Driving the locus coeruleus: a novel continuous highway driving paradigm
Creators: name: Reid, Andrew T.
name: Gerven, Marcel Van
Publisher: name: F1000 Research Limited
Year: 2018

description: Introduction<br><br>Typically, paradigms that target specific cognitive functions are designed as repetitive, static, and highly controlled presentations of sensory stimuli, whose objective is to reduce all sources of "nuisance" variance and focus on the process of interest. However, such simplistic paradigms may fail to sufficiently engage arousal and motivational systems, such as those subserved by noradrenergic and dopaminergic systems, to assess the role of these systems in motivation, decision making, adaptive learning, and cognitive control (see, e.g., Aston-Jones &amp; Cohen, 2005; Cools, 2016). Here, we present an alternative approach for gauging cognitive function, which makes use of a continuous, naturalistic stimulus stream, in the form of a highway driving simulation. We argue that an event-based approach, wherein discrete events that occur in the course of a highway driving session can be logged, classified, and analyzed, can provide a means of both challenging subjects in more naturalistic ways than traditional stimulus presentation protocols, while maintaining a sufficient degree of control with which to test specific hypotheses.<br><br>Methods<br><br>We have developed a Java-based simulator, built on the open source JMonkeyEngine (www.jmonkeyengine.org) and OpenDS (www.opends.eu) platforms. Our simulator software allows the researcher to define the position and behaviour of highway traffic, road signs, and other stimuli which can be used to challenge subjects. Events that occur along the way can be assigned specific reward magnitudes (positive or negative valance), which can be used to implement reinforcement learning. The simulator implements an event-based design, wherein discrete events that occur along the course (lane changes, braking, acceleration, feedback, appearance of traffic, etc.), will produce a detailed log, as well as sending precisely timed trigger signals to any recording devices (eye trackers, EEG, MEG, fMRI). <br><br>Results<br><br>Figure 1 shows a schematic of the simulator, which describes how specific task scenarios can be specified, how 3D assets such as highways, lanes, and vehicles can be utilized, and how experimental runs can be logged and integrated with neurophysiological signals such as eye tracking or EEG. Figure 2 shows two screenshots of a specific implementation of the simulator, in which the subject faces a decision regarding how to interact with other traffic vehicles (overtake or brake?). Feedback is displayed in the top right of the window.<br><br>Conclusions<br><br>We present a new Java-based highway driving simulator, designed specifically for testing hypotheses about cognitive function in a continuous, naturalistic way. Our software is flexible and easy to customize, and provides a systematic way to evaluate variables in an event-driven manner. Our future research goals include applying this simulation to the assessment of tasks that involve reinforcement learning, continuous decision making, working memory, and neuromodulatory processes (such as dopamine, norepinephrine, or serotonin systems), simultaneously with eye tracking and EEG data collection.