License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ITP.2022.1
URN: urn:nbn:de:0030-drops-167100
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16710/
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Felty, Amy

Modelling and Verifying Properties of Biological Neural Networks (Invited Talk)

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LIPIcs-ITP-2022-1.pdf (0.4 MB)

Abstract

In this talk, I present a formal model of biological neural networks and discuss the use of model checking and interactive theorem proving to verify some of their properties. Having a formal model can increase our understanding of the behavior and properties of such networks, as well as provide insight into their response to external factors such as disease, medicine, and environmental changes. We focus on neuronal micro-networks, considering properties of single neurons as well as properties of slightly larger ones called archetypes, which represent specific computational functions. Archetypes, in turn, represent the building blocks of larger more complicated neuronal circuits. I first present work by colleagues on a model checking approach, and then present our joint work on a newer theorem proving approach. Using interactive theorem proving allows us to generalize the kinds of properties that we can prove. This work is joint with Abdorrahim Bahrami and Elisabetta De Maria.

BibTeX - Entry

@InProceedings{felty:LIPIcs.ITP.2022.1,
  author =	{Felty, Amy},
  title =	{{Modelling and Verifying Properties of Biological Neural Networks}},
  booktitle =	{13th International Conference on Interactive Theorem Proving (ITP 2022)},
  pages =	{1:1--1:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-252-5},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{237},
  editor =	{Andronick, June and de Moura, Leonardo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16710},
  URN =		{urn:nbn:de:0030-drops-167100},
  doi =		{10.4230/LIPIcs.ITP.2022.1},
  annote =	{Keywords: Neuronal networks, Model checking, Theorem proving, Coq}
}

Keywords: Neuronal networks, Model checking, Theorem proving, Coq
Collection: 13th International Conference on Interactive Theorem Proving (ITP 2022)
Issue Date: 2022
Date of publication: 03.08.2022

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