Causal Interactions Within a Frontal-Cingulate-Parietal Network During Cognitive Control: Convergent Evidence from a Multisite-Multitask Investigation

被引:112
作者
Cai, Weidong [1 ]
Chen, Tianwen [1 ]
Ryali, Srikanth [1 ]
Kochalka, John [1 ]
Li, Chiang-Shan R. [4 ]
Menon, Vinod [1 ,2 ,3 ]
机构
[1] Stanford Univ, Sch Med, Dept Psychiat & Behav Sci, 401 Quarry Rd, Stanford, CA 94305 USA
[2] Stanford Univ, Sch Med, Dept Neurol & Neurol Sci, Stanford, CA 94305 USA
[3] Stanford Univ, Sch Med, Stanford Neurosci Inst, Stanford, CA 94305 USA
[4] Yale Univ, Sch Med, Dept Neurobiol, New Haven, CT 06519 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
brain network; connectivity; fMRI; human; temporal dependence; SCALE BRAIN NETWORKS; RESPONSE-INHIBITION; ANTERIOR INSULA; FUNCTIONAL PARCELLATION; EXECUTIVE FUNCTIONS; CONNECTIVITY; CORTEX; TASK; ATTENTION; MODELS;
D O I
10.1093/cercor/bhv046
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Cognitive control plays an important role in goal-directed behavior, but dynamic brain mechanisms underlying it are poorly understood. Here, using multisite fMRI data from over 100 participants, we investigate causal interactions in three cognitive control tasks within a core Frontal-Cingulate-Parietal network. We found significant causal influences from anterior insula (AI) to dorsal anterior cingulate cortex (dACC) in all three tasks. The AI exhibited greater net causal outflow than any other node in the network. Importantly, a similar pattern of causal interactions was uncovered by two different computational methods for causal analysis. Furthermore, the strength of causal interaction from AI to dACC was greater on high, compared with low, cognitive control trials and was significantly correlated with individual differences in cognitive control abilities. These results emphasize the importance of the AI in cognitive control and highlight its role as a causal hub in the Frontal-Cingulate-Parietal network. Our results further suggest that causal signaling between the AI and dACC plays a fundamental role in implementing cognitive control and are consistent with a two-stage cognitive control model in which the AI first detects events requiring greater access to cognitive control resources and then signals the dACC to execute load-specific cognitive control processes.
引用
收藏
页码:2140 / 2153
页数:14
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