Dynamic Memory for Robot Control Using Delay-Based Coincidence Detection Neurones

  • Francis Jeanson
  • Tony White
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8131)


This paper demonstrates the feasibility of dynamic memory in transmission delay coincidence detection networks. We present a low complexity, procedural algorithm for determining delay connectivity for the control of a simulated e-puck robot to solve the t-maze memory task. This work shows that dynamic memory modules need not undergo structural change during learning but that peripheral structures could be alternate candidates for this. Overall, this supports the view that delay coincidence detection networks can be effectively coupled to produce embodied adaptive behaviours.


Dynamic Memory Transmission Delays Coincidence Detection Spiking Neural Networks Embodied Cognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Francis Jeanson
    • 1
  • Tony White
    • 1
  1. 1.Springer-Verlag, Computer Science EditorialHeidelbergGermany

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