## A Simple Cell Model With Dominating Opponent Inhibition for Robust Contrast Detection (2000)

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Venue: | Kognitionswissenschaft |

Citations: | 7 - 2 self |

### BibTeX

@ARTICLE{Hansen00asimple,

author = {Thorsten Hansen and Gregory Baratoff and Heiko Neumann},

title = {A Simple Cell Model With Dominating Opponent Inhibition for Robust Contrast Detection},

journal = {Kognitionswissenschaft},

year = {2000},

volume = {9},

pages = {93--100}

}

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### Abstract

ist m oglicherweise der Grund f ur die physiologisch gemessene dominante Inhibition und f ur die Repr asentation von Kontrastinformation in zwei komplement aren Dom anen. Basierend auf diesen Ergebnissen stellen wir die Hypothese auf, dass dominante opponente Inhibition im visuellen System verwendet wird, um in verrauschten Umgebungen Kontraste robust extrahieren zu k onnen. Summary. In the primary visual pathway, information is represented in two distinct, complementary domains, namely "on" and "off" cells. In this work we examine how on and off cells may interact to form the input to simple cell subfields. On the basis of physiological evidence, we propose a mechanism of dominating opponent inhibition, where a simple cell subfield is driven by both on and off domains, receiving more heavily weighted input from the opponent pathway. We demonstrate that the model can account for physiological data on luminance gradient reversal recorded from simple cells in cat striate c

### Citations

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(Show Context)
Citation Context ...et al. 1998; Hirsch et al. 1998). With this mechanism of dominating opponent inhibition (DOI), the model (1) reproduces physiological data of simple cell responses to luminance gradient reversal, and =-=(2)-=- is more robust to noise than a model with balanced excitation and inhibition. The paper is organized as follows. Section 2 gives a brief overview of the equations defining the model and formally intr... |

103 | Neural mechanisms of orientation selectivity in the visual cortex, Annu. Rev. Neurosci. 23 (2000) 441–471. 12 J. Schummers et al
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(Show Context)
Citation Context ...d length of the dark bar (right) yields a more concise equation. The resulting simple cell activity consists of a linear and a nonlinear, i.e., multiplicative, term �S = αS(Ron + Roff)+2βS(RonRoff=-=) . (5) αSγS +-=- βSγS(Ron + Roff) The parameters are set to αS =1.0, βS = 10 000.0, and γS =0.01. Their specific choice is not critical as long as the linear components scaled by αS and γS are small compared t... |

81 |
Spatially opponent excitation and inhibition in simple cells of the cat visual cortex
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(Show Context)
Citation Context ...f-wave rectification. The DoG is given by the difference of a center Gaussian with small standard deviation σc = 1 and a surround Gaussian with larger standard deviation σs =3: DoGσc,σs = Gσc −=-= Gσs . (3) The-=- Gaussians are sampled within a 3σ interval, resulting in a filter mask of size 19 × 19 (3σs × 2 + 1 = 19). Figure 2 shows the filter mask of the DoG operator together with a horizontal cross-sect... |

68 | Synaptic integration in striate cortical simple cells - Hirsch, Alonso, et al. - 1998 |

56 | Contrastinvariant orientation tuning in cat visual cortex: thalamocortical input tuning and correlation-based intracortical connectivity - Troyer, Krukowski, et al. - 1998 |

31 | A contrast- and luminance-driven multiscale network model of brightness perception - Pessoa, Mingolla, et al. - 1995 |

13 |
Receptive field organization of simple cells in cat striate cortex
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(Show Context)
Citation Context ...n stimulus linear nonlinear nonlinear with DOI stimulus linear nonlinear nonlinear with DOI E{y} = = � ∞ −∞ � 0 −∞ yfy(y) dy ygσξ(y) dy + = − 1 √ 2π σξ + 1 √ 2π σ � ∞ 0 =-=ygσ(y) dy = − 1 √ 2π σ(ξ − 1). (7) The -=-result shows that the mean is (1) negative for ξ>1 and (2) proportional to the DOI parameter ξ − 1 and to the noise level σ. The expression for the mean of y (Eq. 7) explains the suppression of n... |

13 | Interaction of On and Off pathways for visual contrast measurement - Neumann, Pessoa, et al. - 1999 |

12 |
The synaptic inputs to simple cells in the cat visual cortex
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(Show Context)
Citation Context ...lution of the weighted difference of unoriented LGN responses Xon and Xoff with the subfield mask Gθ of the same orientation preference: Ron,θ = [(Xon − ξXoff)∗Gθ] + , Roff,θ = [(Xoff − ξX=-=on)∗Gθ] + . (4) T-=-he case of equally weighted on and off inputs occurs for ξ = 1. The newly proposed scheme of dominating opponent inhibition (DOI) introduces ξ>1; which scales up the opponent contribution. This intr... |

7 |
Quantitative studies of enhancement and suppression zones in the receptive field of simple cells in cat striate cortex
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(Show Context)
Citation Context ...ail. Using Eq. 2 and the equality [x] + − [−x] + = x, we can rewrite Eq. 4 as Ron,θ = [(Xon − ξXoff)∗Gθ] + = [(Xon − Xoff)∗Gθ − (ξ − 1)Xoff∗Gθ] + =[X∗Gθ − (ξ − 1)Xoff��=-=�Gθ] � �� � dynamic threshold + . (8) T-=-his shows that DOI interaction introduces a dynamic threshold that is proportional to ξ and depends on the strength of the signal in the opponent pathway. Note that in the nondominating case for ξ =... |

6 | A neural architecture of brightness perception: nonlinear contrast detection and geometrydriven diffusion - Neumann, Pessoa, et al. - 1998 |

6 | Receptive field structure in cat striate cortex - Palmer, Davis - 1981 |

5 |
Influence of luminance gradient reversal on simple cells in feline striate cortex
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(Show Context)
Citation Context ...sensitive to opposite contrast polarity, i.e., light-dark and dark-light, finally undergo mutual inhibition, which sharpens the activity profile: � Sld = �Sld − � � + Sdl , � Sdl = �Sdl =-=− � � + Sld . (6) L-=-ight-dark and dark-light simple cells are obtained by sampling the subfield activity with different offsets ±τ =3 orthogonal to the axis of orientation of the simple cell: a light-dark cell has an o... |

1 |
A model for the intracortical origin of orientation tuning in macaque striate cortex
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(Show Context)
Citation Context ...ight: the corresponding horizontal cross-section taken at the center of the mask 2.1 LGN cells The input luminance distribution is given by a stimulus I, with luminance values normalized to the range =-=[0; 1]-=-. Responses of isotropic LGN cells are modeled by convolution of the input stimulus I with a difference of Gaussians (DoG) operator. LGN on and off cell activities Xon and Xoff are modeled as rectifie... |