Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Clinical Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany.
Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands.
Mol Psychiatry. 2024 Oct;29(10):3245-3267. doi: 10.1038/s41380-024-02556-y. Epub 2024 Apr 24.
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.
环境体验在塑造大脑结构和功能方面起着至关重要的作用。几十年来，大脑对外界刺激的这种可塑性一直是研究的重点。在这篇综述中，我们探讨了逆境对大脑结构和功能的影响，以及它对大脑发育、适应和心理健康障碍出现的影响。我们专注于个体周围环境中出现的不利事件，即微环境。它们包括儿童虐待、同伴受害、社交孤立、情感丧失、家庭冲突和贫困。我们还考虑了环境毒素的暴露。越来越多的证据表明，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，它们通常是孤立地研究的，这限制了我们对它们综合影响以及它们相互影响的性质的理解。通过大型、深度表型数据集的整合和合作努力，可以提供足够的分析高维环境特征的能力，并推进神经元机制的系统映射。这篇综述为未来的研究提供了背景，强调了通过数据驱动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。
