A model for learning color selective receptive cells from natural scenes
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1
Westfälische Wilhelms-Universität, Department of Psychology, Germany
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2
University of Technology, Department of Artificial Intelligence, Germany
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3
Justus-Liebig-University, Department of General and Experimental Psychology, Germany
Different from the standard view of color perception that proposes largely different pathways for color and shape perception, recently it has been discovered that in the primary visual cortex, color and shape are not processed apart from one another. Electrophysiological studies suggest that cells do not only respond to stimuli of a certain orientation or shape but at the same time they can be color selective [1]. Different receptive field types have been reported: color-responsive single-opponent cells, color-responsive double-opponent cells (circular and orientated) and non-color-responsive cells [1]. We here show that such receptive fields can emerge from Hebbian learning when presenting colored natural scenes to a model of V1 that has previously been proven to learn “edge-detecting” receptive fields (RFs) out of gray-scale images similar to those of primary visual cortex of macaque monkey [2].
As a first step we simulate color receptive (L-, M- and S-) cones of the lateral geniculate nucleus (LGN) [4]. Second, the LGN output is fed into our algorithm of learning.
The Figure shows the receptive fields of miscellaneous categorized cells and their responses to changes in orientation and spatial frequency of the underlying (fitted) Gabor-filter. The learnt RFs are either only responsive to stimuli of a certain color, a specific achromatic edge or to stimuli with different colors and orientations. In correspondence to the literature [1,3], the cells are categorized by means of their orientation- and frequency-selectivity as well as their response to different colors.
Figure: Presentation of examples for a non-color-responsive, a single-opponent and a double-opponent cell. For each cell the following is shown: the RF (left) and the tuning characteristic to orientation (middle) and frequency (right). The green line in the tuning characteristics denotes the response to the original stimuli, the red line the response to the corresponding chromatic stimuli and black to the corresponding luminance stimuli.
References
[1] EN Johnson, MJ Hawken und R Shapley: The Orientation Selectivity of Color-Responsive Neurons in Macaque V1, J Neurosci, 28: 8096-8106, 2008.
[2]J Wiltschut and FH Hamker: Efficient coding correlates with spatial frequency tuning in a model of V1 receptive field organization, Vis Neurosci, 26: 21-34, 2009
[3]EN Johnson, MJ Hawken und R Shapley: Cone Inputs in Macaque Primary Visual Cortex, J Neurophysiol, 92: 2501-2514, 2004.
[4] R Clay Reid and RM Shapley: Space and Time Maps of Cone Photoreceptor Signals in Macaque Lateral Geniculate Nucleus, J Neurosci, 22: 6158-6175, 2002
Learning*; Information Processing; Modelling; Neural Dynamics; Neural Encoding; Sensory Processing
Keywords:
Information Processing,
Learning*,
modelling,
neural dynamics,
Neural Encoding,
sensory processing
Conference:
Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010.
Presentation Type:
Presentation
Topic:
Bernstein Conference on Computational Neuroscience
Citation:
Wiltschut
J,
Truschzinski
M,
Hansen
T and
Hamker
FH
(2010). A model for learning color selective receptive cells from natural scenes.
Front. Comput. Neurosci.
Conference Abstract:
Bernstein Conference on Computational Neuroscience.
doi: 10.3389/conf.fncom.2010.51.00122
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Received:
31 Aug 2010;
Published Online:
23 Sep 2010.
*
Correspondence:
Dr. Jan Wiltschut, Westfälische Wilhelms-Universität, Department of Psychology, Münster, Germany, wiltschj@uni-muenster.de