Disrupted Topological Organization of Resting-State Functional Brain Networks in Age-Related Hearing Loss

Abstract

PurposeAge-related hearing loss (ARHL), associated with the function of speech perception decreases characterized by bilateral sensorineural hearing loss at high frequencies, has become an increasingly critical public health problem. This study aimed to investigate the topological features of the brain functional network and structural dysfunction of the central nervous system in ARHL using graph theory.MethodsForty-six patients with ARHL and forty-five age, sex, and education-matched healthy controls were recruited to undergo a resting-state functional magnetic resonance imaging (fMRI) scan in this study. Graph theory was applied to analyze the topological properties of the functional connectomes by studying the local and global organization of neural networks.ResultsCompared with healthy controls, the patient group showed increased local efficiency (Eloc) and clustering coefficient (Cp) of the small-world network. Besides, the degree centrality (Dc) and nodal efficiency (Ne) values of the left inferior occipital gyrus (IOG) in the patient group showed a decrease in contrast with the healthy control group. In addition, the intra-modular interaction of the occipital lobe module and the inter-modular interaction of the parietal occipital module decreased in the patient group, which was positively correlated with Dc and Ne. The intra-modular interaction of the occipital lobe module decreased in the patient group, which was negatively correlated with the Eloc.ConclusionBased on fMRI and graph theory, we indicate the aberrant small-world network topology in ARHL and dysfunctional interaction of the occipital lobe and parietal lobe, emphasizing the importance of dysfunctional left IOG. These results suggest that early diagnosis and treatment of patients with ARHL is necessary, which can avoid the transformation of brain topology and decreased brain function.

Aging effects on dual‐route speech processing networks during speech perception in noise

“…Thus, a sparsity threshold 0.25 < S < 0.49 with an interval of 0.015 was applied to binarize adjacency networks in the theoretical analysis graph. Previous studies had found that a measure of the graph‐theoretical network was able to reveal developmental changes in the functional organization in patients with age‐related hearing loss (Wang et al, 2022; Yong et al, 2022). We therefore focused on the measures of global network parameters of small‐world: $$$ L $$$ (characteristic path length), $$$ C $$$ (clustering coefficient), $$$ \gamma $$$ (normalized clustering coefficient), $$$ \lambda $$$ (normalized characteristic path length), $$$ \delta $$$ (small‐worldness) and the network efficiency parameters including $$$ {E}_g $$$ (global efficiency) and $$$ {E}_l $$$ (local efficiency) to characterize the global topological structure.…”

“…Network integration describes how well information from segregated areas can be integrated (Schill et al, 2022 ), which could be measured by network efficiency and node degree. Some studies suggest that aging is associated with changes in the whole‐brain topological network (Martin et al, 2023 ; Yong et al, 2022 ). However, results are controversial with some studies reporting a decrease in network integration during healthy aging (Chan et al, 2014 ; Chong et al, 2019 ; Spreng et al, 2016 ), whereas some found an increase (Schill et al, 2022 ; Stumme et al, 2020 ) which suggests a pattern of compensational response.…”