Implementing spike-timing-dependent plasticity on SpiNNaker neuromorphic hardware

Xin Jin, Alexander Rast, Francesco Galluppi, Sergio Davies, Steve Furber

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents an efficient approach for implementing spike-timing-dependent plasticity (STDP) on the SpiNNaker neuromorphic hardware. The event-address mapping and the distributed synaptic weight storage schemes used in parallel neuromorphic hardware such as SpiNNaker make the conventional pre-post-sensitive scheme of STDP implementation inefficient, since STDP is triggered when either a pre- or post-synaptic neuron fires. An alternative pre-sensitive scheme approach is presented to solve this problem, where STDP is triggered only when a pre-synaptic neuron fires. An associated deferred event-driven model is developed to enable the pre-sensitive scheme by deferring the STDP process until there are sufficient history spike timing records. The paper gives detailed description of the implementation as well as performance estimation of STDP on multi-chip SpiNNaker machine, along with the discussion on some issues related to efficient STDP implementation on a parallel neuromorphic hardware. © 2010 IEEE.
Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks|Proc Int Jt Conf Neural Networks
Place of PublicationUSA
PublisherIEEE
ISBN (Print)9781424469178
DOIs
Publication statusPublished - 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona
Duration: 1 Jul 2010 → …

Conference

Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
CityBarcelona
Period1/07/10 → …

Keywords

  • brain models , neural nets

Fingerprint

Dive into the research topics of 'Implementing spike-timing-dependent plasticity on SpiNNaker neuromorphic hardware'. Together they form a unique fingerprint.

Cite this