Shape Representation in Area V4: Position-Specific Tuning for Boundary Conformation
Abstract
Visual shape recognition in primates depends on a multi-stage pathway running from primary visual cortex (V1) to inferotemporal cortex (IT). The mechanisms by which local shape signals from V1 are transformed into selectivity for abstract object categories in IT are unknown. One approach to this issue is to investigate shape representation at intermediate stages in the pathway, such as area V4. We studied 109 V4 cells that appeared sensitive to complex shape in preliminary tests. To achieve a more complete picture of shape representation in V4, we tested each cell with a set of 366 stimuli, constructed by systematically combining convex and concave boundary elements into closed shapes. Using this large, diverse stimulus set, we found that all the cells in our sample responded to a wide variety of shapes and did not appear to encode any single type of global shape. However, for most cells the shapes evoking strongest responses were characterized by a consistent type of boundary conformation at a specific position within the stimulus. For example, a given cell might be tuned for shapes containing concave curvature at the right, with other parts of the shape having little or no effect on responses. Many cells were tuned for more complex boundary configurations (e.g., a convex angle adjacent to a concave curve). We quantified this kind of shape tuning with Gaussian functions on a curvature × position domain. These tuning functions fit the neural responses much better than tuning functions based on edge or axis orientation. Thus individual V4 cells appear to encode moderately complex boundary information at specific locations within larger shapes. This finding suggests that, at intermediate stages in the V1-IT transformation, complex objects are represented at least partly in terms of the configurations and positions of their contour components.
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Some C2 units in the model show a tuning for boundary conformations consistent with recordings from V4.
“some of the C 2 units in the model show a tuning for boundary conformations which is consistent with recordings from V4 (29)”
From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [29]
Cites
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783 · see citing works
Receptive fields and functional architecture of monkey striate cortex
Hubel, D. H., & Wiesel, T. N. (1968) · The Journal of Physiology · doi:10.1113/jphysiol.1968.sp008455 · Cited by 6,520 · see citing works
Recognition-by-components: A theory of human image understanding.
Biederman, I. (1987) · Psychological Review · doi:10.1037/0033-295x.94.2.115 · Cited by 5,621 · see citing works
Ungerleider, L. G. (1982) · Medical Entomology and Zoology · Cited by 4,531 · see citing works
Ingle, D., Goodale, M. A., & Mansfield, R. J. W. (1982) · The MIT Press eBooks · Cited by 4,118 · see citing works
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309 · see citing works
A Method of Measuring Eye Movemnent Using a Scieral Search Coil in a Magnetic Field
Robinson, D. A. (1963) · IEEE Transactions on Bio-medical Electronics · doi:10.1109/tbmel.1963.4322822 · Cited by 2,214 · see citing works
Representation and recognition of the spatial organization of three-dimensional shapes
Marr, D., & Nishihara, H. K. (1978) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.1978.0020 · Cited by 2,159 · see citing works
A method of measuring eye movements using a scleral search coil in a magnetic field
Robinson, D. A. (1963) · Medical Entomology and Zoology · Cited by 1,709 · see citing works
Implantation of magnetic search coils for measurement of eye position: An improved method
Judge, S. J., Richmond, B. J., & Chu, F. C. (1980) · Vision Research · doi:10.1016/0042-6989(80)90128-5 · Cited by 1,545 · see citing works
Hoffman, D. D., & Richards, W. A. (1984) · Cognition · doi:10.1016/0010-0277(84)90022-2 · Cited by 1,352 · see citing works
Kobatake, E., & Tanaka, K. (1994) · Journal of Neurophysiology · doi:10.1152/jn.1994.71.3.856 · Cited by 807 · see citing works
Coding visual images of objects in the inferotemporal cortex of the macaque monkey
Tanaka, K., Saito, H., Fukada, Y., & Moriya, M. (1991) · Journal of Neurophysiology · doi:10.1152/jn.1991.66.1.170 · Cited by 773 · see citing works
Coding of Border Ownership in Monkey Visual Cortex
Zhou, H., Friedman, H. S., & von der Heydt, R. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-17-06594.2000 · Cited by 727 · see citing works
Visual properties of neurons in area V4 of the macaque: sensitivity to stimulus form
Desimone, R., & Schein, S. (1987) · Journal of Neurophysiology · doi:10.1152/jn.1987.57.3.835 · Cited by 681 · see citing works
Visuotopic organization and extent of V3 and V4 of the macaque
Gattass, R., Sousa, A., & Gross, C. (1988) · The Journal of Neuroscience · doi:10.1523/jneurosci.08-06-01831.1988 · Cited by 676 · see citing works
Aligning pictorial descriptions: An approach to object recognition
Ullman, S. (1989) · Cognition · doi:10.1016/0010-0277(89)90036-x · Cited by 562 · see citing works
Responses to Contour Features in Macaque Area V4
Pasupathy, A., & Connor, C. E. (1999) · Journal of Neurophysiology · doi:10.1152/jn.1999.82.5.2490 · Cited by 548 · see citing works
Self-citationSelectivity for Polar, Hyperbolic, and Cartesian Gratings in Macaque Visual Cortex
Gallant, J. L., Braun, J., & Essen, D. C. V. (1993) · Science · doi:10.1126/science.8418487 · Cited by 526 · see citing works
Spatial Attention Effects in Macaque Area V4
Connor, C. E., Preddie, D. C., Gallant, J. L., & Van Essen, D. C. (1997) · The Journal of Neuroscience · doi:10.1523/jneurosci.17-09-03201.1997 · Cited by 448 · see citing works
Self-citationNeural responses to polar, hyperbolic, and Cartesian gratings in area V4 of the macaque monkey
Gallant, J. L., Connor, C. E., Rakshit, S., Lewis, J. W., & Essen, D. C. V. (1996) · Journal of Neurophysiology · doi:10.1152/jn.1996.76.4.2718 · Cited by 443 · see citing works
Self-citationRichmond, B. J., Optican, L. M., Podell, M., & Spitzer, H. (1987) · Journal of Neurophysiology · doi:10.1152/jn.1987.57.1.132 · Cited by 428 · see citing works
Shape recognition and inferior temporal neurons.
Schwartz, E., Desimone, R., Albright, T. D., & Gross, C. G. (1983) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.80.18.5776 · Cited by 328 · see citing works
Selectivity for Complex Shapes in Primate Visual Area V2
Hegdé, J., & Essen, D. C. V. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-05-j0001.2000 · Cited by 325 · see citing works
Endstopped neurons in the visual cortex as a substrate for calculating curvature
Dobbins, A. C., Zucker, S. W., & Cynader, M. S. (1987) · Nature · doi:10.1038/329438a0 · Cited by 296 · see citing works
Wilkinson, F. E., James, T. W., Wilson, H. R., Gati, J. S., Menon, R. S., & Goodale, M. A. (2000) · Current Biology · doi:10.1016/s0960-9822(00)00800-9 · Cited by 272 · see citing works
Concentric orientation summation in human form vision
Wilson, H. R., Wilkinson, F. E., & Asaad, W. F. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00104-1 · Cited by 250 · see citing works
Macaque inferior temporal neurons are selective for disparity-defined three-dimensional shapes
Janssen, P., Vogels, R., & Orban, G. A. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.14.8217 · Cited by 189 · see citing works
Parsing silhouettes: The short-cut rule
Singh, M., Seyranian, G. D., & Hoffman, D. D. (1999) · Perception & Psychophysics · doi:10.3758/bf03205536 · Cited by 179 · see citing works
From volumes to views: An approach to 3-D object recognition
Dickinson, S., Pentland, A., & Rosenfeld, A. (1992) · CVGIP Image Understanding · doi:10.1016/1049-9660(92)90013-s · Cited by 143 · see citing works
Convexity and Symmetry in Figure-Ground Organization
Kanizsa, W., & Gerbino, W. (1976) · ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) · Cited by 138 · see citing works
Form Processing Modules in Primate Area V4
Ghose, G. M., & Ts’o, D. Y. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.4.2191 · Cited by 125 · see citing works
Contour curvature analysis: Hyperacuities in the discrimination of detailed shape
Watt, R. J., & Andrews, D. P. (1982) · Vision Research · doi:10.1016/0042-6989(82)90193-6 · Cited by 117 · see citing works
Distance Modulation of Neural Activity in the Visual Cortex
Dobbins, A. C., Jeo, R. M., Fiser, J., & Allman, J. M. (1998) · Science · doi:10.1126/science.281.5376.552 · Cited by 115 · see citing works
Parts of Visual Objects: An Experimental Test of the Minima Rule
Braunstein, M. L., Hoffman, D. D., & Saidpour, A. (1989) · Perception · doi:10.1068/p180817 · Cited by 81 · see citing works
Disparity tuning in macaque area V4
Hinkle, D. A., & Connor, C. E. (2001) · Neuroreport · doi:10.1097/00001756-200102120-00036 · Cited by 70 · see citing works
Self-citationHanazawaᎂᎂ, A., & Komatsu, H. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-12-04490.2001 · Cited by 68 · see citing works
Angle judgment: Is the whole the sum of its parts?
Chen, S., & Levi, D. M. (1996) · Vision Research · doi:10.1016/0042-6989(95)00245-6 · Cited by 61 · see citing works
View-based Models of 3D Object Recognition: Invariance to Imaging Transformations
Vetter, T., Hurlbert, A. C., & Poggio, T. (1995) · Cerebral Cortex · doi:10.1093/cercor/5.3.261 · Cited by 59 · see citing works
Responses of visual cortical neurons to curved stimuli and chevrons
Versavel, M., Orban, G. A., & Lagae, L. G. (1990) · Vision Research · doi:10.1016/0042-6989(90)90039-n · Cited by 53 · see citing works
Mechanisms Specialized for the Perception of Image Geometry
Heeley, D. W., & Buchanan‐Smith, H. M. (1996) · Vision Research · doi:10.1016/0042-6989(96)00077-6 · Cited by 51 · see citing works
Evidence for a neural mechanism that encodes angles
Regan, D., Gray, R. C., & Hamstra, S. J. (1996) · Vision Research · doi:10.1016/0042-6989(95)00113-e · Cited by 51 · see citing works
Attentional frames, frame curves and figural boundaries: The inside/outside dilemma
Subirana-Vilanova, J. B., & Richards, W. (1996) · Vision Research · doi:10.1016/0042-6989(95)00274-x · Cited by 24 · see citing works
Responses of striate cortical cells to moving edges of different curvatures
Heggelund, P., & Hohmann, A. (1975) · Experimental Brain Research · doi:10.1007/bf00235462 · Cited by 15 · see citing works
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Population coding of shape in area V4
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- Authors
- Pasupathy, A., & Connor, C. E.
- Affiliations
- Johns Hopkins University (US)
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2001-11-01
- Volume
- 86
- Issue
- 5
- Pages
- 2505-2519
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- OpenAlex
- W1777366511
- Cited by
- 483
- References
- 44
- Citations by year
- 2026: 19 · 2025: 12 · 2024: 23 · 2023: 19 · 2022: 16 · 2021: 18 · 2020: 17 · 2019: 21 · 2018: 23 · 2017: 10 · 2016: 15 · 2015: 25 · 2014: 28 · 2013: 19 · 2012: 31
- FWCI
- 4.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Neurophysiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Neurological Disorders and Stroke (NS 38034, P01NS038034)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
- Keywords
- area V4, complex shapes, single neuron responses, visual cortex
- MeSH terms
- Animals, Electrophysiology, Female, Form Perception, Macaca mulatta, Neurons, Afferent, Photic Stimulation, Visual Cortex, Visual Pathways
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