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Updated: Jun 6, 2026
Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
Published on: November 12, 2019
An STDP training algorithm for a spiking neural network with dynamic threshold neurons
T J Strain1, L J McDaid, T M McGinnity
1Intelligent Systems Research Centre, University of Ulster, Magee Campus, School of Computing and Intelligent Systems, Derry, Northern Ireland, BT48 7JL, UK.
Abstract:
This paper proposes a supervised training algorithm for Spiking Neural Networks (SNNs) which modifies the Spike Timing Dependent Plasticity (STDP)learning rule to support both local and network level training with multiple synaptic connections and axonal delays. The training algorithm applies the rule to two and three layer SNNs, and is benchmarked using the Iris and Wisconsin Breast Cancer (WBC) data sets. The effectiveness of hidden layer dynamic threshold neurons is also investigated and results are presented.
