Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces.

ABSTRACT: Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method, "MINDFUL", to measure instabilities in neural data for useful long-term iBCI, without needing labels of user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed de

SUBMITTER: Pun TK 

PROVIDER: S-EPMC11494208 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature