Computing the direction of moving terminators without end-stopped cells

G. Löffler*, H. S. Orhach

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Purpose. Terminators arc widely regarded as essential for the correct perception of object motion. End-stopped cells have been used as integral parts of models to compute the veridical direction of motion of terminators (Shimojo et al '89, J.Lorenceau et al '93. S.Grossberg & E.Mingolla '93). Can the veridical motion of terminators be computed using standard motion energy units ted by simple cells? Methods. Model simulations were performed on a Power Macintosh 7500 using the Matlab environment. The simulation included contributions from Fourier and Non-Fourier pathways (H.R.Wilson et al '92). Arbitrary two dimensional patterns were convolved with symmetric receptive field filters (1.7 cpd channel) feeding modified Reichardt detectors pooled into MT component units. The direction of moving terminators was finally calculated at the level of MT pattern cells. We incorporated contrast gain controls for VI and V2 cells, and, with slightly different characteristics, for MT component units. A weighted summation over both Fourier and non-Fourier component responses gave the final direction of motion. Results. In many cases, the Fourier pathway alone did not compute correct directions of motion. However, when non-Fourier contributions were included, our model yielded veridical directions of motion (generally within 5°) for a wide range of terminator orientations, widths and speeds. Conclusions. VI simple cells seem to be sufficient if included in the correct model to predict veridical motion, even of terminators. However, the simulation predicts non-veridical motion for short durations when the nonFourier pathway is not fully activated.

Original languageEnglish
Pages (from-to)S374
JournalInvestigative Ophthalmology and Visual Science
Issue number4
Publication statusPublished - 1997

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience


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