Age-Related Changes in Attentional Refocusing during Simulated Driving

EEG alpha and theta signatures of socially and non-socially cued working memory in virtual reality

In this preregistered study (https://osf.io/s4rm9) we investigated the behavioural and neurological [electroencephalography; alpha (attention) and theta (effort)] effects of dynamic non-predictive social and non-social cues on working memory. In a virtual environment realistic human-avatars dynamically looked to the left or right side of a table. A moving stick served as a non-social control cue. Kitchen items were presented in the valid cued or invalid un-cued location for encoding. Behavioural findings showed a similar influence of the cues on working memory performance. Alpha power changes were equivalent for the cues during cueing and encoding, reflecting similar attentional processing. However, theta power changes revealed different patterns for the cues. Theta power increased more strongly for the non-social cue compared to the social cue during initial cueing. Furthermore, while for the non-social cue there was a significantly larger increase in theta power for valid compared to invalid conditions during encoding, this was reversed for the social cue, with a significantly larger increase in theta power for the invalid compared to valid conditions, indicating differences in the cues' effects on cognitive effort. Therefore, while social and non-social attention cues impact working memory performance in a similar fashion, the underlying neural mechanisms appear to differ.

Changes in theta and alpha oscillatory signatures of attentional control in older and middle age

BACKGROUND

Recent behavioural research has reported age-related changes in the costs of refocusing attention from a temporal (rapid serial visual presentation) to a spatial (visual search) task. Using magnetoencephalography, we have now compared the neural signatures of attention refocusing between three age groups (19-30, 40-49 and 60+ years) and found differences in task-related modulation and cortical localisation of alpha and theta oscillations. Efficient, faster refocusing in the youngest group compared to both middle age and older groups was reflected in parietal theta effects that were significantly reduced in the older groups. Residual parietal theta activity in older individuals was beneficial to attentional refocusing and could reflect preserved attention mechanisms. Slowed refocusing of attention, especially when a target required consolidation, in the older and middle-aged adults was accompanied by a posterior theta deficit and increased recruitment of frontal (middle-aged and older groups) and temporal (older group only) areas, demonstrating a posterior to anterior processing shift. Theta but not alpha modulation correlated with task performance, suggesting that older adults' stronger and more widely distributed alpha power modulation could reflect decreased neural precision or dedifferentiation but requires further investigation. Our results demonstrate that older adults present with different alpha and theta oscillatory signatures during attentional control, reflecting cognitive decline and, potentially, also different cognitive strategies in an attempt to compensate for decline.

Applications of brain imaging methods in driving behaviour research

Applications of neuroimaging methods have substantially contributed to the scientific understanding of human factors during driving by providing a deeper insight into the neuro-cognitive aspects of driver brain. This has been achieved by conducting simulated (and occasionally, field) driving experiments while collecting driver brain signals of various types. Here, this sector of studies is comprehensively reviewed at both macro and micro scales. At the macro scale, bibliometric aspects of these studies are analysed. At the micro scale, different themes of neuroimaging driving behaviour research are identified and the findings within each theme are synthesised. The surveyed literature has reported on applications of four major brain imaging methods. These include Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), Functional Near-Infrared Spectroscopy (fNIRS) and Magnetoencephalography (MEG), with the first two being the most common methods in this domain. While collecting driver fMRI signal has been particularly instrumental in studying neural correlates of intoxicated driving (e.g. alcohol or cannabis) or distracted driving, the EEG method has been predominantly utilised in relation to the efforts aiming at development of automatic fatigue/drowsiness detection systems, a topic to which the literature on neuro-ergonomics of driving particularly has shown a spike of interest within the last few years. The survey also reveals that topics such as driver brain activity in semi-automated settings or neural activity of drivers with brain injuries or chronic neurological conditions have by contrast been investigated to a very limited extent. Potential topics in driving behaviour research are identified that could benefit from the adoption of neuroimaging methods in future studies. In terms of practicality, while fMRI and MEG experiments have proven rather invasive and technologically challenging for adoption in driving behaviour research, EEG and fNIRS applications have been more diverse. They have even been tested beyond simulated driving settings, in field driving experiments. Advantages and limitations of each of these four neuroimaging methods in the context of driving behaviour experiments are outlined in the paper.

Erratum: Huizeling, E.; et al. Age-Related Changes in Attentional Refocusing during Simulated Driving. Brain Sci. 2020, 10, 530

The authors would like to submit the following corrections to the published paper [...].