ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Chronically Stable, High-Resolution Micro-Electrocorticographic Brain-Computer Interfaces for Real-Time Motor Decoding.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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.
The trial behind it
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
5 citing papers in PubMed.
- Multifunctional material platforms for neural interfaces: active orchestration of dynamic foreign body response across implantation lifetimes.Bioactive materials · 2026Review
- Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Brain-Adhesive Bioelectronics With Shape-Morphable and Biodegradable Properties for Stable Brain Signal Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Chronically Stable, High-Resolution Micro-Electrocorticographic Brain-Computer Interfaces for Real-Time Motor Decoding.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Advancements in the application of brain-computer interfaces based on different paradigms in amyotrophic lateral sclerosis.Frontiers in neuroscience · 2025Review
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Brain-computer interfaces (BCIs) enable communication between individuals and computers or other assistive devices by decoding brain activity, thereby reconstructing speech and motor functions for patients with neurological disorders. This study presents a high-resolution micro-electrocorticography (µECoG) BCI based on a flexible, high-density µECoG electrode array, capable of chronically stable and real-time motor decoding. Leveraging micro-nano manufacturing technology, the µECoG BCI achieves a 64-fold increase in electrode density compared to conventional clinical electrode arrays, enhancing spatial resolution while featuring scalability. Over a 203-day in vivo experiment, high-resolution µECoG carrying fine spatial specificity information demonstrated the potential to improve decoding performance while reduce implanted devices size. These advancements provide a pathway to overcome the limitations of conventional ECoG BCIs. During awake surgery, the µECoG BCI enabled game control after 7 min of model training. Furthermore, during practice of 19.87 h, the participant achieved cursor control with a bit rate of 1.13 bits per second (BPS) under full volitional control, and the bit rate reached up to 4.15 BPS with enhanced user interface. These results show that the µECoG BCI achieves comparable performance to intracortical electroencephalographic (iEEG) BCIs without intracortical invasiveness, marking a breakthrough in the clinical feasibility of flexible BCIs.
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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.