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自发策略转变和增量任务优化过程中的大脑网络动态。

Brain network dynamics during spontaneous strategy shifts and incremental task optimization.

机构信息

Scuola Internazionale Superiore di Studi Avanzati, Trieste, 34136, Trieste, Italy; Institut de Neurosciences de la Timone, Aix Marseille Université, UMR 7289 CNRS, 13005, Marseille, France.

School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), P.O. Box 19395-5746, Tehran, Iran.

出版信息

Neuroimage. 2020 Aug 15;217:116854. doi: 10.1016/j.neuroimage.2020.116854. Epub 2020 Apr 22.

Abstract

With practice, humans improve their performance in a task by either optimizing a known strategy or discovering a novel, potentially more fruitful strategy. We investigated the neural processes underlying these two fundamental abilities by applying fMRI in a task with two possible alternative strategies. For analysis we combined time-resolved network analysis with Coherence Density Peak Clustering (Allegra et al., 2017), univariate GLM, and multivariate pattern classification. Converging evidence showed that the posterior portion of the default network, i.e. the precuneus and the angular gyrus bilaterally, has a central role in the optimization of the current strategy. These regions encoded the relevant spatial information, increased the strength of local connectivity as well as the long-distance connectivity with other relevant regions in the brain (e.g., visual cortex, dorsal attention network). The connectivity increase was proportional to performance optimization. By contrast, the anterior portion of the default network (i.e. medial prefrontal cortex) and the rostral portion of the fronto-parietal network were associated with new strategy discovery: an early increase of local and long-range connectivity centered on these regions was only observed in the subjects who would later shift to a new strategy. Overall, our findings shed light on the dynamic interactions between regions related to attention and with cognitive control, underlying the balance between strategy exploration and exploitation. Results suggest that the default network, far from being "shut-down" during task performance, has a pivotal role in the background exploration and monitoring of potential alternative courses of action.

摘要

经过练习,人类可以通过优化已知策略或发现新的、可能更有效的策略来提高任务表现。我们通过在一个有两种可能替代策略的任务中应用 fMRI 来研究这两种基本能力的神经过程。为了分析,我们将时间分辨网络分析与相干密度峰聚类(Allegra 等人,2017 年)、单变量 GLM 和多变量模式分类相结合。一致的证据表明,默认网络的后部区域,即双侧的楔前叶和角回,在当前策略的优化中起着核心作用。这些区域编码了相关的空间信息,增加了局部连接的强度以及与大脑中其他相关区域(例如,视觉皮层、背侧注意网络)的远距离连接。连接的增加与性能优化成正比。相比之下,默认网络的前部区域(即内侧前额叶皮层)和额顶网络的前部区域与新策略的发现有关:只有那些后来转向新策略的受试者才会观察到这些区域为中心的局部和远距离连接的早期增加。总的来说,我们的发现揭示了与注意力和认知控制相关的区域之间的动态相互作用,这些区域是策略探索和利用之间的平衡的基础。结果表明,默认网络远非在任务执行期间“关闭”,而是在潜在替代行动方案的背景探索和监测中起着关键作用。

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