Guy H Wilson

The paper measures neural signal instability in long-term intracortical recordings to improve brain-computer interface performance through recalibration timing.

This paper demonstrates a high-performance speech neuroprosthesis that achieves low word error rates and high decoding speeds using intracortical recordings from a person with ALS.

This paper introduces a hidden Markov model for unsupervised recalibration of intracortical brain-computer interfaces, showing improved performance over long-term use.

This study decodes 39 English phonemes from neural signals in the dorsal precentral gyrus using intracortical electrode arrays, achieving 33.9% classification accuracy with a recurrent neural network.

The paper records neural activity in the motor cortex of people with paralysis during speech and non-speaking movements, showing that neurons modulate during speech and revealing common neural dynamics between speech and arm movements.