Binder Julia C, Bezzola Ladina, Haueter Aurea I S, Klein Carina, Kühnis Jürg, Baetschmann Hansruedi, Jäncke Lutz
Division of Gerontopsychology and Gerontology, Department of Psychology, University of Zurich, Zurich, Switzerland.
International Normal Aging and Plasticity Imaging Center (INAPIC), University of Zurich, Zurich, Switzerland.
BMC Neurosci. 2017 Jan 3;18(1):2. doi: 10.1186/s12868-016-0324-1.
In view of age-related brain changes, identifying factors that are associated with healthy aging are of great interest. In the present study, we compared the functional brain network characteristics of three groups of healthy older participants aged 61-75 years who had a different cognitive and motor training history (multi-domain group: participants who had participated in a multi-domain training; visuomotor group: participants who had participated in a visuomotor training; control group: participants with no specific training history). The study's basic idea was to examine whether these different training histories are associated with differences in behavioral performance as well as with task-related functional brain network characteristics. Based on a high-density electroencephalographic measurement one year after training, we calculated graph-theoretical measures representing the efficiency of functional brain networks.
Behaviorally, the multi-domain group performed significantly better than the visuomotor and the control groups on a multi-domain task including an inhibition domain, a visuomotor domain, and a spatial navigation domain. In terms of the functional brain network features, the multi-domain group showed significantly higher functional connectivity in a network encompassing visual, motor, executive, and memory-associated brain areas in the theta frequency band compared to the visuomotor group. These brain areas corresponded to the multi-domain task demands. Furthermore, mean connectivity of this network correlated positively with performance across both the multi-domain and the visuomotor group. In addition, the multi-domain group showed significantly enhanced processing efficiency reflected by a higher mean weighted node degree (strength) of the network as compared to the visuomotor group.
Taken together, our study shows expertise-dependent differences in task-related functional brain networks. These network differences were evident even a year after the acquisition of the different expertise levels. Hence, the current findings can foster understanding of how expertise is positively associated with brain functioning during aging.
鉴于与年龄相关的大脑变化，确定与健康衰老相关的因素备受关注。在本研究中，我们比较了三组年龄在61 - 75岁之间、具有不同认知和运动训练经历的健康老年参与者的功能性脑网络特征（多领域组：参加过多领域训练的参与者；视觉运动组：参加过视觉运动训练的参与者；对照组：无特定训练经历的参与者）。该研究的基本思路是检验这些不同的训练经历是否与行为表现差异以及与任务相关的功能性脑网络特征相关。基于训练一年后的高密度脑电图测量，我们计算了代表功能性脑网络效率的图论指标。
在行为方面，多领域组在包括抑制领域、视觉运动领域和空间导航领域的多领域任务上的表现显著优于视觉运动组和对照组。在功能性脑网络特征方面，与视觉运动组相比，多领域组在包含视觉、运动、执行和记忆相关脑区的网络中，θ频段的功能连接性显著更高。这些脑区与多领域任务需求相对应。此外，该网络的平均连接性与多领域组和视觉运动组的表现均呈正相关。此外，与视觉运动组相比，多领域组的网络平均加权节点度（强度）更高，这反映出其处理效率显著提高。
综上所述，我们的研究表明任务相关的功能性脑网络存在依赖于专业技能的差异。即使在获得不同专业技能水平一年后，这些网络差异仍然明显。因此，当前的研究结果有助于理解专业技能在衰老过程中如何与大脑功能呈正相关。
