Parallel updating and weighting of multiple spatial maps for visual stability during whole body motion

Psychophysical evidence for the involvement of head/body-centered reference frames in egocentric visuospatial memory: A whole-body roll tilt paradigm

Accurate memory regarding the location of an object with respect to one's own body, termed egocentric visuospatial memory, is essential for action directed toward the object. Although researchers have suggested that the brain stores information related to egocentric visuospatial memory not only in the eye-centered reference frame but also in the other egocentric (i.e., head- or body-centered or both) reference frames, experimental evidence is scarce. Here, we tested this possibility by exploiting the perceptual distortion of head/body-centered coordinates via whole-body tilt relative to gravity. We hypothesized that if the head/body-centered reference frames are involved in storing the egocentric representation of a target in memory, then reproduction would be affected by this perceptual distortion. In two experiments, we asked participants to reproduce the remembered location of a visual target relative to their head/body. Using intervening whole-body roll rotations, we manipulated the initial (target presentation) and final (reproduction of the remembered location) body orientations in space and evaluated the effect on the reproduced location. Our results showed significant biases of the reproduced target location and perceived head/body longitudinal axis in the direction of the intervening body rotation. Importantly, the amount of error was correlated across participants. These results provide experimental evidence for the neural encoding and storage of information related to egocentric visuospatial memory in the head/body-centered reference frames.

Predictive steering: integration of artificial motor signals in self-motion estimation

The brain's computations for active and passive self-motion estimation can be unified with a single model that optimally combines vestibular and visual signals with sensory predictions based on efference copies. It is unknown whether this theoretical framework also applies to the integration of artificial motor signals, such as those that occur when driving a car, or whether self-motion estimation in this situation relies on sole feedback control. Here, we examined if training humans to control a self-motion platform leads to the construction of an accurate internal model of the mapping between the steering movement and the vestibular reafference. Participants (n = 15) sat on a linear motion platform and actively controlled the platform's velocity using a steering wheel to translate their body to a memorized visual target (motion condition). We compared their steering behavior to that of participants (n = 15) who remained stationary and instead aligned a nonvisible line with the target (stationary condition). To probe learning, the gain between the steering wheel angle and the platform or line velocity changed abruptly twice during the experiment. These gain changes were virtually undetectable in the displacement error in the motion condition, whereas clear deviations were observed in the stationary condition, showing that participants in the motion condition made within-trial changes to their steering behavior. We conclude that vestibular feedback allows not only the online control of steering but also a rapid adaptation to the gain changes to update the brain's internal model of the mapping between the steering movement and the vestibular reafference.NEW & NOTEWORTHY Perception of self-motion is known to depend on the integration of sensory signals and, when the motion is self-generated, the predicted sensory reafference based on motor efference copies. Here we show, using a closed-loop steering experiment with a direct coupling between the steering movement and the vestibular self-motion feedback, that humans are also able to integrate artificial motor signals, like the motor signals that occur when driving a car.

Sensory Evidence Accumulation Using Optic Flow in a Naturalistic Navigation Task

Sensory evidence accumulation is considered a hallmark of decision-making in noisy environments. Integration of sensory inputs has been traditionally studied using passive stimuli, segregating perception from action. Lessons learned from this approach, however, may not generalize to ethological behaviors like navigation, where there is an active interplay between perception and action. We designed a sensory-based sequential decision task in virtual reality in which humans and monkeys navigated to a memorized location by integrating optic flow generated by their own joystick movements. A major challenge in such closed-loop tasks is that subjects' actions will determine future sensory input, causing ambiguity about whether they rely on sensory input rather than expectations based solely on a learned model of the dynamics. To test whether subjects integrated optic flow over time, we used three independent experimental manipulations, unpredictable optic flow perturbations, which pushed subjects off their trajectory; gain manipulation of the joystick controller, which changed the consequences of actions; and manipulation of the optic flow density, which changed the information borne by sensory evidence. Our results suggest that both macaques (male) and humans (female/male) relied heavily on optic flow, thereby demonstrating a critical role for sensory evidence accumulation during naturalistic action-perception closed-loop tasks.SIGNIFICANCE STATEMENT The temporal integration of evidence is a fundamental component of mammalian intelligence. Yet, it has traditionally been studied using experimental paradigms that fail to capture the closed-loop interaction between actions and sensations inherent in real-world continuous behaviors. These conventional paradigms use binary decision tasks and passive stimuli with statistics that remain stationary over time. Instead, we developed a naturalistic visuomotor visual navigation paradigm that mimics the causal structure of real-world sensorimotor interactions and probed the extent to which participants integrate sensory evidence by adding task manipulations that reveal complementary aspects of the computation.

Influence of sensory modality and control dynamics on human path integration

Path integration is a sensorimotor computation that can be used to infer latent dynamical states by integrating self-motion cues. We studied the influence of sensory observation (visual/vestibular) and latent control dynamics (velocity/acceleration) on human path integration using a novel motion-cueing algorithm. Sensory modality and control dynamics were both varied randomly across trials, as participants controlled a joystick to steer to a memorized target location in virtual reality. Visual and vestibular steering cues allowed comparable accuracies only when participants controlled their acceleration, suggesting that vestibular signals, on their own, fail to support accurate path integration in the absence of sustained acceleration. Nevertheless, performance in all conditions reflected a failure to fully adapt to changes in the underlying control dynamics, a result that was well explained by a bias in the dynamics estimation. This work demonstrates how an incorrect internal model of control dynamics affects navigation in volatile environments in spite of continuous sensory feedback.

External location of touch is constructed post-hoc based on limb choice

When humans indicate on which hand a tactile stimulus occurred, they often err when their hands are crossed. This finding seemingly supports the view that the automatically determined touch location in external space affects limb assignment: the crossed right hand is localized in left space, and this conflict presumably provokes hand assignment errors. Here, participants judged on which hand the first of two stimuli, presented during a bimanual movement, had occurred, and then indicated its external location by a reach-to-point movement. When participants incorrectly chose the hand stimulated second, they pointed to where that hand had been at the correct, first time point, though no stimulus had occurred at that location. This behavior suggests that stimulus localization depended on hand assignment, not vice versa. It is, thus, incompatible with the notion of automatic computation of external stimulus location upon occurrence. Instead, humans construct external touch location post-hoc and on demand.

Learning to use vestibular sense for spatial updating is context dependent

As we move, perceptual stability is crucial to successfully interact with our environment. Notably, the brain must update the locations of objects in space using extra-retinal signals. The vestibular system is a strong candidate as a source of information for spatial updating as it senses head motion. The ability to use this cue is not innate but must be learned. To date, the mechanisms of vestibular spatial updating generalization are unknown or at least controversial. In this paper we examine generalization patterns within and between different conditions of vestibular spatial updating. Participants were asked to update the position of a remembered target following (offline) or during (online) passive body rotation. After being trained on a single spatial target position within a given task, we tested generalization of performance for different spatial targets and an unpracticed spatial updating task. The results demonstrated different patterns of generalization across the workspace depending on the task. Further, no transfer was observed from the practiced to the unpracticed task. We found that the type of mechanism involved during learning governs generalization. These findings provide new knowledge about how the brain uses vestibular information to preserve its spatial updating ability.

Causal inference for spatial constancy across whole body motion

The brain uses self-motion information to internally update egocentric representations of locations of remembered world-fixed visual objects. If a discrepancy is observed between this internal update and reafferent visual feedback, this could be either due to an inaccurate update or because the object has moved during the motion. To optimally infer the object's location it is therefore critical for the brain to estimate the probabilities of these two causal structures and accordingly integrate and/or segregate the internal and sensory estimates. To test this hypothesis, we designed a spatial updating task involving passive whole body translation. Participants, seated on a vestibular sled, had to remember the world-fixed position of a visual target. Immediately after the translation, the reafferent visual feedback was provided by flashing a second target around the estimated "updated" target location, and participants had to report the initial target location. We found that the participants' responses were systematically biased toward the position of the second target position for relatively small but not for large differences between the "updated" and the second target location. This pattern was better captured by a Bayesian causal inference model than by alternative models that would always either integrate or segregate the internally updated target location and the visual feedback. Our results suggest that the brain implicitly represents the posterior probability that the internally updated estimate and the visual feedback come from a common cause and uses this probability to weigh the two sources of information in mediating spatial constancy across whole body motion. NEW & NOTEWORTHY When we move, egocentric representations of object locations require internal updating to keep them in register with their true world-fixed locations. How does this mechanism interact with reafferent visual input, given that objects typically do not disappear from view? Here we show that the brain implicitly represents the probability that both types of information derive from the same object and uses this probability to weigh their contribution for achieving spatial constancy across whole body motion.

Weighted Visual and Vestibular Cues for Spatial Updating During Passive Self-Motion

When walking or driving, it is of the utmost importance to continuously track the spatial relationship between objects in the environment and the moving body in order to prevent collisions. Although this process of spatial updating occurs naturally, it involves the processing of a myriad of noisy and ambiguous sensory signals. Here, using a psychometric approach, we investigated the integration of visual optic flow and vestibular cues in spatially updating a remembered target position during a linear displacement of the body. Participants were seated on a linear sled, immersed in a stereoscopic virtual reality environment. They had to remember the position of a target, briefly presented before a sideward translation of the body involving supra-threshold vestibular cues and whole-field optic flow that provided slightly discrepant motion information. After the motion, using a forced response participants indicated whether the location of a brief visual probe was left or right of the remembered target position. Our results show that in a spatial updating task involving passive linear self-motion humans integrate optic flow and vestibular self-displacement information according to a weighted-averaging process with, across subjects, on average about four times as much weight assigned to the visual compared to the vestibular contribution (i.e., 79% visual weight). We discuss our findings with respect to previous literature on the effect of optic flow on spatial updating performance.

A mass-density model can account for the size-weight illusion

When judging the heaviness of two objects with equal mass, people perceive the smaller and denser of the two as being heavier. Despite the large number of theories, covering bottom-up and top-down approaches, none of them can fully account for all aspects of this size-weight illusion and thus for human heaviness perception. Here we propose a new maximum-likelihood estimation model which describes the illusion as the weighted average of two heaviness estimates with correlated noise: One estimate derived from the object's mass, and the other from the object's density, with estimates' weights based on their relative reliabilities. While information about mass can directly be perceived, information about density will in some cases first have to be derived from mass and volume. However, according to our model at the crucial perceptual level, heaviness judgments will be biased by the objects' density, not by its size. In two magnitude estimation experiments, we tested model predictions for the visual and the haptic size-weight illusion. Participants lifted objects which varied in mass and density. We additionally varied the reliability of the density estimate by varying the quality of either visual (Experiment 1) or haptic (Experiment 2) volume information. As predicted, with increasing quality of volume information, heaviness judgments were increasingly biased towards the object's density: Objects of the same density were perceived as more similar and big objects were perceived as increasingly lighter than small (denser) objects of the same mass. This perceived difference increased with an increasing difference in density. In an additional two-alternative forced choice heaviness experiment, we replicated that the illusion strength increased with the quality of volume information (Experiment 3). Overall, the results highly corroborate our model, which seems promising as a starting point for a unifying framework for the size-weight illusion and human heaviness perception.

Multiple Coordinate Systems and Motor Strategies for Reaching Movements When Eye and Hand Are Dissociated in Depth and Direction

Reaching behavior represents one of the basic aspects of human cognitive abilities important for the interaction with the environment. Reaching movements towards visual objects are controlled by mechanisms based on coordinate systems that transform the spatial information of target location into appropriate motor response. Although recent works have extensively studied the encoding of target position for reaching in three-dimensional space at behavioral level, the combined analysis of reach errors and movement variability has so far been investigated by few studies. Here we did so by testing 12 healthy participants in an experiment where reaching targets were presented at different depths and directions in foveal and peripheral viewing conditions. Each participant executed a memory-guided task in which he/she had to reach the memorized position of the target. A combination of vector and gradient analysis, novel for behavioral data, was applied to analyze patterns of reach errors for different combinations of eye/target positions. The results showed reach error patterns based on both eye- and space-centered coordinate systems: in depth more biased towards a space-centered representation and in direction mixed between space- and eye-centered representation. We calculated movement variability to describe different trajectory strategies adopted by participants while reaching to the different eye/target configurations tested. In direction, the distribution of variability between configurations that shared the same eye/target relative configuration was different, whereas in configurations that shared the same spatial position of targets, it was similar. In depth, the variability showed more similar distributions in both pairs of eye/target configurations tested. These results suggest that reaching movements executed in geometries that require hand and eye dissociations in direction and depth showed multiple coordinate systems and different trajectory strategies according to eye/target configurations and the two dimensions of space.

Mixed body- and gaze-centered coding of proprioceptive reach targets after effector movement

Previous studies demonstrated that an effector movement intervening between encoding and reaching to a proprioceptive target determines the underlying reference frame: proprioceptive reach targets are represented in a gaze-independent reference frame if no movement occurs but are represented with respect to gaze after an effector movement (Mueller and Fiehler, 2014a). The present experiment explores whether an effector movement leads to a switch from a gaze-independent, body-centered reference frame to a gaze-dependent reference frame or whether a gaze-dependent reference frame is employed in addition to a gaze-independent, body-centered reference frame. Human participants were asked to reach in complete darkness to an unseen finger (proprioceptive target) of their left target hand indicated by a touch. They completed 2 conditions in which the target hand remained either stationary at the target location (stationary condition) or was actively moved to the target location, received a touch and was moved back before reaching to the target (moved condition). We dissociated the location of the movement vector relative to the body midline and to the gaze direction. Using correlation and regression analyses, we estimated the contribution of each reference frame based on horizontal reach errors in the stationary and moved conditions. Gaze-centered coding was only found in the moved condition, replicating our previous results. Body-centered coding dominated in the stationary condition while body- and gaze-centered coding contributed equally strong in the moved condition. Our results indicate a shift from body-centered to combined body- and gaze-centered coding due to an effector movement before reaching towards proprioceptive targets.