文章基本信息

标题：Distributed representation of context by intrinsic subnetworks in prefrontal cortex
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作者：Michael L. Waskom ; Anthony D. Wagner
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2017
卷号：114
期号：8
页码：2030-2035
DOI：10.1073/pnas.1615269114
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Human prefrontal cortex supports goal-directed behavior by representing information about task context. The organizational basis of these context representations, and of representations underlying other higher-order processes, is unknown. Here, we use multivariate decoding and analyses of spontaneous correlations to show that context representations are distributed across subnetworks within prefrontal cortex. Examining targeted prefrontal regions, we found that pairs of voxels with similar context preferences exhibited spontaneous correlations that were approximately twice as large as those between pairs with opposite context preferences. This subnetwork organization was stable across task-engaged and resting states, suggesting that context representations are constrained by an intrinsic functional architecture. These results reveal a principle of fine-scaled functional organization in association cortex.
关键词：fMRI ; resting-state ; rule ; cognitive control ; functional organization