Nonlinear interaction of ON and OFF data streams for the detection of visual structure

Visual stimuli lead to neural activity in the retina that is propagated in separate ON and OFF pathways to the cortex. Most models of biological early vision recombine these activity streams by a linear integration at the simple cell level. Based on empirical as well as theoretical investigations we propose a nonlinear recombination circuit that is selectively responsive to contrast magnitude as well as to the sharpness of luminance transition. Simulations with artificial and camera images show a higher positional selectivity for local contrasts than an equivalent linear device. In a multiscale hierarchy the nonlinear circuit produces a unique maximum response in scale-space where scale directly relates to the width of the luminance transition. In order to investigate the biological relevance of the proposed neural circuit, we measured the model sensitivity to luminance gradient reversal in bar stimuli. Our simulations show strong similarity to simple cell recordings in the feline striate cortex. This result further supports the evidence for nonlinear interaction at the simple cell level.

[1]  J. Movshon,et al.  Spatial summation in the receptive fields of simple cells in the cat's striate cortex. , 1978, The Journal of physiology.

[2]  Heiko Neumann,et al.  Neural model for visual contrast detection , 1996, ESANN.

[3]  Peter H. Schiller,et al.  The ON and OFF channels of the visual system , 1992, Trends in Neurosciences.

[4]  D. Pollen,et al.  Spatial and temporal frequency selectivity of neurones in visual cortical areas V1 and V2 of the macaque monkey. , 1985, The Journal of physiology.

[5]  D M MacKay,et al.  Influence of luminance gradient reversal on simple cells in feline striate cortex , 1983, The Journal of physiology.

[6]  M. Carandini,et al.  Summation and division by neurons in primate visual cortex. , 1994, Science.

[7]  Luiz Pessoa,et al.  A Simple Cell Model with Multiple Spatial Frequency Selectivity and Linear/Non-Linear Response Properties , 1994 .

[8]  S Grossberg,et al.  3-D vision and figure-ground separation by visual cortex , 2010, Perception & psychophysics.

[9]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[10]  Heiko Neumann,et al.  Estimating attributes of smooth signal transitions from scale-space , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

[11]  J. Movshon,et al.  Length summation in simple cells of cat striate cortex , 1984, Vision Research.

[12]  D. Pollen,et al.  Interneuronal interaction between members of quadrature phase and anti-phase pairs in the cat's visual cortex , 1992, Vision Research.

[13]  Heiko Neumann,et al.  A Contrast- and Luminance-driven Multiscale Network Model of Brightness Perception , 1995, Vision Research.

[14]  D. Ferster.  Spatially opponent excitation and inhibition in simple cells of the cat visual cortex , 1988, The Journal of neuroscience : the official journal of the Society for Neuroscience.