Abstract
The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are associated with attention and the allocation of mental resources. EEG has also been used to study mental processes while driving, both in real environments and in virtual reality. However, conventional EEG methods are of limited use outside of controlled laboratory settings. While modern EEG technologies offer hardly any restrictions for the user, they often still have limitations in measurement reliability. We recently showed that low-density EEG methods using film-based round the ear electrodes (cEEGrids) are well-suited to map mental processes while driving a car in a driving simulator. In the present follow-up study, we explored aspects of ecological and internal validity of the cEEGrid measurements. We analyzed longitudinal data of 127 adults, who drove the same driving course in a virtual environment twice at intervals of 12-15 months while the EEG was recorded. Modulations in the alpha and theta frequency bands as well as within behavioral parameters (driving speed and steering wheel angular velocity) which were highly consistent over the two measurement time points were found to reflect the complexity of the driving task. At the intraindividual level, small to moderate (albeit significant) correlations were observed in about 2/3 of the participants, while other participants showed significant deviations between the two measurements. Thus, the test-retest reliability at the intra-individual level was rather low and challenges the value of the application for diagnostic purposes. However, across all participants the reliability and ecological validity of cEEGrid electrodes were satisfactory in the context of driving-related parameters.
Highlights
Neurophysiological research methods have a long tradition of deriving mental processes both under laboratory conditions and in real-life environments
While our former study demonstrated that task-related modulations of driving behavior and EEG—previously found in controlled lab settings—are observable in a naturalistic driving simulation and cEEGrids measurements, we focused on the following questions: (1) How have the performance parameters assessed during the driving course changed compared to the first measurement point? (2) Can the previously found dependence of relative alpha and theta power on track difficulty be replicated at a between-subject level? (3) How strong is the intraindividual correspondence of the oscillatory measures in dependence on the track difficulty?
It is to notice that the driving speed increased overall, while the steering wheel angular velocity decreased at MP2 relative to MP1
Summary
Neurophysiological research methods have a long tradition of deriving mental processes both under laboratory conditions and in real-life environments. For example, we showed that mental workload during the processing of cognitive tasks while walking on differently challenging courses was reflected in performance measures, but that it was associated with modulations in brain activity (Reiser et al, 2019, 2020) While both studies clearly demonstrated the usability of EEG measurements under out-of-laboratory everyday conditions, conventional electrode caps have been used here, which offer a good prerequisite for EEG recording, but are unfavorable in real-life environments for many reasons: they are conspicuous, time-consuming to apply, restrict the user’s mobility, and are of limited use when high ecological validity is important – especially when possible influence of the measurement method on the measurement results should be minimized (e.g., Sterr et al, 2018; Mikkelsen et al, 2019). For example, that it is possible to derive neurophysiological correlates of cognitive processes from the oscillatory brain activity recorded via cEEGrid electrodes both in an auditory oddball task (Debener et al, 2015) and a visual Simon task (Pacharra et al, 2017)
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