Biologically Plausible Sequence Learning with Spiking Neural Networks

25 Nov 2019Zuozhu LiuThiparat ChotibutChristopher HillarShaowei Lin

Motivated by the celebrated discrete-time model of nervous activity outlined by McCulloch and Pitts in 1943, we propose a novel continuous-time model, the McCulloch-Pitts network (MPN), for sequence learning in spiking neural networks. Our model has a local learning rule, such that the synaptic weight updates depend only on the information directly accessible by the synapse... (read more)

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