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2016 | OriginalPaper | Buchkapitel

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

verfasst von : Alessandro Ambrosano, Lorenzo Vannucci, Ugo Albanese, Murat Kirtay, Egidio Falotico, Pablo Martínez-Cañada, Georg Hinkel, Jacques Kaiser, Stefan Ulbrich, Paul Levi, Christian Morillas, Alois Knoll, Marc-Oliver Gewaltig, Cecilia Laschi

Erschienen in: Biomimetic and Biohybrid Systems

Verlag: Springer International Publishing

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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.

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Metadaten
Titel
Retina Color-Opponency Based Pursuit Implemented Through Spiking Neural Networks in the Neurorobotics Platform
verfasst von
Alessandro Ambrosano
Lorenzo Vannucci
Ugo Albanese
Murat Kirtay
Egidio Falotico
Pablo Martínez-Cañada
Georg Hinkel
Jacques Kaiser
Stefan Ulbrich
Paul Levi
Christian Morillas
Alois Knoll
Marc-Oliver Gewaltig
Cecilia Laschi
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-42417-0_2