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Summary

This summary is machine-generated.

This study introduces a new self-recalibration method for intracortical brain-computer interfaces (iBCIs) using large language models. This approach maintains high performance for over a year, improving communication for individuals with neurological disorders.

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Area of Science:

Neuroscience
Biomedical Engineering
Artificial Intelligence

Background:

Intracortical brain-computer interfaces (iBCIs) offer communication restoration for individuals with severe motor impairments, such as those with amyotrophic lateral sclerosis (ALS).
Current iBCIs require frequent recalibration to counteract neural signal drift, disrupting user experience and limiting practical application.
This recalibration process necessitates supervised data collection, posing a significant usability challenge for long-term iBCI use.

Conclusions:

The CORP method provides a viable solution for long-term stabilization of high-performance communication iBCIs.
This self-recalibration approach addresses a critical barrier to the clinical translation and widespread adoption of iBCI technology.
The findings suggest a pathway towards more robust and user-friendly brain-computer interfaces for individuals with neurological conditions.