School of Psychology, Shaanxi Normal University, Xi'an, China; Key Laboratory of Behavior and Cognitive Neuroscience of Shaanxi, Shaanxi Normal University, Xi'an, China.
School of Management, Xi'an University of Science and Technology, Xi'an, China.
Behav Brain Res. 2025 Feb 4;477:115322. doi: 10.1016/j.bbr.2024.115322. Epub 2024 Nov 1.
OBJECTIVE: The objective of this study is to investigate the whether multi-tasking performance in (three-dimensional) 3D aid or impede cognition compare to (two-dimensional) 2D environments, as reflected by cognitive load. Specifically, we aim to examine the mechanism of multi-tasking under 3D (virtual reality [VR]) and 2D (PC monitor) conditions using the widely used Multi-Attribute Task Battery (MATB) II paradigm. METHODOLOGY: The MATB-II sub-tasks, namely "Tracking" and "System Monitoring," were conducted with varying task demands in both 3D conditions (Tracking Far - System Monitoring Near [TF-SN], Tracking Near - System Monitoring Far [TN-SF]) and a 2D condition with no depth perception (No Depth [ND]). Participants' cognitive load was assessed using subjective reporting (NASA-TLX) and physiological measure (root mean square of successive difference (RMSSD) of heart rate variability (HRV)). RESULTS: The study found that performance was significantly better in the ND condition compared to the TF-SN and TN-SF conditions. Furthermore, higher NASA-TLX scores and lower RMSSD values were observed in the TF-SN and TN-SN conditions compared to the ND condition, providing additional support for the overall findings of the MATB-II paradigm. CONCLUSION: These findings suggest that processing multiple tasks in different depth planes may lead to poorer performance and increased subjective and physiological cognitive load.
目的:本研究旨在通过认知负荷来探讨多任务处理在三维(3D)环境中相较于二维(2D)环境对认知的促进或阻碍作用。具体而言,我们旨在使用广泛使用的多属性任务电池(MATB)II 范式,研究三维(虚拟现实 [VR])和二维(PC 显示器)条件下多任务处理的机制。
方法:MATB-II 子任务,即“跟踪”和“系统监测”,在 3D 条件下(跟踪远-系统监测近 [TF-SN]、跟踪近-系统监测远 [TN-SF])和没有深度感知的 2D 条件(无深度 [ND])下,根据不同的任务需求进行。使用主观报告(NASA-TLX)和生理测量(心率变异性(HRV)的均方根差的连续差异(RMSSD))来评估参与者的认知负荷。
结果:研究发现,在 ND 条件下的表现明显优于 TF-SN 和 TN-SF 条件。此外,在 TF-SN 和 TN-SN 条件下,NASA-TLX 得分较高,RMSSD 值较低,这为 MATB-II 范式的总体发现提供了额外的支持。
结论:这些发现表明,在不同深度平面上处理多个任务可能会导致较差的表现和增加主观和生理认知负荷。
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