Saccade-confounded image statistics explain visual crowding

Processing of shape information in human peripheral visual fields is impeded beyond what can be expected by poor spatial resolution. Visual crowding, the inability to identify objects in clutter, has been shown to be the primary factor limiting shape perception in peripheral vision. Despite the well-documented effects of crowding, its underlying causes remain poorly understood. Given that spatial attention both facilitates learning of image statistics and directs saccadic eye movements, we propose that the acquisition of image statistics in peripheral visual fields is confounded by eye-movement artifacts. Specifically, the image statistics acquired under a peripherally deployed spotlight of attention are systematically biased by saccade-induced image displacements. These erroneously represented image statistics lead to inappropriate contextual interactions in the periphery and cause crowding.

[1]  H. BOUMA,et al.  Interaction Effects in Parafoveal Letter Recognition , 1970, Nature.

[2]  L. Stark,et al.  Most naturally occurring human saccades have magnitudes of 15 degrees or less. , 1975, Investigative ophthalmology.

[3]  A. Bird,et al.  Aphakic macular edema: incidence and pathogenesis. , 1975, Investigative ophthalmology.

[4]  S. Sherman,et al.  Receptive-field characteristics of neurons in cat striate cortex: Changes with visual field eccentricity. , 1976, Journal of neurophysiology.

[5]  F. Campbell,et al.  Saccadic omission: Why we do not see a grey-out during a saccadic eye movement , 1978, Vision Research.

[6]  C. Gross,et al.  Visual topography of V2 in the macaque , 1981, The Journal of comparative neurology.

[7]  A. Watson,et al.  Quest: A Bayesian adaptive psychometric method , 1983, Perception & psychophysics.

[8]  H. Bedell,et al.  The oculomotor reference in humans with bilateral macular disease. , 1990, Investigative ophthalmology & visual science.

[9]  D. Levi,et al.  The two-dimensional shape of spatial interaction zones in the parafovea , 1992, Vision Research.

[10]  Robert Tibshirani,et al.  An Introduction to the Bootstrap , 1994 .

[11]  C. Gilbert,et al.  Improvement in visual sensitivity by changes in local context: Parallel studies in human observers and in V1 of alert monkeys , 1995, Neuron.

[12]  S Lebedev,et al.  Square-root relations between main saccadic parameters. , 1996, Investigative ophthalmology & visual science.

[13]  P. Cavanagh,et al.  Attentional resolution and the locus of visual awareness , 1996, Nature.

[14]  H. Deubel,et al.  Saccade target selection and object recognition: Evidence for a common attentional mechanism , 1996, Vision Research.

[15]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

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

[17]  R Gattass,et al.  Area V4 in Cebus monkey: extent and visuotopic organization. , 1998, Cerebral cortex.

[18]  C. Gilbert,et al.  Attention Modulates Contextual Influences in the Primary Visual Cortex of Alert Monkeys , 1999, Neuron.

[19]  C. Gilbert,et al.  Interactions between attention, context and learning in primary visual cortex , 2000, Vision Research.

[20]  M. Morrone,et al.  Extraretinal Control of Saccadic Suppression , 2000, The Journal of Neuroscience.

[21]  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.

[22]  Eli Peli,et al.  Intrasaccadic Perception , 2001, The Journal of Neuroscience.

[23]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[24]  Jeffrey S. Perry,et al.  Edge co-occurrence in natural images predicts contour grouping performance , 2001, Vision Research.

[25]  J. Lund,et al.  Compulsory averaging of crowded orientation signals in human vision , 2001, Nature Neuroscience.

[26]  Eric Castet,et al.  Motion perception of saccade-induced retinal translation , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[27]  S. Klein,et al.  Suppressive and facilitatory spatial interactions in peripheral vision: peripheral crowding is neither size invariant nor simple contrast masking. , 2002, Journal of vision.

[28]  Jean Bennett,et al.  Lateral Connectivity and Contextual Interactions in Macaque Primary Visual Cortex , 2002, Neuron.

[29]  Peter Hain.  Why Bigger is Better , 2003 .

[30]  Katsumi Aoki,et al.  Recent development of flow visualization , 2004, J. Vis..

[31]  D. Pelli,et al.  Crowding is unlike ordinary masking: distinguishing feature integration from detection. , 2004, Journal of vision.

[32]  Ohad Ben-Shahar,et al.  Geometrical Computations Explain Projection Patterns of Long-Range Horizontal Connections in Visual Cortex , 2004, Neural Computation.

[33]  C. Raggi,et al.  Mini review , 2004 .

[34]  D. Heeger,et al.  Two Retinotopic Visual Areas in Human Lateral Occipital Cortex , 2006, The Journal of Neuroscience.

[35]  John K. Tsotsos,et al.  A statistical basis for visual field anisotropies , 2006, Neurocomputing.

[36]  Peter Neri,et al.  Spatial resolution for feature binding is impaired in peripheral and amblyopic vision. , 2006, Journal of neurophysiology.

[37]  B. C. Motter,et al.  The roles of cortical image separation and size in active visual search performance. , 2007, Journal of vision.

[38]  Denis G Pelli,et al.  Amblyopic reading is crowded. , 2007, Journal of vision.

[39]  Anirvan S. Nandy,et al.  The nature of letter crowding as revealed by first- and second-order classification images. , 2007, Journal of Vision.

[40]  Y. Petrov,et al.  Crowding is directed to the fovea and preserves only feature contrast. , 2007, Journal of vision.

[41]  Ariella V. Popple,et al.  Crowding and surround suppression: not to be confused. , 2007, Journal of vision.

[42]  W. Geisler.  Visual perception and the statistical properties of natural scenes. , 2008, Annual review of psychology.

[43]  D. Levi.  Crowding—An essential bottleneck for object recognition: A mini-review , 2008, Vision Research.

[44]  D. Pelli.  Crowding: a cortical constraint on object recognition , 2008, Current Opinion in Neurobiology.

[45]  R. Wurtz.  Neuronal mechanisms of visual stability , 2008, Vision Research.

[46]  B. C. Motter.  Central V4 Receptive Fields Are Scaled by the V1 Cortical Magnification and Correspond to a Constant-Sized Sampling of the V1 Surface , 2009, The Journal of Neuroscience.

[47]  Dennis M. Levi,et al.  Crowding in Peripheral Vision: Why Bigger Is Better , 2009, Current Biology.

[48]  Steven C Dakin,et al.  Positional averaging explains crowding with letter-like stimuli , 2009, Proceedings of the National Academy of Sciences.

[49]  Bart Krekelberg,et al.  The Relationship between Saccadic Suppression and Perceptual Stability , 2009, Current Biology.

[50]  Michael S. Lewicki,et al.  Emergence of complex cell properties by learning to generalize in natural scenes , 2009, Nature.

[51]  Brad C. Motter.  Crowding and object integration within the receptive field of V4 neurons , 2010 .

[52]  David Melcher,et al.  Backward Masking and Unmasking Across Saccadic Eye Movements , 2010, Current Biology.

[53]  Jos B. T. M. Roerdink,et al.  A Neurophysiologically Plausible Population Code Model for Feature Integration Explains Visual Crowding , 2010, PLoS Comput. Biol..

[54]  Steven C. Dakin,et al.  Crowding Changes Appearance , 2010, Current Biology.

[55]  Eero P. Simoncelli,et al.  Metamers of the ventral stream , 2011, Nature Neuroscience.

[56]  D. Levi,et al.  Visual crowding: a fundamental limit on conscious perception and object recognition , 2011, Trends in Cognitive Sciences.