ArticleNature biomedical engineering2020
A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain-machine interfaces.
Article in Nature biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
- Review and Analysis of Electrochemical Instrumentation Design for Continuous Multi-Analyte Microfluidic Sensor Arrays.Sensors (Basel, Switzerland) · 2026Review
- Low-power differencing feature extracts spiking-band activities for high-performance intracortical brain-computer interfaces.Communications biology · 2026Article
- Encoding of speech modes and loudness in ventral precentral gyrus.Nature communications · 2026Article
- Shared somatosensory-motor neural population dynamics track motor recovery after stroke.bioRxiv : the preprint server for biology · 2026Article
- NeuroGator: A Low-Power Gating System for Asynchronous BCI Based on LFP Brain State Estimation.Brain sciences · 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
- Challenges and Opportunities of Upconversion Nanoparticles for Emerging NIR Optoelectronic Devices.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Decoding multi-joint hand movements from brain signals by learning a synergy-based neural manifold.Patterns (New York, N.Y.) · 2025Article
- Decoding Handwriting Trajectories from Intracortical Brain Signals for Brain-to-Text Communication.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Prioritized learning of cross-population neural dynamics.Journal of neural engineering · 2025Article
- Real-time, neural signal processing for high-density brain-implantable devices.Bioelectronic medicine · 2025Review
- Long-term performance of intracortical microelectrode arrays in 14 BrainGate clinical trial participants.medRxiv : the preprint server for health sciences · 2025Article
- Investigating the benefits of artificial neural networks over linear approaches to BMI decoding.Journal of neural engineering · 2025Article
- Enhanced control of a brain-computer interface by tetraplegic participants via neural-network-mediated feature extraction.Nature biomedical engineering · 2025Article
- A high-performance brain-computer interface for finger decoding and quadcopter game control in an individual with paralysis.Nature medicine · 2025Article
- Reducing power requirements for high-accuracy decoding in iBCIs.Journal of neural engineering · 2024Article
- Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks.Nature neuroscience · 2024Article
- Brain-computer interfaces for neuropsychiatric disorders.Nature reviews bioengineering · 2024Article
- A brain machine interface framework for exploring proactive control of smart environments.Scientific reports · 2024Article
- Event detection and classification from multimodal time series with application to neural data.Journal of neural engineering · 2024Article
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15 authors.
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Abstract
The large power requirement of current brain-machine interfaces is a major hindrance to their clinical translation. In basic behavioural tasks, the downsampled magnitude of the 300-1,000 Hz band of spiking activity can predict movement similarly to the threshold crossing rate (TCR) at 30 kilo-samples per second. However, the relationship between such a spiking-band power (SBP) and neural activity remains unclear, as does the capability of using the SBP to decode complicated behaviour. By using simulations of recordings of neural activity, here we show that the SBP is dominated by local single-unit spikes with spatial specificity comparable to or better than that of the TCR, and that the SBP correlates better with the firing rates of lower signal-to-noise-ratio units than the TCR. With non-human primates, in an online task involving the one-dimensional decoding of the movement of finger groups and in an offline two-dimensional cursor-control task, the SBP performed equally well or better than the TCR. The SBP may enhance the decoding performance of neural interfaces while enabling substantial cuts in power consumption.
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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.