Patterns and Symmetries in the Visual Cortex and in Natural Images

As borders between different entities, lines are an important element of natural images. Indeed, the neurons of the mammalian visual cortex are tuned to respond best to lines of a given orientation. This preferred orientation varies continuously across most of the cortex, but also has vortex-like singularities known as pinwheels. In attempting to describe such patterns of orientation preference, we are led to consider underlying rotation symmetries: Oriented segments in natural images tend to be collinear; neurons are more likely to be connected if their preferred orientations are aligned to their topographic separation. These are indications of a reduced symmetry requiring joint rotations of both orientation preference and the underlying topography. This is verified by direct statistical tests in both natural images and in cortical maps. Using the statistics of natural scenes we construct filters that are best suited to extracting information from such images, and find qualitative similarities to mammalian vision.

[1]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[2]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[3]  J. Swift,et al.  Hydrodynamic fluctuations at the convective instability , 1977 .

[4]  Jeffrey A. Sloan,et al.  Spatial frequency analysis of the visual environment: Anisotropy and the carpentered environment hypothesis , 1978, Vision Research.

[5]  S. Laughlin A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.

[6]  J. Rothwell Principles of Neural Science , 1982 .

[7]  N. Swindale,et al.  A model for the formation of orientation columns , 1982, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[8]  G. Blasdel,et al.  Voltage-sensitive dyes reveal a modular organization in monkey striate cortex , 1986, Nature.

[9]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[10]  T. Wiesel,et al.  Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex , 1989, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[11]  Joseph J. Atick,et al.  Towards a Theory of Early Visual Processing , 1990, Neural Computation.

[12]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  A. Grinvald,et al.  Relationship between intrinsic connections and functional architecture revealed by optical imaging and in vivo targeted biocytin injections in primate striate cortex. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[14]  William Bialek,et al.  Statistics of Natural Images: Scaling in the Woods , 1993, NIPS.

[15]  M. Cross,et al.  Pattern formation outside of equilibrium , 1993 .

[16]  R C Reid,et al.  Efficient Coding of Natural Scenes in the Lateral Geniculate Nucleus: Experimental Test of a Computational Theory , 1996, The Journal of Neuroscience.

[17]  D. Fitzpatrick,et al.  Orientation Selectivity and the Arrangement of Horizontal Connections in Tree Shrew Striate Cortex , 1997, The Journal of Neuroscience.

[18]  F. Wolf,et al.  Spontaneous pinwheel annihilation during visual development , 1998, Nature.

[19]  J. H. Hateren,et al.  Independent component filters of natural images compared with simple cells in primary visual cortex , 1998 .

[20]  Katepalli R. Sreenivasan,et al.  Extraction of Anisotropic Contributions in Turbulent Flows , 1998, chao-dyn/9804040.

[21]  T. Bonhoeffer,et al.  Overrepresentation of horizontal and vertical orientation preferences in developing ferret area 17. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[22]  J. Langer,et al.  Pattern formation in nonequilibrium physics , 1999 .

[23]  M. Sur,et al.  Stability of Cortical Responses and the Statistics of Natural Scenes , 2001, Neuron.

[24]  Dmitri B. Chklovskii,et al.  Orientation Preference Patterns in Mammalian Visual Cortex A Wire Length Minimization Approach , 2001, Neuron.

[25]  M. Golubitsky,et al.  Geometric visual hallucinations, Euclidean symmetry and the functional architecture of striate cortex. , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[26]  C. Gilbert,et al.  On a common circle: natural scenes and Gestalt rules. , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[27]  P. Adorján,et al.  Axonal topography of cortical basket cells in relation to orientation, direction, and ocular dominance maps , 2001, The Journal of comparative neurology.

[28]  Mehran Kardar,et al.  Information optimization in coupled audio-visual cortical maps , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[29]  David Whitney,et al.  Flexible Retinotopy: Motion-Dependent Position Coding in the Visual Cortex , 2003, Science.

[30]  Ha Youn Lee,et al.  Symmetry considerations and development of pinwheels in visual maps , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[31]  N. Logothetis,et al.  Integration of Local Features into Global Shapes Monkey and Human fMRI Studies , 2003, Neuron.

[32]  Nicholas V. Swindale,et al.  A model for the coordinated development of columnar systems in primate striate cortex , 2004, Biological Cybernetics.

[33]  J. Nelson,et al.  Intracortical facilitation among co-oriented, co-axially aligned simple cells in cat striate cortex , 2004, Experimental Brain Research.

[34]  P. O. Bishop,et al.  Responses to moving slits by single units in cat striate cortex , 2004, Experimental Brain Research.