Spiking neural P systems with structural plasticity and weights

Abstract

Spiking neural (SN) P systems are computational models inspired by the functional and structural attributes of biological neurons and nervous systems. Drawing on insights from biological research, these systems incorporate intriguing mechanisms that have been studied for their computational capabilities and universality. In our current research, we integrate structural plasticity and synaptic weights in synchronous mode, termed as SN P systems with structural plasticity and weights (SNP-SPW systems). These systems utilize plasticity spiking rules to modify their architecture and generate new spikes dynamically. The number of spikes received by post-synaptic neurons could be modulated by the synaptic weights. We have demonstrated that SNP-SPW systems can generate all recursively enumerable sets of numbers, thus establishing their computational universality. Furthermore, we present a small universal SNP-SPW system that requires only nine neurons to perform computing all Turing-computable functions.