Dean J. Krusienski

This study examines bandpower and phase-amplitude coupling in the Globus pallidus internus of Parkinson's patients during different locomotor states, finding correlations with clinical motor scores.

The paper uses time-series models to predict human EEG responses to visual stimuli and finds the simplest AR model performs as well as more complex models.

The paper analyzes intracranial recordings to compare speech activity detection across overt, mouthed, and imagined speech, finding a nested hierarchy of relevant brain channels.

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

The paper shows that high-gamma ECoG activity in the prefrontal cortex tracks musical rhythm periodicity during perception and imagination.

This paper uses deep neural networks to reconstruct speech from ECoG signals, achieving high correlation between reconstructed and original logMel spectrograms.