Resting-state brain connectivity in healthy young and middle-aged adults at risk of progressive Alzheimer's disease. (October 2021)

• Record Type: Journal Article
• Authors: Kucikova, Ludmila; Goerdten, Jantje; Dounavi, Maria-Eleni; Mak, Elijah; Su, Li; Waldman, Adam D.; Danso, Samuel; Muniz-Terrera, Graciela; Ritchie, Craig W.
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 129(2021)
• Page Start: 142
• Page End: 153
• Publication Date: 2021-10
• Subjects: Alzheimer's disease -- Preclinical dementia -- Neurodegeneration -- Functional imaging -- BOLD imaging -- Resting state -- Functional connectivity -- Brain connectivity -- Neuroimaging; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2021.07.024
• Languages: English
• ISSNs: 0149-7634

Abstract

Highlights: Functional connectivity changes are present in individuals with AD-risk factors. The topography shows an overlap with regions characteristic for AD. Less consensus on the directionality of functional connectivity changes. Abstract: Functional brain connectivity of the resting-state networks has gained recent attention as a possible biomarker of Alzheimer's Disease (AD). In this paper, we review the literature of functional connectivity differences in young adults and middle-aged cognitively intact individuals with non-modifiable risk factors of AD (n = 17). We focus on three main intrinsic resting-state networks: The Default Mode network, Executive network, and the Salience network. Overall, the evidence from the literature indicated early vulnerability of functional connectivity across different at-risk groups, particularly in the Default Mode Network. While there was little consensus on the interpretation on directionality, the topography of the findings showed frequent overlap across studies, especially in regions that are characteristic of AD (i.e., precuneus, posterior cingulate cortex, and medial prefrontal cortex areas). We conclude that while resting-state functional connectivity markers have great potential to identify at-risk individuals, implementing more data-driven approaches, further longitudinal and cross-validation studies, and the analysis of greater sample sizes are likely to be necessary to fully establish the effectivity and utility of resting-state network-based analyses.