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. 2022 Apr 28:2022:8034757.
doi: 10.1155/2022/8034757. eCollection 2022.

Topologic Reorganization of White Matter Connectivity Networks in Early-Blind Adolescents

Affiliations

Topologic Reorganization of White Matter Connectivity Networks in Early-Blind Adolescents

Zhifeng Zhou et al. Neural Plast. .

Abstract

Blindness studies are important models for the comprehension of human brain development and reorganization, after visual deprivation early in life. To investigate the global and local topologic alterations and to identify specific reorganized neural patterns in early-blind adolescents (EBAs), we applied diffusion tensor tractography and graph theory to establish and analyze the white matter connectivity networks in 21 EBAs and 22 age- and sex-matched normal-sighted controls (NSCs). The network profiles were compared between the groups using a linear regression model, and the associations between clinical variables and network profiles were analyzed. Graph theory analysis revealed "small-world" attributes in the structural connection networks of both EBA and NSC cohorts. The EBA cohort exhibited significant lower network density and global and local efficiency, as well as significantly elevated shortest path length, compared to the NSC group. The network efficiencies were markedly reduced in the EBA cohort, with the largest alterations in the default-mode, visual, and limbic areas. Moreover, decreased regional efficiency and increased nodal path length in some visual and default-mode areas were strongly associated with the period of blindness in EBA cohort, suggesting that the function of these areas would gradually weaken in the early-blind brains. Additionally, the differences in hub distribution between the two groups were mainly within the occipital and frontal areas, suggesting that neural reorganization occurred in these brain regions after early visual deprivation during adolescence. This study revealed that the EBA brain structural network undergoes both convergent and divergent topologic reorganizations to circumvent early visual deprivation. Our research will add to the growing knowledge of underlying neural mechanisms that govern brain reorganization and development, under conditions of early visual deprivation.

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Conflict of interest statement

The authors have no conflict of interest to declare.

Figures

Figure 1
Figure 1
Group differences in global network metrics of WM structural networks (a) and the correlation between network Eloc and blind duration in the EBA cohort (b). (a) Bar charts and error bars represent the mean values and standard deviations, respectively (EBA: n = 21; NSC: n = 22). ∗p < 0.05 (Bonferroni corrected); ∗∗p < 0.001 (Bonferroni corrected). (b) Scatterplots show the significantly negative correlation between network Eloc and blind duration in the EBA cohort (n = 21). The fitted values indicate the residuals of original values of Eloc adjusted age and sex and corrected with mean value. Abbreviations: Eg: global efficiency; Eloc: local efficiency; Lp: shortest path length; Cp: clustering coefficient; λ: normalized path length; γ: normalized clustering coefficient; σ: small-world parameters; EBA: early-blind adolescents; NSC: normal-sighted controls.
Figure 2
Figure 2
Distribution of brain regions with significant intercohort differences in nodal efficiency (Ne) (a) and the correlation with blind duration in the EBA cohort (b). (a) Regions with decreased Ne are represented in different colors: purple for the default-mode system, green for the visual system, and blue for the limbic system. The node sizes indicate the significance of intercohort differences in Ne. (b) Scatterplots show the significantly negative correlation between Ne and blind duration in EBA cohort (n = 21). The fitted values indicate the residuals of original values of Ne adjusted age and sex and corrected with mean value. The abbreviations of nodes can be referred in Table 4.
Figure 3
Figure 3
Distribution of brain regions with significantly intercohort differences in nodal shortest path length (NLp) (a) and the correlation with blind duration in EBA cohort (b). (a) Regions with longer NLp are represented in different colors: purple for the default-mode system, green for the visual system, and blue for the limbic system. The node sizes indicate the significance of intercohort difference in NLp. (b) Scatterplots show a significantly positive correlation between NLp and blind duration in EBA cohort (n = 21). The fitted values indicate the residuals of original values of NLp adjusted age and sex and corrected with mean value. The abbreviations of nodes can be referred in Table 4.
Figure 4
Figure 4
Hub region distributions (top 13) in the WM structural network in EBA (a) and NSC (b) cohorts. The left panels indicate the 90 brain regions of AAL atlas sorted by mean nodal degree (Nd) in ascending order for each cohort. The right panels show hub distributions of each cohort. The hub nodes are shown in red, and node sizes indicate the significance of intercohort difference in Nd. The abbreviations of brain regions are presented in Table 2.

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