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Contour detection model based on neuron behaviour in primary visual cortex

Contour detection model based on neuron behaviour in primary visual cortex

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In the mammalian primary visual cortex, the response of the classical receptive field (CRF) to visual stimuli can be suppressed by inhibition of non-CRF (nCRF) neurons. Although many biologically plausible models based on these centre–surround interaction properties have been proposed, most of these models have failed to account for two important behaviours of neurons in the primary visual cortex (V1). First, saturation properties of neuron response. Second, the properties of fixational eye movements (FEyeMs). In the present study, the authors proposed a biologically motivated counter detection approach based on these properties. The authors’ work is significant in that they utilised a simple threshold method to ensure that CRF responses were observed within a meaningful range, and multichannel filter bank was proposed to simulate the influence of FEyeMs on nCRF. Both methods effectively preserved object contours and inhibition isolated textures. Extensive experiments indicated that the authors’ model can preserve more object contours and suppress more textures than previous biologically based models.

References

    1. 1)
      • D.H. Hubel , T.N. Wiesel .
        1. Hubel, D.H., Wiesel, T.N.: ‘Receptive fields of single neurones in the cat's striate cortex’, J. Physiol., 1959, 148, (3), pp. 574591.
        . J. Physiol. , 3 , 574 - 591
    2. 2)
      • D.H. Hubel , T.N. Wiesel .
        2. Hubel, D.H., Wiesel, T.N.: ‘Receptive fields, binocular interaction and functional architecture in the cat's visual cortex’, J. Physiol., 1962, 160, (1), pp. 106154.
        . J. Physiol. , 1 , 106 - 154
    3. 3)
      • C. Enroth-Cugell , H. Jakiela .
        3. Enroth-Cugell, C., Jakiela, H.: ‘Suppression of cat retinal ganglion cell responses by moving patterns’, J. Physiol., 1980, 302, p. 49.
        . J. Physiol. , 49
    4. 4)
      • F.S. Werblin .
        4. Werblin, F.S.: ‘Lateral interactions at inner plexiform layer of vertebrate retina: antagonistic responses to change’, Science, 1972, 175, (4025), pp. 10081010.
        . Science , 4025 , 1008 - 1010
    5. 5)
      • M.K. Kapadia , G. Westheimer , C.D. Gilbert .
        5. Kapadia, M.K., Westheimer, G., Gilbert, C.D.: ‘Spatial distribution of contextual interactions in primary visual cortex and in visual perception’, J. Neurophysiol., 2000, 84, (4), pp. 20482062.
        . J. Neurophysiol. , 4 , 2048 - 2062
    6. 6)
      • H. Jones , K. Grieve , W. Wang .
        6. Jones, H., Grieve, K., Wang, W., et al: ‘Surround suppression in primate V1’, J. Neurophysiol., 2001, 86, (4), pp. 20112028.
        . J. Neurophysiol. , 4 , 2011 - 2028
    7. 7)
      • L. Chao-Yi , L. Wu .
        7. Chao-Yi, L., Wu, L.: ‘Extensive integration field beyond the classical receptive field of cat's striate cortical neurons –classification and tuning properties’, Vis. Res., 1994, 34, (18), pp. 23372355.
        . Vis. Res. , 18 , 2337 - 2355
    8. 8)
      • C.-Y. Li .
        8. Li, C.-Y.: ‘Integration fields beyond the classical receptive field: organization and functional properties’, Physiology, 1996, 11, (4), pp. 181186.
        . Physiology , 4 , 181 - 186
    9. 9)
      • G.A. Walker , I. Ohzawa , R.D. Freeman .
        9. Walker, G.A., Ohzawa, I., Freeman, R.D.: ‘Suppression outside the classical cortical receptive field’, Vis. Neurosci., 2000, 17, (03), pp. 369379.
        . Vis. Neurosci. , 3 , 369 - 379
    10. 10)
      • M.K. Kapadia , M. Ito , C.D. Gilbert .
        10. Kapadia, M.K., Ito, M., Gilbert, C.D., et al: ‘Improvement in visual sensitivity by changes in local context: parallel studies in human observers and in V1 of alert monkeys’, Neuron, 1995, 15, (4), pp. 843856.
        . Neuron , 4 , 843 - 856
    11. 11)
      • U. Polat , K. Mizobe , M.W. Pettet .
        11. Polat, U., Mizobe, K., Pettet, M.W., et al: ‘Collinear stimuli regulate visual responses depending on cell's contrast threshold’, Nature, 1998, 391, (6667), pp. 580584.
        . Nature , 6667 , 580 - 584
    12. 12)
      • J.J. Knierim , D.C. Van Essen .
        12. Knierim, J.J., Van Essen, D.C.: ‘Neuronal responses to static texture patterns in area V1 of the alert macaque monkey’, J. Neurophysiol., 1992, 67, (4), pp. 961980.
        . J. Neurophysiol. , 4 , 961 - 980
    13. 13)
      • J.B. Levitt , J.S. Lund .
        13. Levitt, J.B., Lund, J.S.: ‘Contrast dependence of contextual effects in primate visual cortex’, Nature, 1997, 387, (6628), pp. 7376.
        . Nature , 6628 , 73 - 76
    14. 14)
      • D.C. Somers , S.B. Nelson , M. Sur .
        14. Somers, D.C., Nelson, S.B., Sur, M.: ‘An emergent model of orientation selectivity in cat visual cortical simple cells’, J. Neurosci., 1995, 15, (8), pp. 54485465.
        . J. Neurosci. , 8 , 5448 - 5465
    15. 15)
      • A. Das , C.D. Gilbert .
        15. Das, A., Gilbert, C.D.: ‘Topography of contextual modulations mediated by short-range interactions in primary visual cortex’, Nature, 1999, 399, (6737), pp. 655661.
        . Nature , 6737 , 655 - 661
    16. 16)
      • V. Dragoi , M. Sur .
        16. Dragoi, V., Sur, M.: ‘Dynamic properties of recurrent inhibition in primary visual cortex: contrast and orientation dependence of contextual effects’, J. Neurophysiol., 2000, 83, (2), pp. 10191030.
        . J. Neurophysiol. , 2 , 1019 - 1030
    17. 17)
      • C.E. Bredfeldt , D. Ringach .
        17. Bredfeldt, C.E., Ringach, D.: ‘Dynamics of spatial frequency tuning in macaque V1’, J. Neurosci., 2002, 22, (5), pp. 19761984.
        . J. Neurosci. , 5 , 1976 - 1984
    18. 18)
      • W.-F. Xu , Z.-M. Shen , C.-Y. Li .
        18. Xu, W.-F., Shen, Z.-M., Li, C.-Y.: ‘Spatial phase sensitivity of V1 neurons in alert monkey’, Cereb. Cortex, 2005, 15, (11), pp. 16971702.
        . Cereb. Cortex , 11 , 1697 - 1702
    19. 19)
      • W.D. Ross , S. Grossberg , E. Mingolla .
        19. Ross, W.D., Grossberg, S., Mingolla, E.: ‘Visual cortical mechanisms of perceptual grouping: interacting layers, networks, columns, and maps’, Neural Netw., 2000, 13, (6), pp. 571588.
        . Neural Netw. , 6 , 571 - 588
    20. 20)
      • M. Ursino , G.E. La Cara .
        20. Ursino, M., La Cara, G.E.: ‘A model of contextual interactions and contour detection in primary visual cortex’, Neural Netw., 2004, 17, (5), pp. 719735.
        . Neural Netw. , 5 , 719 - 735
    21. 21)
      • T. Hansen , H. Neumann .
        21. Hansen, T., Neumann, H.: ‘A recurrent model of contour integration in primary visual cortex’, J. Vis., 2008, 8, (8), pp. 125.
        . J. Vis. , 8 , 1 - 25
    22. 22)
      • C. Grigorescu , N. Petkov , M.A. Westenberg .
        22. Grigorescu, C., Petkov, N., Westenberg, M.A.: ‘Contour detection based on nonclassical receptive field inhibition’, IEEE Trans. Image Process., 2003, 12, (7), pp. 729739.
        . IEEE Trans. Image Process. , 7 , 729 - 739
    23. 23)
      • N. Petkov , M.A. Westenberg .
        23. Petkov, N., Westenberg, M.A.: ‘Suppression of contour perception by band-limited noise and its relation to nonclassical receptive field inhibition’, Biol. Cybern., 2003, 88, (3), pp. 236246.
        . Biol. Cybern. , 3 , 236 - 246
    24. 24)
      • Q. Tang , N. Sang , T. Zhang .
        24. Tang, Q., Sang, N., Zhang, T.: ‘Extraction of salient contours from cluttered scenes’, Pattern Recognit., 2007, 40, (11), pp. 31003109.
        . Pattern Recognit. , 11 , 3100 - 3109
    25. 25)
      • U. Ernst , H. Van Nathalie , N. Schmitt .
        25. Ernst, U., Van Nathalie, H., Schmitt, N., et al: ‘Predicting eye movements in a contour detection task’, BMC Neurosci., 2012, 13, (Suppl. 1), p. O4.
        . BMC Neurosci. , O4
    26. 26)
      • C. Grigorescu , N. Petkov , M.A. Westenberg .
        26. Grigorescu, C., Petkov, N., Westenberg, M.A.: ‘Contour and boundary detection improved by surround suppression of texture edges’, Image Vis. Comput., 2004, 22, (8), pp. 609622.
        . Image Vis. Comput. , 8 , 609 - 622
    27. 27)
      • G. Papari , N. Petkov .
        27. Papari, G., Petkov, N.: ‘An improved model for surround suppression by steerable filters and multilevel inhibition with application to contour detection’, Pattern Recognit., 2011, 44, (9), pp. 19992007.
        . Pattern Recognit. , 9 , 1999 - 2007
    28. 28)
      • C. Zeng , Y. Li , C. Li .
        28. Zeng, C., Li, Y., Li, C.: ‘Center–surround interaction with adaptive inhibition: a computational model for contour detection’, NeuroImage, 2011, 55, (1), pp. 4966.
        . NeuroImage , 1 , 49 - 66
    29. 29)
      • C. Zeng , Y. Li , K. Yang .
        29. Zeng, C., Li, Y., Yang, K., et al: ‘Contour detection based on a non-classical receptive field model with butterfly-shaped inhibition subregions’, Neurocomputing, 2011, 74, (10), pp. 15271534.
        . Neurocomputing , 10 , 1527 - 1534
    30. 30)
      • K. Yang , Y. Li .
        30. Yang, K., Li, Y.: ‘A coutour detection model based on surround inhibition with multiple cues’, Chinese Conference on Pattern Recognition (CCPR) 2012, Beijing, China, September 24–26 2012, pp. 145152.
        . Chinese Conference on Pattern Recognition (CCPR) 2012 , 145 - 152
    31. 31)
      • H. Wei , B. Lang , Q. Zuo .
        31. Wei, H., Lang, B., Zuo, Q.: ‘Contour detection model with multi-scale integration based on non-classical receptive field’, Neurocomputing, 2013, 103, pp. 247262.
        . Neurocomputing , 247 - 262
    32. 32)
      • K.-F. Yang , C.-Y. Li , Y.-J. Li .
        32. Yang, K.-F., Li, C.-Y., Li, Y.-J.: ‘Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection’, Front. Neural Circuits, 2015, 9, pp. 30.
        . Front. Neural Circuits , 30
    33. 33)
      • K. Yang , S. Gao , C. Li .
        33. Yang, K., Gao, S., Li, C., et al: ‘Efficient color boundary detection with color-opponent mechanisms’. Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition, Portland, OR, USA, 2013.
        . Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition
    34. 34)
      • S. Gao , K. Yang , C. Li .
        34. Gao, S., Yang, K., Li, C., et al: ‘A color constancy model with double-opponency mechanisms’. Proc. of the IEEE Int. Conf. on Computer Vision, Sydney, Australia, 2013.
        . Proc. of the IEEE Int. Conf. on Computer Vision
    35. 35)
      • S.-B. Gao , K.-F. Yang , C.-Y. Li .
        35. Gao, S.-B., Yang, K.-F., Li, C.-Y., et al: ‘Color constancy using double-opponency’, IEEE Trans. Pattern Anal. Mach. Intell., 2015, 37, (10), pp. 19731985.
        . IEEE Trans. Pattern Anal. Mach. Intell. , 10 , 1973 - 1985
    36. 36)
      • K.-F. Yang , S.-B. Gao , C.-F. Guo .
        36. Yang, K.-F., Gao, S.-B., Guo, C.-F., et al: ‘Boundary detection using double-opponency and spatial sparseness constraint’, IEEE Trans. Image Process., 2015, 24, (8), pp. 25652578.
        . IEEE Trans. Image Process. , 8 , 2565 - 2578
    37. 37)
      • X.-S. Zhang , S.-B. Gao , R.-X. Li .
        37. Zhang, X.-S., Gao, S.-B., Li, R.-X., et al: ‘A retinal mechanism inspired color constancy model’, IEEE Trans. Image Process., 2016, 25, (3), pp. 12191232.
        . IEEE Trans. Image Process. , 3 , 1219 - 1232
    38. 38)
      • S. Gao , W. Han , K. Yang .
        38. Gao, S., Han, W., Yang, K., et al: ‘Efficient color constancy with local surface reflectance statistics’. European Conf. on Computer Vision, Zurich, Switzerland, 2014.
        . European Conf. on Computer Vision
    39. 39)
      • J.G. Daugman .
        39. Daugman, J.G.: ‘Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters’, JOSA A, 1985, 2, (7), pp. 11601169.
        . JOSA A , 7 , 1160 - 1169
    40. 40)
      • J.P. Jones , L.A. Palmer .
        40. Jones, J.P., Palmer, L.A.: ‘An evaluation of the two-dimensional gabor filter model of simple receptive fields in cat striate cortex’, J. Neurophysiol., 1987, 58, (6), pp. 12331258.
        . J. Neurophysiol. , 6 , 1233 - 1258
    41. 41)
      • E.R. Kandel , J.H. Schwartz , T.M. Jessell . (2000)
        41. Kandel, E.R., Schwartz, J.H., Jessell, T.M., et al: ‘Principles of neural science’ (McGraw-Hill, New York, 2000).
        .
    42. 42)
      • A.E. Pereda .
        42. Pereda, A.E.: ‘Electrical synapses and their functional interactions with chemical synapses’, Nat. Rev. Neurosci., 2014, 15, (4), pp. 250263.
        . Nat. Rev. Neurosci. , 4 , 250 - 263
    43. 43)
      • R. Krauzlis . (2008)
        43. Krauzlis, R.: ‘Eye movements’, in Squire, L.R., Berg, D. (Eds.): Fundam. Neurosci., (Academic Press, New York, 2008, 3rd edn.), pp. 775792.
        .
    44. 44)
      • C.A. Bosman , T. Womelsdorf , R. Desimone .
        44. Bosman, C.A., Womelsdorf, T., Desimone, R., et al: ‘A microsaccadic rhythm modulates gamma-band synchronization and behavior’, J. Neurosci., 2009, 29, (30), pp. 94719480.
        . J. Neurosci. , 30 , 9471 - 9480
    45. 45)
      • J.P. Hamm , K.A. Dyckman , L.E. Ethridge .
        45. Hamm, J.P., Dyckman, K.A., Ethridge, L.E., et al: ‘Preparatory activations across a distributed cortical network determine production of express saccades in humans’, J. Neurosci., 2010, 30, (21), pp. 73507357.
        . J. Neurosci. , 21 , 7350 - 7357
    46. 46)
      • M.I. Posner .
        46. Posner, M.I.: ‘Orienting of attention’, Q. J. Exp. Psychol., 1980, 32, (1), pp. 325.
        . Q. J. Exp. Psychol. , 1 , 3 - 25
    47. 47)
      • R.D. Wright , L.M. Ward . (2008)
        47. Wright, R.D., Ward, L.M.: ‘Orienting of attention’ (Oxford University Press, Oxford, 2008).
        .
    48. 48)
      • C.W. Eriksen , R.L. Colegate .
        48. Eriksen, C.W., Colegate, R.L.: ‘Selective attention and serial processing in briefly presented visual displays’, Percept. Psychophys., 1971, 10, (5), pp. 321326.
        . Percept. Psychophys. , 5 , 321 - 326
    49. 49)
      • G.G. Gregoriou , S.J. Gotts , H. Zhou .
        49. Gregoriou, G.G., Gotts, S.J., Zhou, H., et al: ‘High-frequency, long-range coupling between prefrontal and visual cortex during attention’, Science, 2009, 324, (5931), pp. 12071210.
        . Science , 5931 , 1207 - 1210
    50. 50)
      • A. Yarbus . (1967)
        50. Yarbus, A.: ‘Eye Movements During Perception of Complex Objects’, in Yarbus, A. (Ed.): Eye Mov. Vis., (Springer, Boston, MA, USA, 1967), pp. 171211.
        .
    51. 51)
      • R.H. Carpenter . (1988)
        51. Carpenter, R.H.: ‘Movements of the eyes (2nd Rev)’ (Pion Limited, London, 1988).
        .
    52. 52)
      • M. Rolfs .
        52. Rolfs, M.: ‘Microsaccades: small steps on a long way’, Vis. Res., 2009, 49, (20), pp. 24152441.
        . Vis. Res. , 20 , 2415 - 2441
    53. 53)
      • M. Greschner , M. Bongard , P. Rujan .
        53. Greschner, M., Bongard, M., Rujan, P., et al: ‘Retinal ganglion cell synchronization by fixational eye movements improves feature estimation’, Nat. Neurosci., 2002, 5, (4), pp. 341347.
        . Nat. Neurosci. , 4 , 341 - 347
    54. 54)
      • S. Martinez-Conde , S.L. Macknik , D.H. Hubel .
        54. Martinez-Conde, S., Macknik, S.L., Hubel, D.H.: ‘The function of bursts of spikes during visual fixation in the awake primate lateral geniculate nucleus and primary visual cortex’, Proc. Natl Acad. Sci. USA, 2002, 99, (21), pp. 1392013925.
        . Proc. Natl Acad. Sci. USA , 21 , 13920 - 13925
    55. 55)
      • S. Martinez-Conde , S.L. Macknik , D.H. Hubel .
        55. Martinez-Conde, S., Macknik, S.L., Hubel, D.H.: ‘Microsaccadic eye movements and firing of single cells in the striate cortex of macaque monkeys’, Nat. Neurosci., 2000, 3, (3), pp. 251258.
        . Nat. Neurosci. , 3 , 251 - 258
    56. 56)
      • W. Bair , L.P. O'keefe .
        56. Bair, W., O'keefe, L.P.: ‘The influence of fixational eye movements on the response of neurons in area Mt of the macaque’, Vis. Neurosci., 1998, 15, (04), pp. 779786.
        . Vis. Neurosci. , 4 , 779 - 786
    57. 57)
      • D.A. Leopold , N.K. Logothetis .
        57. Leopold, D.A., Logothetis, N.K.: ‘Microsaccades differentially modulate neural activity in the striate and extrastriate visual cortex’, Exp. Brain Res., 1998, 123, (3), pp. 341345.
        . Exp. Brain Res. , 3 , 341 - 345
    58. 58)
      • D.M. Snodderly , I. Kagan , M. Gur .
        58. Snodderly, D.M., Kagan, I., Gur, M.: ‘Selective activation of visual cortex neurons by fixational eye movements: implications for neural coding’, Vis. Neurosci., 2001, 18, (2), pp. 259277.
        . Vis. Neurosci. , 2 , 259 - 277
    59. 59)
      • L.A. Riggs , F. Ratliff , J.C. Cornsweet .
        59. Riggs, L.A., Ratliff, F., Cornsweet, J.C., et al: ‘The disappearance of steadily fixated visual test objects’, JOSA, 1953, 43, (6), pp. 495501.
        . JOSA , 6 , 495 - 501
    60. 60)
      • F. Ratliff , L.A. Riggs .
        60. Ratliff, F., Riggs, L.A.: ‘Involuntary motions of the eye during monocular fixation’, J. Exp. Psychol., 1950, 40, (6), p. 687.
        . J. Exp. Psychol. , 6 , 687
    61. 61)
      • R. Ditchburn , B. Ginsborg .
        61. Ditchburn, R., Ginsborg, B.: ‘Involuntary eye movements during fixation’, J. Physiol., 1953, 119, (1), p. 1.
        . J. Physiol. , 1 , 1
    62. 62)
      • T.N. Cornsweet .
        62. Cornsweet, T.N.: ‘Determination of the stimuli for involuntary drifts and saccadic eye movements’, JOSA, 1956, 46, (11), pp. 987993.
        . JOSA , 11 , 987 - 993
    63. 63)
      • R. Ditchburn .
        63. Ditchburn, R.: ‘The function of small saccades’, Vis. Res., 1980, 20, (3), pp. 271272.
        . Vis. Res. , 3 , 271 - 272
    64. 64)
      • J. Canny .
        64. Canny, J.: ‘A computational approach to edge detection’, IEEE Trans. Pattern Analysis Machine Intell., 1986, 8, (6), pp. 679698.
        . IEEE Trans. Pattern Analysis Machine Intell. , 6 , 679 - 698
    65. 65)
      • C. Lin , G. Xu , Y. Cao .
        65. Lin, C., Xu, G., Cao, Y., et al: ‘Improved contour detection model with spatial summation properties based on nonclassical receptive field’, J. Electron. Imaging, 2016, 25, (4), pp. 043018043018.
        . J. Electron. Imaging , 4 , 043018 - 043018
    66. 66)
      • D. Martin , C. Fowlkes , D. Tal .
        66. Martin, D., Fowlkes, C., Tal, D., et al: ‘A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics’. Computer Vision, 2001. ICCV 2001. Proc. Eighth IEEE Int. Conf. on, IEEE, Vancouver, Canada, 2001.
        . Computer Vision, 2001. ICCV 2001. Proc. Eighth IEEE Int. Conf. on, IEEE
    67. 67)
      • M.W. Spratling .
        67. Spratling, M.W.: ‘Image segmentation using a sparse coding model of cortical area V1’, IEEE Trans. Image Process., 2013, 22, (4), pp. 16311643.
        . IEEE Trans. Image Process. , 4 , 1631 - 1643
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