Feed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code

Biological Cybernetics volume 115, pages161–176(2021)Cite this article

Abstract

In studies of the visual system as well as in computer vision, the focus is often on contrast edges. However, the primate visual system contains a large number of cells that are insensitive to spatial contrast and, instead, respond to uniform homogeneous illumination of their visual field. The purpose of this information remains unclear. Here, we propose a mechanism that detects feature homogeneity in visual areas, based on latency coding and spike time coincidence, in a purely feed-forward and therefore rapid manner. We demonstrate how homogeneity information can interact with information on contrast edges to potentially support rapid image segmentation. Furthermore, we analyze how neuronal crosstalk (noise) affects the mechanism’s performance. We show that the detrimental effects of crosstalk can be partly mitigated through delayed feed-forward inhibition that shapes bi-phasic post-synaptic events. The delay of the feed-forward inhibition allows effectively controlling the size of the temporal integration window and, thereby, the coincidence threshold. The proposed model is based on single-spike latency codes in a purely feed-forward architecture that supports low-latency processing, making it an attractive scheme of computation in spiking neuronal networks where rapid responses and low spike counts are desired.

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Acknowledgements

We thank Dr. Ursula Körner for her help and support in compiling the evidence on koniocellular processing strategies across primate species that was instrumental in forming the hypothesis underlying this study. This work was supported by BMBF Grant 01GQ0420 to BCCN Freiburg and EU H2020 Grant 945539 (Human Brain Project SGA3) to the University of Hertfordshire.

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Affiliations

  1. Honda Research Institute Europe GmbH, Offenbach am Main, Germany

    Michael Schmuker, Rüdiger Kupper & Marc-Oliver Gewaltig

  2. Department of Computer Science, Biocomputation Group, University of Hertfordshire, Hatfield, UK

    Michael Schmuker

  3. Bernstein-Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg im Breisgau, Germany

    Ad Aertsen

  4. Department of Biology II, Ludwig-Maximilians-Universität München, München, Germany

    Thomas Wachtler

  5. Blue Brain Project, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Marc-Oliver Gewaltig

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  1. Michael Schmuker
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  2. Rüdiger Kupper
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  3. Ad Aertsen
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  5. Marc-Oliver Gewaltig
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Correspondence to Michael Schmuker.

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Schmuker, M., Kupper, R., Aertsen, A. et al. Feed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code. Biol Cybern 115, 161–176 (2021). https://doi.org/10.1007/s00422-021-00866-w

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