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A Multiple Sub-regions Design of non-Classical Receptive Field

  • Hui Wei
  • Heng Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)

Abstract

The non-classical receptive field (nCRF) is a large area outside the classical receptive field (CRF). Stimulating such area alone fails to elicit neural responses but can modulate the neural response to CRF stimulation. The receptive field (RF) of retinal ganglion cell (GC) also has such a property and can vary with the different visual stimuli. Previous nCRF models are mainly based on fixed RF whose dynamic characteristics are overlooked. In this paper, we establish a multilayer neural computation model with feedback for the basic structure of nCRF, and use it to simulate the mechanisms of fixation eye movements to ascertain the properties of the stimuli within adjacent areas. In our model, GC’s RF can dynamically and self-adaptively adjust its size according to stimulus properties. RF becomes smaller in areas where the image details need distinguishing and larger where the image information has no obvious difference. The experimental results fully reflect these dynamic characteristics.

Keywords

nCRF multiple sub-regions self-adaptive image processing 

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References

  1. 1.
    Ikeda, H., Wright, M.J.: The outer disinhibitory surround of the retinal ganglion cell receptive field. J. Physiol. 226, 511–544 (1972)Google Scholar
  2. 2.
    Krüger, J., Fischer, B.: Strong periphery effect in cat retinal ganglion cells. Excitatory responses in ON- and OFF-center neurons to single grid displacements. Exp. Brain Res. 18, 316–318 (1973)Google Scholar
  3. 3.
    Sun, C.: Spatial Property of Extraclassical Receptive Field of the Relay Cells in Cat’s Dorsal Lateral Geniculate Nucleus and its Interaction with the Classical Receptive Field, PhD thesis, Fudan University (2004)Google Scholar
  4. 4.
    Li, Z., et al.: A New Computational Model of Retinal Ganglion Cell Receptive Fields-I. A Model of Ganglion Cell Receptive Fields with Extended Disinhibitory Area. Biophysica Sinica 16 (2000)Google Scholar
  5. 5.
    Ghosh, K., Sarkar, S., Bhaumik, K.: A possible explanation of the low-level brightness–contrast illusions in the light of an extended classical receptive field model of retinal ganglion cells. Biological Cybernetics 94, 89–96 (2006)zbMATHCrossRefGoogle Scholar
  6. 6.
    Qiu, F.T., Li, C.Y.: Mathematical simulation of disinhibitory properties of concentric receptive field. Acta Biophysica Sinica 11, 214–220 (1995)Google Scholar
  7. 7.
    Li, C.Y.: New Advances in Neuronal Mechanisms of Image Information Processing. Bulletin of National Natural Science Foundation of China 3, 201–204 (1997)Google Scholar
  8. 8.
    Ruderman, D.L., et al.: Statistics of natural images: scaling in the woods. Phys. Rev. Lett. 73, 814–817 (1994)CrossRefGoogle Scholar
  9. 9.
    Vinje, W.E., Gallant, J.L.: Natural stimulation of the nonclassical receptive field increases information transmission efficiency in V1. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 22(7), 2904–2915 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hui Wei
    • 1
  • Heng Wu
    • 1
  1. 1.School of Computer Science, Laboratory of Cognitive Model and AlgorithmFudan UniversityShanghaiChina

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