Spiking neural networks for reconfigurable POEtic tissue

J Eriksson, O Torres, A Mitchell, G Tucker, K Lindsay, D Halliday, J Rosenberg, J M Moreno, A E P Villa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Vertebrate and most invertebrate organisms interact with their environment through processes of adaptation and learning. Such processes are generally controlled by complex networks of nerve cells, or neurons, and their interactions. Neurons are characterized by all-or-none discharges - the spikes and the time series corresponding to the sequences of the discharges - the spike trains - carry most of the information used for intercellular communication. This paper describes biologically inspired spiking neural network models suitable for digital hardware implementation. We consider bio-realism, hardware friendliness, and performance as factors which influence the ability of these models to integrate into a flexible computational substrate inspired by evolutionary, developmental and learning aspects of living organisms. Both software and hardware simulations have been used to assess and compare the different models to determine the most suitable spiking neural network model.

Original languageEnglish
Title of host publicationEVOLVABLE SYSTEMS: FROM BIOLOGY TO HARDWARE, PROCEEDINGS
EditorsAM Tyrrell, PC Haddow, J Torresen
Place of PublicationBERLIN
PublisherSpringer
Pages165-173
Number of pages9
ISBN (Print)3-540-00730-X
Publication statusPublished - 2003
Event5th International Conference on Evolvable Systems - TRONDHEIM
Duration: 17 Mar 200320 Mar 2003

Conference

Conference5th International Conference on Evolvable Systems
CityTRONDHEIM
Period17/03/0320/03/03

Keywords

  • SYNAPTIC PLASTICITY
  • SIMULATION
  • MEMORY
  • LONG

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