Dataset Information

A model of how depth facilitates scene-relative object motion perception.

ABSTRACT: Many everyday interactions with moving objects benefit from an accurate perception of their movement. Self-motion, however, complicates object motion perception because it generates a global pattern of motion on the observer's retina and radically influences an object's retinal motion. There is strong evidence that the brain compensates by suppressing the retinal motion due to self-motion, however, this requires estimates of depth relative to the object-otherwise the appropriate self-motion component to remove cannot be determined. The underlying neural mechanisms are unknown, but neurons in brain areas MT and MST may contribute given their sensitivity to motion parallax and depth through joint direction, speed, and disparity tuning. We developed a neural model to investigate whether cells in areas MT and MST with well-established neurophysiological properties can account for human object motion judgments during self-motion. We tested the model by comparing simulated object motion signals to human object motion judgments in environments with monocular, binocular, and ambiguous depth. Our simulations show how precise depth information, such as that from binocular disparity, may improve estimates of the retinal motion pattern due the self-motion through increased selectivity among units that respond to the global self-motion pattern. The enhanced self-motion estimates emerged from recurrent feedback connections in MST and allowed the model to better suppress the appropriate direction, speed, and disparity signals from the object's retinal motion, improving the accuracy of the object's movement direction represented by motion signals.

SUBMITTER: Layton OW

PROVIDER: S-EPMC6879150 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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A model of how depth facilitates scene-relative object motion perception.

Layton Oliver W OW Niehorster D C DC

PLoS computational biology 20191114 11

Many everyday interactions with moving objects benefit from an accurate perception of their movement. Self-motion, however, complicates object motion perception because it generates a global pattern of motion on the observer's retina and radically influences an object's retinal motion. There is strong evidence that the brain compensates by suppressing the retinal motion due to self-motion, however, this requires estimates of depth relative to the object-otherwise the appropriate self-motion comp ...[more]

PMID: 31725723

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Project description:Flying insects, such as flies or bees, rely on consistent information regarding the depth structure of the environment when performing their flight maneuvers in cluttered natural environments. These behaviors include avoiding collisions, approaching targets or spatial navigation. Insects are thought to obtain depth information visually from the retinal image displacements ("optic flow") during translational ego-motion. Optic flow in the insect visual system is processed by a mechanism that can be modeled by correlation-type elementary motion detectors (EMDs). However, it is still an open question how spatial information can be extracted reliably from the responses of the highly contrast- and pattern-dependent EMD responses, especially if the vast range of light intensities encountered in natural environments is taken into account. This question will be addressed here by systematically modeling the peripheral visual system of flies, including various adaptive mechanisms. Different model variants of the peripheral visual system were stimulated with image sequences that mimic the panoramic visual input during translational ego-motion in various natural environments, and the resulting peripheral signals were fed into an array of EMDs. We characterized the influence of each peripheral computational unit on the representation of spatial information in the EMD responses. Our model simulations reveal that information about the overall light level needs to be eliminated from the EMD input as is accomplished under light-adapted conditions in the insect peripheral visual system. The response characteristics of large monopolar cells (LMCs) resemble that of a band-pass filter, which reduces the contrast dependency of EMDs strongly, effectively enhancing the representation of the nearness of objects and, especially, of their contours. We furthermore show that local brightness adaptation of photoreceptors allows for spatial vision under a wide range of dynamic light conditions.

Project description:The perception of depth from relative motion is believed to be a slow process that "builds-up" over a period of observation. However, in the case of motion parallax, the potential accuracy of the depth estimate suffers as the observer translates during the viewing period. Our recent quantitative model for the perception of depth from motion parallax proposes that relative object depth (d) can be determined from retinal image motion (d?/dt), pursuit eye movement (d?/dt), and fixation distance (f) by the formula: d/f?d?/d?. Given the model's dynamics, it is important to know the integration time required by the visual system to recover d? and d?, and then estimate d. Knowing the minimum integration time reveals the incumbent error in this process. A depth-phase discrimination task was used to determine the time necessary to perceive depth-sign from motion parallax. Observers remained stationary and viewed a briefly translating random-dot motion parallax stimulus. Stimulus duration varied between trials. Fixation on the translating stimulus was monitored and enforced with an eye-tracker. The study found that relative depth discrimination can be performed with presentations as brief as 16.6 ms, with only two stimulus frames providing both retinal image motion and the stimulus window motion for pursuit (mean range=16.6-33.2 ms). This was found for conditions in which, prior to stimulus presentation, the eye was engaged in ongoing pursuit or the eye was stationary. A large high-contrast masking stimulus disrupted depth-discrimination for stimulus presentations less than 70-75 ms in both pursuit and stationary conditions. This interval might be linked to ocular-following response eye-movement latencies. We conclude that neural mechanisms serving depth from motion parallax generate a depth estimate much more quickly than previously believed. We propose that additional sluggishness might be due to the visual system's attempt to determine the maximum d?/d? ratio for a selection of points on a complicated stimulus.

Dataset Information

A model of how depth facilitates scene-relative object motion perception.

Publications

A model of how depth facilitates scene-relative object motion perception.

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