Oxytocin modulates white matter functional connectivity tensor dynamics and circuit-targeted reconfiguration in depressive symptoms
Abstract
Major depressive disorder involves disrupted neural circuit dynamics. While oxytocin has demonstrated modulatory effects on functional connectivity, its therapeutic potential for depression, particularly through white matter circuit modulation, remains poorly understood. Here we show that reduced functional connectivity tensor fractional anisotropy in the genu of the corpus callosum (GCC) serves as a candidate mechanism distinguishing major depressive disorder (N = 34) from healthy controls (N = 33), but not in generalized anxiety disorder cohort (N = 31). This diagnostic validity was further confirmed in subclinical populations (N = 108). Crucially, oral oxytocin administration selectively increased GCC tensor metrics in individuals with high depressive traits and altered GCC-prefrontal connectivity during negative social processing (N = 69). These findings established GCC-centric WM functional connectivity tensor as a circuit-level substrate for depression in both clinical and sub-clinical populations and revealed that oral oxytocin can modulate these altered connections. Our work therefore suggests oxytocin-sensitive GCC functional organization may represent a candidate mechanism warranting further investigation in depression-related conditions. We investigate how white matter functional connectivity is altered in depression and how oral oxytocin modulates these changes. We find that altered functional organization of the genu of the corpus callosum is associated with depressive symptoms and is modulated by oxytocin in individuals with elevated depressive traits.
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Authors: Xiao Dong Zhang, Chunmei Lan, Peng Qing, Xiaolei Xu, Yuanshu Chen, Juan Kou, Lei Xu, Xinqi Zhou, Dezhong Yao, Benjamin Becker, Keith M. Kendrick, Weihua Zhao
Institutions: University of Hong Kong, Chinese University of Hong Kong, Southwest University of Science and Technology, University of Electronic Science and Technology of China, Sichuan Normal University, Shandong Normal University