Functional Connectivity Within the Fronto-Parietal Network Predicts Complex Task Performance: A fNIRS Study

Quentin Chenot, E. Lepron, X. de Boissezon, S. Scannella
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引用次数: 9

Abstract

Performance in complex tasks is essential for many high risk operators. The achievement of such tasks is supported by high-level cognitive functions arguably involving functional activity and connectivity in a large ensemble of brain areas that form the fronto-parietal network. Here we aimed at determining whether the functional connectivity at rest within this network could predict performance in a complex task: the Space Fortress video game. Functional Near Infrared Spectroscopy (fNIRS) data from 32 participants were recorded during a Resting-State period, the completion of a simple version of Space Fortress (monotask) and the original version (multitask). The intrinsic functional connectivity within the fronto-parietal network (i.e., during the Resting-State) was a significant predictor of performance at Space Fortress multitask but not at its monotask version. The same pattern was observed for the functional connectivity during the task. Our overall results suggest that Resting-State functional connectivity within the fronto-parietal network could be used as an intrinsic brain marker for performance prediction of a complex task achievement, but not for simple task performance.
额顶叶网络功能连接预测复杂任务表现:一项近红外光谱研究
对于许多高风险操作人员来说,复杂任务的性能至关重要。这些任务的完成是由高水平的认知功能支持的,这可能涉及到形成额顶叶网络的大量大脑区域的功能活动和连通性。在这里,我们的目标是确定该网络中静止的功能连接是否可以预测复杂任务中的表现:太空堡垒电子游戏。研究人员记录了32名参与者在静息状态、完成简单版《太空堡垒》(单任务)和原始版《太空堡垒》(多任务)期间的功能近红外光谱(fNIRS)数据。额顶叶网络内的内在功能连通性(即在静息状态期间)是《太空堡垒》多任务表现的重要预测因子,而不是单任务版本。在任务期间的功能连接中也观察到相同的模式。我们的总体结果表明,额顶叶网络内的静息状态功能连通性可以用作预测复杂任务成就的内在大脑标记,但不能用于预测简单任务的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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