Alyan Emad, Arnau Stefan, Getzmann Stephan, Reiser Julian Elias, Karthaus Melanie, Wascher Edmund
Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors, 44139, Dortmund, Germany.
Heliyon. 2024 Dec 14;11(1):e41164. doi: 10.1016/j.heliyon.2024.e41164. eCollection 2025 Jan 15.
Driving is a complex task that requires effective neural processing and coordination, which degrade with aging. Previous studies suggest that age-related changes in cognitive and motor functions can influence driving performance. Herein, we investigated age-related differences and differences between reactive and proactive driving in blink behavior-related potentials, and source-level functional connectivity. Seventy-six subjects participated in two experiments with reactive (19 young, 28 older) and proactive (16 young, 13 older) driving scenarios, consisting of a lane-keeping task with either varying levels of crosswind or curve road, respectively. While blink rate analysis revealed no significant age or driving condition effects, blink duration was notably longer in younger participants. Also, significant age effects were observed in blink-related potentials, mainly in the frontal N2 and occipital P0 and P2 components, with higher amplitudes in younger participants, signifying more efficient neural processing. The parietal N2 component showed significant age and interaction effects, with older individuals showing higher amplitudes in reactive conditions, potentially due to increased cognitive effort and attentional demands. Furthermore, functional connectivity analysis revealed that aging most significantly affects the visual network in the beta band. More specifically, younger participants showed an increase in the clustering coefficient and degrees of the networks, reflecting more robust neural network integration. This pattern of higher connectivity measures in younger participants was also observed in the default mode, control, and limbic networks. Conversely, the dorsal attention network in the theta band showed an increased degree and clustering coefficient in older adults, which could indicate a compensatory mechanism for maintaining cognitive demands. This study highlights the impact of aging on neural activity and connectivity characteristics during driving and emphasizes the requirement of age-tailored interventions, aimed to improve driving safety.
驾驶是一项复杂的任务，需要有效的神经处理和协调能力，而这些能力会随着年龄增长而衰退。先前的研究表明，认知和运动功能的年龄相关变化会影响驾驶表现。在此，我们研究了眨眼行为相关电位以及源水平功能连接中与年龄相关的差异，以及反应性驾驶和主动性驾驶之间的差异。76名受试者参与了两项实验，分别为反应性驾驶（19名年轻人，28名老年人）和主动性驾驶（16名年轻人，13名老年人）场景，分别包括在不同侧风水平或弯道道路上的车道保持任务。虽然眨眼频率分析未发现显著的年龄或驾驶条件影响，但年轻参与者的眨眼持续时间明显更长。此外，在眨眼相关电位中观察到显著的年龄影响，主要在额叶N2以及枕叶P0和P2成分中，年轻参与者的振幅更高，这表明神经处理更高效。顶叶N2成分显示出显著的年龄和交互作用影响，老年人在反应性条件下振幅更高，这可能是由于认知努力和注意力需求增加所致。此外，功能连接分析表明，衰老对β波段的视觉网络影响最为显著。更具体地说，年轻参与者的网络聚类系数和度数增加，反映出神经网络整合更稳健。在默认模式、控制和边缘网络中也观察到年轻参与者中这种更高连接性指标的模式。相反，老年人在θ波段的背侧注意网络的度数和聚类系数增加，这可能表明一种维持认知需求的补偿机制。这项研究强调了衰老对驾驶过程中神经活动和连接特征的影响，并强调了针对年龄的干预措施的必要性，旨在提高驾驶安全性。
