Local functional connectivity abnormalities in mild cognitive impairment and Alzheimer's disease: A meta-analytic investigation using minimum Bayes factor activation likelihood estimation

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2024-09, Vol.298, p.120798, Article 120798
• Main Authors: Costa, Tommaso, Premi, Enrico, Borroni, Barbara, Manuello, Jordi, Cauda, Franco, Duca, Sergio, Liloia, Donato
• Format: Article
• Language: English
• Subjects: Algorithms; Alzheimer's disease; Bayes Factor; Bayesian analysis; Bayesian statistics; Biomarker; Brain mapping; Brain research; BrainMap; Brodmann's area; Cognitive ability; Cortex (cingulate); Cortex (parietal); Default mode network; Dementia; Experiments; fMRI; Functional magnetic resonance imaging; Localization; Magnetic resonance imaging; Medical imaging; Meta-analysis; Neural networks; Neurodegenerative diseases; Neuroimaging; Neurosciences; NeuroSynth; Parahippocampal gyrus; Software; Temporal gyrus; Temporal lobe
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2024.120798

•We reviewed and meta-analyzed regional homogeneity studies about MCI and AD.•We present a novel Bayesian implementation for the activation likelihood estimation method.•Distinctive and non-overlapping short-range connectivity changes were found for MCI and AD.•ReHo variations are localized within hub nodes of the default mode network.•Functional aberrations are statistically associated with memory, language, and social functioning domains. Functional magnetic resonance imaging research employing regional homogeneity (ReHo) analysis has uncovered aberrant local brain connectivity in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) in comparison with healthy controls. However, the precise localization, extent, and possible overlap of these aberrations are still not fully understood. To bridge this gap, we applied a novel meta-analytic and Bayesian method (minimum Bayes Factor Activation Likelihood Estimation, mBF-ALE) for a systematic exploration of local functional connectivity alterations in MCI and AD brains. We extracted ReHo data via a standardized MEDLINE database search, which included 35 peer-reviewed experiments, 1,256 individuals with AD or MCI, 1,118 healthy controls, and 205 x-y-z coordinates of ReHo variation. We then separated the data into two distinct datasets: one for MCI and the other for AD. Two mBF-ALE analyses were conducted, thresholded at “very strong evidence” (mBF ≥ 150), with a minimum cluster size of 200 mm³. We also assessed the spatial consistency and sensitivity of our Bayesian results using the canonical version of the ALE algorithm. For MCI, we observed two clusters of ReHo decrease and one of ReHo increase. Decreased local connectivity was notable in the left precuneus (Brodmann area – BA 7) and left inferior temporal gyrus (BA 20), while increased connectivity was evident in the right parahippocampal gyrus (BA 36). The canonical ALE confirmed these locations, except for the inferior temporal gyrus. In AD, one cluster each of ReHo decrease and increase were found, with decreased connectivity in the right posterior cingulate cortex (BA 30 extending to BA 23) and increased connectivity in the left posterior cingulate cortex (BA 31). These locations were confirmed by the canonical ALE. The identification of these distinct functional connectivity patterns sheds new light on the complex pathophysiology of MCI and AD, offering promising directions for future neuroimaging-based interventions. Additional