Understanding vision in wholly empirical terms

This article considers visual perception, the nature of the information on which perceptions seem to be based, and the implications of a wholly empirical concept of perception and sensory processing for vision science. Evidence from studies of lightness, brightness, color, form, and motion all indicate that, because the visual system cannot access the physical world by means of retinal light patterns as such, what we see cannot and does not represent the actual properties of objects or images. The phenomenology of visual perceptions can be explained, however, in terms of empirical associations that link images whose meanings are inherently undetermined to their behavioral significance. Vision in these terms requires fundamentally different concepts of what we see, why, and how the visual system operates.

[1]  B. Craven.  Orientation dependence of human line-length judgements matches statistical structure in real-world scenes , 1993, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[2]  W. Köhler.  Gestalt Psychology: An Introduction to New Concepts in Modern Psychology , 1970 .

[3]  A. Gilchrist.  Seeing in Black and White , 2006 .

[4]  David J. Field,et al.  Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.

[5]  D. Knill,et al.  The Bayesian brain: the role of uncertainty in neural coding and computation , 2004, Trends in Neurosciences.

[6]  S. Ullman,et al.  Rigidity and Smoothness of Motion , 1987 .

[7]  E H Adelson,et al.  Spatiotemporal energy models for the perception of motion. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[8]  W. C. Shipley,et al.  The apparent length of tilted lines. , 1949, Journal of experimental psychology.

[9]  J. van Santen,et al.  Temporal covariance model of human motion perception. , 1984, Journal of the Optical Society of America. A, Optics and image science.

[10]  H. Wallach.  On the visually perceived direction of motion ' ' by Hans Wallach : 60 years later , 1997 .

[11]  H. Helmholtz.  Helmholtz's Treatise on Physiological Optics , 1963 .

[12]  W. PEDDIE,et al.  Helmholtz's Treatise on Physiological Optics , 1926, Nature.

[13]  E. O. Cormack,et al.  Stimulus configuration and line orientation in the horizontal-vertical illusion , 1974 .

[14]  Ellen C. Hildreth,et al.  Measurement of Visual Motion , 1984 .

[15]  Dale Purves,et al.  An empirical explanation of aperture effects , 2009, Proceedings of the National Academy of Sciences.

[16]  D. Kersten,et al.  Illusions, perception and Bayes , 2002, Nature Neuroscience.

[17]  D. Purves,et al.  Why we see what we do : an empirical theory of vision , 2003 .

[18]  A. Bethe,et al.  Handbuch der Normalen und Pathologischen Physiologie , 1925 .

[19]  Leonard E. White,et al.  Mapping multiple features in the population response of visual cortex , 2003, Nature.

[20]  A. Yuille,et al.  A Theoretical Framework for Visual Motion , 1996 .

[21]  Bruno A. Olshausen,et al.  Vision and the Coding of Natural Images , 2000, American Scientist.

[22]  Rajesh P. N. Rao,et al.  Probabilistic Models of the Brain: Perception and Neural Function , 2002 .

[23]  W. Davis.  The Ecological Approach to Visual Perception , 2012 .

[24]  Dale Purves,et al.  Range image statistics can explain the anomalous perception of length , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[25]  J. Gibson.  The Ecological Approach to Visual Perception , 1979 .

[26]  R. Woodworth,et al.  The Integrative Action of the Nervous System , 1908 .

[27]  W. T. Pollock,et al.  The Apparent Length of a Line as a Function of Its Inclination* , 1952 .

[28]  Edward H. Adelson,et al.  Motion illusions as optimal percepts , 2002, Nature Neuroscience.

[29]  I. Murakami,et al.  Latency difference, not spatial extrapolation , 1998, Nature Neuroscience.

[30]  Daniel Kersten,et al.  Bayesian models of object perception , 2003, Current Opinion in Neurobiology.

[31]  D. Purves,et al.  An Empirical Explanation of the Speed-Distance Effect , 2009, PloS one.

[32]  Romi Nijhawan,et al.  Motion extrapolation in catching , 1994, Nature.

[33]  T J Sejnowski,et al.  Motion integration and postdiction in visual awareness. , 2000, Science.

[34]  Terrence J Sejnowski,et al.  Untangling spatial from temporal illusions , 2002, Trends in Neurosciences.

[35]  D. Purves,et al.  Why we see what we do redux : a wholly empirical theory of vision , 2011 .

[36]  E. Adelson,et al.  The analysis of moving visual patterns , 1985 .

[37]  Dale Purves,et al.  Natural-scene geometry predicts the perception of angles and line orientation. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[38]  C. Sherrington.  Integrative Action of the Nervous System , 1907 .

[39]  J. O. Robinson.  The Psychology of Visual Illusion , 1972 .

[40]  David J. Field,et al.  What Is the Goal of Sensory Coding? , 1994, Neural Computation.

[41]  Dale Purves,et al.  The statistical structure of natural light patterns determines perceived light intensity. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[42]  Dale Purves,et al.  An empirical explanation of the flash-lag effect , 2008, Proceedings of the National Academy of Sciences.

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

[44]  D Marr,et al.  Directional selectivity and its use in early visual processing , 1981, Proceedings of the Royal Society of London. Series B. Biological Sciences.