Emergent BCM via neuromorphic VLSI synapses with STDP

Conference Contribution ResearchOnline@JCU
Rahimi Azghadi, Mostafa;Al-Sarawi, Said;Iannella, Nicolangelo;Abbott, Derek
Abstract

The Bienenstock-Cooper-Munro (BCM) rule1-3 is an experimentally verified form of synaptic plasticity where the alteration of synaptic weight depends upon the rate of pre and postsynaptic firing of action potentials. Previous theoretical studies have investigated how the precise timing of random pre- and post-synaptic spike activity and spike timing-dependent plasticity (STDP) leads to changes in the efficacy of synaptic weights, assuming Poissonian spike statistics. In particular, when a particular class of STDP rule, based upon multiple spike interactions are used, the time averaged behaviour of synaptic weight changes was shown to exhibit analogous behaviour to the classical BCM rule and can inherit its functional properties. Here, we present two distinct neuromorphic VLSI circuit implementations and some of their behaviour. The first circuit implements the classical pair-based STDP4, while the second realizes a previously described triplet-based STDP rule5. We use these different circuits to examine whether BCM learning is an emergent property. A 0.35 µm standard CMOS process model has been used in HSpice to implement the two mentioned circuits. Simulation results demonstrate how well, the proposed triplet-based STDP circuit produces the threshold-based behaviour of the BCM. Also, the results testify to similar behaviour for the VLSI circuit for pair-based STDP ingenerating the BCM.

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5th Australian Workshop on Computational Neuroscience

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1

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University of Western Sydney, Campbelltown, NSW

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The Australian Association of Computational Neuroscientists and Neuromorphic Engineers

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Sydney, NSW, Australia

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