在沉浸式多任务处理过程中,瞳孔关联的唤醒调节了注意力重新定向的网络级脑电图特征。

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Pawan Lapborisuth, Sharath Koorathota, Paul Sajda
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引用次数: 0

摘要

目标。当同时处理多项任务时,我们必须在不同的任务之间动态地重新调整我们的注意力。注意重定向被认为是通过生理唤醒和全脑网络动态的相互作用而产生的。在这项研究中,我们研究了在虚拟现实中进行的多任务驱动范式下瞳孔相关觉醒与脑电图(EEG)脑动力学之间的关系。我们假设在觉醒和脑电图动态之间会有一种相互作用,这种相互作用与多任务处理的表现有关。我们收集了受试者在模拟城市环境中驾驶摩托车时的脑电图和眼动追踪数据,并指示他们在避免撞上领头车辆的同时,计算他们观察到的目标图像的数量。该范式要求受试者在两个任务之间不断地重新调整他们的注意力。受试者在两种条件下执行范式,其中一种比另一种更难。主要的结果。我们发现,任务难度与瞳孔相关的唤醒并没有很强的相关性,而且随着唤醒水平的提高,整体任务表现也会提高。一项单试验分析揭示了与瞳孔相关的觉醒和与任务相关的脑电图动态之间的几个有趣的关系。采用精确的低分辨率电磁断层扫描,我们发现较高的瞳孔相关唤醒导致更大的脑电图振荡活动,特别是在与背侧注意网络和腹侧注意网络(VAN)相关的区域。与我们的假设一致,我们发现脑电图功能连通性和瞳孔相关的觉醒之间存在关系,作为多任务处理的功能。具体来说,我们发现随着瞳孔相关唤醒的增加,突出网络(SN)和VAN区域之间的功能连接减少,这表明在高唤醒水平下,多任务处理性能的提高可能是由于VAN和SN之间耦合的下调。我们的研究结果表明,在多任务处理时,我们的大脑会重新平衡基于唤醒的重新定向,这样就可以满足个人任务的需求,而不会过早地重新定向到竞争任务上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pupil-linked arousal modulates network-level EEG signatures of attention reorienting during immersive multitasking.

Objective. When multitasking, we must dynamically reorient our attention between different tasks. Attention reorienting is thought to arise through interactions of physiological arousal and brain-wide network dynamics. In this study, we investigated the relationship between pupil-linked arousal and electroencephalography (EEG) brain dynamics in a multitask driving paradigm conducted in virtual reality. We hypothesized that there would be an interaction between arousal and EEG dynamics and that this interaction would correlate with multitasking performance.Approach. We collected EEG and eye tracking data while subjects drove a motorcycle through a simulated city environment, with the instructions to count the number of target images they observed while avoiding crashing into a lead vehicle. The paradigm required the subjects to continuously reorient their attention between the two tasks. Subjects performed the paradigm under two conditions, one more difficult than the other.Main results. We found that task difficulty did not strongly correlate with pupil-linked arousal, and overall task performance increased as arousal level increased. A single-trial analysis revealed several interesting relationships between pupil-linked arousal and task-relevant EEG dynamics. Employing exact low-resolution electromagnetic tomography, we found that higher pupil-linked arousal led to greater EEG oscillatory activity, especially in regions associated with the dorsal attention network and ventral attention network (VAN). Consistent with our hypothesis, we found a relationship between EEG functional connectivity and pupil-linked arousal as a function of multitasking performance. Specifically, we found decreased functional connectivity between regions in the salience network (SN) and the VAN as pupil-linked arousal increased, suggesting that improved multitasking performance at high arousal levels may be due to a down-regulation in coupling between the VAN and the SN. Our results suggest that when multitasking, our brain rebalances arousal-based reorienting so that individual task demands can be met without prematurely reorienting to competing tasks.

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来源期刊
Journal of neural engineering
Journal of neural engineering 工程技术-工程:生物医学
CiteScore
7.80
自引率
12.50%
发文量
319
审稿时长
4.2 months
期刊介绍: The goal of Journal of Neural Engineering (JNE) is to act as a forum for the interdisciplinary field of neural engineering where neuroscientists, neurobiologists and engineers can publish their work in one periodical that bridges the gap between neuroscience and engineering. The journal publishes articles in the field of neural engineering at the molecular, cellular and systems levels. The scope of the journal encompasses experimental, computational, theoretical, clinical and applied aspects of: Innovative neurotechnology; Brain-machine (computer) interface; Neural interfacing; Bioelectronic medicines; Neuromodulation; Neural prostheses; Neural control; Neuro-rehabilitation; Neurorobotics; Optical neural engineering; Neural circuits: artificial & biological; Neuromorphic engineering; Neural tissue regeneration; Neural signal processing; Theoretical and computational neuroscience; Systems neuroscience; Translational neuroscience; Neuroimaging.
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