Does perceptual-motor recalibration of locomotion depend on perceived self motion or the magnitude of optical flow?

In a previous functional neuroimaging study we found that early visual areas deactivated when a rotating optical flow stimulus elicited the illusion of self-motion (vection) compared with when it was perceived as a moving object. Here, we investigated whether electrical cortical responses to an independent central visual probe stimulus change as a function of whether optical flow stimulation in the periphery induces the illusion of self-motion or not. Visual-evoked potentials (VEPs) were obtained in response to pattern-reversals in the central visual field in the presence of a constant peripheral large-field optokinetic stimulus that rotated around the naso-occipital axis and induced intermittent sensations of vection. As control, VEPs were also recorded during a stationary peripheral stimulus and showed no difference than those obtained during optokinetic stimulation. The VEPs during constant peripheral stimulation were then divided into two groups according to the time spans where the subjects reported object- or self-motion, respectively. The N70 VEP component showed a significant amplitude reduction when, due to the peripheral stimulus, subjects experienced self-motion compared to when the peripheral stimulus was perceived as object-motion. This finding supplements and corroborates our recent evidence from functional neuroimaging that early visual cortex deactivates when a visual flow stimulus elicits the illusion of self-motion compared with when the same sensory input is interpreted as object-motion. This dampened responsiveness might reflect a redistribution of sensorial and attentional resources when the monitoring of self-motion relies on a sustained and veridical processing of optic flow and may be compromised by other sources of visual input.

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Velocity Modulation of Optical Flow Affects Self-Motion Perception during Body Motion

i-Perception ◽

10.1068/ic858 ◽

2011 ◽

Vol 2 (8) ◽

pp. 858-858

Author(s):

Tomoko Yonemura ◽

Shin Okamoto ◽

Hiroki Kawasaki ◽

Daisuke Kondo ◽

Yuki Hashimoto ◽

...

Keyword(s):

Optical Flow ◽

Motion Perception ◽

Body Motion ◽

Velocity Modulation ◽

Self Motion

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Optical Flow and Texture Variables Useful for Detecting Changes in Simulated Self Motion

Proceedings of the Human Factors Society Annual Meeting ◽

10.1177/154193128302701213 ◽

1983 ◽

Vol 27 (12) ◽

pp. 996-1000

Author(s):

Dean H. Owen ◽

Lawrence J. Hettinger ◽

Shirley B. Tobias ◽

Lawrence Wolpert ◽

Rik Warren

Keyword(s):

Optical Flow ◽

Flow Pattern ◽

High Speed ◽

Flight Simulator ◽

Practical Relevance ◽

Motion Information ◽

Flow Acceleration ◽

Level Flight ◽

Texture Density ◽

Self Motion

Several methods are presented for breaking linkages among global optical flow and texture variables in order to assess their usefulness in experiments requiring observers to distinguish change in speed or heading of simulated self motion from events representing constant speed or level flight. Results of a series of studies testing for sensitivity to flow acceleration or deceleration, flow-pattern expansion variables, and the distribution of optical texture density are presented. Theoretical implications for determining the metrics of visual self-motion information, and practical relevance for pilot and flight simulator evaluation and for low-level, high-speed flight are discussed.

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Direction of self-motion is perceived from optical flow

Nature ◽

10.1038/336162a0 ◽

1988 ◽

Vol 336 (6195) ◽

pp. 162-163 ◽

Cited By ~ 371

Author(s):

William H. Warren ◽

Daniel J. Hannon

Keyword(s):

Optical Flow ◽

Self Motion

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Visual Information in Judgments of Head-On Collisions

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193120705102409 ◽

2007 ◽

Vol 51 (24) ◽

pp. 1555-1559

Author(s):

Kerstan S. Mork ◽

Patricia R. DeLucia

Keyword(s):

Optical Flow ◽

Flow Pattern ◽

Computer Simulations ◽

Visual Information ◽

Flow Information ◽

Self Motion

Head-on collisions result in a substantial number of fatalities. To detect head-on collisions, drivers must judge effectively the direction or heading of their own vehicle in relation to the heading of oncoming vehicles. In our previous study, we used computer simulations of self-motion through a traffic scene to measure judgments about whether a head-on collision was imminent. Results suggested that judgments about head-on collision are affected by both the optical flow information provided by the centerline and the optical flow information provided by the oncoming car. The objective of the current study was to further examine the effect of different components of the optical flow pattern on judgments of head-on collisions. We measured judgments about head on collisions while manipulating local optical flow from the oncoming car and global optical flow from the background scenery. Our results suggest that visual information about the oncoming car's motion was more effective than visual information about self motion. The implication is that it may be beneficial for drivers to focus greater attention on the information about the oncoming car's motion in order to improve judgments about head-on collisions. Further research is needed to evaluate this possibility.

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Development of Automatic Steering System by Modeling Human Behavior Based on Optical Flow

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2015.p0136 ◽

2015 ◽

Vol 27 (2) ◽

pp. 136-145 ◽

Cited By ~ 8

Author(s):

Yuki Okafuji ◽

◽

Takanori Fukao ◽

Hiroshi Inou ◽

Keyword(s):

Optical Flow ◽

Human Behavior ◽

Visual Information ◽

Control Method ◽

Steering System ◽

Vehicle Simulation ◽

Automatic Steering ◽

Behavior Based ◽

Self Motion ◽

Oriented System

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/03.jpg"" width=""300"" /> Manipulated optical flow field</div> Recently, various driving support systems have been developed to improve safety. However, because drivers occasionally feel that something is wrong, systems need to be designed based on information that drivers perceive. Therefore, we focused on optical flow, which is one of the visual information used by humans to improve driving feel. Humans are said to perceive the direction of self-motion from optical flow and also utilize it during driving. Applying the optical flow model to automatic steering systems, a human-oriented system might be able to be developed. In this paper, we derive the focus of expansion (FOE) in the frame of a camera that is the direction of self-motion in optical flow and propose a nonlinear control method based on the FOE. The effectiveness of the proposed method was verified through a vehicle simulation, and the results showed that the proposed method simulates human behavior. Based on these results, this approach may serve as a foundation of human-oriented system designs. </span>

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