Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study

Abstract

Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

Figure 1. Global parameters of the brain functional networks for the heroin-dependent individuals (HDIs) and the normal controls (NCs) changing with the sparsity threshold.

The error bar represents the standard deviation of a parameter at a given sparsity across all subjects. The symbol (*) means that significant between-group difference in the given parameter was detected (p<0.05). Except for the sparsity range of 0.05≤sparsity≤0.09, no statistically significant between-group differences were detected for other values of sparsity. , clustering coefficient; , characteristic path length; , normalized clustering coefficient; , normalized shortest path length; , small-worldness; , global efficiency; , local efficiency.

Figure 2. Bar plots of the differences in the integrated global topological parameters of brain functional networks between the heroin-dependent individuals (HDIs) and the normal controls (NCs).

The symbol (*) indicates significant between-group differences in the integrated normalized clustering coefficient (p = 0.049) and integrated small-worldness (p = 0.035). , integrated clustering coefficient; , integrated characteristic path length; , integrated normalized shortest path length; , integrated global efficiency; , integrated local efficiency.

Figure 3. Brain regions exhibiting abnormal integrated nodal parameters of the brain functional networks and their relationship with the duration of heroin addiction in the heroin-dependent individuals (HDIs) compared to the normal controls (NCs).

(a) Surface visualization of regions with abnormal nodal centralities using BrainNet Viewer (http://www.nitrc.org/projects/bnv/). Areas color-coded in red (blue) indicate the regions in which the values of nodal centralities corresponding to HDIs were higher (lower) than those of controls. See Table 2 for details. (b) Scatter plot of the integrated nodal parameters against the duration of heroin addiction. In the left hippocampus (HIP.L), we detected a significantly positive correlation between the integrated nodal degree and the duration of heroin addiction (p = 0.042) and a tendency toward a positive correlation between the integrated nodal efficiency and the duration of heroin addiction (p = 0.054) in HDIs. The abbreviations of regions are listed in Table S2.

Figure 4. The connected subnetwork showing decreased functional connections in the heroin-dependent individuals (HDIs) compared to the normal controls (NCs).

(a) Visualization of decreased functional connections related to heroin addiction using BrainNet Viewer (http://www.nitrc.org/projects/bnv/). The width of the line indicates the t-value of the connection comparisons between the two groups. A single, connected subnetwork containing 19 nodes and 19 connections was determined using the network-based statistic (NBS) method. (b) Scatter plot of the integrated clustering coefficient, , against the mean functional connectivity of this connected subnetwork averaged over all subjects. (c) Same as (b) but for the integrated normalized clustering coefficient, . (d) Same as (b) but for integrated small-worldness, . The abbreviations of the regions are listed in Table S2.