Emulating the Visual Receptive-Field Properties of MST Neurons with a Template Model of Heading Estimation

Abstract

We have proposed previously a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to those of neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. These detectors, arranged within cortical-like maps, were designed to extract self-translation (heading) and self-rotation, as well as the scene layout (relative distances) ahead of a moving observer. We then postulated that heading from optic flow is directly encoded by individual neurons acting as heading detectors within the medial superior temporal (MST) area. Others have questioned whether individual MST neurons can perform this function because some of their receptive-field properties seem inconsistent with this role. To resolve this issue, we systematically compared MST responses with those of detectors from two different configurations of the model under matched stimulus conditions. We found that the characteristic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support self-motion estimation via a direct encoding of heading and that the template model provides an explicit set of testable hypotheses that can guide future exploration of MST and adjacent areas within the superior temporal sulcus.

Heading Representation in MST: Sensory Interactions and Population Encoding

“…20). This is consistent with population models of heading estimation in MST (Lappe and Rauschecker 1993;Perrone and Stone 1998) and with pursuit altering single neuron optic flow responses while the population heading vector remained veridical (Page and Duffy 1999).…”

Attending to visual motion

“…In order to demonstrate that ST can indeed operate with realistic representations, the motion domain is chosen because enough is known about motion processing to enable a reasonable attempt at defining the feed-forward pyramid. Moreover, the effort is unique because it seems that no past model has presented a motion hierarchy plus attention to motion [3][4][5][6][7][8][9][10][11][12].…”

Attending to Motion: Localizing and Classifying Motion Patterns in Image Sequences

“…Here, the motion domain is chosen in order to demonstrate that STM can indeed operate as desired with realistic representations because enough is known about motion processing to enable a reasonable attempt at defining the feedforward pyramid. In addition, the effort is unique because it seems that no past model presented a motion hierarchy plus attention to motion [34,35,36,37,38,39,40,41,42]. The remainder of this paper will focus on this issue.…”