Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-24T13:04:38.943Z Has data issue: false hasContentIssue false

Neuronal response to texture- and contrast-defined boundaries in early visual cortex

Published online by Cambridge University Press:  12 April 2007

YUNING SONG
Affiliation:
McGill Vision Research Unit, Department of Ophthalmology, McGill University, Montréal, Québec, Canada
CURTIS L. BAKER
Affiliation:
McGill Vision Research Unit, Department of Ophthalmology, McGill University, Montréal, Québec, Canada

Abstract

Natural scenes contain a variety of visual cues that facilitate boundary perception (e.g., luminance, contrast, and texture). Here we explore whether single neurons in early visual cortex can process both contrast and texture cues. We recorded neural responses in cat A18 to both illusory contours formed by abutting gratings (ICs, texture-defined) and contrast-modulated gratings (CMs, contrast-defined). We found that if a neuron responded to one of the two stimuli, it also responded to the other. These neurons signaled similar contour orientation, spatial frequency, and movement direction of the two stimuli. A given neuron also exhibited similar selectivity for spatial frequency of the fine, stationary grating components (carriers) of the stimuli. These results suggest that the cue-invariance of early cortical neurons extends to different kinds of texture or contrast cues, and might arise from a common nonlinear mechanism.

Type
Research Article
Copyright
© 2007 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Albright, T.D. (1992). Form-cue invariant motion processing in primate visual cortex. Science 225, 11411143.CrossRefGoogle Scholar
Arsenault, S.A., Wilkinson, F. & Kingdom, F.A.A. (1999). Modulation frequency and orientation tuning of second-order texture mechanisms. Journal the Optical Society of America A 16, 427435.CrossRefGoogle Scholar
Badcock, D.R. & Derrington, A.M. (1985). Detecting the displacement of periodic patterns. Vision Research 25, 12531258.CrossRefGoogle Scholar
Baumann, R., van der Zwan, R. & Peterhans, E. (1997). Figure-ground segregation at contours: A neural mechanism in the visual cortex of the alert monkey. European Journal of Neuroscience 9, 12901303.CrossRefGoogle Scholar
Bergen, J.R. & Landy, M.S. (1991). Computational modelling of visual texture segregation. In Computational Models of Visual Processing, ed. Landy, M.S. & Movshon, J.A., pp. 253271. Cambridge, Massachusetts: The MIT Press.
Brainard, D.H. (1997). The psychophysics toolbox. Spatial Vision 10, 433436.CrossRefGoogle Scholar
Cavanagh, P., Arguin, M. & von Grünau, M. (1989). Interattribute apparent motion. Vision Research 29, 11971204.CrossRefGoogle Scholar
Chaudhuri, A. & Albright, T.D. (1997). Neuronal responses to edges defined by luminance vs. temporal texture in macaque area V1. Visual Neuroscience 14, 94962.Google Scholar
Chubb, C. & Sperling, G. (1988). Drift-balanced random stimuli: A general basis for studying non-Fourier motion perception. Journal of the Optical Society of America A 5, 19862007.CrossRefGoogle Scholar
Chubb, C. & Sperling, G. (1991). Texture quilts: Basic tools for studying motion from texture. Journal of Mathematical Psychology 35, 411442.CrossRefGoogle Scholar
Derrington, A.M. & Badcock, D.R. (1985). Separate detectors for simple and complex grating patterns? Vision Research 25, 186978.Google Scholar
Derrington, A.M. & Badcock, D.R. (1986). Detection of spatial beats: Nonlinearity or contrast increment detection. Vision Research 26, 34348.CrossRefGoogle Scholar
Derrington, A.M., Badcock, D.R. & Henning, G.B. (1993). Discriminating the direction of second-order motion at short stimulus durations. Vision Research 33, 17851794.CrossRefGoogle Scholar
Dupont, P., De Bruyn, B., Vandenberghe, R., Rosier, A.M., Michiels, J., Marchal, G., Mortelmans, L. & Orban, G.A. (1997). The kinetic occipital region in human visual cortex. Cerebral Cortex 7, 283292.CrossRefGoogle Scholar
Efron, B. & Tibshirani, B. (1993). An introduction to the bootstrap. New York: Chapman & Hall.CrossRef
Eger, E., Schyns, P.G. & Kleinschmidt, A. (2004). Scale invariant adaptation in fusiform face-responsive regions. Neuroimage 22, 23242.CrossRefGoogle Scholar
Field, D.J. (1987). Relations between the statistics of natural images and the response properties of cortical cells. Journal of the Optical Society of America A 4, 237994.CrossRefGoogle Scholar
Gallant, J.L., Connor, C.E., Rakshit, S., Lewis, J.W. & Van Essen, D.C. (1996). Neural responses to polar, hyperbolic, and Cartesian gratings in area V4 of the macaque monkey. Journal of Neurophysiology 76, 271839.Google Scholar
Geesaman, B.J. & Anderson, R.A. (1996). The analysis of complex motion patterns by form/cue invariant MSTd neurons. Journal of Neuroscience 16, 47164732.Google Scholar
Graham, N. & Sutter, A. (1998). Spatial summation in simple (Fourier) and complex (non-Fourier) texture channels. Vision Research 38, 231257.CrossRefGoogle Scholar
Graham, N., Beck, J. & Sutter, A. (1992). Nonlinear processes in spatial-frequency channel models of perceived segregation: Effects of sign and amount of contrast. Vision Research 32, 719743.CrossRefGoogle Scholar
Grill-Spector, K., Kushnir, T., Edelman, S., Avidan, G., Itzchak, Y. & Malach, R. (1999). Differential processing of objects under various viewing conditions in the human lateral occipital complex. Neuron 24, 187203.CrossRefGoogle Scholar
Grill-Spector, K., Kushnir, T., Edelman, S., Itzchak, Y. & Malach, R. (1998). Cue-invariant activation in object-related areas of the human occipital lobe. Neuron 21, 191202.CrossRefGoogle Scholar
Grosof, D.H., Shapley, R.M. & Hawken, M.J. (1993). Macaque V1 neurons can signal “illusory” contours. Nature 365, 550552.CrossRefGoogle Scholar
Grossberg, S. & Mingolla, E. (1985). Neural dynamics of form perception: Boundary completion, illusory figures, and enon color spreading. Psychological Review 92, 173211.CrossRefGoogle Scholar
Gurnsey, R., Fleet, D. & Potechin, C. (1998). Second-order motions contribute to vection. Vision Research 38, 280116.CrossRefGoogle Scholar
Heider, B., Spillmann, L. & Peterhans, E. (2002). Stereoscopic illusory contours, cortical neuron responses, and human perception. Journal of Cognitive Neuroscience 14, 10181029.CrossRefGoogle Scholar
Heitger, F., Rosenthaler, L., von der Heydt, R., Peterhans, E. & Kubler, O. (1992). Simulation of neural contour mechanisms: from simple to end-stopped cells. Vision Research 32, 963981.CrossRefGoogle Scholar
Kanizsa, G. (1976). Subjective contours. Scientific American 234, 4852.CrossRefGoogle Scholar
Kellman, P.J. & Shipley, R. (1991). A theory of visual interpolation in object perception. Cognitive Psychology 23, 141221.CrossRefGoogle Scholar
Kingdom, F.A.A. & Keeble, D.R.T. (1996). A linear systems approach to the detection of both abrupt and smooth spatial variations in orientation-defined textures. Vision Research 36, 409420.CrossRefGoogle Scholar
Kourtzi, Z. & Kanwisher, N. (2001). Representation of perceived object shape by the human lateral occipital complex. Science 293, 15061509.CrossRefGoogle Scholar
Krummenacher, J., Müller, H. & Heller, D. (2001). Visual search for dimensionally redundant pop-out targets: Evidence for parallel-coactive processing of dimensions, Perception and Psychophysics 63, 901917.Google Scholar
Lennie, P. (1998). Single units and visual cortical organization. Perception 27, 889935.CrossRefGoogle Scholar
Lesher, G.W. & Mingolla, E. (1993). The role of edges and line-ends in illusory contour formation. Vision Research 33, 22532270.CrossRefGoogle Scholar
Leventhal, A.G., Wang, Y., Schmolesky, M.T. & Zhou, Y. (1998). Neural correlates of boundary perception. Visual Neuroscience 15, 11071118.CrossRefGoogle Scholar
Livingstone, M. & Hubel, D. (1988). Segregation of form, color, movement, and depth: Anatomy, physiology, and perception. Science 240, 740749.CrossRefGoogle Scholar
Loffler, G. & Orbach, H.S. (1999). Computing feature motion without feature detectors: a model for terminator motion without end-stopped cells. Vision Research 39, 859871.Google Scholar
Logothetis, N.K. & Charles, E.R. (1990). V4 responses to gratings defined by random dot motion. Investigative Ophthalmology and Visual Science 31, 90.Google Scholar
Lui, L.L., Bourne, J.A. & Rosa, M.G. (2005). Single-unit responses to kinetic stimuli in New World monkey area V2: Physiological characteristics of cue-invariant neurones. Experimental Brain Research 162, 100108.CrossRefGoogle Scholar
Malik, J. & Perona, P. (1990). Preattentive texture discrimination with early vision mechanisms. Journal of the Optical Society of America A 7, 923932.CrossRefGoogle Scholar
Mareschal, I. & Baker, C.L., Jr. (1998). A cortical locus for the processing of contrast-defined contours. Nature Neuroscience 1, 150154.CrossRefGoogle Scholar
Mareschal, I. & Baker, C.L., Jr. (1999). Cortical processing of second-order motion. Visual Neuroscience 16, 527540.CrossRefGoogle Scholar
Marida, K.V. (1972). Statistics of Directional Data. New York: Academic Press.
Neumann, M.H. & Mingolla, E. (2001). Computational neural models of spatial integration in perceptual grouping. In From Fragments to Objects: Grouping and Segmentation in Vision, ed. Shipley, T.F. & Kellman, P.J., pp. 353400. Amsterdam: Elsevier.CrossRef
Nieder, A. (2002). Seeing more than meets the eye: Processing of illusory contours in animals. Journal of Comparative Physiology 188, 24960.CrossRefGoogle Scholar
Pelli, D.G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision 10, 437442.CrossRefGoogle Scholar
Peterhans, E. & von der Heydt, R. (1989). Mechanisms of contour perception in monkey visual cortex. II. Contours bridging gaps. Journal of Neuroscience 9, 17491763.Google Scholar
Peterhans, E. (1997). Functional organization of Area V2 in the awake monkey. In Cerebral Cortex, pp. 335357. New York: Plenum Press.CrossRef
Peterson, M.R., Li, B. & Freeman, R.D. (2004). The derivation of direction selectivity in the striate cortex. Journal of Neuroscience 24, 35833591.Google Scholar
Ramsden, B.M., Hung, C.P. & Roe, A.W. (2001). Real and illusory contour processing in area V1 of the primate: A cortical balancing act. Cerebral Cortex 11, 648665.CrossRefGoogle Scholar
Redies, C., Crook, J.M. & Creutzfeldt, O.D. (1986). Neuronal responses to borders with and without luminance gradients in cat visual cortex and dorsal lateral geniculate nucleus. Experimental Brain Research 61, 469481.Google Scholar
Rivest, J. & Cavanagh, P. (1996). Localizing contours defined by more than one attribute. Vision Research 36, 5366.CrossRefGoogle Scholar
Sary, G., Vogels, R. & Orban, G. (1993). Cue-invariant shape selectivity of Macaque inferior temporal neurons. Science 260, 995997.CrossRefGoogle Scholar
Sary, G., Vogels, R., Kovacs, G. & Orban, G.A. (1995). Responses of monkey inferior temporal neurons to luminance-, motion-, and texture-defined gratings. Journal of Neurophysiology 73, 13411354.Google Scholar
Saul, A.B. & Humphrey, A.L. (1990). Spatial and temporal response properties of lagged and nonlagged cells in the cat lateral geniculate nucleus. Journal of Neurophysiology 64, 206224.Google Scholar
Scott-Samuel, N.E. & Georgeson, M.A. (1999). Does early non-linearity account for second-order motion? Vision Research 39, 28532865.Google Scholar
Sheth, B.R., Sharma, J., Rao, S.C. & Sur, M. (1996). Orientation maps of subjective contours in visual cortex. Science 274, 21102115.CrossRefGoogle Scholar
Skottun, B.C. (1994). Illusory contours and linear filters. Experimental Brain Research 100, 360364.CrossRefGoogle Scholar
Skottun, B.C., De Valois, R.L., Grosof, D.H., Movshon, J.A., Albrecht, D.G. & Bonds, A.B. (1991). Classifying simple and complex cells on the basis of response modulation. Vision Research 31, 10791086.Google Scholar
Smith, A.T. & Ledgeway, T. (1997). Separate detection of moving luminance and contrast modulations: Fact or artifact? Vision Research 37, 4562.Google Scholar
Smith, A.T. & Ledgeway, T. (2001). Motion detection in human vision: A unifying approach based on energy and features. Proceedings: Biological Sciences 268, 18891899.Google Scholar
Song, Y. & Baker, C.L., Jr. (2006). Neural mechanisms mediating responses to abutting gratings: Luminance edges vs. illusory contours. Visual Neuroscience 23, 181199.CrossRefGoogle Scholar
Sutter, A. & Graham, N. (1995). Investigating simple and complex mechanisms in texture segregation using speed-accuracy trade-off method. Vision Research 35, 28252843.CrossRefGoogle Scholar
Sutter, A., Sperling, G. & Chubb, C. (1995). Measuring the spatial frequency selectivity of second-order texture mechanisms. Vision Research 35, 915924.CrossRefGoogle Scholar
Tanaka, H. & Ohzawa, I. (2006). Neural basis for stereopsis from second-order contrast cues. Journal of Neuroscience 26, 43704382.CrossRefGoogle Scholar
Treisman, A. & Sato, S. (1990). Conjunction search revisited. Journal of Experimental Psychology: Human Perception and Performance 16, 459478.CrossRefGoogle Scholar
von der Heydt, R. & Peterhans, E. (1989). Mechanisms of contour perception in monkey visual cortex. I. Lines of pattern discontinuity. Journal of Neuroscience 9, 17311748.Google Scholar
von der Heydt, R., Peterhans, E. & Baumgartner, G. (1984). Illusory contours and cortical neuron responses. Science 224, 12601262.CrossRefGoogle Scholar
Vuilleumier, P., Henson, R.N., Driver, J. & Dolan, R.J. (2002). Multiple levels of visual object constancy revealed by event-related fMRI of repetition priming. Nature Neuroscience 5, 491499.CrossRefGoogle Scholar
Wilson, H.R. & Wilkinson, F. (1998). Detection of global structure in Glass patterns: Implications for form vision. Vision Research 38, 29332947.CrossRefGoogle Scholar
Wilson, H.R. & Richards, W.A. (1992). Curvature and separation discrimination at texture boundaries. Journal of the Optical Society of America A 9, 16531662.CrossRefGoogle Scholar
Wilson, H.R. (1999). Non-Fourier cortical processes in texture, form, and motion perception. In Cerebral Cortex: Models of Cortical Circuitry, ed. Ulinski, P.S. & Jones, E.G., pp. 445477. New York: Kluwer Academic/Plenum.CrossRef
Wilson, H.R., Wilkinson, F. & Asaad, W. (1997). Concentric orientation summation in human form vision. Vision Research 37, 23252330.CrossRefGoogle Scholar
Wolfe, J.M. & Cave, K.R. (1999). The psychophysical evidence for a binding problem in human vision. Neuron 24, 1117.CrossRefGoogle Scholar
Zeki, S. (1993). A vision of the brain. 380 pp. Boston: Blackwell Scientific Publications.
Zeki, S.M. (1978). Functional specialisation in the visual cortex of the rhesus monkey. Nature 274, 423428.CrossRefGoogle Scholar
Zeki, S., Perry, R.J. & Bartels, A. (2003). The processing of kinetic contours in the brain. Cerebral Cortex 13, 189202.CrossRefGoogle Scholar
Zhan, C.A. & Baker, C.L., Jr. (2006). Boundary cue invariance in cortical orientation maps. Cerebral Cortex 16, 896906.Google Scholar
Zhou, Y.F., Jia, F., Tao, H.Y. & Shou, T.D. (2001). The responses to illusory contours of neurons in cortex areas 17 and 18 of the cats. C-Life Sciences 44, 136145.CrossRefGoogle Scholar
Zhou, Y.X. & Baker, C.L., Jr. (1993). A processing stream in mammalian visual cortex neurons for non-Fourier responses. Science 261, 98101.CrossRefGoogle Scholar
Zhou, Y.X. & Baker, C.L., Jr. (1996). Spatial properties of envelope-responsive cells in area 17 and 18 neurons of the cat. Journal of Neurophysiology 75, 10381050.Google Scholar