ArticleNature communications2024
BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Organoid intelligence: a promising paradigm for autism spectrum disorder research.Molecular psychiatry · 2026Review
- Fabrication of High-Density Multimodal Neural Probes Based on Heterogeneously Integrated CMOS.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Wnt activation and dual SMAD inhibition for induction and maintenance of hindbrain-like neural stem cell from hiPSCs.Cell reports methods · 2026Article
- Online supervised learning of temporal patterns in biological neural networks under feedback control.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Shape-conformal porous frameworks for full coverage of neural organoids and high-resolution electrophysiology.Nature biomedical engineering · 2026Article
- Advancing neuroengineering with Neuromorphic Twins.Nature communications · 2026Review
- Advances in large-scale electrophysiology with high-density microelectrode arrays.Lab on a chip · 2025Review
- Building an Egocentric-to-Allocentric Travelling Direction Transformation Model for Enhanced Navigation in Intelligent Agents.Sensors (Basel, Switzerland) · 2025Article
- Multiscale fusion enhanced spiking neural network for invasive BCI neural signal decoding.Frontiers in neuroscience · 2025Article
- Biomaterials for neuroengineering: applications and challenges.Regenerative biomaterials · 2025Review
- Real-time multicompartment Hodgkin-Huxley neuron emulation on SoC FPGA.Frontiers in neuroscience · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.