Study On The Principles And Algorithms Of ECoG Analysis-based Brain Mapping Of Motor Cortex

In the cortical eloquent surgery, mapping of motor cortex could real-time diagnosis the boundary of eloquent area such as brain neuromotor, which helped doctors resecting the lesions to maximum as well as protecting the normal brain tissues surrounding the lesions to maximum, and therefore could avoid the damage of neural function and improve quality of life in the postoperative patients. Based on its clinical demand background, the study on mapping of motor cortex had important application value of neurosurgical operations. Mapping of motor cortex under accurate, rapid, noninvasive, and even non-conscious conditions is a basic theoretical problem for clinical and neural medicine to resolve urgently.Aimed at clinical application of mapping of motor cortex by specific analysis of cortical electroencephalogram (ECoG), the ECoG specificity and its processing technology had been studied; the principles and algorithms of ECoG for mapping of motor cortex had been discussed, which could provide theoretical basis for clinical applications of mapping of motor cortex under accurate, rapid and noninvasive conditions during surgery.Firstly, the existing problem of mapping of motor cortex was presented according to the applications and recent progress of mapping of motor cortex; new principle conception for mapping of motor cortex using wavelet analysis of the ECoG during surgery were proposed combined with the recent progress in the Electroencephalogram (EEG) processing technology.Secondly, cortex and function division, in addition to origin and properties of EEG, had been studied systemically. On this basis, combined the principle of ECoG specificity with wavelet transform, the algorithms for feature extraction and classification of ECoG were designed and verified by experimental data. The results showed that, feature extraction and classification of mu rhythm on the basis of event-related desynchronization and synchronization (ERD/ERS) was a feasible algorithm with detection and accuracy rate of 93%; feature extraction and classification of slow cortical potentials (SCP) on the basis of event related potentials (ERP) was a feasible algorithm with detection and accuracy rate of 83%. Based on the algorithm for single modal feature extraction and classification, the detection and accuracy rate of multi-modal feature extraction and classification of ECoG ranged from 78% to 100% according to the principle of ECoG multi-modal specificity. The above three principles and algorithms were feasible, which provided theoretical basis for clinical applications.Finally, multi-modal mapping system of motor cortex based on mμrhythm and SCP for clinic applications was first proposed and designed. The results showed that the multi-modal mapping system of motor cortex during surgery had advantages of accurate, rapid and noninvasive compared with currently used methods.