Research On Target Stereotactic Localization Of Neuronal Structures Based On Neuronal Discharges

Electrophysiological target localization is the key technology in microelectrode guided stereotactic neurosurgery for Parkinson's disease, MER-based functional targeting locate the nominal anatomical target location based on MRI more precisely. The research is based on clinic microelelctrode data of Parkinson's disease. The goal of the study is to identify neuronal structures of microelectrode depth intraoperatively by extracting the characteristics of neuronal discharge signals; to realize objective and automated precise real time localization and to achieve microelectrode guided surgery by analyzing characteristics of the MER data. An in-depth study is given systemically of signal pretreatment, spike enhancement, spike detection, spike extraction, spike sort techniques and characteristic parameters, key technologies of locating microelectrode position, methods of signal processing is given step by step. The main achievements and innovative results are described in the following parts:1,A wavelet transform based method is introduced for removing the baseline draft and high frequency noises in neuronal signals at the same time. The wavelet type for human neuronal spike and optimal decomposition scale levels are selected for avoiding discharge wave distortion during denosing process.2,Two enhancement algorithms of wavelet coefficients and nonlinear energy operator are applied to improving signal to noise ratio. The process of spike detection and extraction are proposed separately to solve the contradiction between detecting accurately and wave distortion of neuronal spikes.3,An exact detection is foundation of spike characteristic analysis. The detection precision is influenced by detection threshold . Two algorithms of threshold and four detection methods are introduced to extract neuronal spikes of different nucleus. A novel algorithm of adaptive threshold detection is presented , the threshold is adjusted automatically for various amplitude and signal to noise ratio. These algorithms are verified by simulative signal and clinical MER signal. The methods of spike detection and classification are correct. Neuronal spikes are extracted of different nucleus, the latency of human neuronal discharge is obtained. Spikes are classificated using PCA.4,Four feature parameters of box dimension, detection threshold, energy modulation, interspike interval are extracted from microelectrode recordings for objective and quantitative target localization, four targeting techniques are presented. The subjective localization of microelectrode position intraoperatively is overcomed. Four targeting techniques can improve localization accuracy, and can be used in clinic neurosurgery. Visual targeting method is given in addition.5,A novel method of identification the fractal scaleless center in correlative dimension is proposed. The choice of fractal scaleless is unsupervised based on the formula presented, correlative dimension can be calculated automatically.6,The animal experimental system is set up. The neuronal spike data are sampled by microelectrode, and processed by spike extraction.four targeting parameters is ued for microelectrode localization. Methods of spike extraction and four targeting techniques are validated by animal experiment.