ReviewCyborg and bionic systems (Washington, D.C.)2023
An Overview of In Vitro Biological Neural Networks for Robot Intelligence.
Review in Cyborg and bionic systems (Washington, D.C.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- Effects of robot assisted mirror therapy on motor function and cortical activation in patients with right hemisphere damage.Scientific reports · 2025Trial
- Researchers are building computers that run on brain organoids - but have neglected a major ethical issue.Nature · 2026Article
- Janus Synapses as Modular Neurointerfaces.ACS applied materials & interfaces · 2026Review
- Regulation of Synaptic Plasticity and Adaptive Convergence Under Rhythmic Stimulation of an In Vitro Hippocampal Neuronal Network of Cultured Cells.Biosensors · 2026Article
- Microelectrode arrays cultured with in vitro neural networks for motion control tasks: encoding and decoding progress and advances.Microsystems & nanoengineering · 2025Review
- Article
- Optogenetically enhanced physical reservoir computing withJournal of biomedical optics · 2025Article
- Brain organoid maturation and implantation integration based on electrical signals input.Journal of advanced research · 2025Article
- Biomimetic Visual Information Spatiotemporal Encoding Method for In Vitro Biological Neural Networks.Biomimetics (Basel, Switzerland) · 2025Article
- Bioengineering innovations for neural organoids with enhanced fidelity and function.Cell stem cell · 2025Review
- Effects of induced electric field on the sensitivity of a two-compartment neuron model.PloS one · 2025Article
- Biohybrid living robotics: A comprehensive review of recent advances, technological innovation, and future prospects.npj Robotics · 2025Article
- Opportunities and Challenges of Brain-on-a-Chip Interfaces.Cyborg and bionic systems (Washington, D.C.) · 2025Review
- Tunable Neuromorphic Computing for Dynamic Multi-Timescale Sensing in Motion Recognition.Cyborg and bionic systems (Washington, D.C.) · 2025Article
- Neuroscientific insights about computer vision models: a concise review.Biological cybernetics · 2024Review
- Constructing organoid-brain-computer interfaces for neurofunctional repair after brain injury.Nature communications · 2024Article
- Leveraging Machine Learning for Optimized Mechanical Properties and 3D Printing of PLA/cHAP for Bone Implant.Biomimetics (Basel, Switzerland) · 2024Article
- Stable Jumping Control Based on Deep Reinforcement Learning for a Locust-Inspired Robot.Biomimetics (Basel, Switzerland) · 2024Article
- Article
- Underwater Robots and Key Technologies for Operation Control.Cyborg and bionic systems (Washington, D.C.) · 2024Article
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
In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based neurorobotic systems, can interact with the external world, so that they can present some preliminary intelligent behaviors, including learning, memory, robot control, etc. This work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems, with a particular focus on those related to robot intelligence. In this work, we first introduce the necessary biological background to understand the 2 characteristics of the BNNs: nonlinear computing capacity and network plasticity. Then, we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects: from robots to BNNs and from BNNs to robots. Next, we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity (computing capacity-dependent) or depend also on the network plasticity (network plasticity-dependent), which are then expounded respectively, with a focus on those related to the realization of robot intelligence. Finally, the development trends and challenges of the BNN-based neurorobotic systems are discussed.
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.