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International Workshop on Brain-Inspired Computing

BrainComp 2015: Brain-Inspired Computing pp 86–100Cite as

Visual Processing in Cortical Architecture from Neuroscience to Neuromorphic Computing

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10087))

Abstract

Primate cortices are organized into different layers which constitute a compartmental structure on a functional level. We show how composite structural elements form building blocks to define canonical elements for columnar computation in cortex. As a further abstraction, we define a dynamical three-stage model of a cortical column for processing that allows to investigate the dynamic response properties of cortical algorithms, e.g., feedforward signal integration as feature detection filters, lateral feature grouping, and the integration of modulatory (feedback) signals. Using such multi-stage cortical model, we investigate the detection and integration of spatio-temporal motion measured by event-based (frame-less) cameras. We demonstrate how the canonical neural circuit can improve such representations using normalization and feedback and develop key computational elements to map such a model onto neuromorphic hardware (IBM’s TrueNorth chip). This makes a step towards implementing real-time and energy-efficient neuromorphic optical flow detectors based on realistic principles of computation in cortical columns.

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Notes

  1. 1.

    See www.informatik.uni-ulm.de/ni/staff/HNeumann.

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Acknowledgments

This work has been supported in part by a grant from the Transregional Collaborative Research Center “A Companion-Technology for Cognitive Technical Systems” SFB/TRR 62 funded by the German Research Foundation (DFG). The authors also gratefully acknowledge the support via a field test agreement between Ulm University and IBM Research Almaden as well as the support of NVIDIA Corporation with the donation of the Tesla K40 GPU used for this research.

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Authors and Affiliations

  1. Neural Information Processing, Faculty of Engineering, Computer Science, and Psychology, Ulm University, Oberer Eselsberg, 89081, Ulm, Germany

    Tobias Brosch, Stephan Tschechne & Heiko Neumann

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  1. Tobias Brosch
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  2. Stephan Tschechne
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  3. Heiko Neumann
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Correspondence to Heiko Neumann .

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Editors and Affiliations

  1. Forschungszentrum Jülich, Jülich, Germany

    Katrin Amunts

  2. University of Calabria , Rende, Italy

    Lucio Grandinetti

  3. Forschungszentrum Jülich, Jülich, Germany

    Thomas Lippert

  4. University of Groningen , Groningen, The Netherlands

    Nicolai Petkov

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Brosch, T., Tschechne, S., Neumann, H. (2016). Visual Processing in Cortical Architecture from Neuroscience to Neuromorphic Computing. In: Amunts, K., Grandinetti, L., Lippert, T., Petkov, N. (eds) Brain-Inspired Computing. BrainComp 2015. Lecture Notes in Computer Science(), vol 10087. Springer, Cham. https://doi.org/10.1007/978-3-319-50862-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-50862-7_7

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