A comparison of methods of assessing cue combination during navigation

Integration of auditory and visual cues in spatial navigation under normal and impaired viewing conditions

Auditory landmarks can contribute to spatial updating during navigation with vision. Whereas large inter-individual differences have been identified in how navigators combine auditory and visual landmarks, it is still unclear under what circumstances audition is used. Further, whether or not individuals optimally combine auditory cues with visual cues to decrease the amount of perceptual uncertainty, or variability, has not been well-documented. Here, we test audiovisual integration during spatial updating in a virtual navigation task. In Experiment 1, 24 individuals with normal sensory acuity completed a triangular homing task with either visual landmarks, auditory landmarks, or both. In addition, participants experienced a fourth condition with a covert spatial conflict where auditory landmarks were rotated relative to visual landmarks. Participants generally relied more on visual landmarks than auditory landmarks and were no more accurate with multisensory cues than with vision alone. In Experiment 2, a new group of 24 individuals completed the same task, but with simulated low vision in the form of a blur filter to increase visual uncertainty. Again, participants relied more on visual landmarks than auditory ones and no multisensory benefit occurred. Participants navigating with blur did not rely more on their hearing compared with the group that navigated with normal vision. These results support previous research showing that one sensory modality at a time may be sufficient for spatial updating, even under impaired viewing conditions. Future research could investigate task- and participant-specific factors that lead to different strategies of multisensory cue combination with auditory and visual cues.

Super-optimality and relative distance coding in location memory

The prevailing model of landmark integration in location memory is Maximum Likelihood Estimation, which assumes that each landmark implies a target location distribution that is narrower for more reliable landmarks. This model assumes weighted linear combination of landmarks and predicts that, given optimal integration, the reliability with multiple landmarks is the sum of the reliabilities with the individual landmarks. Super-optimality is reliability with multiple landmarks exceeding optimal reliability given the reliability with each landmark alone; this is shown when performance exceeds predicted optimal performance, found by aggregating reliability values with single landmarks. Past studies claiming super-optimality have provided arguably impure measures of performance with single landmarks given that multiple landmarks were presented at study in conditions with a single landmark at test, disrupting encoding specificity and thereby leading to underestimation in predicted optimal performance. This study, unlike those prior studies, only presented a single landmark at study and the same landmark at test in single landmark trials, showing super-optimality conclusively. Given that super-optimal information integration occurs, emergent information, that is, information only available with multiple landmarks, must be used. With the target and landmarks all in a line, as throughout this study, relative distance is the only emergent information available. Use of relative distance was confirmed here by finding that, when both landmarks are left of the target at study, the target is remembered further right of its true location the further left the left landmark is moved from study to test.

Effects of older age on visual and self-motion sensory cue integration in navigation

Older adults demonstrate impairments in navigation that cannot be explained by general cognitive and motor declines. Previous work has shown that older adults may combine sensory cues during navigation differently than younger adults, though this work has largely been done in dark environments where sensory integration may differ from full-cue environments. Here, we test whether aging adults optimally combine cues from two sensory systems critical for navigation: vision (landmarks) and body-based self-motion cues. Participants completed a homing (triangle completion) task using immersive virtual reality to offer the ability to navigate in a well-lit environment including visibility of the ground plane. An optimal model, based on principles of maximum-likelihood estimation, predicts that precision in homing should increase with multisensory information in a manner consistent with each individual sensory cue's perceived reliability (measured by variability). We found that well-aging adults (with normal or corrected-to-normal sensory acuity and active lifestyles) were more variable and less accurate than younger adults during navigation. Both older and younger adults relied more on their visual systems than a maximum likelihood estimation model would suggest. Overall, younger adults' visual weighting matched the model's predictions whereas older adults showed sub-optimal sensory weighting. In addition, high inter-individual differences were seen in both younger and older adults. These results suggest that older adults do not optimally weight each sensory system when combined during navigation, and that older adults may benefit from interventions that help them recalibrate the combination of visual and self-motion cues for navigation.

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.

Path integration, rather than being suppressed, is used to update spatial views in familiar environments with constantly available landmarks

This project tested three hypotheses conceptualizing the interaction between path integration based on self-motion and piloting based on landmarks in a familiar environment with persistent landmarks. The first hypothesis posits that path integration functions automatically, as in environments lacking persistent landmarks (environment-independent hypothesis). The second hypothesis suggests that persistent landmarks suppress path integration (suppression hypothesis). The third hypothesis proposes that path integration updates the spatial views of the environment (updating-spatial-views hypothesis). Participants learned a specific object's location. Subsequently, they undertook an outbound path originating from the object and then indicated the object's location (homing). In Experiments 1&1b, there were landmarks throughout the first 9 trials. On some later trials, the landmarks were presented during the outbound path but unexpectedly removed during homing (catch trials). On the last trials, there were no landmarks throughout (baseline trials). Experiments 2-3 were similar but added two identical objects (the original one and a rotated distractor) during homing on the catch and baseline trials. Experiment 4 replaced two identical objects with two groups of landmarks. The results showed that in Experiments 1&1b, homing angular error on the first catch trial was significantly larger than the matched baseline trial, undermining the environment-independent hypothesis. Conversely, in Experiment 2-4, the proportion of participants who recognized the original object or landmarks was similar between the first catch and the matched baseline trial, favoring the updating-spatial-views hypothesis over the suppression hypothesis. Therefore, while mismatches between updated spatial views and actual views of unexpected removal of landmarks impair homing performance, the updated spatial views help eliminate ambiguous targets or landmarks within the familiar environment.

Statistically Optimal Cue Integration During Human Spatial Navigation

In 2007, Cheng and colleagues published their influential review wherein they analyzed the literature on spatial cue interaction during navigation through a Bayesian lens, and concluded that models of optimal cue integration often applied in psychophysical studies could explain cue interaction during navigation. Since then, numerous empirical investigations have been conducted to assess the degree to which human navigators are optimal when integrating multiple spatial cues during a variety of navigation-related tasks. In the current review, we discuss the literature on human cue integration during navigation that has been published since Cheng et al.'s original review. Evidence from most studies demonstrate optimal navigation behavior when humans are presented with multiple spatial cues. However, applications of optimal cue integration models vary in their underlying assumptions (e.g., uninformative priors and decision rules). Furthermore, cue integration behavior depends in part on the nature of the cues being integrated and the navigational task (e.g., homing versus non-home goal localization). We discuss the implications of these models and suggest directions for future research.

Remote research on locomotion interfaces for virtual reality: Replication of a lab-based study on teleporting interfaces

The wide availability of consumer-oriented virtual reality (VR) equipment has enabled researchers to recruit existing VR owners to participate remotely using their own equipment. Yet, there are many differences between lab environments and home environments, as well as differences between participant samples recruited for lab studies and remote studies. This paper replicates a lab-based experiment on VR locomotion interfaces using a remote sample. Participants completed a triangle-completion task (travel two path legs, then point to the path origin) using their own VR equipment in a remote, unsupervised setting. Locomotion was accomplished using two versions of the teleporting interface varying in availability of rotational self-motion cues. The size of the traveled path and the size of the surrounding virtual environment were also manipulated. Results from remote participants largely mirrored lab results, with overall better performance when rotational self-motion cues were available. Some differences also occurred, including a tendency for remote participants to rely less on nearby landmarks, perhaps due to increased competence with using the teleporting interface to update self-location. This replication study provides insight for VR researchers on aspects of lab studies that may or may not replicate remotely.

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.

Integration of visual landmark cues in spatial memory

Over the past two decades, much research has been conducted to investigate whether humans are optimal when integrating sensory cues during spatial memory and navigational tasks. Although this work has consistently demonstrated optimal integration of visual cues (e.g., landmarks) with body-based cues (e.g., path integration) during human navigation, little work has investigated how cues of the same sensory type are integrated in spatial memory. A few recent studies have reported mixed results, with some showing very little benefit to having access to more than one landmark, and others showing that multiple landmarks can be optimally integrated in spatial memory. In the current study, we employed a combination of immersive and non-immersive virtual reality spatial memory tasks to test adult humans' ability to integrate multiple landmark cues across six experiments. Our results showed that optimal integration of multiple landmark cues depends on the difficulty of the task, and that the presence of multiple landmarks can elicit an additional latent cue when estimating locations from a ground-level perspective, but not an aerial perspective.

Cue combination in goal-oriented navigation

This study examined cue combination of self-motion and landmark cues in goal-localisation. In an immersive virtual environment, before walking a two-leg path, participants learned the locations of three goal objects (one at the path origin, that is, home) and landmarks. After walking the path without seeing landmarks or goals, participants indicated the locations of the home and non-home goals in four conditions: (1) path integration only, (2) landmarks only, (3) both path integration and the landmarks, and (4) path integration and rotated landmarks. The ratio of the length between the testing position (P) and the turning point (T) over the length between the T and the three goals (G) (i.e., PT/TG) was manipulated. The results showed the cue combination consistently for participants’ heading estimates but not for goal-localisation. In Experiments 1 and 2 (using distal landmarks), the cue combination for goal estimates appeared in a small length ratio (PT/TG = 0.5) but disappeared in a large length ratio (PT/TG = 2). In Experiments 3 and 4 (using proximal landmarks), while the cue combination disappeared for the home with a medium length ratio (PT/TG = 1), it appeared for the non-home goal with a large length ratio (PT/TG = 2) and only disappeared with a very large length ratio (PT/TG = 3). These findings are explained by a model stipulating that cue combination occurs in self-localisation (e.g., heading estimates), which leads to one estimate of the goal location; proximal landmarks produce another goal location estimate; these two goal estimates are then combined, which may only occur for non-home goals.