Hadar Levi-Aharoni

This paper introduces a multi-user transformer-based decoder for intracortical speech BCIs, achieving lower word error rates with less training data than individual models.

The paper shows that during typing skill acquisition using a BCI, neural population dynamics in the dorsal premotor cortex become more compact, with left hemisphere showing enhanced firing-rate modulation and generalization.

This paper decodes intended speech from a person with anarthria and locked-in syndrome using an intracortical brain-computer interface, showing that phonemes, words, and higher-order language units can be decoded above chance.

The paper uses lossy compression models to estimate individual memory capacity from P300 responses in an auditory oddball task.