Impaired stationarity perception is associated with increased virtual reality sickness

Abstract

Stationarity perception refers to the ability to accurately perceive the surrounding visual environment as world-fixed during self-motion. Perception of stationarity depends on mechanisms that evaluate the congruence between retinal/oculomotor signals and head movement signals. In a series of psychophysical experiments, we systematically varied the congruence between retinal/oculomotor and head movement signals to find the range of visual gains that is compatible with perception of a stationary environment. On each trial, human subjects wearing a head-mounted display execute a yaw head movement and report whether the visual gain was perceived to be too slow or fast. A psychometric fit to the data across trials reveals the visual gain most compatible with stationarity (a measure of accuracy) and the sensitivity to visual gain manipulation (a measure of precision). Across experiments, we varied 1) the spatial frequency of the visual stimulus, 2) the retinal location of the visual stimulus (central vs. peripheral), and 3) fixation behavior (scene-fixed vs. head-fixed). Stationarity perception is most precise and accurate during scene-fixed fixation. Effects of spatial frequency and retinal stimulus location become evident during head-fixed fixation, when retinal image motion is increased. Virtual Reality sickness assessed using the Simulator Sickness Questionnaire covaries with perceptual performance. Decreased accuracy is associated with an increase in the nausea subscore, while decreased precision is associated with an increase in the oculomotor and disorientation subscores.

Figure 1.

(Left) Conflict detection task. Subjects align a fixation point with a point in the center of the scene. This triggers a white circle to appear to the left or right of center, indicating the direction of rotation. Subjects make a yaw head rotation while maintaining fixation on the point. The trial ends, and subjects are prompted to respond, “With or Against?” Subjects respond, and the process repeats for 300 trials. (Right) Virtual Environment for both experiments. Subjects were seated in the center of an optokinetic drum in VR.

Figure 2.

Experimental designs. Each icon depicts a top-down view of the subject performing a head rotation. The wire-frame rectangle and framed stimuli represent the starting and ending positions of the HMD viewport, respectively. Red-dashed lines indicate fixation direction. (Left) Experiment 1. 2 × 2 design with factor fixation (head-fixed, scene-fixed) and spatial frequency (low - 0.2 cpd, high - 2 cpd). (Right) Experiment 2. 2 × 2 design with factors fixation (head-fixed, scene-fixed) and retinal stimulus location (central, peripheral). The central region subtended 40° of visual angle.

Figure 3.

Example psychometric function and staircase from one subject and condition. The graph on the left shows the psychometric fit generated from the subject’s with/against response data. The PSE value for the fit is shown as a black dot, and the JND is shown as the red line extending to the 84% correct interval. The figure on the right shows the staircase from the same recording. On the 3Down1Up staircase (shown in blue), if the subject responds “against” three times, the gain is reduced. If the subject responds, “with” while a trial from this staircase is being presented, the gain is increased. The inverse of these rules are followed for the 1Down3Up staircase (shown in orange).

Figure 4.

Accuracy of stationarity perception - points of subjective equality (PSEs). Experiment 1 (left), Experiment 2 (right). Note that high-frequency full-field data from Experiment 1 are replotted alongside results of experiment 2 (translucent points) to facilitate comparison. The PSE is the mean of the cumulative Gaussian psychometric fit to data from each subject and condition. Log_e(Gain) of zero indicates that speed of visual motion was equal to head motion. Negative and positive values indicate that slower and faster speeds were required, respectively. Means of each condition are shown as a red circle, and individual subject PSEs are shown as points in grey. The blue lines indicate the standard deviation of the PSE values, extending one standard deviation above and below the mean. The left hand scale of each graph represents the natural log of the gain. The right hand scale of each graph is the gain in linear units.

Figure 5.

Precision of stationarity perception - just-noticeable differences (JNDs). Experiment 1 (left), Experiment 2 (right). Note that high-frequency full-field data from experiment 1 are replotted alongside results of experiment 2 (translucent points) to facilitate comparison. The JND is the standard deviation of the cumulative Gaussian psychometric fit to the data from each subject and condition. Values indicate the proportional increase/decrease needed relative to the PSE in order to reliably elicit responses of “against”/“with.” The red circles represent the mean JND for that condition, and individual subject JND values are shown as gray points. The standard deviation for the JND values are shown via the blue lines which extend one standard deviation above and below the mean. The left hand scale of each graph represents the natural log of the gain. The right hand scale of each graph is the gain in linear units.