Sensory entrainment: Neurobiological underpinnings for accident prevention.

Over the course of the last 30 years, a large body of experimental and theoretical literature has suggested that perception is a discrete phenomenon (Marti., 2017; VanRullen., 2016; VanRullen and Koch, 2003; Asplund et al., 2014; Thibault., et al 2016; Varela et al., 1981; Seth et al., 2008; Sergent & Dehaene., 2004; Friston., 2005; Friston, Daunizeau, Kilner, & Kiebel, 2010). This is, human perception is based on discrete neural processing cycles rather than a continuous stream of accumulating information. Such processing cycles have been often associated with brain rhythms; short-lived voltage variations observable at the level of microcircuits and large-scale neural networks emerging from the apparently stochastic behavior of individual neurons (Buzsáki, 2006).  Such “coordinated” brain activity is frequently associated with rhythmic fluctuations in the excitation–inhibition cycle of local neuronal populations, modulating the global organization of our nervous system (Herter, 1967; Hirsh & Serrick, 1961; Varela et al., 1981; Le van quyen & Bragin 2007; Le van quyen 2011; VanRullen et al., 2011; Varela et al., 2001) and generating variability in sensory and perceptual processing (Varela et al., 1981). To form, thus a coherent representation of the world around us, the brain must dynamically organize the different sensory features composing our global perception (Varela et al., 2001; Hasson et al., 2008; Le van queyen, 2001; Bagdasaryan & Le van queyen, 2013)The nervous system’s ability to continuously couple with dynamic visual inputs depends on the synchronous neural entrainment to the rhythm of incoming stimuli (Spaak et al., 2012; Spaak et al., 2014). Improved perceptual processing and increased behavioral performance can be reached through “optimal” brain rhythm coupling mechanisms (Ronconi & Melcher, 2017; Arnal & Kleinschmidt, 2017; Henry & Obleser 2012) and in this manner, taking advantage of the entrainment property of endogenous neural oscillations involving sensory processing reorganization. However, few studies have applied this knowledge, implementing ecological tools supporting human sensory adaptation in complex environments.
Within this context, automobile driving can be understood as a complex task requiring sensory information processing, visual perception integration, and decision making under conditions of high perceptual uncertainty. In natural driving conditions, a busy road with incoming traffic is a common scenario. Eye fixations will concentrate on the road ahead, while periodically fixating towards the rear-view mirror sets (Nunes & Recarte, 2002). Moreover, covert attention will be deployed towards the incoming traffic and potential pedestrians; shifting between unattended visual fields. Thus, driver performance studies are a well-suited model for studying neural mechanisms allowing the identification and processing of diverse dynamic stimuli.
The fields of Cognitive Psychology and -more recently- Cognitive Neuroscience has produced a variety of research tools composed by experimental and computational techniques. These methodological tools allow the identification and modulation of oscillatory brain activity; having direct impact on sensory, perceptual, and behavioral processes (Wutz, Weiz, Braun & Melcher, 2014; Thut, Schyns & Gross, 2011). It is thus that, a several of hypotheses about the impact of sensory-neural entrainment on perceptual processing can be tested. Likewise, a growing number of studies provide key insights about psychophysiological factors impacting driving performance (Klinestiver, 1980; Mehler, Reimer, Couhling & Dusek, 2009; Thiffault & Bergeron, 2003; Lal & Craig, 2001). These studies focus on quantifying the impact on driving performance of cellphone calls (Nunes and Recarte, 2002), texting while driving (Caird et al., 2014), conversations with passengers (Drews et al., 2008), spontaneous episodes of breakdown of attentional stream (i.e. mind wandering) (He, Becic, Lee & McCarey, 2014; Yanko & Spalek, 2014; Thomson, Seli, Besner & Smilek, 2014; Henriquez, Chica, Billeke & Bartolomeo, 2016 ), among others factors. Additionally, other human demographical and historical factors such as age and driver accident records are variables that also impact overall driving performance (Horberry et al., 2006; Ball et al., 1993). Thus, growing evidence indicate these distractions are associated with reduction of reaction times, attentional impairments such as “tunnel vision”, limiting peripheral vision, and -of course- increasing the overall risk of accidents (Alexander et al., 2004; Robb et al., 2008; Petridou and Moustaki, 2000). Although relevant evidence has been gathered about built environment, human, and cognitive factors predicting automobile accidents, a unifying neurobiological model providing clear empirical hypothesis is still lacking.
The present perspective will highlight the role of perceptual cycles and sensory entrainment processes as an integrative and ecological neurobiological model of driver’s cognitive and behavioral performance. Our main hypothesis is that external modulation of visual sensory processing of incoming stimuli, would improve the perception and behavior (i.e: sensory-motor coupling) during automobile driving. If true, our hypothesis suggests the possibility to set a driver’s sensory system within a range of “optimal perceptual state”, allowing processing external sensory demands successfully. Furthermore, we suggest cognitive neuroscience should work towards establishing a relationship between driving performance and external sensory entrainment of neural oscillations. Establishing such a link would allow the implementation of real-time information delivery systems working alongside innovative probabilistic collision prediction applications indicating collisions and road hazards (Basso et al., 2018). Providing thus a starting point for the development of interactive vial infrastructures and sensory-perceptual-directed applications for accident cars prevention.