模拟虚拟环境中驾驶辅助的听觉神经关联与神经工效学。

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL Journal of neural engineering Pub Date : 2023-08-03 DOI:10.1088/1741-2552/ace79b
Halim I Baqapuri, Erik Roecher, Jana Zweerings, Stefan Wolter, Eike A Schmidt, Ruben C Gur, Klaus Mathiak
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引用次数: 0

摘要

目标。驾驶辅助系统在现代车辆中发挥着越来越重要的作用。在目前的技术水平下,驾驶员在使用驾驶辅助系统时必须持续监督驾驶,并在必要时进行干预。驾驶员的注意力在这种人机交互中起着重要的作用。我们的目标是设计一个简单的技术框架,用于在功能磁共振成像(fMRI)环境下研究驾驶情况的神经相关性。在这项工作中,我们评估了我们所提出的平台的可行性。方法:我们提出了一个驾驶员辅助的虚拟环境(VE)模拟作为研究与部分自动驾驶相关的大脑状态的框架。我们关注的是不同驾驶场景下听觉信号的处理,因为它们在驾驶情况下被证明是有利的警告刺激。这为在fMRI环境下研究不同环境要求下的大脑听觉注意网络提供了必要的基础。为此,我们对20名健康参与者进行了一项研究,以评估VE模拟的可行性。结果表明,我们提出的VE可以引发与驾驶相关的大脑激活模式。相关驾驶事件诱发了双侧听觉、感觉运动、视觉和岛叶皮层的反应,这些皮层与驾驶辅助过程中的感知和行为过程有关。可以想象,注意机制增加了体感整合,减少了内感受,这与在部分自动驾驶过程中请求交互有关。在现代车辆中,驾驶辅助技术正发挥着越来越普遍的作用。研究这些系统与驾驶员注意力反应之间的相互作用对未来辅助系统的优化具有重要意义。提议的VE为这一努力提供了基础的第一步。这种模拟的虚拟汽车为在半自然环境中进行驾驶行为实验提供了一个安全的环境。
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Auditory neural correlates and neuroergonomics of driving assistance in a simulated virtual environment.

Objective.Driver assistance systems play an increasingly important role in modern vehicles. In the current level of technology, the driver must continuously supervise the driving and intervene whenever necessary when using driving assistance systems. The driver's attentiveness plays an important role in this human-machine interaction. Our aim was to design a simplistic technical framework for studying neural correlates of driving situations in a functional magnetic resonance imaging (fMRI) setting. In this work we assessed the feasibility of our proposed platform.Methods.We proposed a virtual environment (VE) simulation of driver assistance as a framework to investigate brain states related to partially automated driving. We focused on the processing of auditory signals during different driving scenarios as they have been shown to be advantageous as warning stimuli in driving situations. This provided the necessary groundwork to study brain auditory attentional networks under varying environmental demands in an fMRI setting. To this end, we conducted a study with 20 healthy participants to assess the feasibility of the VE simulation.Results.We demonstrated that the proposed VE can elicit driving related brain activation patterns. Relevant driving events evoked, in particular, responses in the bilateral auditory, sensory-motor, visual and insular cortices, which are related to perceptual and behavioral processes during driving assistance. Conceivably, attentional mechanisms increased somatosensory integration and reduced interoception, which are relevant for requesting interactions during partially automated driving.Significance.In modern vehicles, driver assistance technologies are playing an increasingly prevalent role. It is important to study the interaction between these systems and drivers' attentional responses to aid in future optimizations of the assistance systems. The proposed VE provides a foundational first step in this endeavor. Such simulated VEs provide a safe setting for experimentation with driving behaviors in a semi-naturalistic environment.

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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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