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For over 100 years, neurologists have used eye movements to identify neural impairment, disease, or injury. Prior to the age of modern imaging, qualitative assessment of eye movements was a critical, routine component of diagnosis and remains today a routine law-enforcement tool for detecting impaired driving due to drugs or alcohol. We will describe the application of a simple 5-minute oculomotor tracking task coupled with a broad range of quantitative analyses of high-resolution oculomotor measurements for the sensitive detection of sub-clinical neural impairment and for the potential differentiation of various causes. Specifically, we will show that there are distinct patterns of impairment across our set of oculometric parameters observed with brain trauma, sleep and circadian disruption, and alcohol consumption. Such differences could form the basis of a self-administered medical monitoring or diagnostic support tool.

Oculomotor tracking performance changes according to time awake. A constant routine (CR) study demonstrated that increasing time awake 1) reduces the precision of visual motion processing, 2) decreases steady-state closed-loop pursuit performance and 3) decreases peak saccadic velocity. We aimed to determine the contribution of homeostatic sleep pressure on these oculometric changes by administering low-dose caffeine over one night of sleep deprivation. Participants completed two weeks of at-home 8.5 hours sleep per day, followed by an approximately 24-hour laboratory CR in semi-recumbent posture under less than 4 lux of light. The visual tracking task was performed every two hours after waking and hourly overnight. Low-dose caffeine of 0.3 milligrams per kilogram was administered hourly during the biological night. Nine participants (5F) completed the study. Caffeine dosing: 1) prevented the impairment of visual motion processing, 2) reduced by approximately half the impairment of closed-loop pursuit performance (gain, minus 0.47 percent per hour, significance of slope change: p (probability) less than 0.006; proportion smooth, minus 0.35 percent per hour, p less than 0.005), and 3) had an insignificant (p less than 0.39) effect on the impairment of saccadic peak velocity (slope, minus 1.13 percent per hour; intercept, minus 0.62 percent per hour). These results suggest that visual motion processing and some proportion of closed-loop pursuit performance are impaired due to homeostatic mechanisms during sleep deprivation.

Eye movements are the most frequent (~3 per second), shortest-latency (~150-250 ms), and biomechanically simplest (1 joint, no inertial complexities) voluntary motor behavior in primates, providing a model system to assess sensorimotor disturbances arising from trauma, fatigue, aging, or disease states (e.g., Diefendorf and Dodge, 1908). We developed a 15-minute behavioral tracking protocol consisting of randomized stepramp radial target motion to assess several aspects of the behavioral response to dynamic visual motion, including pursuit initiation, steadystate tracking, direction-tuning, and speed-tuning thresholds. This set of oculomotor metrics provide valid and reliable measures of dynamic visual performance (Stone and Krauzlis, 2003; Krukowski and Stone, 2005; Stone et al, 2009; Liston and Stone, 2014), and may prove to be a useful assessment tool for functional impairments of dynamic visual processing.

The vestibulo-ocular reflex (VOR) consists of two intermingled non-linear subsystems; namely, nystagmus and saccade. Typically, nystagmus is analysed using a single sufficiently long signal or a concatenation of them. Saccade information is not analysed and discarded due to insufficient data length to provide consistent and minimum variance estimates. This paper presents a novel sparse matrix approach to system identification of the VOR. It allows for the simultaneous estimation of both nystagmus and saccade signals. We show via simulation of the VOR that our technique provides consistent and unbiased estimates in the presence of output additive noise.

Viewing a scene through an optical window provides observers with numerous visual properties. In order to create a 'virtual window' that is perceptually compelling, it must be determined which properties are most critical to preserve. We have examined several properties, both static and dynamic, and will discuss which have the greatest impact on apparent realism (and user performance).