Dendrite P systems

Neural Netw. 2020 Jul:127:110-120. doi: 10.1016/j.neunet.2020.04.014. Epub 2020 Apr 18.

Abstract

It was recently found that dendrites are not just a passive channel. They can perform mixed computation of analog and digital signals, and therefore can be abstracted as information processors. Moreover, dendrites possess a feedback mechanism. Motivated by these computational and feedback characteristics, this article proposes a new variant of neural-like P systems, dendrite P (DeP) systems, where neurons simulate the computational function of dendrites and perform a firing-storing process instead of the storing-firing process in spiking neural P (SNP) systems. Moreover, the behavior of the neurons is characterized by dendrite rules that are abstracted by two characteristics of dendrites. Different from the usual firing rules in SNP systems, the firing of a dendrite rule is controlled by the states of the corresponding source neurons. Therefore, DeP systems can provide a collaborative control capability for neurons. We discuss the computational power of DeP systems. In particular, it is proven that DeP systems are Turing-universal number generating/accepting devices. Moreover, we construct a small universal DeP system consisting of 115 neurons for computing functions.

Keywords: Computational power; Dendrite P systems; Neural-like P systems; P systems.

MeSH terms

  • Action Potentials / physiology
  • Dendrites* / physiology
  • Humans
  • Models, Neurological*
  • Neural Networks, Computer*
  • Neurons / physiology
  • Synapses / physiology