A Neurophysiologically Plausible Population Code Model for Feature Integration Explains Visual Crowding

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called “crowding”. Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, “compulsory averaging”, and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

[1]  H. Wilson,et al.  Lateral interactions in peripherally viewed texture arrays. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

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

[3]  I. Pigarev,et al.  Distant cortical locations of the upper and lower quadrants of the visual field represented by neurons with elongated and radially oriented receptive fields , 2004, Experimental Brain Research.

[4]  Susana T. L. Chung,et al.  Spatial-frequency and contrast properties of crowding , 2001, Vision Research.

[5]  Sheng He,et al.  Reduction of the Crowding Effect in Spatially Adjacent but Cortically Remote Visual Stimuli , 2009, Current Biology.

[6]  I. Rentschler,et al.  Contrast thresholds for identification of numeric characters in direct and eccentric view , 1991, Perception & psychophysics.

[7]  H. Burian,et al.  A study of separation difficulty. Its relationship to visual acuity in normal and amblyopic eyes. , 1962, American journal of ophthalmology.

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

[9]  G. Westheimer,et al.  Global stimulus configuration modulates crowding. , 2009, Journal of vision.

[10]  Sabine Kastner,et al.  Neurons with radial receptive fields in monkey area V4A: evidence of a subdivision of prelunate gyrus based on neuronal response properties , 2002, Experimental Brain Research.

[11]  S. Solomon,et al.  Contrast sensitivity in natural scenes depends on edge as well as spatial frequency structure. , 2009, Journal of vision.

[12]  R. Shapley,et al.  Contrast's effect on spatial summation by macaque V1 neurons , 1999, Nature Neuroscience.

[13]  D. Pelli,et al.  The uncrowded window of object recognition , 2008, Nature Neuroscience.

[14]  Patrick Cavanagh,et al.  The extent of crowding in peripheral vision does not scale with target size , 2002, Vision Research.

[15]  I. Pigarev,et al.  Whether radial receptive field organization of the fourth extrastriate crescent (area V4A) gives special advantage for analysis of the optic flow. Comparison with the first crescent (area V2) , 2007, Experimental Brain Research.

[16]  W. Korte,et al.  Über die Gestaltauffassung im indirekten Sehen , 1923 .

[17]  Irving Biederman,et al.  Object recognition, attention, and action , 2007 .

[18]  H. Bouma.  Visual interference in the parafoveal recognition of initial and final letters of words. , 1973, Vision research.

[19]  R. Hess,et al.  Ladder contours are undetectable in the periphery: a crowding effect? , 2007, Journal of vision.

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

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

[22]  Alexandre Pouget,et al.  Probabilistic Interpretation of Population Codes , 1996, Neural Computation.

[23]  P. Cavanagh,et al.  Temporal properties of the polarity advantage effect in crowding. , 2007, Journal of vision.

[24]  Hans Strasburger,et al.  Pattern Recognition in Direct and Indirect View , 2007 .

[25]  Frans W Cornelissen,et al.  On the generality of crowding: visual crowding in size, saturation, and hue compared to orientation. , 2007, Journal of vision.

[26]  C. Gilbert,et al.  Spatial integration and cortical dynamics. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[27]  David Whitney,et al.  Holistic crowding of Mooney faces. , 2009, Journal of vision.

[28]  Tracey D. Berger,et al.  Crowding and eccentricity determine reading rate. , 2007, Journal of vision.

[29]  H. Strasburger.  Unfocused spatial attention underlies the crowding effect in indirect form vision. , 2004, Journal of vision.

[30]  H. Bouma,et al.  Eccentric vision: Adverse interactions between line segments , 1976, Vision Research.

[31]  Wei Ji Ma,et al.  Population Codes: Theoretic Aspects , 2009 .

[32]  D. Levi,et al.  The effect of similarity and duration on spatial interaction in peripheral vision. , 1994, Spatial vision.

[33]  Dennis M. Levi,et al.  The perception of spatial order at a glance , 2005, Vision Research.

[34]  E. Louie,et al.  Holistic crowding: selective interference between configural representations of faces in crowded scenes. , 2007, Journal of vision.

[35]  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.

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

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

[38]  Wei Ji Ma,et al.  Bayesian inference with probabilistic population codes , 2006, Nature Neuroscience.

[39]  Taiyong Bi,et al.  The effect of crowding on orientation-selective adaptation in human early visual cortex. , 2009, Journal of vision.

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

[41]  D. Pelli,et al.  Are faces processed like words? A diagnostic test for recognition by parts. , 2005, Journal of vision.

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

[43]  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.

[44]  Björn N. S. Vlaskamp,et al.  Saccadic search performance: the effect of element spacing , 2005, Experimental Brain Research.

[45]  Dov Sagi,et al.  Configuration influence on crowding. , 2007, Journal of vision.

[46]  W Singer,et al.  The Perceptual Grouping Criterion of Colinearity is Reflected by Anisotropies of Connections in the Primary Visual Cortex , 1997, The European journal of neuroscience.

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

[48]  David J. Field,et al.  Contour integration by the human visual system: Evidence for a local “association field” , 1993, Vision Research.

[49]  K. Krikke,et al.  How important is lateral masking in visual search? , 2006, Experimental Brain Research.

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