Spatial updating: how the brain keeps track of changing object locations during observer motion

2008 ◽  
Vol 11 (10) ◽  
pp. 1223-1230 ◽  
Author(s):  
Thomas Wolbers ◽  
Mary Hegarty ◽  
Christian Büchel ◽  
Jack M Loomis
Keyword(s):  
Spatial Updating ◽  
Object Locations ◽  
Observer Motion ◽  
The Brain

Perceived Continuity of Occluded Visual Objects

1995 ◽  
Vol 6 (3) ◽  
pp. 182-186 ◽  
Author(s):  
Steven Yantis
Keyword(s):  
Retinal Image ◽  
Three Dimensional ◽  
Visual Object ◽  
Neural Signals ◽  
Visual Objects ◽  
Surface Layout ◽  
Visual Tasks ◽  
Motion Display ◽  
Observer Motion ◽  
The Brain

The human visual system does not rigidly preserve the properties of the retinal image as neural signals are transmitted to higher areas of the brain Instead, it generates a representation that captures stable surface properties despite a retinal image that is often fragmented in space and time because of occlusion caused by object and observer motion The recovery of this coherent representation depends at least in part on input from an abstract representation of three-dimensional (3-D) surface layout In the two experiments reported, a stereoscopic apparent motion display was used to investigate the perceived continuity of a briefly interrupted visual object When a surface appeared in front of the object's location during the interruption, the object was more likely to be perceived as persisting through the interruption (behind an occluder) than when the surface appeared behind the object's location under otherwise identical stimulus conditions The results reveal the influence of 3-D surface-based representations even in very simple visual tasks

scholarly journals Spatial constancy mechanisms in motor control

2011 ◽  
Vol 366 (1564) ◽  
pp. 476-491 ◽  
Author(s):  
W. Pieter Medendorp
Keyword(s):  
Motor Control ◽  
Eye Movements ◽  
Three Dimensional ◽  
Spatial Updating ◽  
Feedback Processing ◽  
Feed Forward ◽  
Motor Information ◽  
Induced Motion ◽  
Forward Process ◽  
The Brain

The success of the human species in interacting with the environment depends on the ability to maintain spatial stability despite the continuous changes in sensory and motor inputs owing to movements of eyes, head and body. In this paper, I will review recent advances in the understanding of how the brain deals with the dynamic flow of sensory and motor information in order to maintain spatial constancy of movement goals. The first part summarizes studies in the saccadic system, showing that spatial constancy is governed by a dynamic feed-forward process, by gaze-centred remapping of target representations in anticipation of and across eye movements. The subsequent sections relate to other oculomotor behaviour, such as eye–head gaze shifts, smooth pursuit and vergence eye movements, and their implications for feed-forward mechanisms for spatial constancy. Work that studied the geometric complexities in spatial constancy and saccadic guidance across head and body movements, distinguishing between self-generated and passively induced motion, indicates that both feed-forward and sensory feedback processing play a role in spatial updating of movement goals. The paper ends with a discussion of the behavioural mechanisms of spatial constancy for arm motor control and their physiological implications for the brain. Taken together, the emerging picture is that the brain computes an evolving representation of three-dimensional action space, whose internal metric is updated in a nonlinear way, by optimally integrating noisy and ambiguous afferent and efferent signals.

scholarly journals Causal inference for spatial constancy across whole-body motion

2018 ◽  
Author(s):  
Florian Perdreau ◽  
James Cooke ◽  
Mathieu Koppen ◽  
W. Pieter Medendorp
Keyword(s):  
Causal Inference ◽  
Sensory Feedback ◽  
Target Location ◽  
Target Position ◽  
Body Motion ◽  
Whole Body ◽  
Spatial Updating ◽  
Sources Of Information ◽  
The World ◽  
The Brain

AbstractThe brain can estimate the amplitude and direction of self-motion by integrating multiple sources of sensory information, and use this estimate to update object positions in order to provide us with a stable representation of the world. A strategy to improve the precision of the object position estimate would be to integrate this internal estimate and the sensory feedback about the object position based on their reliabilities. Integrating these cues, however, would only be optimal under the assumption that the object has not moved in the world during the intervening body displacement. Therefore, the brain would have to infer whether the internal estimate and the feedback relate to a same external position (stable object), and integrate and/or segregate these cues based on this inference – a process that can be modeled as Bayesian Causal inference. To test this hypothesis, we designed a spatial updating task across passive whole body translation in complete darkness, in which participants (n=11), seated on a vestibular sled, had to remember the world-fixed position of a visual target. Immediately after the translation, a second target (feedback) was briefly flashed 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 position and the visual feedback. Our results suggest that the brain implicitly represents the posterior probability that the internally updated estimate and the sensory feedback come from a common cause, and use this probability to weigh the two sources of information in mediating spatial constancy across whole-body motion.Author SummaryA change of an object’s position on our retina can be caused by a change of the object’s location in the world or by a movement of the eye and body. Here, we examine how the brain solves this problem for spatial updating by assessing the probability that the internally-updated location during body motion and observed retinal feedback after the motion stems from the same object location in the world. Guided by Bayesian causal inference model, we demonstrate that participants’ errrors in spatial updating depend nonlinearly on the spatial discrepancy between internally-updated and reafferent visual feedback about the object’s location in the world. We propose that the brain implicitly represents the probability that the internally updated estimate and the sensory feedback come from a common cause, and use this probability to weigh the two sources of information in mediating spatial constancy across whole-body motion.

scholarly journals Causal inference for spatial constancy across whole body motion

2019 ◽  
Vol 121 (1) ◽  
pp. 269-284 ◽  
Author(s):  
Florian Perdreau ◽  
James R. H. Cooke ◽  
Mathieu Koppen ◽  
W. Pieter Medendorp
Keyword(s):  
Causal Inference ◽  
Visual Feedback ◽  
Target Location ◽  
Target Position ◽  
Body Motion ◽  
Whole Body ◽  
Spatial Updating ◽  
Sources Of Information ◽  
Types Of Information ◽  
The Brain

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.

Modeling Mental Navigation in Scenes with Multiple Objects

2004 ◽  
Vol 16 (9) ◽  
pp. 1851-1872 ◽  
Author(s):  
Patrick Byrne ◽  
Suzanna Becker
Keyword(s):  
Working Memory ◽  
Neural Circuit ◽  
Spatial Information ◽  
Spatial Working Memory ◽  
Spatial Updating ◽  
Multiple Objects ◽  
Object Locations ◽  
Wide Range ◽  
Memory Representations ◽  
Experimental Findings

Various lines of evidence indicate that animals process spatial information regarding object locations differently from spatial information regarding environmental boundaries or landmarks. Following Wang and Spelke's (2002) observation that spatial updating of egocentric representations appears to lie at the heart of many navigational tasks in many species, including humans, we postulate a neural circuit that can support this computation in parietal cortex, assuming that egocentric representations of multiple objects can be maintained in prefrontal cortex in spatial working memory (not simulated here). Our method is a generalization of an earlier model by Droulez and Berthoz (1991), with extensions to support observer rotation. We can thereby simulate perspective transformation of working memory representations of object coordinates based on an egomotion signal presumed to be generated via mental navigation. This biologically plausible transformation would allow a subject to recall the locations of previously viewed objects from novel viewpoints reached via imagined, discontinuous, or disoriented displacement. Finally, we discuss how this model can account for a wide range of experimental findings regarding memory for object locations, and we present several predictions made by the model.

Encoding, learning, and spatial updating of multiple object locations specified by 3-D sound, spatial language, and vision

2002 ◽  
Vol 149 (1) ◽  
pp. 48-61 ◽  
Author(s):  
Roberta L. Klatzky ◽  
Yvonne Lippa ◽  
Jack M. Loomis ◽  
Reginald G. Golledge
Keyword(s):  
Spatial Language ◽  
Spatial Updating ◽  
Multiple Object ◽  
Object Locations ◽  
Language And Vision

scholarly journals The brain-derived neurotrophic factor Val66Met polymorphism affects encoding of object locations during active navigation

2016 ◽  
Vol 45 (12) ◽  
pp. 1501-1511 ◽  
Author(s):  
Joost Wegman ◽  
Anna Tyborowska ◽  
Martine Hoogman ◽  
Alejandro Arias Vásquez ◽  
Gabriele Janzen
Keyword(s):  
Neurotrophic Factor ◽  
Brain Derived Neurotrophic Factor ◽  
Val66met Polymorphism ◽  
Object Locations ◽  
The Brain

scholarly journals Gaze-Centered Updating of Remembered Visual Space During Active Whole-Body Translations

2007 ◽  
Vol 97 (2) ◽  
pp. 1209-1220 ◽  
Author(s):  
Stan Van Pelt ◽  
W. Pieter Medendorp
Keyword(s):  
Motion Parallax ◽  
Translational Motion ◽  
Visual Space ◽  
Brain Structures ◽  
Whole Body ◽  
Spatial Updating ◽  
Hand Position ◽  
Lateral Direction ◽  
Direction Information ◽  
The Brain

Various cortical and sub-cortical brain structures update the gaze-centered coordinates of remembered stimuli to maintain an accurate representation of visual space across eyes rotations and to produce suitable motor plans. A major challenge for the computations by these structures is updating across eye translations. When the eyes translate, objects in front of and behind the eyes’ fixation point shift in opposite directions on the retina due to motion parallax. It is not known if the brain uses gaze coordinates to compute parallax in the translational updating of remembered space or if it uses gaze-independent coordinates to maintain spatial constancy across translational motion. We tested this by having subjects view targets, flashed in darkness in front of or behind fixation, then translate their body sideways, and subsequently reach to the memorized target. Reach responses showed parallax-sensitive updating errors: errors increased with depth from fixation and reversed in lateral direction for targets presented at opposite depths from fixation. In a series of control experiments, we ruled out possible biasing factors such as the presence of a fixation light during the translation, the eyes accompanying the hand to the target, and the presence of visual feedback about hand position. Quantitative geometrical analysis confirmed that updating errors were better described by using gaze-centered than gaze-independent coordinates. We conclude that spatial updating for translational motion operates in gaze-centered coordinates. Neural network simulations are presented suggesting that the brain relies on ego-velocity signals and stereoscopic depth and direction information in spatial updating during self-motion.

scholarly journals Spatial constancy and the brain: insights from neural networks

2007 ◽  
Vol 362 (1479) ◽  
pp. 375-382 ◽  
Author(s):  
Robert L White ◽  
Lawrence H Snyder
Keyword(s):  
Neural Networks ◽  
Spatial Information ◽  
Internal Representation ◽  
Visual Space ◽  
Spatial Location ◽  
Striking Similarity ◽  
Spatial Updating ◽  
Gaze Shift ◽  
Lateral Intraparietal Area ◽  
The Brain

To form an accurate internal representation of visual space, the brain must accurately account for movements of the eyes, head or body. Updating of internal representations in response to these movements is especially important when remembering spatial information, such as the location of an object, since the brain must rely on non-visual extra-retinal signals to compensate for self-generated movements. We investigated the computations underlying spatial updating by constructing a recurrent neural network model to store and update a spatial location based on a gaze shift signal, and to do so flexibly based on a contextual cue. We observed a striking similarity between the patterns of behaviour produced by the model and monkeys trained to perform the same task, as well as between the hidden units of the model and neurons in the lateral intraparietal area (LIP). In this report, we describe the similarities between the model and single unit physiology to illustrate the usefulness of neural networks as a tool for understanding specific computations performed by the brain.

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