Neural Correlates of Cognitive Load While Playing an Emergency Simulation Game: A Functional Near-Infrared Spectroscopy (fNIRS) Study

被引:0
|
作者
Sevcenko, Natalia [1 ,2 ]
Schopp, Betti [3 ]
Dresler, Thomas [3 ,4 ]
Ehlis, Ann-Christine [3 ,4 ]
Ninaus, Manuel [4 ,5 ,6 ,7 ]
Moeller, Korbinian [4 ,8 ]
Gerjets, Peter [4 ,6 ]
机构
[1] Univ Tubingen, Dept Psychol, D-72074 Tubingen, Germany
[2] Daimler Trucks AG, D-70771 Stuttgart, Germany
[3] Univ Hosp Tuebingen, Tubingen Ctr Mental Hlth, Dept Psychiat & Psychotherapy, D-72076 Tubingen, Germany
[4] Univ Tubingen, LEAD Grad Sch & Res Network, D-72072 Tubingen, Germany
[5] Univ Innsbruck, A-6020 Innsbruck, Austria
[6] Univ Tubingen, Leibniz Inst Wissensmedien, D-72076 Tubingen, Germany
[7] Karl Franzens Univ Graz, Dept Psychol, Inst Psychol, A-8010 Graz, Austria
[8] Loughborough Univ, Ctr Math Cognit, Sch Sci, Loughborough LE11 32U, England
关键词
Adaptivity; cognitive load; functional near-infrared spectroscopy (fNIRS); game; simulation; PREFRONTAL CORTEX; OXYGEN-CONSUMPTION; WORKING-MEMORY; TASK; HEMOGLOBIN; ACTIVATION; WORKLOAD;
D O I
10.1109/TG.2022.3142954
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Functional near-infrared spectroscopy (fNIRS) provides reliable results for determining cognitive load based on averaged cortical blood flow during multiple repetitions of short cognitive tasks. At the same time, it remains unclear how to use this technique for assessing cognitive load during prolonged single-trial activity. In this study, we used a computer-based emergency simulation game for inducing different levels of cognitive load. We propose a novel approach to measure cognitive load using specific time slots, determined based on simulation log-data interpreted in light of Barrouillet's time-based resource-sharing model. To validate this approach, we compared cortical activity in dorsolateral prefrontal cortex (DLPFC) and left inferior frontal gyrus (IFG) regions measured at four specific time slots during a simulation. We found significant associations between cognitive load and neuronal activity within the DLPFC depending on the chosen time slot, whereas no such dependencies were found for the IFG. These results illustrate how knowledge of task structure could be used advantageously for the identification of cognitive load. Although requiring further investigation in terms of reliability and generalizability, the presented approach can be considered promising evidence that fNIRS might be suitable for more general reliable assessments of cognitive load during prolonged single-trial activities and for real-time adaptations in simulation-based learning environments.
引用
收藏
页码:696 / 705
页数:10
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