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{{BioPsy}}
 
{{BioPsy}}
A '''simple cell''' in the [[visual cortex|primary visual cortex]] is a cell that responds primarily to oriented edges and gratings (bars of particular orientations). These cells are discovered by [[Torsten Wiesel]] and [[David Hubel]] in the 1960s.
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[[Image:gabor filter.png|thumb|Right|''Gabor filter-type receptive field typical for a simple cell. Blue regions indicate inhibition, red facilitation'']]
   
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A '''simple cell''' in the [[visual cortex|primary visual cortex]] is a cell that responds primarily to oriented edges and gratings (bars of particular orientations). These cells were discovered by [[Torsten Wiesel]] and [[David Hubel]] in the late 1950s.<ref>D. H. Hubel and T. N. Wiesel ''Receptive Fields of Single Neurones in the Cat's Striate Cortex'' J. Physiol. pp. 574-591 (148) 1959</ref>
   
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Hubel and Wiesel named these cells "simple," as opposed to "[[complex cell]]", because they shared the following properties:<ref name="Hubel1962">D. H. Hubel and T. N. Wiesel ''Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex'' J. Physiol. 160 pp. 106-154 1962</ref>
   
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# They have distinct excitatory and inhibitory regions.
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# These regions follow the summation property.
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# These regions have mutual antagonism - excitatory and inhibitory regions balance themselves out in diffuse lighting.
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# It is possible to predict responses of moving stimuli given the map of excitatory and inhibitory regions.
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Some other researchers such as Peter Bishop and Peter Schiller used different definitions for simple and complex cells.<ref>''Brain and Visual Perception: The Story of a 25-Year Collaboration'' D. H. Hubel and T. N. Wiesel Oxford 2005</ref>
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Such cells are tuned to different frequencies and orientations, even with different phase relationships, possibly for extracting disparity (depth) information and to attribute depth to detected lines and edges{{Citation needed|date=August 2009}}. This may result in a 3D 'wire-frame' representation as used in computer graphics. The fact that input from the left and right eyes is very close in the so-called cortical hypercolumns is an indication that depth processing occurs at a very early stage, aiding recognition of 3D objects.
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Using the mathematical Gabor model with sine and cosine components (phases), so-called [[complex cell]]s are then modeled by computing the modulus of complex Gabor responses (cos + i*sin). Both simple and complex cells are seen as linear operators (filters) because they respond to many patterns.
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However, it has been claimed that the Gabor model does not conform to the anatomical structure of the visual system as it short-cuts the [[Lateral geniculate nucleus|LGN]] and uses the 2D image as it is projected on the [[retina]]. Azzopardi and Petkov<ref name="AzzopardiPetkov2012">G. Azzopardi and N. Petkov [http://rd.springer.com/article/10.1007/s00422-012-0486-6 ''A CORF computational model that relies on LGN input outperforms the Gabor function model''] Biological Cybernetics, vol. 106(3), pp. 177-189, DOI: 10.1007/s00422-012-0486-6, 2012</ref> have proposed a computational model of a simple cell, which combines the responses of model [[Lateral geniculate nucleus|LGN]] cells with center-surround [[receptive field]]s (RFs). They call it Combination of RFs (CORF) model. Besides orientation selectivity, it exhibits [[Surround suppression|cross orientation suppression]], contrast invariant orientation tuning and response saturation. These properties are observed in real simple cells but are not possessed by the Gabor model. Using [[Spike-triggered average|simulated reverse correlation]] they also demonstrate that the [[Receptive field|RF]] map of the CORF model can be divided into elongated excitatory and inhibitory regions typical of simple cells.
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Later, many other cells with specific functions have been discovered: (a) '''end-stopped cells''' which are thought to detect singularities like line and edge crossings, vertices and line endings; (b) '''bar and grating cells'''. The latter are not linear operators because a bar cell does not respond when seeing a bar which is part of a periodic grating, and a grating cell does not respond when seeing an isolated bar.
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==See also==
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*[[Complex cells]]
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*[[Hypercomplex cells]]
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== References ==
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<references/>
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{{DEFAULTSORT:Simple Cell}}
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[[Category:Brodmann areas]]
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[[Category:Cerebrum]]
 
[[Category:Visual cortex]]
 
[[Category:Visual cortex]]
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[[Category:Visual system]]

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File:Gabor filter.png

A simple cell in the primary visual cortex is a cell that responds primarily to oriented edges and gratings (bars of particular orientations). These cells were discovered by Torsten Wiesel and David Hubel in the late 1950s.[1]

Hubel and Wiesel named these cells "simple," as opposed to "complex cell", because they shared the following properties:[2]

  1. They have distinct excitatory and inhibitory regions.
  2. These regions follow the summation property.
  3. These regions have mutual antagonism - excitatory and inhibitory regions balance themselves out in diffuse lighting.
  4. It is possible to predict responses of moving stimuli given the map of excitatory and inhibitory regions.

Some other researchers such as Peter Bishop and Peter Schiller used different definitions for simple and complex cells.[3]

Such cells are tuned to different frequencies and orientations, even with different phase relationships, possibly for extracting disparity (depth) information and to attribute depth to detected lines and edges[citation needed]. This may result in a 3D 'wire-frame' representation as used in computer graphics. The fact that input from the left and right eyes is very close in the so-called cortical hypercolumns is an indication that depth processing occurs at a very early stage, aiding recognition of 3D objects.

Using the mathematical Gabor model with sine and cosine components (phases), so-called complex cells are then modeled by computing the modulus of complex Gabor responses (cos + i*sin). Both simple and complex cells are seen as linear operators (filters) because they respond to many patterns.

However, it has been claimed that the Gabor model does not conform to the anatomical structure of the visual system as it short-cuts the LGN and uses the 2D image as it is projected on the retina. Azzopardi and Petkov[4] have proposed a computational model of a simple cell, which combines the responses of model LGN cells with center-surround receptive fields (RFs). They call it Combination of RFs (CORF) model. Besides orientation selectivity, it exhibits cross orientation suppression, contrast invariant orientation tuning and response saturation. These properties are observed in real simple cells but are not possessed by the Gabor model. Using simulated reverse correlation they also demonstrate that the RF map of the CORF model can be divided into elongated excitatory and inhibitory regions typical of simple cells.

Later, many other cells with specific functions have been discovered: (a) end-stopped cells which are thought to detect singularities like line and edge crossings, vertices and line endings; (b) bar and grating cells. The latter are not linear operators because a bar cell does not respond when seeing a bar which is part of a periodic grating, and a grating cell does not respond when seeing an isolated bar.

See alsoEdit

References Edit

  1. D. H. Hubel and T. N. Wiesel Receptive Fields of Single Neurones in the Cat's Striate Cortex J. Physiol. pp. 574-591 (148) 1959
  2. D. H. Hubel and T. N. Wiesel Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex J. Physiol. 160 pp. 106-154 1962
  3. Brain and Visual Perception: The Story of a 25-Year Collaboration D. H. Hubel and T. N. Wiesel Oxford 2005
  4. G. Azzopardi and N. Petkov A CORF computational model that relies on LGN input outperforms the Gabor function model Biological Cybernetics, vol. 106(3), pp. 177-189, DOI: 10.1007/s00422-012-0486-6, 2012

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