Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering.

Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system

Système biohybride temps-réel avec Spiking Neural Network

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 led to the design of the new generation of neuroprostheses for brain repair.However, its complete development requires deeper understanding and expertise in biohybrid interaction. Here, this thesis work shows a novel real-time, biomimetic, cost-effective and user-friendly neural network for bio-hybrid experiments and real-time emulation.This thesis work allows investigation and reproduction of biophysically detailed neural network dynamics while promoting cost-efficiency, flexibility and ease of use. It showcases the feasibility of conducting biohybrid experiments using standard biophysical interfaces and various biological cells as well as real-time emulation of complex models.The system developped in this work is anticipated to be a step towards developing neuromorphic-based neuroprostheses for bioelectrical therapeutics by enabling communication with biological networks on a similar time scale, facilitated by an easy-to-use and accessible embedded real-time system.The real-time device developped further enhances its potential for practical applications in biohybrid experiments.La caractérisation et la modélisation des réseaux neuronaux biologiques ont émergé comme un domaine permettant des avancées significatives dans notre compréhension des fonctions cérébrales et des pathologies qui y sont liées.À ce jour, les traitements pharmacologiques des troubles neurologiques restent limités, ce qui pousse à explorer des approches alternatives prometteuses telles que l'électroceutique. Les recherches récentes en bioélectronique et en ingénierie neuromorphique ont conduit à la conception d'une nouvelle génération de neuroprothèses pour la réhabilitation du cerveau.Toutefois, leur développement complet nécessite une compréhension et une expertise plus approfondies de l'interaction biohybride. Ici, ce travail de thèse présente un nouveau réseau de neurones biomimétique temps réel à la fois abordable, flexible et accessible pour la réalisation d'expériences bio-hybrides et l'émulation en temps réel.Ce travail de thèse permet d'étudier et de reproduire la dynamique de réseaux de neurones détaillés sur le plan biophysique tout en promouvant une flexibilité et facilité d'utilisation. Il démontre la faisabilité d'expériences biohybrides utilisant des interfaces biophysiques standards et diverses cellules biologiques, ainsi que l'émulation en temps réel de modèles complexes. Le système mis au point permet de réaliser des expériences biohybrides ainsi que l'émulation en temps réel de réseaux de neurones.Le système développé devrait constituer une étape essentielle vers le développement de neuroprothèses neuromorphiques pour les thérapies bioélectriques comme l'électroceutique. Elle permet également la communication avec des réseaux de neurones biologiques sur une échelle de temps similaire, facilitée par un système en temps réel embarqué, facile à utiliser et accessible.Le dispositif en temps réel développé démontre son potentiel dans des applications pratiques et expériences biohybrides

Real-time bio-hybrid system with spiking neural network

La caractérisation et la modélisation des réseaux neuronaux biologiques ont émergé comme un domaine permettant des avancées significatives dans notre compréhension des fonctions cérébrales et des pathologies qui y sont liées.À ce jour, les traitements pharmacologiques des troubles neurologiques restent limités, ce qui pousse à explorer des approches alternatives prometteuses telles que l'électroceutique. Les recherches récentes en bioélectronique et en ingénierie neuromorphique ont conduit à la conception d'une nouvelle génération de neuroprothèses pour la réhabilitation du cerveau.Toutefois, leur développement complet nécessite une compréhension et une expertise plus approfondies de l'interaction biohybride. Ici, ce travail de thèse présente un nouveau réseau de neurones biomimétique temps réel à la fois abordable, flexible et accessible pour la réalisation d'expériences bio-hybrides et l'émulation en temps réel.Ce travail de thèse permet d'étudier et de reproduire la dynamique de réseaux de neurones détaillés sur le plan biophysique tout en promouvant une flexibilité et facilité d'utilisation. Il démontre la faisabilité d'expériences biohybrides utilisant des interfaces biophysiques standards et diverses cellules biologiques, ainsi que l'émulation en temps réel de modèles complexes. Le système mis au point permet de réaliser des expériences biohybrides ainsi que l'émulation en temps réel de réseaux de neurones.Le système développé devrait constituer une étape essentielle vers le développement de neuroprothèses neuromorphiques pour les thérapies bioélectriques comme l'électroceutique. Elle permet également la communication avec des réseaux de neurones biologiques sur une échelle de temps similaire, facilitée par un système en temps réel embarqué, facile à utiliser et accessible.Le dispositif en temps réel développé démontre son potentiel dans des applications pratiques et expériences biohybrides.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 led to the design of the new generation of neuroprostheses for brain repair.However, its complete development requires deeper understanding and expertise in biohybrid interaction. Here, this thesis work shows a novel real-time, biomimetic, cost-effective and user-friendly neural network for bio-hybrid experiments and real-time emulation.This thesis work allows investigation and reproduction of biophysically detailed neural network dynamics while promoting cost-efficiency, flexibility and ease of use. It showcases the feasibility of conducting biohybrid experiments using standard biophysical interfaces and various biological cells as well as real-time emulation of complex models.The system developped in this work is anticipated to be a step towards developing neuromorphic-based neuroprostheses for bioelectrical therapeutics by enabling communication with biological networks on a similar time scale, facilitated by an easy-to-use and accessible embedded real-time system.The real-time device developped further enhances its potential for practical applications in biohybrid experiments

Creation of neural melodies in the frame of an international student project

This work is a collaborative project between the University of Tokyo and the University of Bordeaux. Students are enrolled in their second year of a technical diploma in EEIC (Electrical Engineering and Industrial Computing) major, at IUT Bordeaux, University of Bordeaux, France. One from the University of Tokyo, Japan and two researchers from the University of Bordeaux were supervising the project. The purpose of this project is to create a melody from the electrical activity of in vitro neuronal culture. This music creation has a twofold objective of artistic performance and diagnostic use. The changes in music allow researchers to identify differences between healthy activity of neuronal cultures and activity of cultures affected by neurological disorders. From recordings of neuronal activities performed at the University of Tokyo, the students classified and sorted the different activities in groups of amplitudes associated to notes in the minor pentatonic scale. Taking place during the COVID19 pandemic, this online project shows the importance of international collaborations and their potential to stimulate student interest while developing new skills. These projects also offer the opportunity for students to pursue in an internship

From real-time single to multicompartmental Hodgkin-Huxley neurons on FPGA for bio-hybrid systems

Modeling biological neural networks has been a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain in normal and pathological conditions. The emergence of real-time neuromorphic platforms has been leading to a rising significance of bio-hybrid experiments as part of the development of neuromorphic biomedical devices such as neuroprosthesis. To provide a new tool for the neurological disorder characterization, we design real-time single and multicompartmental Hodgkin-Huxley neurons on FPGA. These neurons allow biological neural network emulation featuring improved accuracy through compartment modeling and show integration in bio-hybrid system thanks to its real-time dynamics

Low power and massively parallel simulation of oscillatory biochemical networks on FPGA

International audienceBiological functions emerge from a multitude of chemical species woven into intricate biochemical networks. It is crucial to compute the dynamics of a biochemical network from its kinetics and topology. In order to reverse engineer networks and map their design space, dynamics needs to be simulated for many different parameters and topologies, leading to a combinatorial explosion that requires heavy computational power. To solve this issue, we show here an application of FPGA platform to simulate biochemical networks. As a toy model, we simulate a structurally simple network with a rich oscillatory dynamics: a predator-prey biochemical oscillators. The network mimics predator-prey dynamics. We show that FPGA can simulate the dynamics of PP faithfully. These results open the door to more energy-efficient simulations