ICANN 98 pp 117-122 | Cite as

Queuing theory for spike driven synaptic dynamics

  • Mario Annunziato
  • Stefano Fusi
Conference paper
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)


We present a model for spike driven, stochastic dynamics of a synapse with two stable states, suited for aVLSI implementation. The stochastic nature of learning, which allows for optimal storage capacity, is due to the variability in spike emission times of pre- and post-synaptic neurons, and emerges as a result of the collective properties of the whole network. The dynamics of the single synapse is studied with the methods of queuing theory. Numerical results show that LTP and LTD are stochastically induced by the two neurons’ activity states and transition probabilities are in the range required by the theory of stochastic learning.


Synaptic Efficacy Stochastic Transition Material Device Synaptic Dynamic Single Synapse 
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Copyright information

© Springer-Verlag London 1998

Authors and Affiliations

  • Mario Annunziato
    • 1
  • Stefano Fusi
    • 2
  1. 1.Physics Dept.University of PisaItaly
  2. 2.INFN Sezione RM1RomeItaly

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