A biologically plausible model of early visual motion processing II: Psychophysical application

We test the model of early visual processing introduced in the companion paper by simulating a range of psychophysical phenomena. We present new data concerning our ability to discriminate the speed of drifting gratings when spatiotemporally apertured in a variety of ways. We shall investigate the role played by the aperture in modifying the grating's behaviour from its idealisation as a pure Fourier component and show that this is not negligible. Other phenomena which we simulate and explain relate to the way perceived velocity is influenced by contrast and spatial frequency. Many of our explanations are couched in terms of the relative number of cells occurring within each locale of the Fourier domain. This use of the cell density map is a unifying concept and avoids the necessity for a range of separate mechanisms. We argue that a neurophysiologically detailed model is necessary in order to explain psychophysical data (Weber fractions) which vary over less than an order of magnitude, and small deviations from veridical encoding of velocity.

[1]  M. J. Wright,et al.  Lower threshold of motion for one and two dimensional patterns in central and peripheral vision , 1992, Vision Research.

[2]  S. McKee,et al.  The detection of motion in the peripheral visual field , 1984, Vision Research.

[3]  P. Thompson.  Perceived rate of movement depends on contrast , 1982, Vision Research.

[4]  D. Whitteridge,et al.  The representation of the visual field on the cerebral cortex in monkeys , 1961, The Journal of physiology.

[5]  Idan Segev.  Single neurone models: oversimple, complex and reduced , 1992, Trends in Neurosciences.

[6]  G. Orban,et al.  Human velocity and direction discrimination measured with random dot patterns , 1988, Vision Research.

[7]  H. Wilson,et al.  Perceived direction of moving two-dimensional patterns , 1990, Vision Research.

[8]  Leslie Welch,et al.  The perception of moving plaids reveals two motion-processing stages , 1989, Nature.

[9]  G. B. Wetherill,et al.  SEQUENTIAL ESTIMATION OF POINTS ON A PSYCHOMETRIC FUNCTION. , 1965, The British journal of mathematical and statistical psychology.

[10]  S. McKee,et al.  Precise velocity discrimination despite random variations in temporal frequency and contrast , 1986, Vision Research.

[11]  A. T. Smith,et al.  The influence of spatial frequency on perceived temporal frequency and perceived speed , 1990, Vision Research.

[12]  E. Adelson,et al.  Phenomenal coherence of moving visual patterns , 1982, Nature.

[13]  P. Thompson,et al.  Human speed perception is contrast dependent , 1992, Vision Research.

[14]  S. McKee.  A local mechanism for differential velocity detection , 1981, Vision Research.

[15]  A J Ahumada,et al.  Model of human visual-motion sensing. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[16]  John H. R. Maunsell,et al.  The visual field representation in striate cortex of the macaque monkey: Asymmetries, anisotropies, and individual variability , 1984, Vision Research.

[17]  M. M. Taylor,et al.  PEST: Efficient Estimates on Probability Functions , 1967 .

[18]  F. Campbell,et al.  The influence of spatial frequency and contrast on the perception of moving patterns , 1981, Vision Research.