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Competitive Dynamics in MSTd: A Mechanism for Robust Heading Perception Based on Optic Flow.

Layton OW, Fajen BR - PLoS Comput. Biol. (2016)

Bottom Line: Simulations of existing heading models that do not contain competitive dynamics yield heading estimates that are far more erratic and unstable than human judgments.Soft winner-take-all dynamics enhance units that code a heading direction consistent with the time history and suppress responses to transient changes to the optic flow field.Our findings support recurrent competitive temporal dynamics as a crucial mechanism underlying the robustness and stability of perception of heading.

View Article: PubMed Central - PubMed

Affiliation: Department of Cognitive Science, Rensselaer Polytechnic Institute, Troy, New York, United States of America.

ABSTRACT
Human heading perception based on optic flow is not only accurate, it is also remarkably robust and stable. These qualities are especially apparent when observers move through environments containing other moving objects, which introduce optic flow that is inconsistent with observer self-motion and therefore uninformative about heading direction. Moving objects may also occupy large portions of the visual field and occlude regions of the background optic flow that are most informative about heading perception. The fact that heading perception is biased by no more than a few degrees under such conditions attests to the robustness of the visual system and warrants further investigation. The aim of the present study was to investigate whether recurrent, competitive dynamics among MSTd neurons that serve to reduce uncertainty about heading over time offer a plausible mechanism for capturing the robustness of human heading perception. Simulations of existing heading models that do not contain competitive dynamics yield heading estimates that are far more erratic and unstable than human judgments. We present a dynamical model of primate visual areas V1, MT, and MSTd based on that of Layton, Mingolla, and Browning that is similar to the other models, except that the model includes recurrent interactions among model MSTd neurons. Competitive dynamics stabilize the model's heading estimate over time, even when a moving object crosses the future path. Soft winner-take-all dynamics enhance units that code a heading direction consistent with the time history and suppress responses to transient changes to the optic flow field. Our findings support recurrent competitive temporal dynamics as a crucial mechanism underlying the robustness and stability of perception of heading.

No MeSH data available.


Related in: MedlinePlus

Overview of the cases in which an object may cross the future path of a moving observer (right panels) and corresponding optic flow fields (left panels). In panels on the left, red and blue arrowheads correspond to optic flow from the object and background, respectively. In the right panels, the black arrow shows the heading direction of the observer and red arrows show the movement direction of the object. In panel b, the fixed-depth object moves in depth at the same rate as the observer (v). (d) A depiction of self-motion in the presence of an approaching moving object that occupies much of the visual field (45° of the 100° field of view). Even though the FoE due to the observer self-motion relative to the background (blue disk) and to the object (red disk) are separated by 20°, the heading bias is quite small—only 1–3°.
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pcbi.1004942.g001: Overview of the cases in which an object may cross the future path of a moving observer (right panels) and corresponding optic flow fields (left panels). In panels on the left, red and blue arrowheads correspond to optic flow from the object and background, respectively. In the right panels, the black arrow shows the heading direction of the observer and red arrows show the movement direction of the object. In panel b, the fixed-depth object moves in depth at the same rate as the observer (v). (d) A depiction of self-motion in the presence of an approaching moving object that occupies much of the visual field (45° of the 100° field of view). Even though the FoE due to the observer self-motion relative to the background (blue disk) and to the object (red disk) are separated by 20°, the heading bias is quite small—only 1–3°.

Mentions: Heading perception is not only accurate, it is also remarkably robust and stable. These qualities warrant further investigation and are the focus of the present study. The robustness and stability of heading perception are especially evident in dynamic environments containing independently moving objects. Regions of the optic array corresponding to moving objects generally contain optic flow that is inconsistent with the background optic flow and uninformative about heading. Nonetheless, heading perception is biased by moving objects by no more than a few degrees. Objects that approach the observer in depth (approaching objects; Fig 1A) induce a bias in the direction opposite the object motion of ~3° [20]. When objects maintain a fixed depth with respect to the observer as they move laterally (fixed-depth objects; Fig 1B), heading perception is biased by ~1° in the direction of object motion [21]. Objects that recede in depth from the observer as they move across the observer’s future path (retreating objects; Fig 1C) yield a heading bias in the direction of object motion of less than 3° (Layton & Fajen, in preparation).


Competitive Dynamics in MSTd: A Mechanism for Robust Heading Perception Based on Optic Flow.

Layton OW, Fajen BR - PLoS Comput. Biol. (2016)

Overview of the cases in which an object may cross the future path of a moving observer (right panels) and corresponding optic flow fields (left panels). In panels on the left, red and blue arrowheads correspond to optic flow from the object and background, respectively. In the right panels, the black arrow shows the heading direction of the observer and red arrows show the movement direction of the object. In panel b, the fixed-depth object moves in depth at the same rate as the observer (v). (d) A depiction of self-motion in the presence of an approaching moving object that occupies much of the visual field (45° of the 100° field of view). Even though the FoE due to the observer self-motion relative to the background (blue disk) and to the object (red disk) are separated by 20°, the heading bias is quite small—only 1–3°.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4920404&req=5

pcbi.1004942.g001: Overview of the cases in which an object may cross the future path of a moving observer (right panels) and corresponding optic flow fields (left panels). In panels on the left, red and blue arrowheads correspond to optic flow from the object and background, respectively. In the right panels, the black arrow shows the heading direction of the observer and red arrows show the movement direction of the object. In panel b, the fixed-depth object moves in depth at the same rate as the observer (v). (d) A depiction of self-motion in the presence of an approaching moving object that occupies much of the visual field (45° of the 100° field of view). Even though the FoE due to the observer self-motion relative to the background (blue disk) and to the object (red disk) are separated by 20°, the heading bias is quite small—only 1–3°.
Mentions: Heading perception is not only accurate, it is also remarkably robust and stable. These qualities warrant further investigation and are the focus of the present study. The robustness and stability of heading perception are especially evident in dynamic environments containing independently moving objects. Regions of the optic array corresponding to moving objects generally contain optic flow that is inconsistent with the background optic flow and uninformative about heading. Nonetheless, heading perception is biased by moving objects by no more than a few degrees. Objects that approach the observer in depth (approaching objects; Fig 1A) induce a bias in the direction opposite the object motion of ~3° [20]. When objects maintain a fixed depth with respect to the observer as they move laterally (fixed-depth objects; Fig 1B), heading perception is biased by ~1° in the direction of object motion [21]. Objects that recede in depth from the observer as they move across the observer’s future path (retreating objects; Fig 1C) yield a heading bias in the direction of object motion of less than 3° (Layton & Fajen, in preparation).

Bottom Line: Simulations of existing heading models that do not contain competitive dynamics yield heading estimates that are far more erratic and unstable than human judgments.Soft winner-take-all dynamics enhance units that code a heading direction consistent with the time history and suppress responses to transient changes to the optic flow field.Our findings support recurrent competitive temporal dynamics as a crucial mechanism underlying the robustness and stability of perception of heading.

View Article: PubMed Central - PubMed

Affiliation: Department of Cognitive Science, Rensselaer Polytechnic Institute, Troy, New York, United States of America.

ABSTRACT
Human heading perception based on optic flow is not only accurate, it is also remarkably robust and stable. These qualities are especially apparent when observers move through environments containing other moving objects, which introduce optic flow that is inconsistent with observer self-motion and therefore uninformative about heading direction. Moving objects may also occupy large portions of the visual field and occlude regions of the background optic flow that are most informative about heading perception. The fact that heading perception is biased by no more than a few degrees under such conditions attests to the robustness of the visual system and warrants further investigation. The aim of the present study was to investigate whether recurrent, competitive dynamics among MSTd neurons that serve to reduce uncertainty about heading over time offer a plausible mechanism for capturing the robustness of human heading perception. Simulations of existing heading models that do not contain competitive dynamics yield heading estimates that are far more erratic and unstable than human judgments. We present a dynamical model of primate visual areas V1, MT, and MSTd based on that of Layton, Mingolla, and Browning that is similar to the other models, except that the model includes recurrent interactions among model MSTd neurons. Competitive dynamics stabilize the model's heading estimate over time, even when a moving object crosses the future path. Soft winner-take-all dynamics enhance units that code a heading direction consistent with the time history and suppress responses to transient changes to the optic flow field. Our findings support recurrent competitive temporal dynamics as a crucial mechanism underlying the robustness and stability of perception of heading.

No MeSH data available.


Related in: MedlinePlus