ArticleNature communications2017
Rapid control and feedback rates enhance neuroprosthetic control.
Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
- High performance communication by people with paralysis using an intracortical brain-computer interface.eLife · 2017Trial
- Assistive algorithms influence neural representations in motor brain-computer interfaces.Nature communications · 2026Article
- Duration-modulated neural population dynamics in humans during BMI controls.Communications biology · 2026Article
- Fuzzing the brain: automated stress testing for the safety of ML-driven neurostimulation.Journal of neural engineering · 2026Article
- Prioritized learning of cross-population neural dynamics.Journal of neural engineering · 2025Article
- Investigating the benefits of artificial neural networks over linear approaches to BMI decoding.Journal of neural engineering · 2025Article
- Less is more: selection from a small set of options improves BCI velocity control.Journal of neural engineering · 2025Article
- Article
- A theory of brain-computer interface learning via low-dimensional control.bioRxiv : the preprint server for biology · 2025Article
- Decoding Continuous Tracking Eye Movements from Cortical Spiking Activity.International journal of neural systems · 2025Article
- Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks.Nature neuroscience · 2024Article
- Nonlinear model predictive control of a conductance-based neuron model via data-driven forecasting.Journal of neural engineering · 2024Article
- Event detection and classification from multimodal time series with application to neural data.Journal of neural engineering · 2024Article
- BRAND: a platform for closed-loop experiments with deep network models.Journal of neural engineering · 2024Article
- Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity.Journal of neural engineering · 2024Article
- Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Decoding motor plans using a closed-loop ultrasonic brain-machine interface.Nature neuroscience · 2024Article
- Unsupervised learning of stationary and switching dynamical system models from Poisson observations.Journal of neural engineering · 2023Article
- Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity.bioRxiv : the preprint server for biology · 2023Article
- Invariant neural dynamics drive commands to control different movements.Current biology : CB · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-machine interfaces (BMI) create novel sensorimotor pathways for action. Much as the sensorimotor apparatus shapes natural motor control, the BMI pathway characteristics may also influence neuroprosthetic control. Here, we explore the influence of control and feedback rates, where control rate indicates how often motor commands are sent from the brain to the prosthetic, and feedback rate indicates how often visual feedback of the prosthetic is provided to the subject. We developed a new BMI that allows arbitrarily fast control and feedback rates, and used it to dissociate the effects of each rate in two monkeys. Increasing the control rate significantly improved control even when feedback rate was unchanged. Increasing the feedback rate further facilitated control. We also show that our high-rate BMI significantly outperformed state-of-the-art methods due to higher control and feedback rates, combined with a different point process mathematical encoding model. Our BMI paradigm can dissect the contribution of different elements in the sensorimotor pathway, providing a unique tool for studying neuroprosthetic control mechanisms.
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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.