Bätz Leona Rahel, Ye Shuer, Lan Xiaqing, Ziaei Maryam
Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway.
Queensland Brain Institute, University of Queensland, Brisbane, Australia.
bioRxiv. 2024 Oct 9:2024.04.10.588823. doi: 10.1101/2024.04.10.588823.
Across the adult lifespan, emotion regulation ability remains stable or even improves. The corresponding effects, however, in the emotion regulation networks in the brain remain underexplored. By utilizing large-scale datasets such as the Human Connectome Project (HCP-Aging, N=621, 349 females) and Cambridge Centre for Ageing and Neuroscience (Cam-CAN, N=333, 155 females), we were able to investigate how emotion regulation networks' functional topography differs across the entire adult lifespan. Based on previous meta-analytic work that identified four large-scale functional brain networks involved in emotion generation and regulation, we investigated the association between the integration of these emotion regulation networks and measures of mental wellbeing with age in the HCP-Aging dataset. We found an increase in the functional integration of the emotional control network among older adults, which was replicated using the Cam-CAN data set. Further we found that the network that is mediating emotion generative and regulative processes, and carries our introspective and reflective functions, is less integrated in higher age. Our study highlights the importance of identifying topological changes in the functional emotion network architecture across the lifespan, as it allows for a better understanding of functional brain network changes that accompany emotional aging.
在整个成年期,情绪调节能力保持稳定甚至有所提高。然而,大脑中情绪调节网络的相应影响仍未得到充分研究。通过利用大规模数据集,如人类连接组计划(HCP-衰老,N = 621,349名女性)和剑桥衰老与神经科学中心(Cam-CAN,N = 333,155名女性),我们能够研究情绪调节网络的功能拓扑在整个成年期是如何不同的。基于之前的荟萃分析工作,确定了四个参与情绪产生和调节的大规模功能性脑网络,我们在HCP-衰老数据集中研究了这些情绪调节网络的整合与心理健康指标随年龄的关联。我们发现老年人情绪控制网络的功能整合增加,这在Cam-CAN数据集中得到了重复验证。此外,我们发现介导情绪产生和调节过程并执行内省和反思功能的网络在较高年龄时整合程度较低。我们的研究强调了识别整个生命周期中功能性情绪网络架构拓扑变化的重要性,因为这有助于更好地理解伴随情绪衰老的功能性脑网络变化。