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.
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