Attention, Perception, & Psychophysics

, Volume 76, Issue 5, pp 1350–1370 | Cite as

Contrasting accounts of direction and shape perception in short-range motion: Counterchange compared with motion energy detection

Article

Abstract

It has long been thought (e.g., Cavanagh & Mather, 1989) that first-order motion-energy extraction via space-time comparator-type models (e.g., the elaborated Reichardt detector) is sufficient to account for human performance in the short-range motion paradigm (Braddick, 1974), including the perception of reverse-phi motion when the luminance polarity of the visual elements is inverted during successive frames. Human observers’ ability to discriminate motion direction and use coherent motion information to segregate a region of a random cinematogram and determine its shape was tested; they performed better in the same-, as compared with the inverted-, polarity condition. Computational analyses of short-range motion perception based on the elaborated Reichardt motion energy detector (van Santen & Sperling, 1985) predict, incorrectly, that symmetrical results will be obtained for the same- and inverted-polarity conditions. In contrast, the counterchange detector (Hock, Schöner, & Gilroy, 2009) predicts an asymmetry quite similar to that of human observers in both motion direction and shape discrimination. The further advantage of counterchange, as compared with motion energy, detection for the perception of spatial shape- and depth-from-motion is discussed.

Keywords

Short-range motion Motion energy detection Counterchange Reverse-phi 

References

  1. Adelson, E. H., & Bergen, J. R. (1985). Spatiotemporal energy models for the perception of motion. Journal of the Optical Society of America A, 2(2), 284–299.CrossRefGoogle Scholar
  2. Anstis, S. M. (1970). Phi movement as a subtraction process. Vision Research, 10(12), 1411–1430.PubMedCrossRefGoogle Scholar
  3. Azzopardi, P., & Hock, H.S. (2011). Illusory motion perception in blindsight. Proceedings of the National Academy of Sciences, 108, 876–881.Google Scholar
  4. Bours, R., Kroes, M., & Lankheet, M. J. (2009). Sensitivity for reverse-phi motion. Vision Research, 49(1).Google Scholar
  5. Braddick, O. (1974). A short-range process in apparent motion. Vision Research, 14, 519–527.PubMedCrossRefGoogle Scholar
  6. Cavanagh, P., & Mather, G. (1989). Motion: The long and short of it. Spatial vision, 4(2–3), 2–3.Google Scholar
  7. Chubb, C., & Sperling, G. (1988). Drift-balanced random stimuli- A general basis for studying non-Fourier motion perception. Optical Society of America, Journal, A: Optics and Image Science, 5, 1986–2007.CrossRefGoogle Scholar
  8. Dawson, M. R. (1991). The how and why of what went where in apparent motion: Modeling solutions to the motion correspondence problem. Psychological review.Google Scholar
  9. Dosher, B. A., Landy, M. S., & Sperling, G. (1989). Kinetic depth effect and optic flow–I. 3D shape from Fourier motion. Vision Research, 29(12), 1789–1813.PubMedCrossRefGoogle Scholar
  10. Edwards, M., & Badcock, D. R. (1994). Global motion perception: Interaction of the ON and OFF pathways. Vision Research.Google Scholar
  11. Eichner, H., Joesch, M., Schnell, B., Reiff, D. F., & Borst, A. (2011). Internal structure of the fly elementary motion detector. Neuron, 70(6), 1155–1164. doi:10.1016/j.neuron.2011.03.028 PubMedCrossRefGoogle Scholar
  12. Gilroy, L. A., & Hock, H. S. (2009). Simultaneity and sequence in the perception of apparent motion. Attention, Perception & Psychophysics, 71(7), 1563–1575. doi:10.3758/APP.71.7.1563 CrossRefGoogle Scholar
  13. Heeger, D. J. (1993). Modeling simple-cell direction selectivity with normalized, half-squared, linear operators. Journal of Neurophysiology, 70(5), 1885–1898.PubMedGoogle Scholar
  14. Hock, H. S., Gilroy, L., & Harnett, G. (2002). Counter-changing luminance: A non-Fourier, nonattentional basis for the perception of single-element apparent motion. JOURNAL OF EXPERIMENTAL PSYCHOLOGY HUMAN PERCEPTION AND PERFORMANCE, 28(1), 93.CrossRefGoogle Scholar
  15. Hock, H., Schöner, G., & Gilroy, L. (2009). A counterchange mechanism for the perception of motion. Acta Psychologica, 132(1), 1–21.PubMedCrossRefGoogle Scholar
  16. Hock, H. S., & Nichols, D. F. (2013). The perception of object versus objectless motion. Attention, Perception, & Psychophysics, 75(4), 726–737.Google Scholar
  17. Lu, Z. L., & Sperling, G. (2001). Three-systems theory of human visual motion perception: Review and update. Journal of the Optical Society of America A, Optics, image science, and vision, 18(9), 2331–2370.PubMedCrossRefGoogle Scholar
  18. Marr, D., & Ullman, S. (1981). Directional selectivity and its use in early visual processing. Proceedings of the Royal Society B: Biological Sciences, 211(1183), 151–180. doi:10.1098/rspb.1981.0001 CrossRefGoogle Scholar
  19. Morgan, M. J. (1992). Spatial filtering precedes motion detection. Nature, 355(6358), 344–346. doi:10.1038/355344a0 PubMedCrossRefGoogle Scholar
  20. Pelah, A., Barbur, J., Thurrell, A., & Hock, H.S. (2014). The Coupling of Vision with Locomotion in Cortical Blindness. Vision Research, (in revision). Google Scholar
  21. Reichardt, W. (1961). Autocorrelation, a principle for the evaluation of sensory information by the central nervous system. In W. A. Rosenblith (Ed.), Sensory Communication (pp. 303–317). Cambridge: MIT Press.Google Scholar
  22. Sato, T. (1989). Reversed apparent motion with random dot patterns. Vision Research, 29(12), 1749–1758.PubMedCrossRefGoogle Scholar
  23. Seifert, M.S., & Hock, H.S. (2014). The Independent Detection of Motion Energy and Counterchange: Flexibility in Motion Detection. Vision Research, (in revision). Google Scholar
  24. Simoncelli, E. P., & Heeger, D. J. (1998). A model of neuronal responses in visual area MT. Vision Research, 38(5), 743–761.PubMedCrossRefGoogle Scholar
  25. Sperling, G., & Lu, Z.-L. (1998). A systems analysis of visual motion perception. High-level motion processing, 153–183.Google Scholar
  26. Stevens, M., & Merilaita, S. (2009). Animal camouflage: Current issues and new perspectives. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1516), 423–427. doi:10.1098/rstb.2008.0217 CrossRefGoogle Scholar
  27. van Santen, J. P., & Sperling, G. (1984). Temporal covariance model of human motion perception. JOSA A, 1(5), 451–473.CrossRefGoogle Scholar
  28. van Santen, J. P., & Sperling, G. (1985). Elaborated Reichardt detectors. Journal of the Optical Society of America A, Optics and image science, 2(2), 300–321.PubMedCrossRefGoogle Scholar
  29. Wehrhahn, C., & Rapf, D. (1992). ON- and OFF-pathways form separate neural substrates for motion perception: Psychophysical evidence. The Journal of Neuroscience, 1–4. Retrieved from http://www.jneurosci.org.ezproxy.fau.edu/content/12/6/2247.full.pdf
  30. Wertheimer, M. (1912). Experimental studies of the perception of movement (Experimentelle Studien über das Sehen von Bewegung). Zeitschrift für Psychologie under Physiologie der Sinnesorgane, 61, 161–265.Google Scholar
  31. Yuille, A. L., & Grzywacz, N. M. (1998). A theoretical framework for visual motion. In T. Watanabe (Ed.), High-level motion processing (pp. 187–211). Cambridge: The MIT Press.Google Scholar

Copyright information

© Psychonomic Society, Inc. 2014

Authors and Affiliations

  1. 1.Center for Complex Systems and Brain SciencesFlorida Atlantic UniversityBoca RatonUSA
  2. 2.Department of PsychologyFlorida Atlantic UniversityBoca RatonUSA
  3. 3.Institut für NeuroinformatikRuhr-Universität BochumBochumGermany

Personalised recommendations