Neuronal pathway and signal modulation for motor communication

Abstract

The knowledge of the mechanisms of motor imagery (MI) is very important for the development of braincomputer interfaces. Depending on neurophysiological cortical activity, MI can be divided into two categories: visual imagery (VI) and kinesthetic imagery (KI). Our magnetoencephalography (MEG) experiments with ten untrained subjects provided evidences that inhibitory control plays a dominant role in KI. We found that communication between inferior parietal cortex and frontal cortex is realised in the mu-frequency range. We also pinpointed three gamma frequencies to be used for motor command communication. The use of artificial intelligence allowed us to classify MI of left and right hands with maximal classification accuracy using the brain activity encoded in the identified gamma frequencies which were then proposed to be used for communication of specifics. Mu-activity was identified as the carrier of gamma-activity between these areas by means of phase-amplitude coupling similar to the modern day radio wave transmission.