Non-monotone cellular automata: Order prevails over chaos

Research output: Contribution to journalArticlepeer-review

Abstract

We consider a model for the propagation of electrical impulses or activity in a neuronal network. The vertices of a square lattice represent neurons, and the edges of the lattice represent the synaptic connections. Each vertex v is assigned a type: inhibitory or excitatory. The dynamics of propagation of the initial activity captures features of the “integrate-and-fire” model. We study the spread of activation in a large network and describe possible spatio-temporal limiting patterns depending on the initial activation. The rich palette of the limits with qualitatively different properties, including expanding patterns, fixed patterns, and patterns moving across the network, allows us to argue that this is a versatile model for the study of associative memory.

Original languageEnglish
Article number104756
JournalBioSystems
Volume220
DOIs
Publication statusPublished - 2022

Subject classification (UKÄ)

  • Bioinformatics (Computational Biology)

Free keywords

  • Cellular automata
  • Integrate-and-fire neurons
  • Non-monotone bootstrap percolation
  • Spatio-temporal patterns

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