Neuroergonomics Behind the Wheel: Neural Correlates of Driving

Ware, Macie; Feng, Jing; Nam, Chang S.

doi:10.1007/978-3-030-34784-0_18

Cited by 7 publications

(7 citation statements)

References 43 publications

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“…In this study, occipital, parietal, cerebellar and motor areas were recruited in both the R and L conditions, and also the LT condition (Figure 2). The brain regions that were found to be activated (occipital, parietal, cerebellar and motor areas) were consistent with previous studies investigating simple driving as noted above (Calhoun et al, 2002;Uchiyama et al, 2003;Graydon et al, 2004;Spiers and Maguire, 2007;Callan et al, 2009;Crundall and Underwood, 2011;Calhoun and Pearlson, 2012;Li et al, 2012;Hyung-Sik et al, 2014;Choi et al, 2017;Ware et al, 2020). Some additional aspects are noteworthy.…”

Section: Brain Activitysupporting

confidence: 90%

“…Previous simulated driving studies have shown a network of brain regions activated during straight driving, including the occipital and parietal lobes, cerebellum, and areas involved in motor control and somatosensory integration (Calhoun et al, 2002;Uchiyama et al, 2003;Graydon et al, 2004;Spiers and Maguire, 2007;Just et al, 2008;Callan et al, 2009;Crundall and Underwood, 2011;Calhoun and Pearlson, 2012;Li et al, 2012;Schweizer et al, 2013;Hyung-Sik et al, 2014;Choi et al, 2017;Ware et al, 2020). Straight driving involves visual vigilance and small adjustments in driving control to maintain speed and lane position.…”

Section: Brain Activitymentioning

confidence: 99%

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Driving With Distraction: Measuring Brain Activity and Oculomotor Behavior Using fMRI and Eye-Tracking

Yuen

Tam

Churchill

et al. 2021

Front. Hum. Neurosci.

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IntroductionDriving motor vehicles is a complex task that depends heavily on how visual stimuli are received and subsequently processed by the brain. The potential impact of distraction on driving performance is well known and poses a safety concern – especially for individuals with cognitive impairments who may be clinically unfit to drive. The present study is the first to combine functional magnetic resonance imaging (fMRI) and eye-tracking during simulated driving with distraction, providing oculomotor metrics to enhance scientific understanding of the brain activity that supports driving performance.Materials and MethodsAs initial work, twelve healthy young, right-handed participants performed turns ranging in complexity, including simple right and left turns without oncoming traffic, and left turns with oncoming traffic. Distraction was introduced as an auditory task during straight driving, and during left turns with oncoming traffic. Eye-tracking data were recorded during fMRI to characterize fixations, saccades, pupil diameter and blink rate.ResultsBrain activation maps for right turns, left turns without oncoming traffic, left turns with oncoming traffic, and the distraction conditions were largely consistent with previous literature reporting the neural correlates of simulated driving. When the effects of distraction were evaluated for left turns with oncoming traffic, increased activation was observed in areas involved in executive function (e.g., middle and inferior frontal gyri) as well as decreased activation in the posterior brain (e.g., middle and superior occipital gyri). Whereas driving performance remained mostly unchanged (e.g., turn speed, time to turn, collisions), the oculomotor measures showed that distraction resulted in more consistent gaze at oncoming traffic in a small area of the visual scene; less time spent gazing at off-road targets (e.g., speedometer, rear-view mirror); more time spent performing saccadic eye movements; and decreased blink rate.ConclusionOculomotor behavior modulated with driving task complexity and distraction in a manner consistent with the brain activation features revealed by fMRI. The results suggest that eye-tracking technology should be included in future fMRI studies of simulated driving behavior in targeted populations, such as the elderly and individuals with cognitive complaints – ultimately toward developing better technology to assess and enhance fitness to drive.

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Section: Brain Activitysupporting

confidence: 90%

Section: Brain Activitymentioning

confidence: 99%

Driving With Distraction: Measuring Brain Activity and Oculomotor Behavior Using fMRI and Eye-Tracking

Yuen

Tam

Churchill

et al. 2021

Front. Hum. Neurosci.

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“…In Table 1 , we provide a brief summary of each paper including year of publication, author(s), research topics, basic manipulation and studied brain regions of interest. For an in-depth read on neural processes involved in driving, we refer the interested reader to following reviews ( Liu et al, 2016 ; Lohani et al, 2019 ; Kim et al, 2020 ; Ware et al, 2020 ).…”

Section: Methodological Reviewmentioning

confidence: 99%

“…( Begum, 2013 ; Chowdhury et al, 2018 ). At the same time, there have been research efforts to elucidate the neuro-cognitive processes that underlie or precede these physiological or behavioral states via brain imaging ( Kim et al, 2020 ; Ware et al, 2020 ). One brain imaging technique that has particularly gained traction in the past decade is functional near-infrared spectroscopy (fNIRS).…”

Section: Introductionmentioning

confidence: 99%

A Methodological Review of fNIRS in Driving Research: Relevance to the Future of Autonomous Vehicles

Balters

Baker

Geeseman

et al. 2021

Front. Hum. Neurosci.

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As automobile manufacturers have begun to design, engineer, and test autonomous driving systems of the future, brain imaging with functional near-infrared spectroscopy (fNIRS) can provide unique insights about cognitive processes associated with evolving levels of autonomy implemented in the automobile. Modern fNIRS devices provide a portable, relatively affordable, and robust form of functional neuroimaging that allows researchers to investigate brain function in real-world environments. The trend toward “naturalistic neuroscience” is evident in the growing number of studies that leverage the methodological flexibility of fNIRS, and in doing so, significantly expand the scope of cognitive function that is accessible to observation via functional brain imaging (i.e., from the simulator to on-road scenarios). While more than a decade’s worth of study in this field of fNIRS driving research has led to many interesting findings, the number of studies applying fNIRS during autonomous modes of operation is limited. To support future research that directly addresses this lack in autonomous driving research with fNIRS, we argue that a cogent distillation of the methods used to date will help facilitate and streamline this research of tomorrow. To that end, here we provide a methodological review of the existing fNIRS driving research, with the overarching goal of highlighting the current diversity in methodological approaches. We argue that standardization of these approaches will facilitate greater overlap of methods by researchers from all disciplines, which will, in-turn, allow for meta-analysis of future results. We conclude by providing recommendations for advancing the use of such fNIRS technology in furthering understanding the adoption of safe autonomous vehicle technology.

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“…Driving engages various cognitive abilities including decision-making, selected and divided attention, memory, problem solving and planning. It also requires coordination between visuo-spatial attention, visuo-motor skills, perceptual motor skills and auditory skills (Palmiero et al 2019, Ware et al 2020. It is believed that more than forty different tasks are associated with driving among which the response to hazards, lane keeping, speed control and maintaining a safe distance are the primary tasks (Navarro et al 2018).…”

Section: Introductionmentioning

confidence: 99%