ArticleNeuron2021
Real-time linear prediction of simultaneous and independent movements of two finger groups using an intracortical brain-machine interface.
Article in Neuron, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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.
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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
22 citing papers in PubMed, 49 citations in OpenAlex.
- Restoring rapid natural bimanual typing with a neuroprosthesis after paralysis.Nature neuroscience · 2026Article
- Targeting grasp-related cortical areas for intracortical brain-machine interfaces.Neuroimage. Reports · 2026Article
- The Association of Primate Veterinarians and the European Primate Veterinarians Position Statement on the Value of Nonhuman Primates in Research.Journal of the American Association for Laboratory Animal Science : JAALAS · 2026Article
- Overlap in neural representations of coordinated wrist and finger movements in human motor cortex.bioRxiv : the preprint server for biology · 2026Article
- Long-term Intracortical Neural activity and Kinematics (LINK): An intracortical neural dataset for chronic brain-machine interfaces, neuroscience, and machine learning.Advances in neural information processing systems · 2025Article
- Gesture encoding in human left precentral gyrus neuronal ensembles.Communications biology · 2025Article
- EEG-based brain-computer interface enables real-time robotic hand control at individual finger level.Nature communications · 2025Article
- Investigating the benefits of artificial neural networks over linear approaches to BMI decoding.Journal of neural engineering · 2025Article
- Pseudo-linear summation explains neural geometry of multi-finger movements in human premotor cortex.Nature communications · 2025Article
- A high-performance brain-computer interface for finger decoding and quadcopter game control in an individual with paralysis.Nature medicine · 2025Article
- Enhancing neuroprosthesis calibration: the advantage of integrating prior training over exclusive use of new data.Journal of neural engineering · 2024Article
- Evolution, biomechanics, and neurobiology converge to explain selective finger motor control.Physiological reviews · 2024Review
- A flexible intracortical brain-computer interface for typing using finger movements.bioRxiv : the preprint server for biology · 2024Article
- Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces.Advances in neural information processing systems · 2024Article
- Multifunctional fibers enable modulation of cortical and deep brain activity during cognitive behavior in macaques.Science advances · 2023Article
- Error detection and correction in intracortical brain-machine interfaces controlling two finger groups.Journal of neural engineering · 2023Article
- Article
- Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex.Journal of neural engineering · 2023Article
- A brain-computer typing interface using finger movements.International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering · 2023Article
- Neural Decoding for Intracortical Brain-Computer Interfaces.Cyborg and bionic systems (Washington, D.C.) · 2023Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Modern brain-machine interfaces can return function to people with paralysis, but current upper extremity brain-machine interfaces are unable to reproduce control of individuated finger movements. Here, for the first time, we present a real-time, high-speed, linear brain-machine interface in nonhuman primates that utilizes intracortical neural signals to bridge this gap. We created a non-prehensile task that systematically individuates two finger groups, the index finger and the middle-ring-small fingers combined. During online brain control, the ReFIT Kalman filter could predict individuated finger group movements with high performance. Next, training ridge regression decoders with individual movements was sufficient to predict untrained combined movements and vice versa. Finally, we compared the postural and movement tuning of finger-related cortical activity to find that individual cortical units simultaneously encode multiple behavioral dimensions. Our results suggest that linear decoders may be sufficient for brain-machine interfaces to execute high-dimensional tasks with the performance levels required for naturalistic neural prostheses.
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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.