Abstract
A general principle of cortical architecture is the bidirec- tional flow of information along feedforward and feedback connections. In the feedforward path, converging connections mainly define the fea- ture detection characteristics of cells. The computational role of feedback connections, on the contrary, is largely unknown. Based on empirical find- ings we suggest that top-down feedback projections modulate activity of target cells in a context dependent manner. The context is represented by the spatial extension and direction of long-range connections. In this scheme, bottom-up activity which is consistent in a more global context is enhanced, inconsistent activity is suppressed. We present two instantia- tions of this general scheme having complementary functionality, namely a model of cortico-cortical V1-V2 interactions and a model of recurrent intracortical V1 interactions. The models both have long-range interac- tions for the representation of contour shapes and modulating feedback in common. They differ in their response properties to illusory contours and corners, and in the details of computing the bipole filter which models the long-range connections. We demonstrate that the models are capable of basic processing tasks in vision, such as, e.g., contour enhancement, noise suppression and corner detection. Also, a variety of perceptual phe- such as grouping of fragmented shape outline and interpolation nomena of illusory contours can be explained.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
I. Biederman. Human image understanding: Recent research and a theory. CVGIP, 32(1):29–73, 1985.
J. Bolz, C.D. Gilbert, and T. Wiesel. Pharmacological analysis of cortical circuitry. TINS, 12(8):292–296, 1989.
J. Bullier, M.E. McCourt, and G.H. Henry. Physiological studies on the feedback connection to the striate cortex from cortical areas 18 and 19 of the cat. Exp. Brain Res., 70:90–98, 1988.
F. Crick and C. Koch. Why is the a hierarchy of visual cortical and thalamic areas: The no-strong loops hypothesis. Nature, 391:245–250, 1998.
A. Das and C. Gilbert. Topography of contextual modulations mediated by short-range interactions in primary visual cortex. Nature, 399:655–661, 1999.
D.J. Field, A. Hayes, and R.F. Hess. Contour integration by the human visual system: Evidence for local “association field”. Vision Res., 33(2):173–193, 1993.
L.H. Finkel and G.M. Edelman. Integration of distributed cortical systems by reentry: A computer simulation of interactive functionally segregated visual areas. J. Neurosci., 9(9):3188–3208, 1989.
L.H. Finkel and P. Sajda. Object discrimination based on depth-from-occlusion. Neural Comput., 4:901–921, 1992.
C. Gilbert. Horizontal integration and cortical dynamics. Neuron, 9:1–13, 1992.
C.D. Gilbert. Circuitry, architecture, and functional dynamics of visual cortex. Cereb. Cortex, 3(5):373–386, Sep/Oct 1993.
C.D. Gilbert and T.N. Wiesel. Clustered intrinsic connections in cat visual cortex. J. Neurosci., 3:1116–1133, 1983.
C.D. Gilbert and T.N. Wiesel. Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex. J. Neurosci., 9(7):2432–2442, 1989.
A. Gove, S. Grossberg, and E. Mingolla. Brightness perception, illusory contours and corticogeniculate feedback. In Proc. World Conference on Neural Networks (WCNN-93), Vol. I-IV, pages (I) 25–28, Portland (Oreg./USA), July 11-15 1993.
S. Grossberg. How does a brain build a cognitive code? Psych. Rev., 87:1–51, 1980.
S. Grossberg and E. Mingolla. Neural dynamics of perceptual grouping: Textures, boundaries, and emergent segmentation. Percept. Psychophys., 38:141–171, 1985.
S. Grossberg, E. Mingolla, and W.D. Ross. Visual brain and visual perception: how does the cortex do perceptual grouping? TINS, 20(3):106–111, 1997.
T. Hansen and H. Neumann. A model of V1 visual contrast processing utilizing long-range connections and recurrent interactions. In Proc. ICANN, pages 61–66, Edinburgh, UK, Sept. 7-10 1999.
F. Heitger, R. von der Heydt, E. Peterhans, L. Rosenthaler, and O. Kübler. Simulation of neural contour mechanisms: Representing anomalous contours. Image Vis. Comp., 16:407–421, 1998.
J.A. Hirsch and C.D. Gilbert. Synaptic physiology of horizontal connections in the cat’s visual cortex. J. Neurosci., 11(6):1800–1809, June 1991.
J.M. Hupé, A.C. James, B.R. Payne, S.G. Lomber, P. Girard, and J. Bullier. Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons. Nature, 394:784–787, Aug. 1998.
G. Kanizsa. Percezione attuale, esperienza passata l‘“esperimento impossible”. In G. Kanizsa and G. Vicario, editors, Ricerche sperimentali sulla percezione., pages 9–47. Universitá degli studi, Triente, 1968.
G. Kanizsa. Subjective contours. Sci. Am., 234(4):48–52, 1976.
M.K. Kapadia, M. Ito, C.D. Gilbert, and G. Westheimer. Improvement in visual sensitivity by changes in local context: Parallel studies in human observers and in V1 of alert monkeys. Neuron, 15:843–856, Oct. 1995.
J.J. Knierim and D.C. Van Essen. Neuronal responses to static texture patterns in area V1 of the alert macaque monkey. J. Neurophys., 67(4):961–980, 1992.
G.W. Lesher and E. Mingolla. The role of edges and line-ends in illusory contour formation. Vision Res., 33(16):2253–2270, 1993.
Z. Li. Pre-attentive segmentation in the primary visual cortex. M.I.T. A.I. Lab., Memo No. 1640, 1998.
M. Livingstone and D. Hubel. Anatomy and physiology of a color system in the primate visual cortex. J. Neurosci., 4(1):309–356, 1984.
D. Mumford. On the computational architecture of the neocortex II: The role of cortico-cortical loops. Biol. Cybern., 65:241–251, 1991.
H. Neumann and W. Sepp. Recurrent V1-V2 interaction in early visual boundary processing. Biol. Cybern., 81:425–444, 1999.
E. Peterhans and R. von der Heydt. Mechanisms of contour perception in monkey visual cortex. II. Contours bridging gaps. J. Neurosci., 9(5):1749–1763, 1989.
E. Peterhans and R. von der Heydt. Subjective contours-bridging the gap between psychophysics and physiology. TINS, 14(3):112–119, 1991.
U. Polat and D. Sagi. The arcitecture of perceptual spatial interactions. Vision Res., 34:73–78, 1994.
K. Prazdny. Illusory contours are not caused by simultaneous brightness contrast. Percept. Psychophys., 34(4):403–404, 1983.
K. Rockland and A. Virga. Terminal arbors of individual “feedback” axons projecting from area V2 to V1 in the macaque monkey: A study using immunohistochemistry of anterogradely transported Phaseolus vulgaris-lencoagglunitin. J. Comp. Neurol., 285:54–72, 1989.
P.-A. Salin and J. Bullier. Corticocortical connections in the visual system: Structure and function. Physiol. Rev., 75(1):107–154, 1995.
J. Sandell and P. Schiller. Effect of cooling area 18 on striate cortex cells in the squirrel monkey. J. Neurophys., 48(1):38–48, 1982.
K. Schmidt, R. Goebel, S. Löwel, and W. Singer. The perceptual grouping criterion of colinearity is reflected by anisotropies of connections in the primary visual cortex. Europ. J. Neurosci., 9:1083–1089, 1997.
T.F. Shipley and P.J. Kellman. The role of discontinuities in the perception of subjective figures. Percept. Psychophys., 48(3):259–270, 1990.
T.F. Shipley and P.J. Kellman. Strength of visual interpolation depends on the ratio of physically specified to total edge length. Percept. Psychophys., 52(1):97–106, 1992.
S. Ullman. Sequence of seeking and counter streams: A computational model for bidirectional information flow in the visual cortex. Cereb. Cortex, 2:310–335, 1995.
R. von der Heydt, F. Heitger, and E. Peterhans. Perception of occluding contours: Neural mechanisms and a computational model. Biomed. Res., 14:1–6, 1993.
R. von der Heydt and E. Peterhans. Mechanisms of contour perception in monkey visual cortex. I. Lines of pattern discontinuity. J. Neurosci., 9(5):1731–1748, 1989.
R. von der Heydt, E. Peterhans, and G. Baumgartner. Illusory contours and cortical neuron responses. Science, 224:1260–1262, 1984.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Hansen, T., Sepp, W., Neumann, H. (2001). Recurrent Long-Range Interactions in Early Vision. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_9
Download citation
DOI: https://doi.org/10.1007/3-540-44597-8_9
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42363-8
Online ISBN: 978-3-540-44597-5
eBook Packages: Springer Book Archive