Louis Wagner

This paper develops a self-correcting intracranial brain-computer interface (BCI) by integrating error-related neural activity from the insula and prefrontal cortex.

The paper identifies stable global neural dynamics across participants and tasks that predict motor behavior from brain-wide recordings in humans.

The paper decodes arbitrary and informed decisions from intracranial recordings in humans, showing differences in spatio-temporal patterns between the two decision types.

The paper analyzes sleep spindle activity in human anterior thalamus and cortex using EEG and DBS recordings, finding coordinated patterns and frequency-dependent topography.

The paper provides a dataset of intracranial EEG recordings from 10 participants during speech production to study neural mechanisms and develop speech decoding technologies.

This paper decodes executed and imagined grasping movements from non-motor brain areas using a lower dimensional representation, achieving high accuracy without primary motor cortex signals.

This paper develops a real-time speech synthesis system from neural activity for imagined and whispered speech, using implanted electrodes and frontal lobe activity.