in the AD group, and in line with previous findings, accuracy in detecting the target was much lower at the global level than at the local level, thereby confirming the expected deficit in global processing associated with AD. This deficit did not vary according to sex or age.

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Eigenvector alignment: assessing functional network changes in amnestic mild cognitive impairment and Alzheimer’s disease

10.1101/2020.03.23.003327 ◽

2020 ◽

Author(s):

Ruaridh Clark ◽

Niia Nikolova ◽

William J. McGeown ◽

Malcolm Macdonald

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Functional Connectivity ◽

Structural Changes ◽

Amnestic Mild Cognitive Impairment ◽

Functional Networks ◽

Limited Information ◽

The Impact

AbstractEigenvector alignment, introduced herein to investigate human brain functional networks, is adapted from methods developed to detect influential nodes and communities in networked systems. It is used to identify differences in the brain networks of subjects with Alzheimer’s disease (AD), amnestic Mild Cognitive Impairment (aMCI) and healthy controls (HC). Well-established methods exist for analysing connectivity networks composed of brain regions, including the widespread use of centrality metrics such as eigenvector centrality. However, these metrics provide only limited information on the relationship between regions, with this understanding often sought by comparing the strength of pairwise functional connectivity. Our holistic approach, eigenvector alignment, considers the impact of all functional connectivity changes before assessing the strength of the functional relationship, i.e. alignment, between any two regions. This is achieved by comparing the placement of regions in a Euclidean space defined by the network’s dominant eigenvectors. Eigenvector alignment recognises the strength of bilateral connectivity in cortical areas of healthy control subjects, but also reveals degradation of this commissural system in those with AD. Surprisingly little structural change is detected for key regions in the Default Mode Network, despite significant declines in the functional connectivity of these regions. In contrast, regions in the auditory cortex display significant alignment changes that begin in aMCI and are the most prominent structural changes for those with AD. Alignment differences between aMCI and AD subjects are detected, including notable changes to the hippocampal regions. These findings suggest eigenvector alignment can play a complementary role, alongside established network analytic approaches, to capture how the brain’s functional networks develop and adapt when challenged by disease processes such as AD.

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Global and local ancestry in African-Americans: Implications for Alzheimer's disease risk

Alzheimer s & Dementia ◽

10.1016/j.jalz.2015.02.012 ◽

2015 ◽

Vol 12 (3) ◽

pp. 233-243 ◽

Cited By ~ 20

Author(s):

Timothy J. Hohman ◽

Jessica N. Cooke-Bailey ◽

Christiane Reitz ◽

Gyungah Jun ◽

Adam Naj ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

African Americans ◽

Disease Risk ◽

Local Ancestry ◽

Global And Local

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Directed and divided attention in Alzheimer's disease: Impairment in shifting of attention to global and local stimuli

Journal of Clinical and Experimental Neuropsychology ◽

10.1080/01688639208402541 ◽

1992 ◽

Vol 14 (6) ◽

pp. 871-883 ◽

Cited By ~ 53

Author(s):

J. Vincent Filoteo ◽

Dean C. Delis ◽

Paul J. Massman ◽

Theresa Demadura ◽

Nelson Butters ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Divided Attention ◽

Global And Local

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From single layer to multilayer networks in Mild Cognitive Impairment and Alzheimer’s Disease

Journal of Physics: Complexity ◽

10.1088/2632-072x/ac3ddd ◽

2021 ◽

Author(s):

Ignacio Echegoyen ◽

David López-Sanz ◽

Fernando Maestú ◽

Javier M. Buldú

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Multinomial Logistic Regression ◽

Single Layer ◽

Functional Networks ◽

Algebraic Connectivity ◽

Multilayer Networks ◽

Reconstruction Procedure

Abstract We investigate the alterations of functional networks of patients suffering from mild cognitive impairment (MCI) and Alzheimer’s disease (AD) when compared to healthy individuals. Departing from the magnetoencephalographic recordings of these three groups, we construct and analyse the corresponding single layer functional networks at different frequency bands, both at the sensors and the ROIs (regions of interest) levels. Different network parameters show statistically significant differences, with global efficiency being the one having the most pronounced differences between groups. Next, we extend the analyses to the frequency-band multilayer networks of the same dataset. Using the mutual information as a metric to evaluate the coordination between brain regions, we construct the αβ multilayer networks and analyse their algebraic connectivity at baseline λ2−BSL (i.e., the second smallest eigenvalue of the corresponding Laplacian matrices). We report statistically significant differences at the sensor level, despite the fact that these differences are not clearly observed when networks are obtained at the ROIs level (i.e., after a source reconstruction procedure). Next, we modify the weights of the inter-links of the multilayer network to identify the value of the algebraic connectivity λ2−T leading to a transition where layers can be considered to be fully merged. However, differences between the values of λ2−T of the three groups are not statistically significant. Finally, we developed nested multinomial logistic regression models (MNR models), with the aim of predicting group labels with the parameters extracted from the multilayer networks (λ2−BSL and λ2−T ). Using these models, we are able to quantify how age influences the risk of suffering AD and how the algebraic connectivity of frequency-based multilayer functional networks could be used as a biomarker of AD in clinical contexts.

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Large-Scale Functional Networks, Cognition and Brain Structures Supporting Social Cognition and Theory of Mind Performance in Prodromal to Mild Alzheimer’s Disease

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2021.766703 ◽

2021 ◽

Vol 13 ◽

Author(s):

Jose Manuel Valera-Bermejo ◽

Matteo De Marco ◽

Micaela Mitolo ◽

Chiara Cerami ◽

Alessandra Dodich ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Social Cognition ◽

Theory Of Mind ◽

Large Scale ◽

Grey Matter ◽

Network Connectivity ◽

Functional Networks ◽

Default Mode ◽

The Right

Impairment of social cognition (SC) skills such as recognition and attribution of intentions and affective states of others (Theory of Mind, ToM) has been evidenced in Alzheimer’s Disease (AD). This study investigated the neuropsychological, neuroanatomical and brain-functional underpinnings of SC processing to obtain an understanding of the social neurophenotype in early probable AD. Forty-six patients with mild cognitive impairment and mild probable AD underwent SC assessment including emotion recognition (Ekman-60-faces task) and cognitive and affective ToM (Reading-the-Mind-in-the-Eyes test and Story-based Empathy task). Linear models tested the association between SC scores and neuropsychological measures, grey matter maps and large-scale functional networks activity. The executive domain had the most predominant association with SC scores in the cognitive profile. Grey matter volume of the anterior cingulate, orbitofrontal, temporoparietal junction (TPJ), superior temporal, and cerebellar cortices were associated with ToM. Social cognition scores were associated with lower connectivity of the default-mode network with the prefrontal cortex. The right fronto-parietal network displayed higher inter-network connectivity in the right TPJ and insula while the salience network showed lower inter-network connectivity with the left TPJ and insula. Connectivity coupling alterations of executive-attentional networks may support default mode social-cognitive-associated decline through the recruitment of frontal executive mechanisms.

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