According to an embodiment, a method for extracting motion-related network characteristics between cranial nerve cells for decoding motion information may comprise the steps of: using signals of a plurality of cranial nerve cells to extract activity information of the cranial nerve cells; calculating a functional connectivity matrix by measuring the amount of normalized mutual information for a plurality of brain signal cell pairs; extracting a significant network model by removing the cranial nerve cell pairs having less than a threshold amount of normalized mutual information; extracting quantitative network characteristics by extracting the characteristics of the cranial nerve cell pairs of the significant network model; and predicting the motion state of the cranial nerve cells by using the extracted network characteristics by using a machine learning classifier.
METHOD AND APPARATUS FOR EXTRACTING MOTION-RELATED NETWORK CHARACTERISTICS BETWEEN CRANIAL NERVE CELLS FOR DECODING MOTION INFORMATION