Implementation of FitzHugh-Nagumo Neurons using Nanoscale VO<sub>2</sub> Devices
This study focuses on exploiting phase-transition properties in VO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> to develop a brain-inspired FitzHugh-Nagumo neuron. A key feature of our implementation is achieved through a self-coupling synapse that creates a neuron capable of generating complex firing patterns, such as mixed-mode oscillations. These oscillations hold promise for solving time-dependent computing problems. We study the advantages of coupling FitzHugh-Nagumo oscillators in terms of stability and circuit simplicity compared to Kuramoto-based relaxation oscillators. We show how they can excel in solving computational tasks, specifically in pattern recognition applications.
Authors
- Folkert Horst (ORCID: https://orcid.org/0000-0001-6559-2076)
- Bert Jan Offrein (ORCID: https://orcid.org/0000-0001-6082-0068)
- Siegfried Karg (ORCID: https://orcid.org/0000-0001-9873-2717)
- Valeria Bragaglia (ORCID: https://orcid.org/0000-0003-0636-4211)
- Aida Todri‐Sanial (ORCID: https://orcid.org/0000-0001-8573-2910)
- Filip Sabo (ORCID: https://orcid.org/0000-0003-0669-3939)
- Olivier Maher
- Marilyne Sousa
- Du Fancheng
Institutions
- IBM Research - Zurich (CH)
- Eindhoven University of Technology (NL)
Publication Details
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1109/esserc62670.2024.10719575
- Citations
- 2
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.54