Reliability and relative weighting of visual and nonvisual information for perceiving direction of self-motion during walking

Perception of object motion during self-motion: Correlated biases in judgments of heading direction and object motion

This study investigated the relationship between perceived heading direction and perceived motion of an independently moving object during self-motion. Using a dual task paradigm, we tested whether object motion judgments showed biases consistent with heading perception, both across conditions and from trial to trial. Subjects viewed simulated self-motion and estimated their heading direction (Experiment 1), or walked toward a target in virtual reality with conflicting physical and visual cues (Experiment 2). During self-motion, an independently moving object briefly appeared, with varied horizontal velocity, and observers judged whether the object was moving leftward or rightward. In Experiment 1, heading estimates showed an expected center bias, and object motion judgments showed corresponding biases. Trial-to-trial variations were also correlated: on trials with a more rightward heading bias, object motion judgments were consistent with a more rightward heading, and vice versa. In Experiment 2, we estimated the relative weighting of visual and physical cues in control of walking and object motion judgments. Both were strongly influenced by nonvisual cues, with less weighting for object motion (86% vs. 63%). There were also trial-to-trial correlations between biases in walking direction and object motion judgments. The results provide evidence that shared mechanisms contribute to heading perception and perception of object motion.

Different generalization of fast and slow visuomotor adaptation across locomotion and pointing tasks

Sensorimotor adaptation can involve multiple learning processes with different time courses, and these processes may have different patterns of transfer. In this study, we tested how slow learning and fast learning transfer across tasks, and the specificity of transfer. We tested two natural goal-directed tasks: pointing and walking toward a visible target. We also tested a novel "hand locomotion" task in which subjects used pointing movements to cause simulated self-motion in virtual reality. The hand locomotion task used the same physical movement as pointing, but performed the same function as stepping. During an experimental block, subjects performed alternating training trials with perturbed visual feedback and test trials with no feedback. The test trials were either the same task to measure adaptation, or a different task to measure transfer. Perturbations on adaptation trials varied over time as a sum of sinusoids with different frequencies. Fast learning would be expected to produce equal responses to fast and slow perturbations, while slower learning would dampen responses to higher frequency perturbations. Subjects were generally not aware of the smoothly varying perturbations, but showed detectable adaptation for all three tasks. Only pointing produced significantly different responses to high- and low-frequency perturbations, consistent with slow learning. Adaptation of pointing produced more transfer to the hand locomotion task, which shared the same effector and motor actions, than to the stepping task. The other tasks showed fast learning but little or no slow learning, and equal transfer to tasks with different effector or function. Our results suggest that the slower components of sensorimotor adaptation are more movement specific, while faster learning is more generalizable.

Information Is Where You Find It: Perception as an Ecologically Well-Posed Problem

Texts on visual perception typically begin with the following premise: Vision is an ill-posed problem, and perception is underdetermined by the available information. If this were really the case, however, it is hard to see how vision could ever get off the ground. James Gibson's signal contribution was his hypothesis that for every perceivable property of the environment, however subtle, there must be a higher order variable of information, however complex, that specifies it-if only we are clever enough to find them. Such variables are informative about behaviorally relevant properties within the physical and ecological constraints of a species' niche. Sensory ecology is replete with instructive examples, including weakly electric fish, the narwal's tusk, and insect flight control. In particular, I elaborate the case of passing through gaps. Optic flow is sufficient to control locomotion around obstacles and through openings. The affordances of the environment, such as gap passability, are specified by action-scaled information. Logically ill-posed problems may thus, on closer inspection, be ecologically well-posed.

Walking with head-mounted virtual and augmented reality devices: Effects on position control and gait biomechanics

What was once a science fiction fantasy, virtual reality (VR) technology has evolved and come a long way. Together with augmented reality (AR) technology, these simulations of an alternative environment have been incorporated into rehabilitation treatments. The introduction of head-mounted displays has made VR/AR devices more intuitive and compact, and no longer limited to upper-limb rehabilitation. However, there is still limited evidence supporting the use of VR and AR technology during locomotion, especially regarding the safety and efficacy relating to walking biomechanics. Therefore, the objective of this study is to explore the limitations of such technology through gait analysis. In this study, thirteen participants walked on a treadmill in normal, virtual and augmented versions of the laboratory environment. A series of spatiotemporal parameters and lower-limb joint angles were compared between conditions. The center of pressure (CoP) ellipse area (95% confidence ellipse) was significantly different between conditions (p = 0.002). Pairwise comparisons indicated a significantly greater CoP ellipse area for both the AR (p = 0.002) and VR (p = 0.005) conditions when compared to the normal laboratory condition. Furthermore, there was a significant difference in stride length (p<0.001) and cadence (p<0.001) between conditions. No statistically significant difference was found in the hip, knee and ankle joint kinematics between the three conditions (p>0.082), except for maximum ankle plantarflexion (p = 0.001). These differences in CoP ellipse area indicate that users of head-mounted VR/AR devices had difficulty maintaining a stable position on the treadmill. Also, differences in the gait parameters suggest that users walked with an unusual gait pattern which could potentially affect the effectiveness of gait rehabilitation treatments. Based on these results, position guidance in the form of feedback and the use of specialized treadmills should be considered when using head-mounted VR/AR devices.

Multisensory Influences on Driver Steering During Curve Navigation

OBJECTIVE

The effects of inertial (vestibular and somatosensory) information on driver steering during curve navigation were investigated, using an electric four-wheel mobility vehicle outfitted with a steering wheel and a portable virtual reality system.

BACKGROUND

When driving, multiple sources of perceptual information are available. Researchers have focused on visual information, which plays a critical role in steering control. However, it is not yet well established how inertial information might contribute.

METHODS

I biased inertial cues by varying visual/inertial gains (doubled, halved, reversed), as drivers negotiated curving paths, and measured steering accuracy and efficiency. I also assessed whether being exposed to inertial biases had an impact on postbias steering by comparing pre- and posttest session performance measures.

RESULTS

Doubling or halving inertial cues had little effect on steering performance. Inertial information only disrupted steering when it was reversed with respect to visual information. Over time, the influence of this extreme inertial bias was reduced though not eliminated. Postbias curve navigation performance was not impacted, likely because participants had learned to disregard, rather than integrate, biased inertial cues.

CONCLUSION

Results suggest that biased inertial information has little influence on curve navigation performance when visual information is available.

APPLICATION

Though inertial cues may be important for open-loop steering, when visual cues are unavailable, their role in closed-loop steering seems less influential. This has implications for driving simulation and suggests that inertial discrepancies due to limitations in motion-cuing capabilities may not be all that problematic for the simulation of closed-loop curve steering tasks.

When flow is not enough: evidence from a lane changing task

Humans are able to estimate their heading on the basis of optic flow information and it has been argued that we use flow in this way to guide navigation. Consistent with this idea, several studies have reported good navigation performance in flow fields. However, one criticism of these studies is that they have generally focused on the task of walking or steering towards a target, offering an additional, salient directional cue. Hence, it remains a matter of debate as to whether humans are truly able to control steering in the presence of optic flow alone. In this study, we report a set of maneuvers carried out in flow fields in the absence of a physical target. To do this, we studied the everyday task of lane changing, a commonplace multiphase steering maneuver which can be conceptualized without the need for a target. What is more (and here is the crucial quirk), previous literature has found that in the absence of visual feedback, drivers show a systematic, asymmetric steering response, resulting in a systematic final heading error. If optic flow is sufficient for controlling navigation through our environment, we would expect this asymmetry to disappear whenever optic flow is provided. However, our results show that this asymmetry persisted, even in the presence of a flow field, implying that drivers are unable to use flow to guide normal steering responses in this task.