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Evoked potential and psychophysical analysis of Fourier and non-Fourier motion mechanisms

Published online by Cambridge University Press:  02 June 2009

Jonathan D. Victor  and
Mary M. Conte
Jonathan D. Victor
Affiliation:
Department of Neurology and Neuroscience, Cornell University Medical College, New York, New York
Mary M. Conte
Affiliation:
Laboratory of Biophysics, The Rockefeller University, New York, New York
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Abstract

Some visual stimuli produce a strong percept of motion, even though they fail to excite motion detectors based on Fourier energy or cross correlation. Models which suffice to explain the motion percept in these non-Fourier motion (NFM) stimuli include linear spatiotemporal filtering, followed by rectification, followed by standard motion analysis (Chubb & Sperling 1988). We used the human “motion-onset” evoked potential, which has been assigned to area 17 on the basis of work in the macaque (van Dijk et al., 1986; van Dijk & Spekreijse, 1989), to investigate the neural substrate of the processing stages postulated in the above models. Motion-onset VEPs elicited by FM and NFM matched for spatial and temporal characteristics were indistinguishable in temporal characteristics and scalp topography at a transverse chain of electrodes. Addition of textural cues (granularity and higher-order form) did not influence the response dynamics or scalp topography of NFM responses. However, comparison of responses to NFM stimuli and related stimuli without coherent motion but similar spatial and temporal properties showed that the motion-onset responses were distinct from responses to the onset of fixed flicker-defined contours not undergoing coherent motion. We discuss the implications of these results for computational models of motion analysis.

Keywords

HumanModelingMotion mechanismsNonlinear interactionsRectificationVisual-evoked potentials
Type
Research Articles
Information
Visual Neuroscience , Volume 9 , Issue 2 , August 1992 , pp. 105 - 123
Copyright
Copyright © Cambridge University Press 1992

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References

Adelson, E.H. & Bergen, J. (1985). Spatiotemporal energy models for the perception of motion. Journal of the Optical Society of America A 2, 284–299.CrossRefGoogle ScholarPubMed
Adelson, E.H. & Movshon, J.A. (1982). Phenomenal coherence of moving visual patterns. Nature 300, 523–525.CrossRefGoogle ScholarPubMed
Albright, T.D. (1992). Form-cue invariant motion processing in primate visual cortex. Science 255, 1141–1143.CrossRefGoogle ScholarPubMed
Braddick, O. (1974). A short-range process in apparent motion. Vision Research 14, 519–529.CrossRefGoogle ScholarPubMed
Braddick, O. (1980). Low-level and high-level processes in apparent motion. Philosophical Transactions of the Royal Society B (London) 290, 137–151.Google Scholar
Cattel, R.B. (1978). The Scientific Use of Factor Analysis. New York: Plenum Press.CrossRefGoogle Scholar
Chubb, C. & Sperling, G. (1988). Drift-balanced random stimuli: A general basis for studying non-Fourier motion perception. Journal of the Optical Society of America A 5, 1986–2006.CrossRefGoogle ScholarPubMed
Chubb, C. & Sperling, G. (1989). Two motion perception mechanisms revealed through distance-driven reversal of apparent motion. Proceedings of the National Academy of Sciences of the U.S.A. 86, 2985–2989.CrossRefGoogle ScholarPubMed
Emerson, R.C., Bergen, J.R. & Adelson, E.H. (1992). Directionally selective complex cells and the computation of motion energy in cat visual cortex. Vision Research 32, 203–218.CrossRefGoogle ScholarPubMed
Emerson, R.C., Citron, M., Vaughn, W.J. & Klein, S. (1987). Non-linear directionally selective subunits in complex cells of cat striate cortex. Journal of Neurophysiology 58, 33–65.CrossRefGoogle Scholar
Gutowitz, H., Zemon, V., Victor, J.D. & Knight, B.W. (1986). Source geometry and dynamics of the visual evoked potential. Electroencephalography and Clinical Neurophysiology 64, 308–327.CrossRefGoogle ScholarPubMed
Heeger, D. (1987). Model for the extraction of image flow. Journal of the Optical Society of America A 4, 1455–1471.CrossRefGoogle ScholarPubMed
Julesz, B., Gilbert, E.N. & Victor, J.D. (1978). Visual discrimination of textures with identical third-order statistics. Biological Cybernetics 31, 137–140.CrossRefGoogle ScholarPubMed
Mckee, S. & Watamaniuk, S.N.J. (1991). Detecting a single point moving on a linear trajectory amidst randomly moving points. Investigative Ophthalmology and Visual Science (Suppl.) 32, 892.Google Scholar
Mckee, S. & Welch, L. (1985). Sequential recruitment in the discrimination of velocity. Journal of the Optical Society of America A 2, 243–251.CrossRefGoogle ScholarPubMed
Milkman, N., Schick, G., Rossetto, M., Ratliff, F., Shapley, R. & Victor, J.D. (1980). A two-dimensional computer-controlled visual stimulator. Behavior Research Methods and Instrumentation 12, 283–292.CrossRefGoogle Scholar
Nakayama, K. (1985). Biological image motion processing: A review. Vision Research 25, 625–660.CrossRefGoogle ScholarPubMed
Nakayama, K. & Silverman, G.H. (1985). Detection and discrimination of sinusoidal grating displacements. Journal of the Optical Society of America A 2, 267–274.CrossRefGoogle ScholarPubMed
Reichardt, W. (1961). Autocorrelation, a principle for the evaluation of sensory information by the central nervous system. In Sensory Communication, ed. Rosenbluth, W.A., pp. 303–317. New York: John Wiley & Sons.Google Scholar
Simoncelli, E.P. & Adelson, E.H. (1991). Relationship between gradient, spatiotemporal-energy, and regression models for motion perception. Investigative Ophthalmology and Visual Science (Suppl.) 32, 893.Google Scholar
Spekreijse, H., Dagnelie, G., Maier, J. & Regan, D. (1985). Flicker and movement constituents of the pattern reversal response. Vision Research 25, 1297–1304.CrossRefGoogle ScholarPubMed
Turano, K. (1991). Evidence for a common motion mechanism of luminance- and contrast-modulated patterns: Selective adaptation. Perception 20, 455–466.CrossRefGoogle ScholarPubMed
Turano, K. & Pantle, A. (1989). On the mechanism that encodes the movement of contrast variations: Velocity discrimination. Vision Research 29, 207–221.CrossRefGoogle ScholarPubMed
van Duk, B.W., Dagnelie, G. & Spekreuse, H. (1986). Motion onset-offset evoked potentials from rhesus visual cortex. In Evoked Potentials III. The Third International Evoked Potentials Symposium, ed. Barber, C. & Blum, T., pp. 205–212. Boston, Massachusetts: Butterworths.Google Scholar
van Duk, B.W. & Spekreuse, H. (1989). Responses to onset and offset of visual motion. Investigative Ophthalmology and Visual Science (Suppl.) 30, 426.Google Scholar
van Santen, J.P.H. & Sperling, G. (1985). Elaborated Reichardt detectors. Journal of the Optical Society of America A 2, 300–321.CrossRefGoogle ScholarPubMed
Victor, J.D. & Conte, M.M. (1990). Motion mechanisms have only limited access to form information. Vision Research 30, 289–301.CrossRefGoogle ScholarPubMed
Victor, J.D. & Conte, M.M. (1991). Spatial organization of nonlinear interactions in form perception. Vision Research 31, 1457–1488.CrossRefGoogle ScholarPubMed
Victor, J.D., Conte, M.M. & Iadecola, C. (1991). Ocular dependence of hemifield visual-evoked potentials: Relevance to bilateral cortical representation of central vision. Clinical Vision Sciences 6, 261–176.Google Scholar
Victor, J.D. & Mast, J. (1991). A new statistic for steady-state evoked potentials. Electroencephalography and Clinical Neurophysiology 78, 378–388.CrossRefGoogle ScholarPubMed