Nicolas G. Kunigk

This paper introduces error modulation in motor BCIs using pre-error motor cortex activity to improve cursor control performance during online BCI tasks.

The paper uses a finite element model to predict tissue strain from micromotion in Utah arrays and correlates these strains with electrode performance in humans and non-human primates.

This study examines how immersive environments affect BCI performance, finding that prior experience with an environment is more important than its immersiveness for decoder performance and generalization.

The paper trains an autoregressive Transformer on neural spiking data to decode motor behavior, showing broad utility across tasks but highlighting limitations in scaling.