当前位置: X-MOL 学术Cortex › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Age differences in predicting working memory performance from network-based functional connectivity
Cortex ( IF 3.6 ) Pub Date : 2020-09-02 , DOI: 10.1016/j.cortex.2020.08.012
Rachel N Pläschke 1 , Kaustubh R Patil 1 , Edna C Cieslik 1 , Alessandra D Nostro 1 , Deepthi P Varikuti 1 , Anna Plachti 1 , Patrick Lösche 2 , Felix Hoffstaedter 3 , Tobias Kalenscher 4 , Robert Langner 1 , Simon B Eickhoff 1
Affiliation  

Deterioration in working memory capacity (WMC) has been associated with normal aging, but it remains unknown how age affects the relationship between WMC and connectivity within functional brain networks. We therefore examined the predictability of WMC from fMRI-based resting-state functional connectivity (RSFC) within eight meta-analytically defined functional brain networks and the connectome in young and old adults using relevance vector machine in a robust cross-validation scheme. Particular brain networks have been associated with mental functions linked to WMC to a varying degree and are associated with age-related differences in performance. Comparing prediction performance between the young and old sample revealed age-specific effects: In young adults, we found a general unpredictability of WMC from RSFC in networks subserving WM, cognitive action control, vigilant attention, theory-of-mind cognition, and semantic memory, whereas in older adults each network significantly predicted WMC. Moreover, both WM-related and WM-unrelated networks were differently predictive in older adults with low versus high WMC. These results indicate that the within-network functional coupling during task-free states is specifically related to individual task performance in advanced age, suggesting neural-level reorganization. In particular, our findings support the notion of a decreased segregation of functional brain networks, deterioration of network integrity within different networks and/or compensation by reorganization as factors driving associations between individual WMC and within-network RSFC in older adults. Thus, using multivariate pattern regression provided novel insights into age-related brain reorganization by linking cognitive capacity to brain network integrity.



中文翻译:

通过基于网络的功能连接来预测工作内存性能的年龄差异

工作记忆能力(WMC)的恶化与正常衰老相关,但是,年龄如何影响WMC与功能性大脑网络内连接性之间的关系仍是未知的。因此,我们在稳健的交叉验证方案中,使用相关矢量机从八个基于荟萃分析定义的功能性大脑网络内的基于功能磁共振成像的静止状态功能连接(RSFC)和年轻人和老年人的连接组中检验了WMC的可预测性。特定的大脑网络已与WMC关联的心理功能有不同程度的关联,并且与年龄相关的性能差异有关。比较年轻人和老年人样本的预测性能,发现特定年龄段的影响:在年轻人中,我们发现,在服务WM的网络中,RSFC普遍存在WMC的不可预测性,认知动作控制,警惕性关注,理论认知和语义记忆,而在老年人中,每个网络都可以显着预测WMC。此外,与低WMC和高WMC的老年人相比,与WM相关和与WM不相关的网络的预测均不同。这些结果表明,在无任务状态下的网络内功能耦合与高龄个体任务的表现特别相关,这表明神经层次的重组。尤其是,我们的发现支持以下观点:功能性大脑网络的隔离减少,不同网络内网络完整性的恶化和/或通过重组进行补偿,这是驱动老年人个体WMC与网络内RSFC之间关联的因素。从而,

更新日期:2020-10-13
down
wechat
bug