Immersive technologies, such as virtual and augmented reality, initially failed to live up to expectations, but have improved greatly, with many new head-worn displays and associated applications being released over the past few years. Unfortunately, 'cybersickness' remains as a common user problem that must be overcome if mass adoption is to be realized. This article evaluates the state of research on this problem, identifies challenges that must be addressed, and formulates an updated cybersickness research and development (R&D) agenda. The new agenda recommends prioritizing creation of powerful, lightweight, and untethered head-worn displays, reduction of visual latencies, standardization of symptom and aftereffect measurement, development of improved countermeasures, and improved understanding of the magnitude of the problem and its implications for job performance. Some of these priorities are unresolved problems from the original agenda which should get increased attention now that immersive technologies are proliferating widely. If the resulting R&D agenda is carefully executed, it should render cybersickness a challenge of the past and accelerate mass adoption of immersive technologies to enhance training, performance, and recreation.

Computing the shapes of object boundaries from fragmentary image contours poses a formidable problem for the visual system. We investigated the extrapolation of contour shape by human vision. Measurements of extrapolation position and orientation were taken at six distances from the point of occlusion, thereby yielding a detailed representation of the extrapolated contours. Analyses of these measurements revealed that: (i) extrapolation curvature increases linearly with the curvature of the inducing contour, although there is individual bias in the slope; (ii) the precision with which an extrapolated contour is represented is roughly constant, in angular terms, with increasing distance from the point of occlusion; (iii) there is a substantial cost of curvature, in that the overall precision of an extrapolated contour decreases systematically with curvature; (iv) the shapes of visually extrapolated contours are characterized by a nonlinear decrease in curvature, asymptoting to zero; and (v) this decaying pattern of curvature is explained by a Bayesian model in which, with increasing distance from the point of occlusion, the prior tendency to minimize curvature gradually dominates the likelihood tendency to minimize variation in curvature.contour completion ͉ curvature ͉ interpolation ͉ occlusion ͉ shape perception A fundamental problem faced by the visual brain in computing object structure is the fragmentary nature of the retinal inputs. Large portions of object boundaries are often missing in the retinal images, either due to partial occlusion or because of insufficient local image contrast. Occlusion in particular poses a ubiquitous problem, given the multiplicity of objects in the world and the loss of one spatial dimension during image projection. To compute object structure from fragmented image data, the visual system must solve two related problems. It must determine (i) whether disparate image elements are in fact part of a single continuous contour (the ''grouping'' problem), and (ii) what shape the contour has in the missing portions (the ''shape'' problem).A great deal of research has addressed the grouping problem in the contexts of partly occluded contours, illusory contours, and discretely sampled contours (1-11). This research has examined the geometric constraints that underlie the grouping of local elements into extended contours, as well as how these constraints relate to the statistics of natural images. By contrast, there has been relatively little psychophysical work on measuring the shapes of the missing portions (12-15). Because the missing portions of contours are synthesized entirely by the visual system, their detailed shapes are likely to be revealing about its underlying constraints and mechanisms.Two constraints have been recognized in computational vision: (i) minimization of total curvature, and (ii) minimization of variation in curvature. Minimizing total curvature ͐ 2 ds (also known as ''bending energy'') tends to make contours as straight as possible and leads to a class of inte...

Although we have made major advances in understanding motion perception based on the processing of lateral (2D) motion signals on computer displays, the majority of motion in the real (3D) world occurs outside of the plane of fixation, and motion directly toward or away from observers has particular behavioral relevance. Previous work has reported a systematic lateral bias in the perception of 3D motion, such that an object on a collision course with an observer's head is frequently judged to miss it, with obvious negative consequences. To better understand this bias, we systematically investigated the accuracy of 3D motion perception while manipulating sensory noise by varying the contrast of a moving target and its position in depth relative to fixation. Inconsistent with previous work, we found little bias under low sensory noise conditions. With increased sensory noise, however, we revealed a novel perceptual phenomenon: observers demonstrated a surprising tendency to confuse the direction of motion-in-depth, such that approaching objects were reported to be receding and vice versa. Subsequent analysis revealed that the lateral and motion-in-depth components of observers' reports are similarly affected, but that the effects on the motion-in-depth component (i.e., the motion-in-depth confusions) are much more apparent than those on the lateral component. In addition to revealing this novel visual phenomenon, these results shed new light on errors that can occur in motion perception and provide a basis for continued development of motion perception models. Finally, our findings suggest methods to evaluate the effectiveness of 3D visualization environments, such as 3D movies and virtual reality devices.

In the field of neuroscience, despite the fact that the proportion of peer-reviewed publications authored by women has increased in recent decades, the proportion of citations of women-led publications has not seen a commensurate increase: In five broad-scope journals, citations of papers first- and/or last-authored by women have been shown to be fewer than would be expected if gender was not a factor in citation decisions (Dworkin et al., 2020). Given the important implications that such underrepresentation may have on the careers of women researchers, it is important to determine whether this same trend is true in subdisciplines of the field, where interventions might be more effective. Here, we report the results of an extension of the analyses carried out by Dworkin et al. (2020) to citation patterns in the Journal of Cognitive Neuroscience (JoCN). The results indicate that the underrepresentation of women-led publications in reference sections is also characteristic of papers published in JoCN over the past decade. Furthermore, this pattern of citation imbalances is present for all gender classes of authors, implicating systemic factors. These results contribute to the growing body of evidence that intentional action is needed to address inequities in the way that we carry out and communicate our science.

In the field of neuroscience, despite the fact that the proportion of peer-reviewed publications authored by women has increased in recent decades, the proportion of citations of women-led publications has not seen a commensurate increase: In five broad-scope journals, citations of articles first- and/or last-authored by women have been shown to be fewer than would be expected if gender was not a factor in citation decisions [Dworkin, J. D., Linn, K. A., Teich, E. G., Zurn, P., Shinohara, R. T., & Bassett, D. S. The extent and drivers of gender imbalance in neuroscience reference lists. Nature Neuroscience, 23, 918–926, 2020]. Given the important implications that such underrepresentation may have on the careers of women researchers, it is important to determine whether this same trend is true in subdisciplines of the field, where interventions might be more targeted. Here, we report the results of an extension of the analyses carried out by Dworkin et al. (2020) to citation patterns in the Journal of Cognitive Neuroscience. The results indicate that the underrepresentation of women-led publications in reference sections is also characteristic of articles published in Journal of Cognitive Neuroscience over the past decade. Furthermore, this pattern of citation imbalances is present regardless of author gender, implicating systemic factors. These results contribute to the growing body of evidence that intentional action is needed to address inequities in the way that we carry out and communicate our science.