David A. Bjånes

The paper investigates the neural correlates of conscious tactile perception by analyzing single-neuron activity in PPC and S1 during vibrotactile stimulation.

This study investigates how grasp and object properties are encoded in the cortical grasping network of tetraplegic humans, showing separable neural representations in different brain regions that could improve brain-machine interface performance.

This study shows that neural subspaces for imagined movements in the parietal cortex remain stable over several years in humans, improving the long-term reliability of brain-machine interfaces.

This study shows that visual context influences the perceived timing of tactile sensations from intra-cortical microstimulation, indicating temporal misalignment in multisensory integration.

This study decodes grasp and speech signals from high-level cortical areas in a tetraplegic human, showing that SMG and PMv can decode grasp intentions, while SMG also encodes speech.

HSST optimizes spike sorting parameters using neurophysiological metrics, improving sorting accuracy and robustness across varying conditions.