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<p>Depression involves impaired cognitive, affective, and social functions associated with aberrant brain network interactions. The temporoparietal junction (TPJ), a multisensory integration hub, exhibits depression-related connectivity alterations, yet the roles of its subregions during subclinical stages remain unclear. This study examined TPJ subregional communication in non-clinical high-depression individuals.&#xa0;Resting-state fMRI data from 586 medication-free young adults were analyzed. Participants were divided into high-depression (HD, <i>N</i> = 130) and low-depression (LD, <i>N</i> = 130) groups using Beck Depression Inventory scores. TPJ was parcellated into anterior (aTPJ), posterior (pTPJ), and ventral (vTPJ) subregions via community detection. Multi-metric connectivity (functional connectivity/FC, total interdependence/TI, Granger causality/GC) seeded from TPJ subregions was compared between groups. Support vector machine (SVM) fusion analysis identified high-contribution features for network alteration modeling.&#xa0;TPJ subregions showed depression-related connectivity patterns: (1) Altered default mode network DMN interactions featuring enhanced anterior DMN (medial prefrontal cortex) connectivity and weakened posterior DMN (posterior cingulate/precuneus) connectivity; (2) Disrupted left TPJ-reward pathway communication (ventral striatum, putamen, amygdala); (3) Right TPJ/left vTPJ hyperconnectivity with cognitive control systems (frontoparietal network, orbitofrontal cortex, anterior cingulate cortex); (4) Enhanced somatosensory-motor connectivity with reduced visual/auditory input; (5) Impaired intra-TPJ communication.&#xa0;TPJ subregions exhibit distinct dysconnectivity patterns in non-clinical depression, affecting self-referential processing, reward integration, and cognitive control. Multi-metric profiling identifies TPJ as a potential pathophysiological biomarker.</p>

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Functional Breakdown of Temporoparietal Junction Interaction in High-depression Individuals: Evidence from Multi-Metric Connectomics

  • 期刊论文

  • 发表日期：

    2026年4月30日

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  • Xiaotong Wen,
  • Yao Fengge,
  • Bin Han,
  • Guodong Wei,
  • Yuehan Gao,
  • Yuying Chen,
  • Ziyu Hao,
  • Huanhuan Li,
  • Fengyu Dou

摘要

Depression involves impaired cognitive, affective, and social functions associated with aberrant brain network interactions. The temporoparietal junction (TPJ), a multisensory integration hub, exhibits depression-related connectivity alterations, yet the roles of its subregions during subclinical stages remain unclear. This study examined TPJ subregional communication in non-clinical high-depression individuals. Resting-state fMRI data from 586 medication-free young adults were analyzed. Participants were divided into high-depression (HD, N = 130) and low-depression (LD, N = 130) groups using Beck Depression Inventory scores. TPJ was parcellated into anterior (aTPJ), posterior (pTPJ), and ventral (vTPJ) subregions via community detection. Multi-metric connectivity (functional connectivity/FC, total interdependence/TI, Granger causality/GC) seeded from TPJ subregions was compared between groups. Support vector machine (SVM) fusion analysis identified high-contribution features for network alteration modeling. TPJ subregions showed depression-related connectivity patterns: (1) Altered default mode network DMN interactions featuring enhanced anterior DMN (medial prefrontal cortex) connectivity and weakened posterior DMN (posterior cingulate/precuneus) connectivity; (2) Disrupted left TPJ-reward pathway communication (ventral striatum, putamen, amygdala); (3) Right TPJ/left vTPJ hyperconnectivity with cognitive control systems (frontoparietal network, orbitofrontal cortex, anterior cingulate cortex); (4) Enhanced somatosensory-motor connectivity with reduced visual/auditory input; (5) Impaired intra-TPJ communication. TPJ subregions exhibit distinct dysconnectivity patterns in non-clinical depression, affecting self-referential processing, reward integration, and cognitive control. Multi-metric profiling identifies TPJ as a potential pathophysiological biomarker.