Expertise-related functional brain network efficiency in healthy older adults

BMC Neuroscience

Research Article

Aurea I. S. Haueter¹  Julia C. Binder²  Jürg Kühnis³  Carina Klein³  Hansruedi Baetschmann³  Ladina Bezzola⁴  Lutz Jäncke⁵ 

[1] Division of Gerontopsychology and Gerontology, Department of Psychology, University of Zurich, Zurich, Switzerland;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;University Research Priority Program (URPP) “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland;Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany;Division of Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland;International Normal Aging and Plasticity Imaging Center (INAPIC), University of Zurich, Zurich, Switzerland;University Research Priority Program (URPP) “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland;International Normal Aging and Plasticity Imaging Center (INAPIC), University of Zurich, Zurich, Switzerland;University Research Priority Program (URPP) “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland;Division of Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland;Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland;

关键词: Healthy aging;    Expertise;    Functional brain networks;    Electroencephalography (EEG);    Graph theory;    Network-based statistics (NBS);   

DOI  :  10.1186/s12868-016-0324-1

 received in 2016-10-26, accepted in 2016-12-14,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundIn 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.ResultsBehaviorally, 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.ConclusionsTaken 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.

【 授权许可】

CC BY   
© The Author(s) 2017