Shared and Distinct Functional Architectures of Brain Networks Across Psychiatric Disorders

Abstract

Brain network alterations have increasingly been implicated in schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). However, little is known about the similarities and differences in functional brain networks among patients with SCZ, BD, and MDD. A total of 512 participants (121 with SCZ, 100 with BD, 108 with MDD, and 183 healthy controls, matched for age and sex) completed resting-state functional magnetic resonance imaging at a single site. Four global measures (the clustering coefficient, the characteristic shortest path length, the normalized clustering coefficient, and the normalized characteristic path length) were computed at a voxel level to quantify segregated and integrated configurations. Inter-regional functional associations were examined based on the Euclidean distance between regions. Distance strength maps were used to localize regions with altered distances based on functional connectivity. Patient groups exhibited shifts in their network architectures toward randomized configurations, with SCZ>BD>MDD in the degree of randomization. Patient groups displayed significantly decreased short-range connectivity and increased medium-/long-range connectivity. Decreases in short-range connectivity were similar across the SZ, BD, and MDD groups and were primarily distributed in the primary sensory and association cortices and the thalamus. Increases in medium-/long-range connectivity were differentially localized within the prefrontal cortices among the patient groups. We highlight shared and distinct connectivity features in functional brain networks among patients with SCZ, BD, and MDD, which expands our understanding of the common and distinct pathophysiological mechanisms and provides crucial insights into neuroimaging-based methods for the early diagnosis of and interventions for psychiatric disorders.

Keywords: big data; connectome; frontal cortex; functional connectivity; high-resolution network.

Fig. 1.

Differences in global network parameters among the 4 groups. Violin plots represent the distribution of each global network parameter in each group and solid lines indicate the medians. The significance level was set to P < .05. *P < .05, **P < .01, ***P < .001. HC, healthy control; MDD, major depressive disorder; BD, bipolar disorder; SCZ, schizophrenia.

Fig. 2.

Distance-dependent differences in the number of network connections among the 4 groups. (A) Group effects on the number of functional connections in each distance bin were detected by 1-way analysis of covariance. The solid line indicates the mean value for each group across distance bins and the shadow represents the standard deviation. (B) Between-group differences in bins 1, 2, 5, 6, 7, and 8 were further assessed using post hoc analyses. Violin plots represent the distribution of numbers of connections in each group and solid lines indicate medians. The significance level was set to P < .05, with an FDR correction for multiple comparisons. *P < .05, **P < .01, ***P < .001. HC, healthy control; MDD, major depressive disorder; BD, bipolar disorder; SCZ, schizophrenia.

Fig. 3.

Regions with significant group effects on short-range or medium-/long-range distance strength. (A) The 3-dimensional surface illustrates regions with significant group effects on short-range distance strength (0–20 mm). The radar plot shows the normalized mean values for each group at the peak of the significant cluster. For each peak, normalization was performed by dividing the mean values by the maximum mean value obtained from the 4 groups. (B) The 3-dimensional surface illustrates regions with significant group effects on medium-/long-range distance strength (40–80 mm). The radar map shows the normalized mean values for each group at the peak of the significant cluster. The significance level was set to P < .001 at the voxel level, with Gaussian random field corrections for multiple comparisons. HC, healthy control; MDD, major depressive disorder; BD, bipolar disorder; SCZ, schizophrenia; R, right; L, left; B, bilateral; ITG, inferior temporal gyrus; STG, superior temporal gyrus; CAL, calcarine; THA, thalamus; PoCG, postcentral gyrus; SMC, sensorimotor cortex; IFGOrb, inferior frontal gyrus, orbital part; MFG, middle frontal gyrus; SMA, supplementary motor area. The surface visualization was conducted by using BrainNet Viewer.