Dendrite P systems

• Published in: Neural networks 2020-07, Vol.127, p.110-120
• Main Authors: Peng, Hong, Bao, Tingting, Luo, Xiaohui, Wang, Jun, Song, Xiaoxiao, Riscos-Núñez, Agustín, Pérez-Jiménez, Mario J.
• Format: Article
• Language: English
• Subjects: Computational power; Dendrite P systems; Neural-like P systems; P systems
• ISSN: 0893-6080; 1879-2782
• DOI: 10.1016/j.neunet.2020.04.014

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. •We consider dendrites as information processors.•We propose a new model, dendrite P systems (DeP systems, in short).•We prove that DeP systems are Turing-universal number generating/accepting devices.•We construct a small universal DeP system of 115 neurons for computing functions.