Prediction of Reach Goals in Depth and Direction from the Parietal Cortex

Summary: The posterior parietal cortex is well known to mediate sensorimotor transformations during the generation of movement plans, but its ability to control prosthetic limbs in 3D environments has not yet been fully demonstrated. With this aim, we trained monkeys to perform reaches to targets located at various depths and directions and tested whether the reach goal position can be extracted from parietal signals. The reach goal location was reliably decoded with accuracy close to optimal (>90%), and this occurred also well before movement onset. These results, together with recent work showing a reliable decoding of hand grip in the same area, suggest that this is a suitable site to decode the entire prehension action, to be considered in the development of brain-computer interfaces. : Filippini et al. show that it is possible to use parietal cortex activity to predict in which direction the arm will move and how far it will reach. This opens up the possibility of neural prostheses that can accurately guide reach and grasp using signals from this part of the brain. Keywords: neuroprosthetics, offline neural decoding, reaching in depth, monkey, V6A, machine learning, visuomotor transformations, hand guidance, prehension, robotic