Sheng Jinhua, Yang Ze, Zhang Qiao, Wang Luyun, Xin Yu
College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China.
Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, Zhejiang, 310018, China.
Heliyon. 2023 Jul 13;9(7):e18121. doi: 10.1016/j.heliyon.2023.e18121. eCollection 2023 Jul.
The correlation between functional connectivity (FC) network segregation, glucose metabolism and cognitive decline has been recently identified. The coupling relationship between glucose metabolism and the intensity of neuronal activity obtained using hybrid PET/MRI techniques can provide additional information on the physiological state of the brain in patients with AD and mild cognitive impairment (MCI). It is a valuable task to use the above rules for constructing biomarkers that are closely related to the cognitive ability of individuals to monitor the pathological status of patients. This study proposed the concept of the energy connectivity (EC) network and its construction method. We hypothesized that the dissociation between energy connectivity and functional connectivity of brain regions is a valid indicator of cognitive ability in patients with dementia. The number of EC-attenuated brain regions (EC-AR) and the number of FC-attenuated brain regions (FC-AR) are obtained by comparison with the normal group, and the dissociation between functional connectivity and energy connectivity is indicated using the ratio of FC-AR to EC-AR for individuals in the disease group. The findings suggest that FC-AR/EC-AR values are accurate predictors of cognitive performance, while taking into account the cognitive recovery due to compensatory effects of the brain. The cognitive ability of some patients with cognitive recovery can also be predicted more accurately. This also indicates that lower functional connectivity and higher energy connectivity between network modules may be one of the important features that maintain cognitive performance. The concept of energy connectivity also has potential to help explore the pathological state of AD.
最近已确定功能连接（FC）网络分离、葡萄糖代谢与认知衰退之间的相关性。使用混合PET/MRI技术获得的葡萄糖代谢与神经元活动强度之间的耦合关系，可以为阿尔茨海默病（AD）和轻度认知障碍（MCI）患者的大脑生理状态提供更多信息。利用上述规则构建与个体认知能力密切相关的生物标志物以监测患者的病理状态是一项有价值的任务。本研究提出了能量连接（EC）网络的概念及其构建方法。我们假设脑区能量连接与功能连接之间的分离是痴呆患者认知能力的有效指标。通过与正常组比较获得EC减弱脑区（EC-AR）的数量和FC减弱脑区（FC-AR）的数量，并使用疾病组个体的FC-AR与EC-AR之比来表示功能连接与能量连接之间的分离。研究结果表明，FC-AR/EC-AR值是认知表现的准确预测指标，同时考虑到大脑代偿作用导致的认知恢复。一些具有认知恢复的患者的认知能力也可以更准确地预测。这也表明网络模块之间较低的功能连接和较高的能量连接可能是维持认知表现的重要特征之一。能量连接的概念也有潜力帮助探索AD的病理状态。
