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Depressogenic self-schemas are associated with smaller regional grey matter volume in never-depressed preadolescents

机译:压抑的自我模式与永不抑制的重叠者中的较小区域灰质体积相关联

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Self-referential processing (i.e., self-schemas that guide processing of self-descriptive information) emerges early in youth, with deeper encoding of negative self-descriptors and/or shallower encoding of positive self-descriptors causally linked to depression. However, the relationship between depressogenic self-schemas and brain structure is unclear. We investigated associations between self-schemas and regional grey matter volume (GMV) in 84 never-depressed preadolescents oversampled for depression risk based on maternal depression history. Self-schemas were assessed using a Self-Referent Encoding Task (SRET) and regional GMV was indexed via voxel-based morphometry analysis of structural magnetic resonance imaging data. Youths’ positive self-schemas were associated with greater regional GMV within the ventrolateral prefrontal cortex (vlPFC) and posterior cingulate cortex (PCC), while negative self-schemas were associated with smaller regional GMV within vlPFC and PCC, areas important to emotion regulation and self-referential processing. These associations remained significant after controlling for youths’ concurrent depressive symptoms. Exploratory mediation analysis suggested that adolescents’ depressogenic self-schemas may mediate associations between GMV and depressive symptoms. Our findings suggest that the observed GMV variations within vlPFC and PCC may serve as neurobiological markers of depressogenic self-schemas during preadolescence.
机译:青年时期的自我参考处理(即,指导自我描述信息处理的自我模式)出现,具有更深入的编码负面自我描述符和/或正常自我描述符的较浅的编码与抑郁症有关。然而,抑制自我模式与大脑结构之间的关系尚不清楚。我们调查了在84年的自我模式和区域灰质体积(GMV)之间的协会,从未抑制的抑郁症过度采样过采样的抑郁风险。使用自称编码任务(SRET)进行评估自我模式,通过结构磁共振成像数据的基于体素的形态学分析来索引区域GMV。青少年积极的自我图式,用更大的区域GMV中相关腹外侧前额叶皮层(VLPFC),后扣带皮层(PCC),而消极的自我图式进行了内VLPFC和PCC,用较小的区域GMV相关领域的情绪调节重要自我参考处理。在控制青少年的同时抑郁症状后,这些协会仍然重大。探索性调解分析表明青少年的压抑性自我模式可以在GMV和抑郁症状之间介导关联。我们的研究结果表明,VLPFC和PCC内观察到的GMV变异可以作为预循环期间的降抑性自我模式的神经生物学标志物。

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