ArticleScientific reports2017
Leveraging neural dynamics to extend functional lifetime of brain-machine interfaces.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 46 citations in OpenAlex.
- Stabilizing brain-computer interfaces through alignment of latent dynamics.Nature communications · 2025Article
- Reducing power requirements for high-accuracy decoding in iBCIs.Journal of neural engineering · 2024Article
- Similar neural states, but dissimilar decoding patterns for motor control in parietal cortex.Network neuroscience (Cambridge, Mass.) · 2024Article
- Invariant neural dynamics drive commands to control different movements.Current biology : CB · 2023Article
- Neural Plasticity in Sensorimotor Brain-Machine Interfaces.Annual review of biomedical engineering · 2023Review
- The science and engineering behind sensitized brain-controlled bionic hands.Physiological reviews · 2022Review
- Cortical Control of Virtual Self-Motion Using Task-Specific Subspaces.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Increasing Robustness of Brain-Computer Interfaces Through Automatic Detection and Removal of Corrupted Input Signals.Frontiers in neuroscience · 2022Article
- Article
- Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior.Nature communications · 2021Article
- A Framework for Optimizing Co-adaptation in Body-Machine Interfaces.Frontiers in neurorobotics · 2021Article
- Stabilization of a brain-computer interface via the alignment of low-dimensional spaces of neural activity.Nature biomedical engineering · 2020Article
- Long-term stability of cortical population dynamics underlying consistent behavior.Nature neuroscience · 2020Article
- Classifying Intracortical Brain-Machine Interface Signal Disruptions Based on System Performance and Applicable Compensatory Strategies: A Review.Frontiers in neurorobotics · 2020Review
- Structure and variability of delay activity in premotor cortex.PLoS computational biology · 2019Article
- Innovations in electrical stimulation harness neural plasticity to restore motor function.Bioelectronics in medicine · 2018Article
- Latent Factors and Dynamics in Motor Cortex and Their Application to Brain-Machine Interfaces.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Intracortical brain-machine interfaces (BMIs) aim to restore lost motor function to people with neurological deficits by decoding neural activity into control signals for guiding prostheses. An important challenge facing BMIs is that, over time, the number of neural signals recorded from implanted multielectrode arrays will decline and result in a concomitant decrease of BMI performance. We sought to extend BMI lifetime by developing an algorithmic technique, implemented entirely in software, to improve performance over state-of-the-art algorithms as the number of recorded neural signals decline. Our approach augments the decoder by incorporating neural population dynamics remembered from an earlier point in the array lifetime. We demonstrate, in closed-loop experiments with two rhesus macaques, that after the loss of approximately 60% of recording electrodes, our approach outperforms state-of-the-art decoders by a factor of 3.2× and 1.7× (corresponding to a 46% and 22% recovery of maximal performance). Further, our results suggest that neural population dynamics in motor cortex are invariant to the number of recorded neurons. By extending functional BMI lifetime, this approach increases the clinical viability of BMIs.
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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.