Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea; Center for Systems and Translational Brain Sciences, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, South Korea.
The Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.
Neuroimage. 2018 Apr 1;169:485-495. doi: 10.1016/j.neuroimage.2017.12.067. Epub 2017 Dec 25.
Although the relationship between resting-state functional connectivity and task-related activity has been addressed, the relationship between task and resting-state directed or effective connectivity - and its behavioral concomitants - remains elusive. We evaluated effective connectivity under an N-back working memory task in 24 participants using stochastic dynamic causal modelling (DCM) of 7 T fMRI data. We repeated the analysis using resting-state data, from the same subjects, to model connectivity among the same brain regions engaged by the N-back task. This allowed us to: (i) examine the relationship between intrinsic (task-independent) effective connectivity during resting (A) and task states (A), (ii) cluster phenotypes of task-related changes in effective connectivity (B) across participants, (iii) identify edges (B) showing high inter-individual effective connectivity differences and (iv) associate reaction times with the similarity between B and A in these edges. We found a strong correlation between A and A over subjects but a marked difference between B and A. We further observed a strong clustering of individuals in terms of B, which was not apparent in A. The task-related effective connectivity B varied highly in the edges from the parietal to the frontal lobes across individuals, so the three groups were clustered mainly by the effective connectivity within these networks. The similarity between B and A at the edges from the parietal to the frontal lobes was positively correlated with 2-back reaction times. This result implies that a greater change in context-sensitive coupling - from resting-state connectivity - is associated with faster reaction times. In summary, task-dependent connectivity endows resting-state connectivity with a context sensitivity, which predicts the speed of information processing during the N-back task.
尽管静息态功能连接与任务相关活动之间的关系已经得到了研究，但任务与静息态导向或有效连接之间的关系——及其行为伴随物——仍然难以捉摸。我们使用 7T fMRI 数据的随机动态因果建模（DCM）评估了 24 名参与者在 N-back 工作记忆任务下的有效连接。我们使用来自同一受试者的静息态数据重复了分析，以对 N-back 任务所涉及的相同脑区之间的连接进行建模。这使我们能够：（i）检查静息（A）和任务状态（A）期间内在（任务独立）有效连接之间的关系，（ii）跨参与者聚类与任务相关的有效连接变化的表型（B），（iii）识别显示个体间有效连接差异较大的边（B），以及（iv）将反应时间与这些边中 B 和 A 之间的相似性相关联。我们发现，尽管 A 与 A 在个体间具有很强的相关性，但 B 与 A 之间存在明显的差异。我们进一步观察到，以 B 衡量的个体聚类具有很强的聚类性，而 A 中则没有。个体间的任务相关有效连接 B 在从顶叶到额叶的边缘上变化很大，因此三个组主要是根据这些网络内的有效连接进行聚类的。边缘处的 B 与 A 的相似性与 2 回反应时间呈正相关。这一结果表明，上下文敏感耦合（来自静息态连接）的变化越大，与反应时间越快相关。总之，任务相关的连接赋予静息态连接以上下文敏感性，这预测了 N-back 任务期间信息处理的速度。
