Advertisement

A Model of Position-Invariant, Optic Flow Pattern-Selective Cells

  • Robert I. Pitts
  • V. Sundareswaran
  • Lucia M. Vaina

Abstract

Two apparently inconsistent proposals for the functionality of MSTd cells exist, based either on optic flow patterns being represented by motion components 2–4, such as translation, expansion/contraction and rotation, or by a continuum of motion patterns that includes spirals6. A model, consisting of excitatory and inhibitory subunits, has been proposed3 to support the component view. Here, we used a neural network to show that a model of this type can be selective to the continuum of patterns6. We extended this model by adding inhibitory connections between units to account for the reported6 position-invariant characteristics of MSTd cells.

Keywords

Receptive Field Optic Flow Local Motion Prefer Pattern Spiral Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Beardsley, S. A., Vaina, L. M. and Poggio, T. The development of optic flow selectivity in MSTd neurons using backpropagation networks. Soc. Neurosci. Abstr 22, 1619 (1996).Google Scholar
  2. [2]
    Duffy, C. J. and Wurtz, R. H. Sensitivity of MST neurons to optic flow stimuli. I. A continuum of response selectivity to large-field stimuli. J. Neurophysiol. 65, 1329–1345 (1991).PubMedGoogle Scholar
  3. [3]
    Duffy, C. J. and Wurtz, R. H. Sensitivity of MST neurons to optic flow stimuli. Il. Mechanisms of response selectivity revealed by small-field stimuli. J. Neurophysiol. 65, 1346–1359 (1991).PubMedGoogle Scholar
  4. [4]
    Duffy, C. J. and Wurtz, R. H. Response of monkey MST neurons to optic flow stimuli with shifted centers of motion. J. Neurosci. 15, 5192–5208 (1995).PubMedGoogle Scholar
  5. [5]
    Duffy, C. J. and Wurtz, R. H. Personal communication.Google Scholar
  6. [6]
    Graziano, M. S. A., Andersen, R. A., and Snowden, R. J. Tuning of MST neurons to spiral motion. J. Neu osci. 14, 54–67 (1994).Google Scholar
  7. [7]
    Lappe, M. and Rauschecker, J. P. A neural network for the processing of optic flow from ego-motion in man and higher mammals. Neural Comp. 5, 374–391 (1993).CrossRefGoogle Scholar
  8. [8]
    Morrone, M. C., Burr, D. C., and Vaina, L. M. Two stages of visual processing for radial and circular motion. Nature. 376, 507–509 (1995).PubMedCrossRefGoogle Scholar
  9. [9]
    Pitts, R. I. and Vaina, L. M. A computational model of MSTd neurons sensitive to optic flow patterns. (Submitted).Google Scholar
  10. [10]
    Saito, H., Yukie, M., Tanaka, K., Hikosaka, K., Fukada, Y., and Iwai, E. Integration of direction signals of image motion in the superior temporal sulcus of the macaque monkey. J Neurosci. 6, 145–157 (1986).PubMedGoogle Scholar
  11. [11]
    Wang, R. A simple competitive account of some response properties of visual neurons in area MSTd. Neural Comp. 7, 290–306 (1995).CrossRefGoogle Scholar
  12. [12]
    Zhang, K., Sereno, M. 1., and Sereno, M. E. Emergence of position-independent detectors of sense of rotation and dilation with hebbian learning: an analysis. Neural Comp. 5, 597–612 (1993).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Robert I. Pitts
    • 1
    • 2
  • V. Sundareswaran
    • 2
  • Lucia M. Vaina
    • 2
  1. 1.Department of Computer ScienceBoston UniversityBostonUSA
  2. 2.Brain and Vision Research Laboratory Department of Biomedical EngineeringBoston UniversityBoston

Personalised recommendations