BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network

Romain Beaubois, Jérémy Cheslet, Tomoya Duenki, Giuseppe De Venuto, Marta Carè, Farad Khoyratee, Michela Chiappalone, Pascal Branchereau, Yoshiho Ikeuchi and Timothée Levi ()
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Romain Beaubois: University of Bordeaux
Jérémy Cheslet: University of Bordeaux
Tomoya Duenki: The University of Tokyo
Giuseppe De Venuto: University of Genova
Marta Carè: University of Genova
Farad Khoyratee: University of Bordeaux
Michela Chiappalone: University of Genova
Pascal Branchereau: University of Bordeaux
Yoshiho Ikeuchi: The University of Tokyo
Timothée Levi: University of Bordeaux

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments.

Date: 2024
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DOI: 10.1038/s41467-024-48905-x

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