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通过宏观大脑组织的个体差异来修正抑郁症的自我调节表型。

Revising a Self-Regulation Phenotype for Depression Through Individual Differences in Macroscale Brain Organization.

作者信息

Strauman Timothy J, Hariri Ahmad R

机构信息

Department of Psychology and Neuroscience, Duke University.

出版信息

Curr Dir Psychol Sci. 2023 Aug;32(4):267-275. doi: 10.1177/09637214221149742. Epub 2023 Apr 16.

Abstract

denotes the processes by which people initiate, maintain, and control their own thoughts, behaviors, or emotions to produce a desired outcome or avoid an undesired outcome. Self-regulation brings the influence of distal factors such as biology, temperament, and socialization history onto cognition, motivation, and behavior. Dysfunction in self-regulation represents a contributory causal factor for psychopathology. Accordingly, we previously proposed a risk phenotype model for depression drawing from regulatory focus theory and traditional task-based fMRI studies. In this article, we revise and expand our risk phenotype model using insights from new methodologies allowing quantification of individual differences in task-free macroscale brain organization. We offer a set of hypotheses as examples of how examination of intrinsic macroscale brain organization can extend and enrich investigations of self-regulation and depression. In doing so, we hope to promote a useful heuristic for model development and for identifying transdiagnostic risk phenotypes in psychopathology.

摘要

自我调节是指人们启动、维持和控制自己的思维、行为或情绪,以产生期望的结果或避免不期望的结果的过程。自我调节将生物学、气质和社会化历史等远端因素的影响施加于认知、动机和行为上。自我调节功能障碍是精神病理学的一个促成因果因素。因此,我们之前从调节焦点理论和传统的基于任务的功能磁共振成像研究中提出了一个抑郁症风险表型模型。在本文中,我们利用新方法的见解对我们的风险表型模型进行了修订和扩展,这些新方法能够量化无任务宏观大脑组织中的个体差异。我们提出了一组假设,作为内在宏观大脑组织检查如何扩展和丰富自我调节与抑郁症研究的示例。通过这样做,我们希望为模型开发以及识别精神病理学中的跨诊断风险表型促进一种有用的启发式方法。

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