A dynamical model for retinal processing is presented. The model describes the output of retinal ganglion cells whose receptive field is composed of a center and a surround combining linearly. However, in comparison to the classical difference-of-Gaussian (DOG) model, center and surround are generated in two separate layers of reaction-diffusion systems, through a difference in the speed of activity-propagation between both layers. Thus, intra-layer coupling is based exclusively on next-neighbor interactions. This makes the model suitable for VLSI implementation. Furthermore, the layers are connected by equations with feedback-inhibition to form ON-center/OFF-surround and OFF-center/OFF-surround receptive fields. The model's output in the early dynamics corresponds to high-resolution contrast information, whereas the output at later times can be considered as correlated with local brightness and darkness, respectively. To examine this in more detail, simulations with the Hermann/Hering-grid and grating induction were carried out.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A neurodynamical retinal network based on reaction-diffusion systems


    Contributors:
    Keil, M.S. (author) / Cristobal, G. (author) / Neumann, H. (author)


    Publication date :

    2001-01-01


    Size :

    707998 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A Neurodynamical Retinal Network Based on Reaction-Diffusion Systems

    Keil, M. / Cristobal, G. / Neumann, H. et al. | British Library Conference Proceedings | 2001


    Adaptive edge enhancement using a neurodynamical model of visual attention

    Gasparini, F. / Corchs, S. / Schettini, R. | IEEE | 2005


    Adaptive Edge Enhancement using A Neurodynamical Model of Visual Attention

    Gasparini, F. / Corchs, S. / Schettini, R. | British Library Conference Proceedings | 2005


    Neural Network Based Retinal Image Analysis

    David, J. / Krishnan, Rekha / A., Sukesh Kumar | IEEE | 2008


    Simulations of Elderly Drivers' Retinal Responses Based on a Mathematical Model of Retinal Neuron Network

    Kubo, Kensuke / Sakai, Hiroyuki / Uchiyama, Yuji et al. | British Library Online Contents | 2017