Oculometric Assessment of Sensorimotor Impairment Associated with TBI

Abstract

Supplemental digital content is available in the text.

Distinct pattern of oculomotor impairment associated with acute sleep loss and circadian misalignment

“…with respect to visual space in polar coordinates). In our recent study of TBI (Liston et al 2017), we found a different qualitative pattern of effects than those presented here. In particular, we found significant impairment in speed responsiveness (accuracy) without significant changes in speed and direction noise (precision) associated with TBI, yet the opposite pattern here.…”

“…r Speed responsiveness was defined as the best-fitting linear regression slope of the mean radial pursuit speed J Physiol 597.17 (independent of direction) versus target speed. This is slightly different from the method we used previously (Liston and Stone, 2014;Liston et al 2017) as we now use raw radial speed (as opposed to projected speed along the direction of target motion), which makes this metric more uncorrelated with pursuit gain. In addition to those trials culled for the computation of gain (see above), those trials with very low gains (for which pursuit was <4 deg/s) were excluded from the computations of speed responsiveness and speed noise (11.7% of trials).…”

“…The trial-by-trial latencies were localized objectively using a hinge function, least-square best-fit to the eye-velocity trace searching for latencies between 90 and 300 ms, with an added prior probability bias that assumes a reci-normal distribution of latencies (Oswal et al 2007) with a mean of 5.95/s (corresponding to the inverse of the median latency, 168 ms, of our prior population of 41 normal human subjects (Liston and Stone, 2014)) and standard deviation of 6/s, which biases fits towards those expected from our population of normal subjects. We used a much weaker prior than the narrow one used previously (2/s in Liston and Stone, 2014;Liston et al 2017) to allow for greater sensitivity to the a posteriori data, while still preventing spurious fits that can often result from any blind least-squares minimization. Trials for which the fixation baseline data were not stable (SD >3 deg/s) or for which there was less than 28 ms of saccade-free data in either the 100 ms baseline or the initial 100 ms pursuit acceleration interval were excluded from the computation of latency, acceleration and direction (13.9% of trials).…”

“…von Hofsten and Rosander, 1997) was defined as the median across trials of the proportion of time that tracking within the steady-stated interval was smooth, as a metric of how much pursuit is contributing to steady-state tracking. This approach is different from how we computed proportion smooth in previous studies (Liston and Stone, 2014;Liston et al 2017), where we used the ratio of distance travelled. We abandoned this previous method as it is biased upward by backward saccades (when present) or downward by hypermetric forward saccades (when present).…”

“…r Saccadic amplitude was defined as the median amplitude of the forward (positive) catch-up saccades occurring in the steady-state tracking interval 400-700 ms after motion onset. Our prior published saccadic amplitude data (Liston and Stone, 2014;Liston et al 2017) did not restrict the metric to those saccades made during the 400-700 ms steady-state period and did not correct for the significant change in eye position due to the ongoing pursuit displacement occurring in concurrence with the saccade. As such, the values reported here are smaller than previously reported by us, but correspond to the true amplitude of the underlying catch-up saccades (de Brouwer et al 2002a,b;Blohm et al 2003).…”