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Head-Mounted Displays (HMDs) are increasingly used to support mobile work (Laramee & Ware, 2002). Human operators sometimes require additional auditory support when using an HMD, which raises the question of whether sound is better delivered publicly in free-field or privately via earpiece. A novel experimental procedure was created in which participants had to identify mismatches between auditory information and visual information on an HMD. Different conditions of sound delivery and physical movement were manipulated within-subjects. Participants heard the sound either via earpiece or free-field while they either sat or moved about the test room. Predictions were based on the idea that inconsistent spatial mapping of vision and sound would compromise mismatch detection. First, I predicted a main effect of movement such that participants‟ mismatch detection would be worse when they moved than when they sat. Second, I predicted an interaction between movement and sound delivery. When participants are seated there will be no difference in mismatch detection between the two methods of sound delivery. When participants are walking, however, mismatch detection will be better with an earpiece than with free-field delivery. Results supported the first prediction. For the second prediction, the significant interaction found took a different form than predicted. With the earpiece, participants performed equally well whether sitting or walking, but with free-field sound, participants performed better when sitting than when walking. Results have implications for understanding necessary auditory conditions for effective crossmodal integration and may indicate a cause for concern for people who use HMDs and auditory displays in safety-critical environments.

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<p>A fundamental characteristic of human visual perception is the ability to group together disparate elements in a scene and treat them as a single unit. The mechanisms by which humans create such groupings remain unknown, but grouping seems to play an important role in a wide variety of visual phenomena. I propose a neural model of grouping; through top-down control of its circuits, the model implements a grouping strategy that involves both a connection strategy (which elements to connect) and a selection strategy (spatiotemporal properties of a selection signal that segments target elements to facilitate identification). With computer simulations I explain how the circuits work and show how they can account for a wide variety of Gestalt principles of perceptual grouping. Additionally, I extend the model so that it can simulate visual search tasks. I show that when the model uses particular grouping strategies, simulated results closely match empirical results from replication experiments of three visual search tasks. In these experiments, perceptual grouping was induced by proximity and shape similarity (Palmer & Beck, 2007), by the spacing of irrelevant distractors and size similarity (Vickery, 2008), or by the proximity of dots and the proximity and shape similarity of line figures (Trick & Enns, 1997). Thus, I show that the model accounts for a variety of grouping effects and indicates which grouping strategies were likely used to promote performance in three visual search tasks. </p>

<p dir="ltr">The Black Hole Illusion (BHI) is a nighttime aviation landing illusion where pilots overestimate their descent angle. The BHI occurs when only the outline of the runway is visible to pilots, usually at night with little illumination of the environment. This illusion is dangerous, as it causes pilots to perceive themselves at a high descent angle; and they compensate by flying lower, resulting in a possible crash into the ground or obstacles before the runway. A common interpretation of the BHI is that it represents a perceptual illusion, where the descent angle is misperceived. We quantitatively analyzed two different perceptual theories that predict pilots perceived descent angle during the BHI experience; and we also quantitatively analyzed another perceptual theory to apply during nighttime approaches to alleviate the disorientation experienced from the BHI. Of the first two theories, Perrone's algorithm (Perrone, 1983) predicts that the magnitude of the illusion should vary with runway width/length in nighttime conditions, compared to no illusion and no effect of runway width/length in daylight conditions. On the other hand, the eye-level algorithm (adapted from the work in Galanis, Jennings, and Beckett (1998) and Robinson, Williams, and Biggs (2020)) predicts that there should be no effect of runway width/length in either nighttime or daylight conditions. The last algorithm, the focus of expansion algorithm (adapted from the theory of Gibson (1950) and Gibson (1966)), details a way that pilots can obtain the landing position of their aircraft without estimating their angle of descent, thereby alleviating possible disorientation experienced during nighttime approaches. Additionally, we conducted three empirical studies: The first two aimed at testing Perrone's algorithm and the eye-level algorithm; and the third aimed at testing the focus of expansion algorithm. Across the first two empirical studies, we did demonstrate a BHI for the nighttime evaluations of descent angle; but the data did not support either algorithm. In the third empirical study, the data did not support the focus of expansion algorithm; however, we found that participants were more accurate with estimating the aircraft's landing position when the landing position was closer to the beginning of the runway. Overall, we conclude that the BHI may reflect general disorientation in conditions with limited information.</p>