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A Real-Time, Event-Driven Neuromorphic System for Goal-Directed Attentional Selection

  • Francesco Galluppi
  • Kevin Brohan
  • Simon Davidson
  • Teresa Serrano-Gotarredona
  • José-Antonio Pérez Carrasco
  • Bernabé Linares-Barranco
  • Steve Furber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)

Abstract

Computation with spiking neurons takes advantage of the abstraction of action potentials into streams of stereotypical events, which encode information through their timing. This approach both reduces power consumption and alleviates communication bottlenecks. A number of such spiking custom mixed-signal address event representation (AER) chips have been developed in recent years.

In this paper, we present i) a flexible event-driven platform consisting of the integration of a visual AER sensor and the SpiNNaker system, a programmable massively parallel digital architecture oriented to the simulation of spiking neural networks; ii) the implementation of a neural network for feature-based attentional selection on this platform.

Keywords

Attention Selection Neuromorphic SpiNNaker AER 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Francesco Galluppi
    • 1
  • Kevin Brohan
    • 2
  • Simon Davidson
    • 1
  • Teresa Serrano-Gotarredona
    • 3
  • José-Antonio Pérez Carrasco
    • 4
  • Bernabé Linares-Barranco
    • 3
  • Steve Furber
    • 1
  1. 1.School of Computer ScienceThe University of ManchesterUnited Kingdom
  2. 2.School of Electronic and Electrical EngineeringThe University of ManchesterUnited Kingdom
  3. 3.Instituto de Microelectrónica de SevillaSevillaSpain
  4. 4.Departemento de Teoría de la Señal y ComunicacionesUniversidad de SevilleSevillaSpain

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