Extraction Of Dynamic Cognitive Evoked Potentials And It's Application

Average cognitive evoked potentials (CEP) have been used since 1971 in clinic and medical research for brain cognitive function. Because CEPs are dynamic and from the complex neural systems, which have rich dynamic informations for dynamic behavior of brain. Therefore, the averaged CEP can't satisfy to investigate dynamics in brain. However, there are difficult in extracting CEPs from high noise background: (1) CEPs submerged in noise from background ongoing spontaneous electroencephalogram (EEG); (2) the frequency region of CEPs is overlap with that of EEGs; (3) the latency of CEPs vary at a large area.The main purpose of this study is to investigate single-trial extracting late wave of AEP(LWAEP), which is one kind of CEP, in both simulation the experiment of rat cognitive function.The late wave of AEP was simulated, where latency was varied at ±10% and ±20% of its duration. A combination of third-order correlation (TOC) and wavelet transform (WT) was used to extract single-trial of late wave of AEP.More details of the techniques proposed in this thesis are as follows.1. According to the knowledge of signal-to-noise ratio (SNR) and latency of LWAEP, the late wave of AEP was simulated with SNR of OdB and the varies area of latency of ±10% and ±20%. where noises were consisted by white noise and colored noise.2. TOC-WT method was used to extract single-trial of late wave of AEP from noisy AEP in simulation cases to validate the effect of the method. The core of TOC method was to estimate the impulse response of TOC filter by the noisyAEP. Then the TOC filter was used to extract noisy-free AEP, which includs both mid-latency wave and late wave. Because dynamic AEP was extracted one by one, so TOC filter can be insensitive to latency of late wave changing in a large area. On the other hand, TOC filter was insensitive to both white noise and colored noise. WT was used to extract dynamic LWAEP from dynamic AEP which is the output from TOC filter. WT decomposition was at five scale and with bi-orthogonal splines mother function.3. The noisy AEPs of Alzheimer's disease (AD) rat model and control rat were recorded, and then were single-trial LWAEPs were extracted by TOC-WT. The dynamic-average latency and dynamic-average amplitude of PI wave in LWAEPs were used as dynamic indexes for brain cognitive function of the rats. The dynamic-average latency for AD rat model was larger and the dynamic-average amplitude of PI wave for AD rat model was higher compared with those of the control rats.The results of this study are: (1) for the simulated AEPs with latency varing at± 10% of the duration, the relative mean square error (RMSE) of the single trial LWAEP was about 2%; RMSE of P1 wave latency in late wave is about 1.6% , and 5% for PI wave amplitude; (2) for the simulated AEP with latency varing at± 20% of the duration,, the relative mean square error (RMSE) of the single trial LWAEP was about 2%; RMSE of PI wave latency in late wave is about 1.8% , and 6% for PI wave amplitude; (3)the comparison of dynamic-average latency and amplitude of PI wave of LWAEP for AD and control rats show that: the dynamic-average amplitude of PI for AD rats was significantly higher than that for the control(P<0.05,a = 0.05); dynamic-average latency of PI for AD rats was longer than that for control(P<0.05, a = 0.05 ).