Dunås Tora, Wåhlin Anders, Nyberg Lars, Boraxbekk Carl-Johan
Umeå Center for Functional Brain Imaging (UFBI), Umeå University, S-901 87 Umeå, Sweden.
Centre for Demographic and Ageing Research (CEDAR), Umeå University, S-901 87 Umeå, Sweden.
Cereb Cortex. 2021 Jun 10;31(7):3393-3407. doi: 10.1093/cercor/bhab019.
Maintaining a youthful brain structure and function throughout life may be the single most important determinant of successful cognitive aging. In this study, we addressed heterogeneity in brain aging by making image-based brain age predictions and relating the brain age prediction gap (BAPG) to cognitive change in aging. Structural, functional, and diffusion MRI scans from 351 participants were used to train and evaluate 5 single-modal and 4 multimodal prediction models, based on 7 regression methods. The models were compared on mean absolute error and whether they were related to physical fitness and cognitive ability, measured both currently and longitudinally, as well as study attrition and years of education. Multimodal prediction models performed at a similar level as single-modal models, and the choice of regression method did not significantly affect the results. Correlation with the BAPG was found for current physical fitness, current cognitive ability, and study attrition. Correlations were also found for retrospective physical fitness, measured 10 years prior to imaging, and slope for cognitive ability during a period of 15 years. The results suggest that maintaining a high physical fitness throughout life contributes to brain maintenance and preserved cognitive ability.
终生保持年轻的大脑结构和功能可能是认知衰老成功的最重要单一决定因素。在本研究中，我们通过基于图像的脑龄预测以及将脑龄预测差距（BAPG）与衰老过程中的认知变化相关联，来探讨脑衰老的异质性。利用来自351名参与者的结构、功能和扩散磁共振成像扫描数据，基于7种回归方法训练并评估了5种单模态和4种多模态预测模型。对这些模型的平均绝对误差以及它们是否与当前和纵向测量的身体素质和认知能力相关进行了比较，同时还比较了研究损耗和受教育年限。多模态预测模型的表现与单模态模型相似，回归方法的选择对结果没有显著影响。发现BAPG与当前身体素质、当前认知能力和研究损耗相关。还发现与成像前10年测量的回顾性身体素质以及15年期间认知能力的斜率相关。结果表明，终生保持较高的身体素质有助于维持大脑功能并保留认知能力。
