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Retina Color-Opponency Based Pursuit Implemented Through Spiking Neural Networks in the Neurorobotics Platform

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9793)

Abstract

The ‘red-green’ pathway of the retina is classically recognized as one of the retinal mechanisms allowing humans to gather color information from light, by combining information from L-cones and M-cones in an opponent way. The precise retinal circuitry that allows the opponency process to occur is still uncertain, but it is known that signals from L-cones and M-cones, having a widely overlapping spectral response, contribute with opposite signs. In this paper, we simulate the red-green opponency process using a retina model based on linear-nonlinear analysis to characterize context adaptation and exploiting an image-processing approach to simulate the neural responses in order to track a moving target. Moreover, we integrate this model within a visual pursuit controller implemented as a spiking neural network to guide eye movements in a humanoid robot. Tests conducted in the Neurorobotics Platform confirm the effectiveness of the whole model. This work is the first step towards a bio-inspired smooth pursuit model embedding a retina model using spiking neural networks.

Keywords

Receptive Field Humanoid Robot Smooth Pursuit Spike Neural Network Retinal Slip 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604102 (Human Brain Project). The authors would like to thank the Italian Ministry of Foreign Affairs, General Directorate for the Promotion of the “Country System”, Bilateral and Multilateral Scientific and Technological Cooperation Unit, for the support through the Joint Laboratory on Biorobotics Engineering project.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.The BioRobotics Institute, Scuola Superiore Sant’AnnaPontederaItaly
  2. 2.Department of Intelligent Systems and Production Engineering (ISPE IDS/TKS)FZI Research Center for Information TechnologyKarlsruheGermany
  3. 3.Blue Brain Project (BBP)École polytechnique fédérale de Lausanne (EPFL)GenevaSwitzerland
  4. 4.Department of Software Engineering (SE)FZI Research Center for Information TechnologyKarlsruheGermany
  5. 5.Department of InformaticsTechnical University of MunichGarchingGermany
  6. 6.Department of Computer Architecture and TechnologyCITIC, University of GranadaGranadaSpain

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