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

Quentin Chenot,Xavier De Boissezon,Evelyne Lepron,Sébastien Scannella

doi:10.3389/fnrgo.2021.718176

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.

Highlights

The ability to predict performance based on psychophysiological markers is one of the major interests of neuroergonomics (Ayaz et al, 2019)
Space Fortress Sub-scores Contribution to Resting-State Functional Connectivity Prediction Because a positive relationship was found between the fronto-parietal network (FPN) functional connectivity during RS and SF multitask performance, we investigated from post-hoc correlations4 to what extent the sub-scores contributed to this relationship
Our results are in favor of this hypothesis as we observed a significant relationship between the intrinsic functional connectivity of the FPN and SF multitask performance

Summary

Introduction

The ability to predict performance based on psychophysiological markers is one of the major interests of neuroergonomics (Ayaz et al, 2019). High-risk operators, in particular, are faced with multiple, complex tasks, and their ability to perform them successfully is important as it can have a major economic or human impact. The prediction of this capacity could be used as part of a selection process and/or as an indicator to target individualized trainings. We focused on the relationship between functional connectivity within the fronto-parietal network (FPN) at rest, and performance in Space Fortress (Mané and Donchin, 1989), a complex and semi-ecological task

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Conclusion