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The impact of psychosocial adversity on brain and behaviour: an overview of existing knowledge and directions for future research
Molecular Psychiatry ( IF 11.0 ) Pub Date : 2024-04-24 , DOI: 10.1038/s41380-024-02556-y
Nilakshi Vaidya , Andre F. Marquand , Frauke Nees , Sebastian Siehl , Gunter Schumann

Environmental experiences play a critical role in shaping the structure and function of the brain. Its plasticity in response to different external stimuli has been the focus of research efforts for decades. In this review, we explore the effects of adversity on brain’s structure and function and its implications for brain development, adaptation, and the emergence of mental health disorders. We are focusing on adverse events that emerge from the immediate surroundings of an individual, i.e., microenvironment. They include childhood maltreatment, peer victimisation, social isolation, affective loss, domestic conflict, and poverty. We also take into consideration exposure to environmental toxins. Converging evidence suggests that different types of adversity may share common underlying mechanisms while also exhibiting unique pathways. However, they are often studied in isolation, limiting our understanding of their combined effects and the interconnected nature of their impact. The integration of large, deep-phenotyping datasets and collaborative efforts can provide sufficient power to analyse high dimensional environmental profiles and advance the systematic mapping of neuronal mechanisms. This review provides a background for future research, highlighting the importance of understanding the cumulative impact of various adversities, through data-driven approaches and integrative multimodal analysis techniques.



中文翻译:

社会心理逆境对大脑和行为的影响:现有知识概述和未来研究方向

环境经历在塑造大脑的结构和功能方面发挥着至关重要的作用。几十年来,其对不同外部刺激的可塑性一直是研究的焦点。在这篇综述中,我们探讨了逆境对大脑结构和功能的影响及其对大脑发育、适应和心理健康障碍出现的影响。我们关注的是个体周围环境(即微环境)中出现的不良事件。其中包括童年虐待、同伴受害、社会孤立、情感丧失、家庭冲突和贫困。我们还考虑到环境毒素的暴露。汇聚的证据表明,不同类型的逆境可能具有共同的潜在机制,同时也表现出独特的途径。然而,它们经常被孤立地研究,限制了我们对其综合效应及其影响的相互关联性质的理解。大型、深层表型数据集和协作努力的整合可以提供足够的能力来分析高维环境概况并推进神经元机制的系统映射。本综述为未来的研究提供了背景,强调通过数据驱动的方法和综合多模态分析技术了解各种逆境的累积影响的重要性。

更新日期:2024-04-24
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