ReviewiScience2020
Plasticity and Adaptation in Neuromorphic Biohybrid Systems.
Review in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Engineered Living Systems With Self-Organizing Neural Networks: From Anatomy to Behavior and Gene Expression.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Advancing neuroengineering with Neuromorphic Twins.Nature communications · 2026Review
- A neuromorphic processor with on-chip learning for beyond-CMOS device integration.Nature communications · 2025Article
- Spontaneous Dynamics Predict the Effects of Targeted Intervention in Hippocampal Neuronal Cultures.bioRxiv : the preprint server for biology · 2025Article
- Home-Cage Training for Non-Human Primates: An Opportunity to Reduce Stress and Study Natural Behavior in Neurophysiology Experiments.Animals : an open access journal from MDPI · 2025Review
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Lattice physics approaches for neural networks.iScience · 2024Review
- Biohybrid Robotic Hand to Investigate Tactile Encoding and Sensorimotor Integration.Biomimetics (Basel, Switzerland) · 2024Article
- 68-channel neural signal processing system-on-chip with integrated feature extraction, compression, and hardware accelerators for neuroprosthetics in 22 nm FDSOI.Frontiers in neuroscience · 2024Article
- Dynamic and Functional Alterations of Neuronal Networks In Vitro upon Physical Damage: A Proof of Concept.Micromachines · 2022Article
- Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering.Brain sciences · 2022Review
- Advances in construction and modeling of functional neural circuits in vitro.Neurochemical research · 2022Article
- Will microfluidics enable functionally integrated biohybrid robots?Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Memristor-Based Neuromodulation Device for Real-Time Monitoring and Adaptive Control of Neuronal Populations.ACS applied electronic materials · 2022Article
- Classification of Whisker Deflections From Evoked Responses in the Somatosensory Barrel Cortex With Spiking Neural Networks.Frontiers in neuroscience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuromorphic systems take inspiration from the principles of biological information processing to form hardware platforms that enable the large-scale implementation of neural networks. The recent years have seen both advances in the theoretical aspects of spiking neural networks for their use in classification and control tasks and a progress in electrophysiological methods that is pushing the frontiers of intelligent neural interfacing and signal processing technologies. At the forefront of these new technologies, artificial and biological neural networks are tightly coupled, offering a novel "biohybrid" experimental framework for engineers and neurophysiologists. Indeed, biohybrid systems can constitute a new class of neuroprostheses opening important perspectives in the treatment of neurological disorders. Moreover, the use of biologically plausible learning rules allows forming an overall fault-tolerant system of co-developing subsystems. To identify opportunities and challenges in neuromorphic biohybrid systems, we discuss the field from the perspectives of neurobiology, computational neuroscience, and neuromorphic engineering.
Indexed as
Identifiers
What OpenQuestion holds
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.