Abnormal topological structure of structural covariance networks based on fractal dimension in noise induced hearing loss

Abstract

The topological attributes of structural covariance networks (SCNs) based on fractal dimension (FD) and changes in brain network connectivity were investigated using graph theory and network-based statistics (NBS) in patients with noise-induced hearing loss (NIHL). High-resolution 3D T1 images of 40 patients with NIHL and 38 healthy controls (HCs) were analyzed. FD-based Pearson correlation coefficients were calculated and converted to Fisher's Z to construct the SCNs. Topological attributes and network hubs were calculated using the graph theory. Topological measures between groups were compared using nonparametric permutation tests. Abnormal connection networks were identified using NBS analysis. The NIHL group showed a significantly increased normalized clustering coefficient, normalized characteristic path length, and decreased nodal efficiency of the right medial orbitofrontal gyrus. Additionally, the network hubs based on betweenness centrality and degree centrality were both the right transverse temporal gyrus and left parahippocampal gyrus in the NIHL group. The NBS analysis revealed two subnetworks with abnormal connections. The subnetwork with enhanced connections was mainly distributed in the default mode, frontoparietal, dorsal attention, and somatomotor networks, whereas the subnetwork with reduced connections was mainly distributed in the limbic, visual, default mode, and auditory networks. These findings demonstrate the abnormal topological structure of FD-based SCNs in patients with NIHL, which may contribute to understand the complex mechanisms of brain damage at the network level, providing a new theoretical basis for neuropathological mechanisms.

Keywords: Fractal dimension; Graph theory analysis; Network-based statistical analysis; Noise-induced hearing loss; Structural covariance network.

Fig. 1

Changes and between-group differences in global network attributes at different network sparsity (0.06–0.3) between NIHL and HCs groups. Graphs (A,C,E,G,I,K,M) showed changes, and graphs (B,D,F,H,J,L,N) showed between-group differences under different network sparsity in NIHL and HCs groups. The blue lines (-.) represented a 95% confidence interval, whereas the black lines (-) in the middle denoted the mean differences after 1000 permutations at each network sparsity. The pink lines (·) represented the real between-group differences between NIHL and HCs groups, which fell outside the confidence intervals and indicated significant between-group differences (p < 0.05) under the current threshold. The positive values indicated NIHL > HCs, and the negative values indicated NIHL < HCs. * represented significant differences.

Fig. 1

Changes and between-group differences in global network attributes at different network sparsity (0.06–0.3) between NIHL and HCs groups. Graphs (A,C,E,G,I,K,M) showed changes, and graphs (B,D,F,H,J,L,N) showed between-group differences under different network sparsity in NIHL and HCs groups. The blue lines (-.) represented a 95% confidence interval, whereas the black lines (-) in the middle denoted the mean differences after 1000 permutations at each network sparsity. The pink lines (·) represented the real between-group differences between NIHL and HCs groups, which fell outside the confidence intervals and indicated significant between-group differences (p < 0.05) under the current threshold. The positive values indicated NIHL > HCs, and the negative values indicated NIHL < HCs. * represented significant differences.

Fig. 2

Network hubs based on BC and DC in NIHL and HCs groups. Hubs based on BC were shown with green in HCs (A) and blue in HINL (B). Hubs based on DC were shown with pink in HCs (C) and yellow in HINL (D).The size of dot represented the values of BC and DC. NIHL noise-induced hearing loss, HCs healthy controls, BC betweenness centrality, DC degree centrality, L left, R right. Abbreviations were listed in Table 5.

Fig. 3

Network of increased connections between NIHL and HCs groups based on NBS (p < 0.001). (A) Nodes and Edges of networks of increased connections. Colored dots represented nodes, and nodes were divided into different colors according to resting-state brain networks which were listed in Table 1. Lines represented edges, and the thickness of lines represented the strength of the connection. (B) The spatial distribution of networks of increased connections. The red lines represented edges with significantly increased connections. L left, R right. Abbreviations were listed in Table 5.

Fig. 4

Network of decreased connections between NIHL and HCs groups based on NBS (p < 0.001). (A) Nodes and Edges of networks of decreased connections. Colored dots represented nodes, and nodes were divided into different colors according to resting-state brain networks which were listed in Table 1. Lines represented edges, and the thickness of lines represented the strength of the connection. (B) The spatial distribution of networks of decreased connections. The blue lines represented edges with significantly decreased connections. L: left, R: right. Abbreviations were listed in Table 5.