Measurement and modeling of depth cue combination: in defense of weak fusion

Embeddedness of Earth's gravity in visual perception

Falling objects are commonplace in daily life, requiring precise perceptual judgments for interception and avoidance. We argue that human judgments of projectile motion arise from the interplay between sensory information and predictions constrained by Newtonian mechanics. Our study investigates how individuals perceive falling objects under various gravitational conditions, aiming to understand the role of internalized gravity in visual perception. Through meticulously controlling the available information, we demonstrated that these phenomena cannot be explained solely by simple heuristics nor representational momentum. Instead, we found that the perceptual judgments of humans (n = 11, 13, 14, and 11, respectively, in Experiments 1, 2, 3, and 4) are influenced by a combination of sensory information and gravity predictions, highlighting the role of internalized physical constraints in the perception of projectile motion.

Lightness constancy in reality, in virtual reality, and on flat-panel displays

Virtual reality (VR) displays are being used in an increasingly wide range of applications. However, previous work shows that viewers often perceive scene properties very differently in real and virtual environments and so realistic perception of virtual stimuli should always be a carefully tested conclusion, not an assumption. One important property for realistic scene perception is surface color. To evaluate how well virtual platforms support realistic perception of achromatic surface color, we assessed lightness constancy in a physical apparatus with real lights and surfaces, in a commercial VR headset, and on a traditional flat-panel display. We found that lightness constancy was good in all three environments, though significantly better in the real environment than on the flat-panel display. We also found that variability across observers was significantly greater in VR and on the flat-panel display than in the physical environment. We conclude that these discrepancies should be taken into account in applications where realistic perception is critical but also that in many cases VR can be used as a flexible alternative to flat-panel displays and a reasonable proxy for real environments.

Human navigation strategies and their errors result from dynamic interactions of spatial uncertainties

Goal-directed navigation requires continuously integrating uncertain self-motion and landmark cues into an internal sense of location and direction, concurrently planning future paths, and sequentially executing motor actions. Here, we provide a unified account of these processes with a computational model of probabilistic path planning in the framework of optimal feedback control under uncertainty. This model gives rise to diverse human navigational strategies previously believed to be distinct behaviors and predicts quantitatively both the errors and the variability of navigation across numerous experiments. This furthermore explains how sequential egocentric landmark observations form an uncertain allocentric cognitive map, how this internal map is used both in route planning and during execution of movements, and reconciles seemingly contradictory results about cue-integration behavior in navigation. Taken together, the present work provides a parsimonious explanation of how patterns of human goal-directed navigation behavior arise from the continuous and dynamic interactions of spatial uncertainties in perception, cognition, and action.

Comparison of Depth-Related Visuomotor Task Performance in Uniocular Individuals and in Binocular Controls With and Without Temporary Monocular Occlusion

Purpose

Do one-eyed (uniocular) humans use monocular depth cues differently from those with intact binocularity to perform depth-related visuomotor tasks that emulate complex activities of daily living? If so, does performance depend on the participant's age, duration of uniocularity and head movements?

Methods

Forty-five uniocular cases (age range 6-37 years; 2.4 months-31.0 years of uniocularity) and 46 age-similar binocular controls performed a task that required them to pass a hoop around an electrified wire convoluted in depth multiple times, while avoiding contact as indicated by auditory feedback. The task was performed with and without head restraint, in random order. The error rate and speed were calculated from the frequency of contact between the hoop and wire and the total task duration (adjusting for error time), respectively, all determined from video recordings of the task. Head movements were analyzed from the videos using face-tracking software.

Results

Error rate decreased with age (P < 0.001) until the late teen years while speed revealed no such trend. Across all ages, the error rate increased and speed decreased in the absence of binocularity (P < 0.001). There was no additional error reduction with duration of uniocularity (P = 0.16). Head movements provided no advantage to task performance, despite generating parallax disparities comparable to binocular viewing.

Conclusions

Performance in a dynamic, depth-related visuomotor task is reduced in the absence of binocular viewing, independent of age-related performance level. This study finds no evidence for a prolonged experience with monocular depth cues being advantageous for such tasks over transient loss of binocularity.

Complexity of mental geometry for 3D pose perception

Biological visual systems rely on pose estimation of 3D objects to navigate and interact with their environment, but the neural mechanisms and computations for inferring 3D poses from 2D retinal images are only partially understood, especially where stereo information is missing. We previously presented evidence that humans infer the poses of 3D objects lying centered on the ground by using the geometrical back-transform from retinal images to viewer-centered world coordinates. This model explained the almost veridical estimation of poses in real scenes and the illusory rotation of poses in obliquely viewed pictures, which includes the "pointing out of the picture" phenomenon. Here we test this model for more varied configurations and find that it needs to be augmented. Five observers estimated poses of sloped, elevated, or off-center 3D sticks in each of 16 different poses displayed on a monitor in frontal and oblique views. Pose estimates in scenes and pictures showed remarkable accuracy and agreement between observers, but with a systematic fronto-parallel bias for oblique poses similar to the ground condition. The retinal projection of the pose of an object sloped wrt the ground depends on the slope. We show that observers' estimates can be explained by the back-transform derived for close to the correct slope. The back-transform explanation also applies to obliquely viewed pictures and to off-center objects and elevated objects, making it more likely that observers use internalized perspective geometry to make 3D pose inferences while actively incorporating inferences about other aspects of object placement.

Dissecting Bayes: Using influence measures to test normative use of probability density information derived from a sample

Bayesian decision theory (BDT) is frequently used to model normative performance in perceptual, motor, and cognitive decision tasks where the possible outcomes of actions are associated with rewards or penalties. The resulting normative models specify how decision makers should encode and combine information about uncertainty and value-step by step-in order to maximize their expected reward. When prior, likelihood, and posterior are probabilities, the Bayesian computation requires only simple arithmetic operations: addition, etc. We focus on visual cognitive tasks where Bayesian computations are carried out not on probabilities but on (1) probability density functions and (2) these probability density functions are derived from samples. We break the BDT model into a series of computations and test human ability to carry out each of these computations in isolation. We test three necessary properties of normative use of pdf information derived from a sample-accuracy, additivity and influence. Influence measures allow us to assess how much weight each point in the sample is assigned in making decisions and allow us to compare normative use (weighting) of samples to actual, point by point. We find that human decision makers violate accuracy and additivity systematically but that the cost of failure in accuracy or additivity would be minor in common decision tasks. However, a comparison of measured influence for each sample point with normative influence measures demonstrates that the individual's use of sample information is markedly different from the predictions of BDT. We will show that the normative BDT model takes into account the geometric symmetries of the pdf while the human decision maker does not. An alternative model basing decisions on a single extreme sample point provided a better account for participants' data than the normative BDT model.

Conflicts between short- and long-term experiences affect visual perception through modulating sensory or motor response systems: Evidence from Bayesian inference models

The independent effects of short- and long-term experiences on visual perception have been discussed for decades. However, no study has investigated whether and how these experiences simultaneously affect our visual perception. To address this question, we asked participants to estimate their self-motion directions (i.e., headings) simulated from optic flow, in which a long-term experience learned in everyday life (i.e., straight-forward motion being more common than lateral motion) plays an important role. The headings were selected from three distributions that resembled a peak, a hill, and a flat line, creating different short-term experiences. Importantly, the proportions of headings deviating from the straight-forward motion gradually increased in the peak, hill, and flat distributions, leading to a greater conflict between long- and short-term experiences. The results showed that participants biased their heading estimates towards the straight-ahead direction and previously seen headings, which increased with the growing experience conflict. This suggests that both long- and short-term experiences simultaneously affect visual perception. Finally, we developed two Bayesian models (Model 1 vs. Model 2) based on two assumptions that the experience conflict altered the likelihood distribution of sensory representation or the motor response system. The results showed that both models accurately predicted participants' estimation biases. However, Model 1 predicted a higher variance of serial dependence compared to Model 2, while Model 2 predicted a higher variance of the bias towards the straight-ahead direction compared to Model 1. This suggests that the experience conflict can influence visual perception by affecting both sensory and motor response systems. Taken together, the current study systematically revealed the effects of long- and short-term experiences on visual perception and the underlying Bayesian processing mechanisms.

How small changes to one eye's retinal image can transform the perceived shape of a very familiar object

Vision can provide useful cues about the geometric properties of an object, like its size, distance, pose, and shape. But how the brain merges these properties into a complete sensory representation of a three-dimensional object is poorly understood. To address this gap, we investigated a visual illusion in which humans misperceive the shape of an object due to a small change in one eye's retinal image. We first show that this illusion affects percepts of a highly familiar object under completely natural viewing conditions. Specifically, people perceived their own rectangular mobile phone to have a trapezoidal shape. We then investigate the perceptual underpinnings of this illusion by asking people to report both the perceived shape and pose of controlled stimuli. Our results suggest that the shape illusion results from distorted cues to object pose. In addition to yielding insights into object perception, this work informs our understanding of how the brain combines information from multiple visual cues in natural settings. The shape illusion can occur when people wear everyday prescription spectacles; thus, these findings also provide insight into the cue combination challenges that some spectacle wearers experience on a regular basis.

Both stimulus-specific and configurational features of multiple visual stimuli shape the spatial ventriloquism effect

Studies on multisensory perception often focus on simplistic conditions in which one single stimulus is presented per modality. Yet, in everyday life, we usually encounter multiple signals per modality. To understand how multiple signals within and across the senses are combined, we extended the classical audio-visual spatial ventriloquism paradigm to combine two visual stimuli with one sound. The individual visual stimuli presented in the same trial differed in their relative timing and spatial offsets to the sound, allowing us to contrast their individual and combined influence on sound localization judgements. We find that the ventriloquism bias is not dominated by a single visual stimulus but rather is shaped by the collective multisensory evidence. In particular, the contribution of an individual visual stimulus to the ventriloquism bias depends not only on its own relative spatio-temporal alignment to the sound but also the spatio-temporal alignment of the other visual stimulus. We propose that this pattern of multi-stimulus multisensory integration reflects the evolution of evidence for sensory causal relations during individual trials, calling for the need to extend established models of multisensory causal inference to more naturalistic conditions. Our data also suggest that this pattern of multisensory interactions extends to the ventriloquism aftereffect, a bias in sound localization observed in unisensory judgements following a multisensory stimulus.

Correctly establishing evidence for cue combination via gains in sensory precision: Why the choice of comparator matters

Studying how sensory signals from different sources (sensory cues) are integrated within or across multiple senses allows us to better understand the perceptual computations that lie at the foundation of adaptive behaviour. As such, determining the presence of precision gains - the classic hallmark of cue combination - is important for characterising perceptual systems, their development and functioning in clinical conditions. However, empirically measuring precision gains to distinguish cue combination from alternative perceptual strategies requires careful methodological considerations. Here, we note that the majority of existing studies that tested for cue combination either omitted this important contrast, or used an analysis approach that, unknowingly, strongly inflated false positives. Using simulations, we demonstrate that this approach enhances the chances of finding significant cue combination effects in up to 100% of cases, even when cues are not combined. We establish how this error arises when the wrong cue comparator is chosen and recommend an alternative analysis that is easy to implement but has only been adopted by relatively few studies. By comparing combined-cue perceptual precision with the best single-cue precision, determined for each observer individually rather than at the group level, researchers can enhance the credibility of their reported effects. We also note that testing for deviations from optimal predictions alone is not sufficient to ascertain whether cues are combined. Taken together, to correctly test for perceptual precision gains, we advocate for a careful comparator selection and task design to ensure that cue combination is tested with maximum power, while reducing the inflation of false positives.

Depth perception of stereoscopic transparent stimuli with frame manipulation

Depth perception is crucial in human vision, allowing us to move and interact with our 3-D surroundings. We used a stereoscopic transparent stimulus comprising parallel overlapping transparent stereoscopic surfaces (POTS) to understand depth perception better. The study focused on exploring the effect of a surrounding frame on the perceived depth of a POTS configuration. The research was based on a proposed idea that explains an "off-frame" effect: a frame at a different depth from a 2-D photograph depicting a 3-D scene increases its apparent depth qualitatively. The idea assumes that processing the disparity between a frame and a photo reduces the reliability of the photograph's flatness cues and increases depth magnitude in depth cue integration. We examined whether the idea can be applied to a 3-D POTS with the flatness cue as the constant accommodation. Through three experiments, the study showed that frames impact the perceived depth magnitude of a POTS configuration. More specifically, the depth magnitude increases as the frame's disparity concerning the monitor plane increases and decreases as the frame's size increases. We discussed the results in the context of depth cue combination.

Linear perspective cues have a greater effect on the perceptual rescaling of distant stimuli than textures in the virtual environment

The presence of pictorial depth cues in virtual environments is important for minimising distortions driven by unnatural viewing conditions (e.g., vergence-accommodation conflict). Our aim was to determine how different pictorial depth cues affect size constancy in virtual environments under binocular and monocular viewing conditions. We systematically removed linear perspective cues and textures of a hallway in a virtual environment. The experiment was performed using the method of constant stimuli. The task required participants to compare the size of 'far' (10 m) and 'near' (5 m) circles displayed inside a virtual environment with one or both or none of the pictorial depth cues. Participants performed the experiment under binocular and monocular viewing conditions while wearing a virtual reality headset. ANOVA revealed that size constancy was greater for both the far and the near circles in the virtual environment with pictorial depth cues compared to the one without cues. However, the effect of linear perspective cues was stronger than textures, especially for the far circle. We found no difference between the binocular and monocular viewing conditions across the different virtual environments. We conclude that linear perspective cues exert a stronger effect than textures on the perceptual rescaling of far stimuli placed in the virtual environment, and that this effect does not vary between binocular and monocular viewing conditions.

A theory of visibility measures in the dissociation paradigm

Research on perception without awareness primarily relies on the dissociation paradigm, which compares a measure of awareness of a critical stimulus (direct measure) with a measure indicating that the stimulus has been processed at all (indirect measure). We argue that dissociations between direct and indirect measures can only be demonstrated with respect to the critical stimulus feature that generates the indirect effect, and the observer's awareness of that feature, the critical cue. We expand Kahneman's (Psychological Bulletin, 70, 404-425, 1968) concept of criterion content to comprise the set of all cues that an observer actually uses to perform the direct task. Different direct measures can then be compared by studying the overlap of their criterion contents and their containment of the critical cue. Because objective and subjective measures may integrate different sets of cues, one measure generally cannot replace the other without sacrificing important information. Using a simple mathematical formalization, we redefine and clarify the concepts of validity, exclusiveness, and exhaustiveness in the dissociation paradigm, show how dissociations among different awareness measures falsify both single-valued measures and monocausal theories of "consciousness," and formulate the demand that theories of visual awareness should be sufficiently specific to explain dissociations among different facets of awareness.

Detecting visual texture patterns in binary sequences through pattern features

We measured human ability to detect texture patterns in a signal detection task. Observers viewed sequences of 20 blue or yellow tokens placed horizontally in a row. They attempted to discriminate sequences generated by a random generator ("a fair coin") from sequences produced by a disrupted Markov sequence (DMS) generator. The DMSs were generated in two stages: first a sequence was generated using a Markov chain with probability, pr = 0.9, that a token would be the same color as the token to its left. The Markov sequence was then disrupted by flipping each token from blue to yellow or vice versa with probability, pd-the probability of disruption. Disruption played the role of noise in signal detection terms. We can frame what observers are asked to do as detecting Markov texture patterns disrupted by noise. The experiment included three conditions differing in pd (0.1, 0.2, 0.3). Ninety-two observers participated, each in only one condition. Overall, human observers' sensitivities to texture patterns (d' values) were markedly less than those of an optimal Bayesian observer. We considered the possibility that observers based their judgments not on the entire texture sequence but on specific features of the sequences such as the length of the longest repeating subsequence. We compared human performance with that of multiple optimal Bayesian classifiers based on such features. We identify the single- and multiple-feature models that best match the performance of observers across conditions and develop a pattern feature pool model for the signal detection task considered.

Perceiving depth and motion in depth from successive occlusion

Occlusion, or interposition, is one of the strongest and best-known pictorial cues to depth. Furthermore, the successive occlusions of previous objects by newly presented objects produces an impression of increasing depth. Although the perceived motion associated with this illusion has been studied, the depth percept has not. To investigate, participants were presented with two piles of disks with one always static and the other either a static pile or a stacking pile where a new disk was added every 200 ms. We found static piles with equal number of disks appeared equal in height. In contrast, the successive presentation of disks in the stacking condition appeared to enhance the perceived height of the stack-fewer disks were needed to match the static pile. Surprisingly, participants were also more precise when comparing stacking versus static piles of disks. Reversing the stacking by removing rather than adding disks reversed the bias and degraded precision. In follow-up experiments, we used nonoverlapping static and dynamic configurations to show that the effects are not due to simple differences in perceived numerosity. In sum, our results show that successive occlusions generate a greater sense of height than occlusion alone, and we posit that dynamic occlusion may be an underappreciated source of depth information.

Multisensory cues for walking in virtual reality: humans combine conflicting visual and self-motion information to reproduce distances

When humans walk, it is important for them to have some measure of the distance they have traveled. Typically, many cues from different modalities are available, as humans perceive both the environment around them (for example, through vision and haptics) and their own walking. Here, we investigate the contribution of visual cues and nonvisual self-motion cues to distance reproduction when walking on a treadmill through a virtual environment by separately manipulating the speed of a treadmill belt and of the virtual environment. Using mobile eye tracking, we also investigate how our participants sampled the visual information through gaze. We show that, as predicted, both modalities affected how participants (N = 28) reproduced a distance. Participants weighed nonvisual self-motion cues more strongly than visual cues, corresponding also to their respective reliabilities, but with some interindividual variability. Those who looked more toward those parts of the visual scene that contained cues to speed and distance tended also to weigh visual information more strongly, although this correlation was nonsignificant, and participants generally directed their gaze toward visually informative areas of the scene less than expected. As measured by motion capture, participants adjusted their gait patterns to the treadmill speed but not to walked distance. In sum, we show in a naturalistic virtual environment how humans use different sensory modalities when reproducing distances and how the use of these cues differs between participants and depends on information sampling.NEW & NOTEWORTHY Combining virtual reality with treadmill walking, we measured the relative importance of visual cues and nonvisual self-motion cues for distance reproduction. Participants used both cues but put more weight on self-motion; weight on visual cues had a trend to correlate with looking at visually informative areas. Participants overshot distances, especially when self-motion was slow; they adjusted steps to self-motion cues but not to visual cues. Our work thus quantifies the multimodal contributions to distance reproduction.

How the brain controls decision making in a multisensory world

Sensory systems evolved to provide the organism with information about the environment to guide adaptive behaviour. Neuroscientists and psychologists have traditionally considered each sense independently, a legacy of Aristotle and a natural consequence of their distinct physical and anatomical bases. However, from the point of view of the organism, perception and sensorimotor behaviour are fundamentally multi-modal; after all, each modality provides complementary information about the same world. Classic studies revealed much about where and how sensory signals are combined to improve performance, but these tended to treat multisensory integration as a static, passive, bottom-up process. It has become increasingly clear how this approach falls short, ignoring the interplay between perception and action, the temporal dynamics of the decision process and the many ways by which the brain can exert top-down control of integration. The goal of this issue is to highlight recent advances on these higher order aspects of multisensory processing, which together constitute a mainstay of our understanding of complex, natural behaviour and its neural basis. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Multisensory causal inference is feature-specific, not object-based

Multisensory integration depends on causal inference about the sensory signals. We tested whether implicit causal-inference judgements pertain to entire objects or focus on task-relevant object features. Participants in our study judged virtual visual, haptic and visual-haptic surfaces with respect to two features-slant and roughness-against an internal standard in a two-alternative forced-choice task. Modelling of participants' responses revealed that the degree to which their perceptual judgements were based on integrated visual-haptic information varied unsystematically across features. For example, a perceived mismatch between visual and haptic roughness would not deter the observer from integrating visual and haptic slant. These results indicate that participants based their perceptual judgements on a feature-specific selection of information, suggesting that multisensory causal inference proceeds not at the object level but at the level of single object features. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Self-motion perception and sequential decision-making: where are we heading?

To navigate and guide adaptive behaviour in a dynamic environment, animals must accurately estimate their own motion relative to the external world. This is a fundamentally multisensory process involving integration of visual, vestibular and kinesthetic inputs. Ideal observer models, paired with careful neurophysiological investigation, helped to reveal how visual and vestibular signals are combined to support perception of linear self-motion direction, or heading. Recent work has extended these findings by emphasizing the dimension of time, both with regard to stimulus dynamics and the trade-off between speed and accuracy. Both time and certainty-i.e. the degree of confidence in a multisensory decision-are essential to the ecological goals of the system: terminating a decision process is necessary for timely action, and predicting one's accuracy is critical for making multiple decisions in a sequence, as in navigation. Here, we summarize a leading model for multisensory decision-making, then show how the model can be extended to study confidence in heading discrimination. Lastly, we preview ongoing efforts to bridge self-motion perception and navigation per se, including closed-loop virtual reality and active self-motion. The design of unconstrained, ethologically inspired tasks, accompanied by large-scale neural recordings, raise promise for a deeper understanding of spatial perception and decision-making in the behaving animal. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Different types of uncertainty in multisensory perceptual decision making

Efficient decision-making requires accounting for sources of uncertainty (noise, or variability). Many studies have shown how the nervous system is able to account for perceptual uncertainty (noise, variability) that arises from limitations in its own abilities to encode perceptual stimuli. However, many other sources of uncertainty exist, reflecting for example variability in the behaviour of other agents or physical processes. Here we review previous studies on decision making under uncertainty as a function of the different types of uncertainty that the nervous system encounters, showing that noise that is intrinsic to the perceptual system can often be accounted for near-optimally (i.e. not statistically different from optimally), whereas accounting for other types of uncertainty can be much more challenging. As an example, we present a study in which participants made decisions about multisensory stimuli with both intrinsic (perceptual) and extrinsic (environmental) uncertainty and show that the nervous system accounts for these differently when making decisions: they account for internal uncertainty but under-account for external. Human perceptual systems may be well equipped to account for intrinsic (perceptual) uncertainty because, in principle, they have access to this. Accounting for external uncertainty is more challenging because this uncertainty must be learned. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Temporal and spatial properties of vestibular signals for perception of self-motion

It is well recognized that the vestibular system is involved in numerous important cognitive functions, including self-motion perception, spatial orientation, locomotion, and vector-based navigation, in addition to basic reflexes, such as oculomotor or body postural control. Consistent with this rationale, vestibular signals exist broadly in the brain, including several regions of the cerebral cortex, potentially allowing tight coordination with other sensory systems to improve the accuracy and precision of perception or action during self-motion. Recent neurophysiological studies in animal models based on single-cell resolution indicate that vestibular signals exhibit complex spatiotemporal dynamics, producing challenges in identifying their exact functions and how they are integrated with other modality signals. For example, vestibular and optic flow could provide congruent and incongruent signals regarding spatial tuning functions, reference frames, and temporal dynamics. Comprehensive studies, including behavioral tasks, neural recording across sensory and sensory-motor association areas, and causal link manipulations, have provided some insights into the neural mechanisms underlying multisensory self-motion perception.

Near-optimal integration of the magnitude information of time and numerosity

Magnitude information is often correlated in the external world, providing complementary information about the environment. As if to reflect this relationship, the perceptions of different magnitudes (e.g. time and numerosity) are known to influence one another. Recent studies suggest that such magnitude interaction is similar to cue integration, such as multisensory integration. Here, we tested whether human observers could integrate the magnitudes of two quantities with distinct physical units (i.e. time and numerosity) as abstract magnitude information. The participants compared the magnitudes of two visual stimuli based on time, numerosity, or both. Consistent with the predictions of the maximum-likelihood estimation model, the participants integrated time and numerosity in a near-optimal manner; the weight of each dimension was proportional to their relative reliability, and the integrated estimate was more reliable than either the time or numerosity estimate. Furthermore, the integration approached a statistical optimum as the temporal discrepancy of the acquisition of each piece of information became smaller. These results suggest that magnitude interaction arises through a similar computational mechanism to cue integration. They are also consistent with the idea that different magnitudes are processed by a generalized magnitude system.

Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration

Bayesian inference theories have been extensively used to model how the brain derives three-dimensional (3D) information from ambiguous visual input. In particular, the maximum likelihood estimation (MLE) model combines estimates from multiple depth cues according to their relative reliability to produce the most probable 3D interpretation. Here, we tested an alternative theory of cue integration, termed the intrinsic constraint (IC) theory, which postulates that the visual system derives the most stable, not most probable, interpretation of the visual input amid variations in viewing conditions. The vector sum model provides a normative approach for achieving this goal where individual cue estimates are components of a multidimensional vector whose norm determines the combined estimate. Individual cue estimates are not accurate but related to distal 3D properties through a deterministic mapping. In three experiments, we show that the IC theory can more adeptly account for 3D cue integration than MLE models. In Experiment 1, we show systematic biases in the perception of depth from texture and depth from binocular disparity. Critically, we demonstrate that the vector sum model predicts an increase in perceived depth when these cues are combined. In Experiment 2, we illustrate the IC theory radical reinterpretation of the just noticeable difference (JND) and test the related vector sum model prediction of the classic finding of smaller JNDs for combined-cue versus single-cue stimuli. In Experiment 3, we confirm the vector sum prediction that biases found in cue integration experiments cannot be attributed to flatness cues, as the MLE model predicts.

Despite Impaired Binocular Function, Binocular Disparity Integration Across the Visual Field Is Spared in Normal Aging and Glaucoma

Purpose

To examine how binocularly asymmetric glaucomatous visual field damage affects binocular disparity processing across the visual field.

Methods

We recruited 18 patients with primary open-angle glaucoma, 16 age-matched controls, and 13 young controls. Participants underwent standard clinical assessments of binocular visual acuity, binocular contrast sensitivity, stereoacuity, and perimetry. We employed a previously validated psychophysical procedure to measure how sensitivity to binocular disparity varied across spatial frequencies and visual field sectors (i.e., with full-field stimuli spanning the central 21° of the visual field and with stimuli restricted to annular regions spanning 0°-3°, 3°-9°, or 9°-21°). We employed measurements with annular stimuli to model different possible scenarios regarding how disparity information is combined across visual field sectors. We adjudicated between potential mechanisms by comparing model predictions to the patterns observed with full-field stimuli.

Results

Perimetry confirmed that patients with glaucoma exhibited binocularly asymmetric visual field damage (P < 0.001). Across participant groups, foveal regions preferentially processed disparities at finer spatial scales, whereas periphery regions were tuned for coarser scales (P < 0.001). Disparity sensitivity also decreased from fovea to periphery (P < 0.001) and across participant groups (Ps < 0.01). Finally, similar to controls, patients with glaucoma exhibited near-optimal disparity integration, specifically at low spatial frequencies (P < 0.001).

Conclusions

Contrary to the conventional view that glaucoma spares central vision, we find that glaucomatous damage causes a widespread loss of disparity sensitivity across both foveal and peripheral regions. Despite these losses, cortical integration mechanisms appear to be well preserved, suggesting that patients with glaucoma make the best possible use of their remaining binocular function.

Examining the Results of Virtual Reality-Based Egocentric Distance Estimation Tests Based on Immersion Level

Depth perception as well as egocentric distance estimation can be trained in virtual spaces, although incorrect estimates can occur in these environments. To understand this phenomenon, a virtual environment with 11 changeable factors was created. Egocentric distance estimation skills of 239 participants were assessed with it in the range [25 cm, 160 cm]. One hundred fifty-seven people used a desktop display and seventy-two the Gear VR. According to the results, these investigated factors can have various effects combined with the two display devices on distance estimation and its time. Overall, desktop display users are more likely to accurately estimate or overestimate distances, and significant overestimations occur at 130 and 160 cm. With the Gear VR, distances in the range [40 cm, 130 cm] are significantly underestimated, while at 25 cm, they are significantly overestimated. Estimation times are significantly decreased with the Gear VR. When developing future virtual environments that require depth perception skills, developers should take these results into account.

Comparing the Effects of Visual Realism on Size Perception in VR versus Real World Viewing through Physical and Verbal Judgments

Virtual Reality (VR) is well-known for its use in interdisciplinary applications and research. The visual representation of these applications could vary depending in their purpose and hardware limitation, and in those situations could require an accurate perception of size for task performance. However, the relationship between size perception and visual realism in VR has not yet been explored. In this contribution, we conducted an empirical evaluation using a between-subject design over four conditions of visual realism, namely Realistic, Local Lighting, Cartoon, and Sketch on size perception of target objects in the same virtual environment. Additionally, we gathered participants' size estimates in the real world via a within-subject session. We measured size perception using concurrent verbal reports and physical judgments. Our result showed that although participants' size perception was accurate in the realistic condition, surprisingly they could still tune into the invariant but meaningful information in the environment to accurately estimate the size of targets in the non-photorealistic conditions as well. We additionally found that size estimates in verbal and physical responses were generally different in real world and VR viewing and were moderated by trial presentation over time and target object widths.

Luminance contrast provides metric depth information

The perception of depth from retinal images depends on information from multiple visual cues. One potential depth cue is the statistical relationship between luminance and distance; darker points in a local region of an image tend to be farther away than brighter points. We establish that this statistical relationship acts as a quantitative cue to depth. We show that luminance variations affect depth in naturalistic scenes containing multiple cues to depth. This occurred when the correlation between variations of luminance and depth was manipulated within an object, but not between objects. This is consistent with the local nature of the statistical relationship in natural scenes. We also showed that perceived depth increases as contrast is increased, but only when the depth signalled by luminance and binocular disparity are consistent. Our results show that the negative correlation between luminance and distance, as found under diffuse lighting, provides a depth cue that is combined with depth from binocular disparity, in a way that is consistent with the simultaneous estimation of surface depth and reflectance variations. Adopting more complex lighting models such as ambient occlusion in computer rendering will thus contribute to the accuracy as well as the aesthetic appearance of three-dimensional graphics.

Familiar size affects perception differently in virtual reality and the real world

The promise of virtual reality (VR) as a tool for perceptual and cognitive research rests on the assumption that perception in virtual environments generalizes to the real world. Here, we conducted two experiments to compare size and distance perception between VR and physical reality (Maltz et al. 2021 J. Vis. 21, 1-18). In experiment 1, we used VR to present dice and Rubik's cubes at their typical sizes or reversed sizes at distances that maintained a constant visual angle. After viewing the stimuli binocularly (to provide vergence and disparity information) or monocularly, participants manually estimated perceived size and distance. Unlike physical reality, where participants relied less on familiar size and more on presented size during binocular versus monocular viewing, in VR participants relied heavily on familiar size regardless of the availability of binocular cues. In experiment 2, we demonstrated that the effects in VR generalized to other stimuli and to a higher quality VR headset. These results suggest that the use of binocular cues and familiar size differs substantially between virtual and physical reality. A deeper understanding of perceptual differences is necessary before assuming that research outcomes from VR will generalize to the real world. This article is part of a discussion meeting issue 'New approaches to 3D vision'.

New Approaches to 3D Vision

New approaches to 3D vision are enabling new advances in artificial intelligence and autonomous vehicles, a better understanding of how animals navigate the 3D world, and new insights into human perception in virtual and augmented reality. Whilst traditional approaches to 3D vision in computer vision (SLAM: simultaneous localization and mapping), animal navigation (cognitive maps), and human vision (optimal cue integration) start from the assumption that the aim of 3D vision is to provide an accurate 3D model of the world, the new approaches to 3D vision explored in this issue challenge this assumption. Instead, they investigate the possibility that computer vision, animal navigation, and human vision can rely on partial or distorted models or no model at all. This issue also highlights the implications for artificial intelligence, autonomous vehicles, human perception in virtual and augmented reality, and the treatment of visual disorders, all of which are explored by individual articles. This article is part of a discussion meeting issue 'New approaches to 3D vision'.

Minimal theory of 3D vision: new approach to visual scale and visual shape

Since Kepler and Descartes in the early-1600s, vision science has been committed to a triangulation model of stereo vision. But in the early-1800s, we realized that disparities are responsible for stereo vision. And we have spent the past 200 years trying to shoe-horn disparities back into the triangulation account. The first part of this article argues that this is a mistake, and that stereo vision is a solution to a different problem: the eradication of rivalry between the two retinal images, rather than the triangulation of objects in space. This leads to a 'minimal theory of 3D vision', where 3D vision is no longer tied to estimating the scale, shape, and direction of objects in the world. The second part of this article then asks whether the other aspects of 3D vision, which go beyond stereo vision, really operate at the same level of visual experience as stereo vision? I argue they do not. Whilst we want a theory of real-world 3D vision, the literature risks giving us a theory of picture perception instead. And I argue for a two-stage theory, where our purely internal 'minimal' 3D percept (from stereo vision) is linked to the world through cognition. This article is part of a discussion meeting issue 'New approaches to 3D vision'.

From pictures to reality: modelling the phenomenology and psychophysics of 3D perception

The dominant inferential approach to human 3D perception assumes a model of spatial encoding based on a physical description of objects and space. Prevailing models based on this physicalist approach assume that the visual system infers an objective, unitary and mostly veridical representation of the external world. However, careful consideration of the phenomenology of 3D perception challenges these assumptions. I review important aspects of phenomenology, psychophysics and neurophysiology which suggest that human visual perception of 3D  objects and space is underwritten by distinct and dissociated spatial encodings that are optimized for specific regions of space. Specifically, I argue that 3D perception is underwritten by at least three distinct encodings for (1) egocentric distance perception at the ambulatory scale, (2) exocentric distance (scaled depth) perception optimized for near space, and (3) perception of object shape and layout (unscaled depth). This tripartite division can more satisfactorily account for the phenomenology, psychophysics and adaptive logic of human 3D perception. This article is part of a discussion meeting issue 'New approaches to 3D vision'.

Virtual Reality for Vision Science

Virtual reality (VR) allows us to create visual stimuli that are both immersive and reactive. VR provides many new opportunities in vision science. In particular, it allows us to present wide field-of-view, immersive visual stimuli; for observers to actively explore the environments that we create; and for us to understand how visual information is used in the control of behaviour. In contrast with traditional psychophysical experiments, VR provides much greater flexibility in creating environments and tasks that are more closely aligned with our everyday experience. These benefits of VR are of particular value in developing our theories of the behavioural goals of the visual system and explaining how visual information is processed to achieve these goals. The use of VR in vision science presents a number of technical challenges, relating to how the available software and hardware limit our ability to accurately specify the visual information that defines our virtual environments and the interpretation of data gathered in experiments with a freely moving observer in a responsive environment.

Enhancement of visual cues to self-motion during a visual/vestibular conflict

Perceiving our orientation and motion requires sensory information provided by vision, our body and acceleration. Normally, these cues are redundant however in some situations they can conflict. Here, we created a visual-vestibular conflict by simulating a body-upright virtual world while participants were either standing (no conflict), supine or prone (conflict) and assessed the perception of "forward" distance travelled induced by visual motion. Some participants felt they were standing upright even when lying, indicating a visual reorientation illusion (VRI). We previously showed that when experiencing a VRI, visually induced self-motion is enhanced. Here, we determined if there was a relationship between VRI vulnerability and sensory weighting. Confirming our previous findings, the VRI-vulnerable group showed enhanced self-motion perception. We then assessed the relative weightings of visual and non-visual cues in VRI-vulnerable and VRI-resistant individuals using the Oriented Character Recognition Test. Surprisingly, VRI-vulnerable individuals weighted visual cues less and gravity cues more compared to VRI-resistant individuals. These findings are in line with robust integration where, when the difference between two cues is large, the discrepant cue (here gravity) is ignored. Ignoring the gravity cue then leads to relatively more emphasis being placed on visual information and thus a higher gain.

A General Framework for Inferring Bayesian Ideal Observer Models from Psychophysical Data

A central question in neuroscience is how sensory inputs are transformed into percepts. At this point, it is clear that this process is strongly influenced by prior knowledge of the sensory environment. Bayesian ideal observer models provide a useful link between data and theory that can help researchers evaluate how prior knowledge is represented and integrated with incoming sensory information. However, the statistical prior employed by a Bayesian observer cannot be measured directly, and must instead be inferred from behavioral measurements. Here, we review the general problem of inferring priors from psychophysical data, and the simple solution that follows from assuming a prior that is a Gaussian probability distribution. As our understanding of sensory processing advances, however, there is an increasing need for methods to flexibly recover the shape of Bayesian priors that are not well approximated by elementary functions. To address this issue, we describe a novel approach that applies to arbitrary prior shapes, which we parameterize using mixtures of Gaussian distributions. After incorporating a simple approximation, this method produces an analytical solution for psychophysical quantities that can be numerically optimized to recover the shapes of Bayesian priors. This approach offers advantages in flexibility, while still providing an analytical framework for many scenarios. We provide a MATLAB toolbox implementing key computations described herein.

Binocular Information Improves the Reliability and Consistency of Pictorial Relief

Binocular disparity is an important cue to three-dimensional shape. We assessed the contribution of this cue to the reliability and consistency of depth in stereoscopic photographs of natural scenes. Observers viewed photographs of cluttered scenes while adjusting a gauge figure to indicate the apparent three-dimensional orientation of the surfaces of objects. The gauge figure was positioned on the surfaces of objects at multiple points in the scene, and settings were made under monocular and binocular, stereoscopic viewing. Settings were used to create a depth relief map, indicating the apparent three-dimensional structure of the scene. We found that binocular cues increased the magnitude of apparent depth, the reliability of settings across repeated measures, and the consistency of perceived depth across participants. These results show that binocular cues make an important contribution to the precise and accurate perception of depth in natural scenes that contain multiple pictorial cues.

Shedding Light on Cast Shadows: An Investigation of Perceived Ground Contact in AR and VR

Virtual objects in augmented reality (AR) often appear to float atop real world surfaces, which makes it difficult to determine where they are positioned in space. This is problematic as many applications for AR require accurate spatial perception. In the current study, we examine how the way we render cast shadows-which act as an important monocular depth cue for creating a sense of contact between an object and the surface beneath it-impacts spatial perception. Over two experiments, we evaluate people's sense of surface contact given both traditional and non-traditional shadow shading methods in optical see-through augmented reality (OST AR), video see-through augmented reality (VST AR), and virtual reality (VR) head-mounted displays. Our results provide evidence that nontraditional shading techniques for rendering shadows in AR displays may enhance the accuracy of one's perception of surface contact. This finding implies a possible tradeoff between photorealism and accuracy of depth perception, especially in OST AR displays. However, it also supports the use of more stylized graphics like non-traditional cast shadows to improve perception and interaction in AR applications.

Combination of visuo-tactile and visuo-vestibular correlations in illusory body ownership and self-motion sensations

Previous studies have shown that illusory ownership over a mannequin's body can be induced through synchronous visuo-tactile stimulation as well as through synchronous visuo-vestibular stimulation. The current study aimed to elucidate how three-way combinations of correlated visual, tactile and vestibular signals contribute to the senses of body ownership and self-motion. Visuo-tactile temporal congruence was manipulated by touching the mannequin's body and the participant's unseen real body on the trunk with a small object either synchronously or asynchronously. Visuo-vestibular temporal congruence was manipulated by synchronous or asynchronous presentation of a visual motion cue (the background rotating around the mannequin in one direction) and galvanic stimulation of the vestibular nerve generating a rotation sensation (in the same direction). The illusory experiences were quantified using a questionnaire; threat-evoked skin-conductance responses (SCRs) provided complementary indirect physiological evidence for the illusion. Ratings on the illusion questionnaire statement showed significant main effects of synchronous visuo-vestibular and synchronous visuo-tactile stimulations, suggesting that both of these pairs of bimodal correlations contribute to the ownership illusion. Interestingly, visuo-tactile synchrony dominated because synchronous visuo-tactile stimulation combined with asynchronous visuo-vestibular stimulation elicited a body ownership illusion of similar strength as when both bimodal combinations were synchronous. Moreover, both visuo-tactile and visuo-vestibular synchrony were associated with enhanced self-motion perception; self-motion sensations were even triggered when visuo-tactile synchrony was combined with visuo-vestibular asynchrony, suggesting that ownership enhanced the relevance of visual information as a self-motion cue. Finally, the SCR results suggest that synchronous stimulation of either modality pair led to a stronger illusion compared to the asynchronous conditions. Collectively, the results suggest that visuo-tactile temporal correlations have a stronger influence on body ownership than visuo-vestibular correlations and that ownership boosts self-motion perception. We present a Bayesian causal inference model that can explain how visuo-vestibular and visuo-tactile information are combined in multisensory own-body perception.

The pinna enhances angular discrimination in the frontal hemifield

Human sound localization in the horizontal dimension is thought to be dominated by binaural cues, particularly interaural time delays, because monaural localization in this dimension is relatively poor. Remaining ambiguities of front versus back and up versus down are distinguished by high-frequency spectral cues generated by the pinna. The experiments in this study show that this account is incomplete. Using binaural listening throughout, the pinna substantially enhanced horizontal discrimination in the frontal hemifield, making discrimination in front better than discrimination at the rear, particularly for directions away from the median plane. Eliminating acoustic effects of the pinna by acoustically bypassing them or low-pass filtering abolished the advantage at the front without affecting the rear. Acoustic measurements revealed a pinna-induced spectral prominence that shifts smoothly in frequency as sounds move from 0° to 90° azimuth. The improved performance is discussed in terms of the monaural and binaural changes induced by the pinna.

How Peripheral Vestibular Damage Affects Velocity Storage: a Causative Explanation

Velocity storage is a centrally-mediated mechanism that processes peripheral vestibular inputs. One prominent aspect of velocity storage is its effect on dynamic responses to yaw rotation. Specifically, when normal human subjects are accelerated to constant angular yaw velocity, horizontal eye movements and perceived angular velocity decay exponentially with a time constant circa 15-30 s, even though the input from the vestibular periphery decays much faster (~ 6 s). Peripheral vestibular damage causes a time constant reduction, which is useful for clinical diagnoses, but a mechanistic explanation for the relationship between vestibular damage and changes in these behavioral dynamics is lacking. It has been hypothesized that Bayesian optimization determines ideal velocity storage dynamics based on statistics of vestibular noise and experienced motion. Specifically, while a longer time constant would make the central estimate of angular head velocity closer to actual head motion, it may also result in the accumulation of neural noise which simultaneously degrades precision. Thus, the brain may balance these two effects by determining the time constant that optimizes behavior. We applied a Bayesian optimal Kalman filter to determine the ideal velocity storage time constant for unilateral damage. Predicted time constants were substantially lower than normal and similar to patients. Building on our past work showing that Bayesian optimization explains age-related changes in velocity storage, we also modeled interactions between age-related hair cell loss and peripheral damage. These results provide a plausible mechanistic explanation for changes in velocity storage after peripheral damage. Results also suggested that even after peripheral damage, noise originating in the periphery or early central processing may remain relevant in neurocomputations. Overall, our findings support the hypothesis that the brain optimizes velocity storage based on the vestibular signal-to-noise ratio.

Measuring PM2.5 Concentrations from a Single Smartphone Photograph

PM2.5 participates in light scattering, leading to degraded outdoor views, which forms the basis for estimating PM2.5 from photographs. This paper devises an algorithm to estimate PM2.5 concentrations by extracting visual cues and atmospheric indices from a single photograph. While air quality measurements in the context of complex urban scenes are particularly challenging, when only a single atmospheric index or cue is given, each one can reinforce others to yield a more robust estimator. Therefore, we selected an appropriate atmospheric index in various outdoor scenes to identify reasonable cue combinations for measuring PM2.5. A PM2.5 dataset (PhotoPM-daytime) was built and used to evaluate performance and validate efficacy of cue combinations. Furthermore, a city-wide experiment was conducted using photographs crawled from the Internet to demonstrate the applicability of the algorithm in large-area PM2.5 monitoring. Results show that smartphones equipped with the developed method could potentially be used as PM2.5 sensors.

Image statistics determine the integration of visual cues to motion-in-depth

Motion-in-depth perception is critical in enabling animals to avoid hazards and respond to potential threats. For humans, important visual cues for motion-in-depth include changing disparity (CD) and changing image size (CS). The interpretation and integration of these cues depends upon multiple scene parameters, such as distance moved, object size and viewing distance, posing a significant computational challenge. We show that motion-in-depth cue integration depends upon sensitivity to the joint probabilities of the scene parameters determining these signals, and on the probability of CD and CS signals co-occurring. Models that took these factors into account predicted human performance in speed-in-depth and cue conflict discrimination tasks, where standard linear integration models could not. These results suggest that cue integration is affected by both the uncertainty of sensory signals and the mapping of those signals to real-world properties. Evidence of a role for such mappings demonstrates the importance of scene and image statistics to the processes underpinning cue integration and the perception of motion-in-depth.

Perceptual scale for transparency: Common fate overrides geometrical and color cues

Objects that pass light through are considered transparent, and we generally expect that the light coming out will match the color of the object. However, when the object is placed on a colored surface, the light coming back to our eyes becomes a composite of surface, illumination, and transparency properties. Despite that, we can often perceive separate overlaid and overlaying layers differing in colors. How neurons separate the information to extract the transparent layer remains unknown, but the physical characteristics of transparent filters generate geometrical and color features in retinal images, which could provide cues for separating layers. We estimated the relative importance of such cues in a perceptual scale for transparency, using stimuli in which X- or T-junctions, different relative motions, and consistent or inconsistent colors cooperated or competed in forced-preference psychophysics experiments. Maximum-likelihood Thurstone scaling revealed that motion increased transparency for X-junctions, but decreased transparency for T-junctions by creating the percept of an opaque patch. However, if the motion of a filter uncovered a dynamically changing but stationary pattern, sharing a common fate with the surround but forming T-junctions, the probability of seeing transparency was almost as high as for moving X-junctions, despite the stimulus being physically improbable. In addition, geometric cues overrode color inconsistency to a great degree. Finally, a linear model of transparency perception as a function of relative motions between filter, overlay, and surround layers, contour continuation, and color consistency, quantified a hierarchy of latent influences on when the filter is seen as a separate transparent layer.

A Generative View of Rationality and Growing Awareness†

In this paper we contrast bounded and ecological rationality with a proposed alternative, generative rationality. Ecological approaches to rationality build on the idea of humans as "intuitive statisticians" while we argue for a more generative conception of humans as "probing organisms." We first highlight how ecological rationality's focus on cues and statistics is problematic for two reasons: (a) the problem of cue salience, and (b) the problem of cue uncertainty. We highlight these problems by revisiting the statistical and cue-based logic that underlies ecological rationality, which originate from the misapplication of concepts in psychophysics (e.g., signal detection, just-noticeable-differences). We then work through the most popular experimental task in the ecological rationality literature-the city size task-to illustrate how psychophysical assumptions have informally been linked to ecological rationality. After highlighting these problems, we contrast ecological rationality with a proposed alternative, generative rationality. Generative rationality builds on biology-in contrast to ecological rationality's focus on statistics. We argue that in uncertain environments cues are rarely given or available for statistical processing. Therefore we focus on the psychogenesis of awareness rather than psychophysics of cues. For any agent or organism, environments "teem" with indefinite cues, meanings and potential objects, the salience or relevance of which is scarcely obvious based on their statistical or physical properties. We focus on organism-specificity and the organism-directed probing that shapes awareness and perception. Cues in teeming environments are noticed when they serve as cues-for-something, requiring what might be called a "cue-to-clue" transformation. In this sense, awareness toward a cue or cues is actively "grown." We thus argue that perception might more productively be seen as the presentation of cues and objects rather than their representation. This generative approach not only applies to relatively mundane organism (including human) interactions with their environments-as well as organism-object relationships and their embodied nature-but also has significant implications for understanding the emergence of novelty in economic settings. We conclude with a discussion of how our arguments link with-but modify-Herbert Simon's popular "scissors" metaphor, as it applies to bounded rationality and its implications for decision making in uncertain, teeming environments.

Neural structure of a sensory decoder for motor control

The transformation of sensory input to motor output is often conceived as a decoder operating on neural representations. We seek a mechanistic understanding of sensory decoding by mimicking neural circuitry in the decoder's design. The results of a simple experiment shape our approach. Changing the size of a target for smooth pursuit eye movements changes the relationship between the variance and mean of the evoked behavior in a way that contradicts the regime of "signal-dependent noise" and defies traditional decoding approaches. A theoretical analysis leads us to propose a circuit for pursuit that includes multiple parallel pathways and multiple sources of variation. Behavioral and neural responses with biomimetic statistics emerge from a biologically-motivated circuit model with noise in the pathway that is dedicated to flexibly adjusting the strength of visual-motor transmission. Our results demonstrate the power of re-imagining decoding as processing through the parallel pathways of neural systems.

Experimentally disambiguating models of sensory cue integration

Sensory cue integration is one of the primary areas in which a normative mathematical framework has been used to define the “optimal” way in which to make decisions based upon ambiguous sensory information and compare these predictions to behavior. The conclusion from such studies is that sensory cues are integrated in a statistically optimal fashion. However, numerous alternative computational frameworks exist by which sensory cues could be integrated, many of which could be described as “optimal” based on different criteria. Existing studies rarely assess the evidence relative to different candidate models, resulting in an inability to conclude that sensory cues are integrated according to the experimenter's preferred framework. The aims of the present paper are to summarize and highlight the implicit assumptions rarely acknowledged in testing models of sensory cue integration, as well as to introduce an unbiased and principled method by which to determine, for a given experimental design, the probability with which a population of observers behaving in accordance with one model of sensory integration can be distinguished from the predictions of a set of alternative models.

[Analysis of Characteristics of Eye Movement While Viewing Movies and Its Application]

In this article, we present the following: a background of visually induced motion sickness (VIMS), the goal of our study, and descriptions of three recent studies conducted by our group on the measurement and analysis of eye movement while viewing movies and the relationship of eye movement with VIMS. First, this study focuses on the relationship between eye movement and motion sickness susceptibility. We investigated the relationship between the motion sickness susceptibility and the frequency of optokinetic nystagmus (OKN) with peripheral viewing. It was revealed that susceptible participants showed a lower OKN frequency under conditions that strongly support the occurrence of OKN than insusceptible participants. Second, this study focuses on the relationship between visual information and postural variation such as visually evoked postural responses (VEPRs). In this study, both eye movement and the center of gravity while viewing a movie were measured. Additionally, we evaluated the difference in the transfer gain of the transfer function (vision as input and equilibrium function as output) due to the type of movie content or way of viewing. The gain for the three-dimensional movie with peripheral viewing exceeded that for the two-dimensional movie with central viewing. Third, this study focuses on eye movement and the application of deep-learning technology. In this study, we classified the eye movement as peripheral or central using a convolutional deep neural network with supervised learning. Then, cross validation was performed to test the classification accuracy. The use of >1-s eye movement data yielded an accuracy of >90%.

Vision-based speedometer regulates human walking

Can we recover self-motion from vision? This basic issue remains unsolved since, while the human visual system is known to estimate the direction of self-motion from optic flow, it remains unclear whether it also estimates the speed. Importantly, the latter requires disentangling self-motion speed and depths of objects in the scene as retinal velocity depends on both. Here we show that our automatic regulator of walking speed based on vision, which estimates and maintains the speed to its preferred range by adjusting stride length, is robust to changes in the depths. The robustness was not explained by temporal-frequency-based speed coding previously suggested to underlie depth-invariant object-motion perception. Meanwhile, it broke down, not only when the interocular distance was virtually manipulated but also when monocular depth cues were deceptive. These observations suggest that our visuomotor system embeds a speedometer that calculates self-motion speed from vision by integrating monocular/binocular depth and motion cues.

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Changes in optic flow speed triggers implicit adjustments of walking speed

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The response is invariant with respect to the depths of objects in the scene

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The invariance is not explained by temporal-frequency-based speed coding

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Both binocular and monocular depth cues contribute to the invariance

Bayesian decision theory and navigation

Spatial navigation is a complex cognitive activity that depends on perception, action, memory, reasoning, and problem-solving. Effective navigation depends on the ability to combine information from multiple spatial cues to estimate one's position and the locations of goals. Spatial cues include landmarks, and other visible features of the environment, and body-based cues generated by self-motion (vestibular, proprioceptive, and efferent information). A number of projects have investigated the extent to which visual cues and body-based cues are combined optimally according to statistical principles. Possible limitations of these investigations are that they have not accounted for navigators' prior experiences with or assumptions about the task environment and have not tested complete decision models. We examine cue combination in spatial navigation from a Bayesian perspective and present the fundamental principles of Bayesian decision theory. We show that a complete Bayesian decision model with an explicit loss function can explain a discrepancy between optimal cue weights and empirical cues weights observed by (Chen et al. Cognitive Psychology, 95, 105-144, 2017) and that the use of informative priors to represent cue bias can explain the incongruity between heading variability and heading direction observed by (Zhao and Warren 2015b, Psychological Science, 26[6], 915-924). We also discuss (Petzschner and Glasauer's , Journal of Neuroscience, 31(47), 17220-17229, 2011) use of priors to explain biases in estimates of linear displacements during visual path integration. We conclude that Bayesian decision theory offers a productive theoretical framework for investigating human spatial navigation and believe that it will lead to a deeper understanding of navigational behaviors.