Institut de Neurosciences des Systèmes (INS), Inserm, Aix-Marseille University, Marseille 13005, France.
Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.
Neuroimage. 2023 Dec 1;283:120403. doi: 10.1016/j.neuroimage.2023.120403. Epub 2023 Oct 20.
The mechanisms of cognitive decline and its variability during healthy aging are not fully understood, but have been associated with reorganization of white matter tracts and functional brain networks. Here, we built a brain network modeling framework to infer the causal link between structural connectivity and functional architecture and the consequent cognitive decline in aging. By applying in-silico interhemispheric degradation of structural connectivity, we reproduced the process of functional dedifferentiation during aging. Thereby, we found the global modulation of brain dynamics by structural connectivity to increase with age, which was steeper in older adults with poor cognitive performance. We validated our causal hypothesis via a deep-learning Bayesian approach. Our results might be the first mechanistic demonstration of dedifferentiation during aging leading to cognitive decline.
认知能力下降及其在健康衰老过程中的变化机制尚不完全清楚,但与白质束和功能大脑网络的重组有关。在这里,我们构建了一个大脑网络建模框架,以推断结构连接性与功能结构之间的因果关系,以及随之而来的衰老过程中的认知能力下降。通过应用结构连接性的大脑半球间退化的计算方法,我们复制了衰老过程中的功能去分化过程。由此,我们发现结构连接性对大脑动力学的全局调制随着年龄的增长而增加,而在认知表现较差的老年人中,这种增加更为陡峭。我们通过深度学习贝叶斯方法验证了我们的因果假设。我们的研究结果可能是衰老过程中去分化导致认知能力下降的第一个机制性证明。