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首页> 外文期刊>Frontiers in Psychology >Task-Dependent Modulation of Effective Connectivity within the Default Mode Network
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Task-Dependent Modulation of Effective Connectivity within the Default Mode Network

机译:默认模式网络内有效连接的任务相关调制

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The default mode network (DMN) has recently attracted widespread interest. Previous studies have found that task-related processing can induce deactivation and changes in the functional connectivity of this network. However, it remains unclear how tasks modulate the underlying effective connectivity within the DMN. Using recent advances in dynamic causal modeling (DCM), we investigated the modulatory effect of (gender judgment) task performance on directed connectivity within the DMN. Sixteen healthy subjects were scanned twice: at rest and while performing a gender judgment task. Group independent component analysis was used to identify independent spatial components. Four subject-specific regions of interest (ROIs) were defined according to the ensuing default mode component: the posterior cingulate cortex, the left lateral parietal cortex, the right lateral parietal cortex, and the medial prefrontal cortex. Effective connectivity among these regions was then characterized with stochastic DCM, revealing enhanced (extrinsic) between region connectivity within the DMN during task sessions – and a universal decrease in (intrinsic) self-inhibition – relative to resting sessions. These results suggest a distributed but systematic modulatory effect of cognitive and attentional set on the effective connectivity subtending the DMN: an effect that increases its sensitivity to inputs and may optimize distributed processing during task performance.
机译:默认模式网络(DMN)最近引起了广泛的关注。先前的研究发现,与任务相关的处理可能会导致该网络的功能连接中的停用和更改。但是,仍然不清楚任务如何在DMN中调节基础有效连接。利用动态因果建模(DCM)的最新进展,我们研究了(性别判断)任务绩效对DMN内定向连接的调节作用。对16名健康受试者进行了两次扫描:休息时和在执行性别判断任务时。组独立成分分析用于识别独立的空间成分。根据随后的默认模式组件,定义了四个受检者特定的感兴趣区域(ROI):后扣带回皮层,左侧顶叶皮层,右侧顶叶皮层和内侧前额叶皮层。然后用随机DCM表征了这些区域之间的有效连通性,揭示了在任务会话期间DMN内的区域连通性之间的增强(外部)相对于静止会话而言(内部)自我抑制普遍降低。这些结果表明,认知和注意力集中对DMN的有效连接具有分布式但系统的调节作用:这种作用增加了其对输入的敏感性,并可能在任务执行期间优化了分布式处理。

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