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首页> 外文会议>2013 7th International Symposium on Medical Information and Communication Technology : Towards Better Personalized Medicine and Healthcare >Age-related changes in resting-state and task-activated functional MRI networks
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Age-related changes in resting-state and task-activated functional MRI networks

机译：与年龄有关的静止状态和任务激活功能MRI网络的变化

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Resting-State Networks (RSNs) shown in functional magnetic resonance imaging (fMRI) have been consistently and reliably identified. Amongst these, the Default Mode Network (DMN) has been most well researched and shown to have age-related decrease in functional connectivity and negative consequences for cognition. There are two other distinct RSNs, Salience Network (SN) and Executive Control Network (ECN), shown to co-activate during fMRI tasks. The SN has been suggested to be correlated with cognitive decline in healthy aging, however, the age-related dynamics between these three RSNs are not well understood. The current study examined the DMN, SN and ECN during resting-state fMRI in young and elderly from Japan and Singapore using data-driven independent component analysis (ICA) and functional network connectivity (FNC). We further investigated if the functional connectivity of the DMN and SN varied across tasks of different cognitive demands between young and elderly. Interestingly, the elderly had increased intrinsic activity that deviated from the expected DMN, SN and ECN, and increased functional connectivity within the anterior SN relative to the young during resting-state fMRI. For task fMRI, the elderly showed decreased activation in the primary networks of visual and motor processing, and increased task related activity for higher cognitive processes. However, the DMN and SN for task fMRI revealed consistent increased activity shifted outside the expected regions for the elderly. Difference in functional connectivity between young and elderly was varied across tasks. The elderly had marginally less number of correlated component pairs compared to the young, suggesting a decline in functional network integrity in aging. The current study demonstrated that resting-state data could be combined across two sites using ICA, as well as the use of DMN and SN as reliable networks to examine age-related changes in rest and task fMRI. Understanding the dynamics of th- se networks in relation to aging will provide potential neuroimaging markers for enhancing cognition, as well as detecting pathological decline.
机译：功能性磁共振成像（fMRI）中显示的静止状态网络（RSN）已得到一致且可靠的识别。其中，对默认模式网络（DMN）的研究最为深入，并显示出与年龄相关的功能连接性下降以及对认知的负面影响。另外还有两个不同的RSN，即显着网络（SN）和执行控制网络（ECN），它们在fMRI任务期间共同激活。 SN被认为与健康衰老中的认知能力下降相关，但是，这三个RSN之间的年龄相关动态尚不十分清楚。当前的研究使用数据驱动的独立成分分析（ICA）和功能网络连接（FNC）在日本和新加坡的年轻人和老年人中对静止状态fMRI期间的DMN，SN和ECN进行了检查。我们进一步调查了DMN和SN的功能连接性是否在年轻人和老年人之间因认知需求不同而异。有趣的是，在静息状态fMRI期间，老年人的内在活动增加，与预期的DMN，SN和ECN有所偏离，并且前SN内相对于年轻人的功能连接性增加。对于任务功能磁共振成像，老年人在视觉和运动处理的主要网络中显示出减少的激活，并在更高的认知过程中增加了与任务相关的活动。然而，用于任务功能磁共振成像的DMN和SN显示，活动持续增加，转移到了老年人的预期区域之外。年轻人和老人之间在功能连接上的差异因任务而异。与年轻人相比，老年人的相关组件对数量略少，这表明衰老时功能网络完整性下降。目前的研究表明，静息状态数据可以使用ICA跨两个站点进行合并，并且可以使用DMN和SN作为可靠的网络来检查与年龄相关的静息和任务功能磁共振成像变化。了解与衰老有关的这些网络的动态变化将提供潜在的神经影像标记物，以增强认知能力并检测病理性衰退。

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