scholarly journals Optic Flow Information Influencing Heading Perception during Rotation

i-Perception ◽  
10.1068/ic270 ◽  
2011 ◽  
Vol 2 (4) ◽  
pp. 270-270
Author(s):  
Diederick C. Niehorster ◽  
William H. Warren ◽  
Li Li
Keyword(s):  
Optic Flow ◽  
Flow Information ◽  
Optic Flow Information

A Self-Organizing Neural Network Architecture for Navigation Using Optic Flow

1998 ◽  
Vol 10 (2) ◽  
pp. 313-352 ◽  
Author(s):  
Seth Cameron ◽  
Stephen Grossberg ◽  
Frank H. Guenther
Keyword(s):  
Neural Network ◽  
Eye Movement ◽  
Optic Flow ◽  
Network Architecture ◽  
Neural Network Architecture ◽  
Object Locations ◽  
Flow Information ◽  
Optic Flow Information ◽  
Scene Depth ◽  
Self Organizing

This article describes a self-organizing neural network architecture that transforms optic flow and eye position information into representations of heading, scene depth, and moving object locations. These representations are used to navigate reactively in simulations involving obstacle avoidance and pursuit of a moving target. The network's weights are trained during an action-perception cycle in which self-generated eye and body movements produce optic flow information, thus allowing the network to tune itself without requiring explicit knowledge of sensor geometry. The confounding effect of eye movement during translation is suppressed by learning the relationship between eye movement outflow commands and the optic flow signals that they induce. The remaining optic flow field is due to only observer translation and independent motion of objects in the scene. A self-organizing feature map categorizes normalized translational flow patterns, thereby creating a map of cells that code heading directions. Heading information is then recombined with translational flow patterns in two different ways to form maps of scene depth and moving object locations. Most of the learning processes take place concurrently and evolve through unsupervised learning. Mapping the learned heading representations onto heading labels or motor commands requires additional structure. Simulations of the network verify its performance using both noise-free and noisy optic flow information.

scholarly journals Optic flow informs distance but not profitability for honeybees

2009 ◽  
Vol 277 (1685) ◽  
pp. 1241-1245 ◽  
Author(s):  
Sharoni Shafir ◽  
Andrew B. Barron
Keyword(s):  
Apis Mellifera ◽  
Optic Flow ◽  
Processing System ◽  
Foraging Efficiency ◽  
Dual Processing ◽  
Energetic Costs ◽  
Flying Insects ◽  
Dance Communication ◽  
Flow Information ◽  
Optic Flow Information

How do flying insects monitor foraging efficiency? Honeybees ( Apis mellifera ) use optic flow information as an odometer to estimate distance travelled, but here we tested whether optic flow informs estimation of foraging costs also. Bees were trained to feeders in flight tunnels such that bees experienced the greatest optic flow en route to the feeder closest to the hive. Analyses of dance communication showed that, as expected, bees indicated the close feeder as being further, but they also indicated this feeder as the more profitable, and preferentially visited this feeder when given a choice. We show that honeybee estimates of foraging cost are not reliant on optic flow information. Rather, bees can assess distance and profitability independently and signal these aspects as separate elements of their dances. The optic flow signal is sensitive to the nature of the environment travelled by the bee, and is therefore not a good index of flight energetic costs, but it provides a good indication of distance travelled for purpose of navigation and communication, as long as the dancer and recruit travel similar routes. This study suggests an adaptive dual processing system in honeybees for communicating and navigating distance flown and for evaluating its energetic costs.

scholarly journals Spatial integration of optic flow information in direction of heading judgments

2015 ◽  
Vol 15 (6) ◽  
pp. 14
Author(s):  
Laurel Issen ◽  
Krystel R. Huxlin ◽  
David Knill
Keyword(s):  
Optic Flow ◽  
Spatial Integration ◽  
Flow Information ◽  
Optic Flow Information

Influence of optic flow on the control of heading and target egocentric direction during steering toward a goal

2014 ◽  
Vol 112 (4) ◽  
pp. 766-777 ◽  
Author(s):  
Li Li ◽  
Diederick C. Niehorster
Keyword(s):  
Optic Flow ◽  
Theoretic Approach ◽  
Global Flow ◽  
Response Delay ◽  
Control Precision ◽  
Direct Support ◽  
Flow Information ◽  
Control Response ◽  
Optic Flow Information ◽  
Egocentric Direction

Although previous studies have shown that people use both optic flow and target egocentric direction to walk or steer toward a goal, it remains in question how enriching the optic flow field affects the control of heading specified by optic flow and the control of target egocentric direction during goal-oriented locomotion. In the current study, we used a control-theoretic approach to separate the control response specific to these two cues in the visual control of steering toward a goal. The results showed that the addition of optic flow information (such as foreground motion and global flow) in the display improved the overall control precision, the amplitude, and the response delay of the control of heading. The amplitude and the response delay of the control of target egocentric direction were, however, not affected. The improvement in the control of heading with enriched optic flow displays was mirrored by an increase in the accuracy of heading perception. The findings provide direct support for the claim that people use the heading specified by optic flow as well as target egocentric direction to walk or steer toward a goal and suggest that the visual system does not internally weigh these two cues for goal-oriented locomotion control.

scholarly journals Extrastriate Area MST and Parietal Area VIP Similarly Represent Forward Headings

2010 ◽  
Vol 104 (1) ◽  
pp. 239-247 ◽  
Author(s):  
James B. Maciokas ◽  
Kenneth H. Britten
Keyword(s):  
Eye Movements ◽  
Optic Flow ◽  
Posterior Parietal Cortex ◽  
Three Dimensional ◽  
Quantitative Comparison ◽  
Medial Superior Temporal ◽  
Flow Information ◽  
Mst Neurons ◽  
Optic Flow Information ◽  
Cloud Of Points

Many studies have documented the involvement of medial superior temporal extrastriate area (MST) in the perception of heading based on optic flow information. Furthermore, both heading perception and the responses of MST neurons are relatively stable in the presence of eye movements that distort the retinal flow information on which perception is based. Area VIP in the posterior parietal cortex also contains a robust representation of optic flow cues for heading. However, the studies in the two areas were frequently conducted using different stimuli, making quantitative comparison difficult. To remedy this, we studied MST using a family of random dot heading stimuli that we have previously used in the study of VIP. These stimuli simulate observer translation through a three-dimensional cloud of points, and a range of forward headings was presented both with and without horizontal smooth pursuit eye movements. We found that MST neurons, like VIP neurons, respond robustly to these stimuli and partially compensate for the presence of pursuit. Quantitative comparison of the responses revealed no substantial difference between the heading responses of MST and VIP neurons or in their degree of pursuit tolerance.

scholarly journals Circuit Organization Underlying Optic Flow Processing in Zebrafish

2021 ◽  
Vol 15 ◽  
Author(s):  
Koji Matsuda ◽  
Fumi Kubo
Keyword(s):  
Optic Flow ◽  
Visual Features ◽  
Optomotor Response ◽  
Imaging Studies ◽  
Optokinetic Response ◽  
Larval Zebrafish ◽  
Specific Manner ◽  
Flow Information ◽  
Optic Flow Information ◽  
Self Motion

Animals’ self-motion generates a drifting movement of the visual scene in the entire field of view called optic flow. Animals use the sensation of optic flow to estimate their own movements and accordingly adjust their body posture and position and stabilize the direction of gaze. In zebrafish and other vertebrates, optic flow typically drives the optokinetic response (OKR) and optomotor response (OMR). Recent functional imaging studies in larval zebrafish have identified the pretectum as a primary center for optic flow processing. In contrast to the view that the pretectum acts as a relay station of direction-selective retinal inputs, pretectal neurons respond to much more complex visual features relevant to behavior, such as spatially and temporally integrated optic flow information. Furthermore, optic flow signals, as well as motor signals, are represented in the cerebellum in a region-specific manner. Here we review recent findings on the circuit organization that underlies the optic flow processing driving OKR and OMR.

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