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Modeling Activity-Dependent Plasticity in BCM Spiking Neural Networks With Application to Human Behavior Recognition

<24>This work developed a new spiking neural network (SNN) model whose weights are adjusted using BCM plasticity rule. A gene regulatory network (GRN) is applied to regulate the BCM parameters depending on neural activities. This is the first SNN model that implements GRN-regulated activity-dependent plasticity and applied to solve complex spatiotemporal pattern recognition problems such as human behaviour recognition. This work, together with a conference paper, has received much interest in the community and as a result, I was invited to give a Keynote at 2011 Evolutionary Developmental Neural Networks Workshop (EvoDevNeuro’2011) in Paris and EvoDevNeuro’2012 in Poznan.