ArticleFrontiers in neurorobotics2015
Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm.
Article in Frontiers in neurorobotics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 29 citations in OpenAlex.
- Regulation of Synaptic Plasticity and Adaptive Convergence Under Rhythmic Stimulation of an In Vitro Hippocampal Neuronal Network of Cultured Cells.Biosensors · 2026Article
- Closed-loop coupling of both physiological spindle model and spinal pathways for sensorimotor control of human center-out reaching.Frontiers in computational neuroscience · 2025Article
- Tutorial: using NEURON for neuromechanical simulations.Frontiers in computational neuroscience · 2023Article
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- Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning.PloS one · 2022Article
- [Recognition of three different imagined movement of the right foot based on functional near-infrared spectroscopy].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2020Article
- Noise-Correlation Is Modulated by Reward Expectation in the Primary Motor Cortex Bilaterally During Manual and Observational Tasks in Primates.Frontiers in behavioral neuroscience · 2020Article
- Adaptive filtering of physiological noises in fNIRS data.Biomedical engineering online · 2018Article
- Geppetto: a reusable modular open platform for exploring neuroscience data and models.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Article
- A Survey of Robotics Control Based on Learning-Inspired Spiking Neural Networks.Frontiers in neurorobotics · 2018Review
- Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm.Frontiers in neuroscience · 2016Article
- Article
- Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis.IBM journal of research and developmentArticle
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Embedding computational models in the physical world is a critical step towards constraining their behavior and building practical applications. Here we aim to drive a realistic musculoskeletal arm model using a biomimetic cortical spiking model, and make a robot arm reproduce the same trajectories in real time. Our cortical model consisted of a 3-layered cortex, composed of several hundred spiking model-neurons, which display physiologically realistic dynamics. We interconnected the cortical model to a two-joint musculoskeletal model of a human arm, with realistic anatomical and biomechanical properties. The virtual arm received muscle excitations from the neuronal model, and fed back proprioceptive information, forming a closed-loop system. The cortical model was trained using spike timing-dependent reinforcement learning to drive the virtual arm in a 2D reaching task. Limb position was used to simultaneously control a robot arm using an improved network interface. Virtual arm muscle activations responded to motoneuron firing rates, with virtual arm muscles lengths encoded via population coding in the proprioceptive population. After training, the virtual arm performed reaching movements which were smoother and more realistic than those obtained using a simplistic arm model. This system provided access to both spiking network properties and to arm biophysical properties, including muscle forces. The use of a musculoskeletal virtual arm and the improved control system allowed the robot arm to perform movements which were smoother than those reported in our previous paper using a simplistic arm. This work provides a novel approach consisting of bidirectionally connecting a cortical model to a realistic virtual arm, and using the system output to drive a robotic arm in real time. Our techniques are applicable to the future development of brain neuroprosthetic control systems, and may enable enhanced brain-machine interfaces with the possibility for finer control of limb prosthetics.
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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.