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A method and apparatus for reducing the visual blur of an object being viewed by an observer experiencing vibration. In various embodiments of the present invention, the visual blur is reduced through stroboscopic image modulation (SIM). A SIM device is operated in an alternating "on/off" temporal pattern according to a SIM drive signal (SDS) derived from the vibration being experienced by the observer. A SIM device (controlled by a SIM control system) operates according to the SDS serves to reduce visual blur by "freezing" (or reducing an image's motion to a slow drift) the visual image of the viewed object. In various embodiments, the SIM device is selected from the group consisting of illuminator(s), shutter(s), display control system(s), and combinations of the foregoing (including the use of multiple illuminators, shutters, and display control systems).

We measured the impacts on human visual function of a range of vibration levels (0.15, 0.3, 0.5, and 0.7 g) at the frequency and along the axis of the anticipated Ares thrust oscillation. We found statistically significant and equivalent decrements in performance on a reading and a numeric processing task at tested vibration levels above 0.3 g (0-to-peak), but no evidence of after-effects. At the smallest font and highest vibration level tested, the average effect was a 50 percent increase in response time and six-fold increase in errors. Our findings support a preliminary trade space in which currently planned Orion font sizes and text spacing appear to be too small to support accurate and efficient reading at the tested vibration levels above 0.3 g, but not too small to support reading at 0.3 g. This study does not address potential impacts on crew cognitive decision-making or motor control and does not test either the full induced Orion-Ares environment with its sustained Gx-loading or the full complexity of the final Orion seat-helmet-suit interface. A final determination of the Orion-Ares program limit on vibration must take these additional factors into consideration and, thus, may need to be lower than that needed to support effective reading at 1-Gx bias.

The goal of the Information Presentation Directed Research Project (DRP) is to address design questions related to the presentation of information to the crew. In addition to addressing display design issues associated with information formatting, style, layout, and interaction, the Information Presentation DRP is also working toward understanding the effects of extreme environments encountered in space travel on information processing. Work is also in progress to refine human factors-based design tools, such as human performance modeling, that will supplement traditional design techniques and help ensure that optimal information design is accomplished in the most cost-efficient manner. The major areas of work, or subtasks, within the Information Presentation DRP for FY10 are: 1) Displays, 2) Controls, 3) Procedures and Fault Management, and 4) Human Performance Modeling. The poster will highlight completed and planned work for each subtask.

It has long been known that ocular pursuit of a moving target has a major influence on its perceived speed (Aubert, 1886; Fleischl, 1882). However, little is known about the effect of smooth pursuit on the perception of target direction. Here we compare the precision of human visual-direction judgments under two oculomotor conditions (pursuit vs. fixation). We also examine the impact of stimulus duration (200 ms vs. ~800 ms) and absolute direction (cardinal vs. oblique). Our main finding is that direction discrimination thresholds in the fixation and pursuit conditions are indistinguishable. Furthermore, the two oculomotor conditions showed oblique effects of similar magnitudes. These data suggest that the neural direction signals supporting perception are the same with or without pursuit, despite remarkably different retinal stimulation. During fixation, the stimulus information is restricted to large, purely peripheral retinal motion, while during steady-state pursuit, the stimulus information consists of small, unreliable foveal retinal motion and a large efference-copy signal. A parsimonious explanation of our findings is that the signal limiting the precision of direction judgments is a neural estimate of target motion in head-centered (or world-centered) coordinates (i.e., a combined retinal and eye motion signal) as found in the medial superior temporal area (MST), and not simply an estimate of retinal motion as found in the middle temporal area (MT).

Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.

Existing models assume that pursuit attempts a direct minimization of retinal image motion or "slip" (e.g. Robinson et al., 1986; Krauzlis & Weisberger, 1989). Using occluded line-figure stimuli, we have previously shown that humans can accurately pursue stimuli for which perfect tracking does not zero retinal slip (Neurologic ARCO). These findings are inconsistent with the standard control strategy of matching eye motion to a target-motion signal reconstructed by adding retinal slip and eye motion, but consistent with a visual front-end which estimates target motion via a global spatio-temporal integration for pursuit and perception. Another possible explanation is that pursuit simply attempts to minimize slip perpendicular to the segments (and neglects parallel "sliding" motion). To resolve this, 4 observers (3 naive) were asked to pursue the center of 2 types of stimuli with identical velocity-space descriptions and matched motion energy. The line-figure "diamond" stimulus was viewed through 2 invisible 3 deg-wide vertical apertures (38 cd/m2 equal to background) such that only the sinusoidal motion of 4 oblique line segments (44 cd/m2 was visible. The "cross" was identical except that the segments exchanged positions. Two trajectories (8's and infinity's) with 4 possible initial directions were randomly interleaved (1.25 cycles, 2.5s period, Ax = Ay = 1.4 deg). In 91% of trials, the diamond appeared rigid. Correspondingly, pursuit was vigorous (mean Again: 0.74) with a V/H aspect ratio approx. 1 (mean: 0.9). Despite a valid rigid solution, the cross however appeared rigid in 8% of trials. Correspondingly, pursuit was weaker (mean Hgain: 0.38) with an incorrect aspect ratio (mean: 1.5). If pursuit were just minimizing perpendicular slip, performance would be the same in both conditions.

Although numerous studies have examined the relationship between smooth-pursuit eye movements and motion perception, it remains unresolved whether a common motion-processing system subserves both perception and pursuit. To address this question, we simultaneously recorded perceptual direction judgments and the concomitant smooth eye movement response to a plaid stimulus that we have previously shown generates systematic perceptual errors. We measured the perceptual direction biases psychophysically and the smooth eye-movement direction biases using two methods (standard averaging and oculometric analysis). We found that the perceptual and oculomotor biases were nearly identical suggesting that pursuit and perception share a critical motion processing stage, perhaps in area MT or MST of extrastriate visual cortex.

Current computational models of smooth-pursuit eye movements assume that the primary visual input is local retinal-image motion (often referred to as retinal slip). However, we show that humans can pursue object motion with considerable accuracy, even in the presence of conflicting local image motion. This finding indicates that the visual cortical area(s) controlling pursuit must be able to perform a spatio-temporal integration of local image motion into a signal related to object motion. We also provide evidence that the object-motion signal that drives pursuit is related to the signal that supports perception. We conclude that current models of pursuit should be modified to include a visual input that encodes perceived object motion and not merely retinal image motion. Finally, our findings suggest that the measurement of eye movements can be used to monitor visual perception, with particular value in applied settings as this non-intrusive approach would not require interrupting ongoing work or training.

Current models of smooth pursuit eye movements assume that it is largely driven by retinal image motion. We tested this hypothesis by measuring pursuit of elliptical motion (3.2s, 0.9 Hz, 1.4 deg x 1.6 deg, 4 randomly interleaved phases) of either a small spot ("real" motion) or of a line-figure diamond viewed through apertures such that only the motion of four isolated oblique line segments was visible ("virtual" motion). Each segment moved sinusoidally along a linear trajectory yet subjects perceived a diamond moving along an elliptical path behind the aperture. We found, as expected, that real motion produced accurate tracking (N = 2) with mean gain (over horizontal and vertical) of 0.9, mean phase of -6 deg (lag), mean relative phase (H vs V) of 90 +/- 8 deg (RMS error). Virtual motion behind an X-shaped aperture (N= 4 with one naive) yielded a mean gain of 0.7, mean phase of -11 deg, mean relative phase of 87 +/- 15 deg. We also measured pursuit with the X-shaped aperture using a higher segment luminance which prevents the segments from being grouped into a coherently moving diamond while keeping the motion otherwise identical. In this incoherent case, the same four subjects no longer showed consistent elliptical tracking (RMS error in relative phase rose to 60 deg) suggesting that perceptual coherence is critical. Furthermore, to rule out tracking of the centroid, we also used vertical apertures so that all segment motion was vertical (N = 3). This stimulus still produced elliptical tracking (mean relative phase of 84 +/- 19 deg), albeit with a lower gain (0.6). These data show that humans can track moving objects reasonably accurately even when the trajectory can only be derived by spatial integration of motion signals. Models that merely seek to minimize retinal or local stimulus motion cannot explain these results.

To determine the extent to which the pursuit eye-movement and perceptual systems share a common neural motion-processing pathway, we simultaneously measure the psychophysical and eye-movement responses to drifting plaids in a direction-discrimination task. Correlation between the noise in the eye movements and percepts would suggest a shared neural substrate. Three observers were asked to track a plaid (Type I 90 deg; TF = 4 Hz, SF = 0.6 c/d; direction = -2, 0, or 2 deg), and to respond whether the motion was to the right or left of vertical. The eye-movement direction is computed from the initial 300 ms of saccade-free tracking (near open-loop). On each trial, we use the eye-movement direction to predict the perceptual response. We then compute the probability of successfully predicting the observer's response. We also use SOC analysis as an alternate measure of the correlation. We compare the data from both these analyses to the predictions of two models in which the eye movements and the percept are driven by either a common noisy signal (correlated model) or by two separate noisy signals (uncorrelated model). We also allow for the fact that our measured eye movements are degraded by eye-tracker noise. This noise causes our measured correlation to be lower than the actual biological correlation. The correlations in our data are higher than those predicted by the uncorrelated model, and are similar to the predictions of the correlated model. The proportion of perceptual responses correctly predicted by the eye movements were 0.66, 0.60, 0.73 for the -2, 0, 2 deg stimuli respectively (correlated model 0.65, 0.60, 0.70; uncorrelated model 0.58, 0.51, 0.60).The SOC proportions were 0.71, 0.64, 0.72 (correlated model 0.66, 0.64, 0.69; uncorrelated model 0.5, 0.5, 0.5). These results show that the oculomotor and perceptual system share a performance-limiting noise source and provide strong evidence that a common neural mechanism (perhaps MT or MST) drives both perception and smooth eye movements.

We have previously shown that windowing a drifting plaid with an asymmetric spatial Gaussian produces systematic biases of similar magnitude in both the perceived direction of motion and the direction of the eye movement response. To further investigate this, we simultaneously measured the pyschophysical and eye-movement responses (with an ISCAN RK426 IR tracker)to drifting plaids in a direction discrimination task. Three observers were instructed to track a plaid (Type I 90 deg.; TF = 4 Hz, SF = 0.6 c/d; windowed by a circular spatial gaussian) and to respond whether the motion was to the right or left of pure vertical. Three plaid directions were presented (-2, 0, 2 deg. with respect to straight down), so there was uncertainty in the perceptual judgements. This enabled us to examine the trial-by-trial relationship between the eye movements and psychophysical responses. The eye-movement direction was computed to be the slope of the best fitting line to the initial 300 ms of saccade-free tracking (near open-loop). Again, we found the mean psychophysical and oculomotor responses were correlated. The mean percentages of rightward responses were 6, 27, 87%, and the mean normalized eye-movement directions were -1.5, 0, and 1.0 deg. for the -2, 0, and 2 deg. stimuli respectively. We also computed the trial-by-trial correlation by performing an SOC analysis. The mean correlations were 0.52, 0.66, and 0.67 for our three observers. Because of eye-tracker measurement noise, the above results are lower limits on the actual correlation. These results support the view that the oculomotor and perceptual system share common motion inputs.

Infrared video cameras offer a simple noninvasive way to measure the position of the eyes using relatively inexpensive equipment. Several commercial systems are available which use special hardware to localize features in the image in real time, but the constraint of realtime performance limits the complexity of the applicable algorithms. In order to get better resolution and accuracy, we have used off-line processing to apply more sophisticated algorithms to the images. In this case, a major technical challenge is the real-time acquisition and storage of the video images. This has been solved using a strictly digital approach, exploiting the burgeoning field of hardware video compression. In this paper we describe the algorithms we have developed for tracking the movements of the eyes in video images, and present experimental results showing how the accuracy is affected by the degree of video compression.