From connectome to cognition: The search for mechanism in human functional brain networks.
From connectome to cognition: The search for mechanism in human functional brain networks.
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DOI：
10.1016/j.neuroimage.2017.01.060
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发表时间：
2017-10-15
期刊：
影响因子：
5.7
通讯作者：
Cole MW
中科院分区：
文献类型：
--
作者：
Mill RD;Ito T;Cole MW
功能连通性研究的最新进展扩大了人类神经成像的范围，从识别区域激活幅度的变化到大规模大脑网络的详细映射。然而，将网络过程与认知中的明确角色联系起来，需要在理论框架、算法和应用的实验方法方面取得进展。这将有助于通过瞄准可以机械地解释认知影响的网络交互，将该领域从描述性状态演变为解释性状态。在目前的综述中，我们提供了一个明确的框架来帮助寻找“网络机制”，它将最近在功能连接性估计方面的方法学进展锚定到重新强调仔细的实验设计上。我们强调这个框架如何解决网络神经科学中的特定问题。这些问题涉及静息状态网络的认知相关性、如何描述任务诱发的和自发的网络动态、如何识别定向的或“有效的”连接，以及如何在网络层面上应用多变量模式分析。同时，我们应用该框架来突出网络组件之间的机械性交互，这些组件在任务域之间保持“稳定”，并且与任务上的重新配置相关的更“灵活”的组件。通过强调需要将各种分析方法的使用与健全的实验结合起来，我们的框架促进了认知思维的工作方式和人脑的大规模网络机制之间的解释性映射。
Recent developments in functional connectivity research have expanded the scope of human neuroimaging, from identifying changes in regional activation amplitudes to detailed mapping of large-scale brain networks. However, linking network processes to a clear role in cognition demands advances in the theoretical frameworks, algorithms, and experimental approaches applied. This would help evolve the field from a descriptive to an explanatory state, by targeting network interactions that can mechanistically account for cognitive effects. In the present review, we provide an explicit framework to aid this search for “network mechanisms”, which anchors recent methodological advances in functional connectivity estimation to a renewed emphasis on careful experimental design. We emphasize how this framework can address specific questions in network neuroscience. These span ambiguity over the cognitive relevance of resting-state networks, how to characterize task-evoked and spontaneous network dynamics, how to identify directed or “effective” connections, and how to apply multivariate pattern analysis at the network level. In parallel, we apply the framework to highlight the mechanistic interaction of network components that remain “stable” across task domains and more “flexible” components associated with on-task reconfiguration. By emphasizing the need to structure the use of diverse analytic approaches with sound experimentation, our framework promotes an explanatory mapping between the workings of the cognitive mind and the large-scale network mechanisms of the human brain.
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