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Related Experiment Video

Updated: Dec 30, 2025

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Chronically Stable, High-Resolution Micro-Electrocorticographic Brain-Computer Interfaces for Real-Time Motor

Erda Zhou1,2, Xiner Wang1,2, Jizhi Liang1,2

  • 12020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|September 6, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a high-density micro-electrocorticography (µECoG) brain-computer interface (BCI) for stable, real-time motor decoding. This flexible BCI offers improved performance and reduced invasiveness for neurological disorder patients.

Keywords:
brain‐computer interfacesflexible conformal micro‐electro‐mechanical systemshigh‐resolution micro‐electrocorticography, real‐time motor decoding

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Medical Devices

Background:

  • Brain-computer interfaces (BCIs) are crucial for restoring communication and motor functions in individuals with neurological disorders.
  • Conventional electrocorticography (ECoG) BCIs face limitations in spatial resolution and device size.
  • High-density electrode arrays are needed to improve the precision of brain activity decoding.

Purpose of the Study:

  • To develop and evaluate a high-resolution, flexible micro-electrocorticography (µECoG) BCI system.
  • To assess the chronic stability and real-time motor decoding capabilities of the µECoG BCI.
  • To demonstrate the potential of µECoG technology to overcome limitations of conventional ECoG BCIs.

Main Methods:

  • Utilized micro-nano manufacturing to create a flexible, high-density µECoG electrode array with a 64-fold increase in electrode density.
  • Conducted a 203-day in vivo experiment to evaluate chronic stability and performance.
  • Implemented real-time motor decoding algorithms for tasks such as game and cursor control.

Main Results:

  • The µECoG BCI demonstrated chronically stable performance over 203 days.
  • Achieved real-time motor decoding, enabling game control within 7 minutes of training.
  • Reached a peak bit rate of 4.15 bits per second (BPS) for cursor control, comparable to intracortical EEG BCIs without invasiveness.

Conclusions:

  • High-resolution µECoG BCIs offer enhanced spatial specificity for improved decoding performance.
  • The flexible, high-density µECoG array significantly advances BCI technology, reducing device size and invasiveness.
  • This µECoG BCI represents a breakthrough in clinical feasibility for flexible, high-performance brain-computer interfaces.