Objective To explore the relationship between the depth of anesthesia and the autocorrelation of spontaneous EEG signals,and to find a new indicator which is easily calculated and involves fewer channels of ECG.Methods Eighteen patients with a surgical operation on chest or abdomen under general anesthesia served as the subjects.EEG signals of the patients were recorded.Change of ? rhythm of the EEG signal during general anesthesia was investigated by autocorrelation.Results The changes of autocorrelation indicator in channels Fp1-Cz and Fp2-Cz were obvious and consistent with the process of anesthesia;The changes of autocorrelation kcr in the two observed channels were almost synchronous.Conclusion The autocorrelation indicator kcr may be a new idea and a new tool for monitoring depth of anesthesia with fewer channels and the method will find wide prospect of application in clinic and in related scientific research work.

Objective To investigate the status of central nervous system(CNS)during general anesthesia using a new method of monitor.Methods Eighteen patients during general anesthesia were randomly chosen as the subjects.EEG signals of the patients were recorded as the subject was undergoing a surgical operation.Status of CNS of the patients during general anesthesia was monitored through the changes of Kolmogorov entropy(KE)of the EEG signals.Results Under the same kind of anesthesia measures,though most patients' CNS presented roughly the same status,but important differences were found in individual cases.Some presented depressed CNS status,some presented excited CNS status and others presented epileptic status.Conclusion The same general anesthesia may have different effects on different subjects.KE can reflect the status of the prefrontal cortex during general anesthesia.KE may be a new tool for monitoring the status of CNS during general anesthesia.

Mental task classification is one of the most important problems in Brain-computer interface. This paper studies the classification of five-class mental tasks. The nonlinear parameter of mean period obtained from frequency domain information was used as features for classification implemented by using the method of SVM (support vector machines). The averaged classification accuracy of 85.6% over 7 subjects was achieved for 2-second EEG segments. And the results for EEG segments of 0.5s and 5.0s compared favorably to those of Garrett's. The results indicate that the parameter of mean period represents mental tasks well for classification. Furthermore, the method of mean period is less computationally demanding, which indicates its potential use for online BCI systems.

Objective To reveal the relationship between the 5-HTTLPR and the Chinese Han nationality children with CA, compared the distribution of the 5-HTTLPR between the Han Chinese children with CA and healthy Han Chinese children ,and analyzed the association between the 5-HTTLPR and clinical symptoms of the Han Chinese children with CA. Methods Genomic DNAs of fifty subjects including 25 autistic children and 25 controls were extracted from blood samples. PCR amplification using Oligonucleotide primers flanking 5-HTTLPR was performed. Results ① Three kinds of alleles including the S (short) allele, the L (long) allele and the VL allele were found , and the 5-HTTLPR genotypes shown were S/S, L/L, S/L and L/VL. ② Allele frequencies did not differ significantly in patient groups in comparison with the control sample. No significant difference was identified between the observed 5-HTTLPR genotype distribution of the patient groups and control group. ③ The distribution of homozygous and heterozygous subjects between the two groups differed significantly. ④ The genotypes of the 5-HTTLPR polymorphism correlated significantly with the Body Movement Factor. ⑤ The allele frequency of healthy Han Chinese population and that of healthy Japanese population were similar. The frequency of S allele in not only autistic subjects but also healthy children in this study was considerably more than that in Caucasians and the frequency of L allele in our subjects decreased correspondingly. Conclusion ① A significant difference in the allele frequency between the Han Chinese and Caucasian populations was found. ② The genotypes of the 5-HTTLPR polymorphism correlated significantly with the Body Movement Factor of the patients. ③ The homozygote and the L allele were positively relevant to CA and they might be the risk factors of CA. The heterozygote and the S allele were negatively relevant to CA and they might be the protective factors of CA.

The event-related desynchronization/synchronization(ERD/ERS) time courses of lower and upper alpha band rhythms during hand motor imagery are investigated respectively by Fourier Sectral Entropy (FSE) in this paper. By analyzing one group of BCI competition data, it was found that FSE within upper alpha band displays a pronounced increase and decrease over contralateral and ipsilaterai brain areas respectively at the onset of hand motor imagery, which is corresponding to the antagonistic ERD/ERS patterns in previous studies. Different from the upper alpha activity pattern, FSE within lower alpha band displays a consistent increase over both two hemispheres hand representative areas. The preliminary results show that FSE could disclose the different behaviors of the upper and lower alpha band rhythms so that a new idea with the complexity measure is provided to characterize functional dissociation of lower and upper frequency alpha rhythms in relation to hand motor imagery.

Water-fat separation is a particularly important problem for magnetic resonance imaging. Although many methods have been proposed, the reliability is still challenging. In this work, we have presented a method based on the combination of the branch-cut method and multigrid algorithm to get a more robust performance of water-fat separation. First, the branch-cut method is applied to identify residues, which violates the requirement that the interacting phase gradient around a closed path be zero. Residues and branches are marked to be zeros and filled to the weighting factor array. Then, the unwrapped phase array can be given by the multigrid algorithm. Finally, the Dixon method for water-fat separation is applied to the unwrapped phase array. Experiments for brain scanning on the 0.3T low field MRI system demonstrate the successful application of the proposed method.

Objective To detect the change of brain activity under different depth of anesthesia (DOA)noninvasively. Methods The Lempel-Ziv complexity C(n) was used to analyze EEG and its four components (delta,theta, alpha, beta), which was recorded from SD rats under different DOA. The relationship between C(n) and DOA was studied. Results The C(n) of EEG will decrease while the depth of anesthesia increasing and vice versa. It can be used to detect the change of DOA sensitively. Compared with power spectrum, the change of C(n) is opposite to that of power spectru,. Only the C(n) of delta rhythm has obvious variations induced by the change of DOA, and the variations of delta is as similar as the EEG's. Conclusion The study shows that the desynchronized EEG is replaced by the synchronized EEG when rat goes into anesthesia state from awake, that is just the reason why complexity and power spectrum appear corresponding changes under different DOA. C(n) of delta rhythm dynamic change leads to the change of EEG, and the delta rhythm is the dominant rhythm during anesthesia for rats.

Objective Previous studies of peripheral nerves activation during magnetic stimulation have focused almost exclusively on the cause of high external parallel electric field along the nerves, whereas the effect of the transverse component has been ignored. In the present paper, the classical cable function is modified to represent the excitation of peripheral nerves stimulated by a transverse electric field during magnetic stimulation. Methods Responses of the Ranvier nodes to a transverse-field are thoroughly investigated by mathematic simulation. Results The simulation demonstrates that the excitation results from the net inward current driven by an external field. Based on a two-stage process, a novel model is introduced to describe peripheral nerves stimulated by a transverse-field. Based on the new model, the classical cable function is modified. Conclusion Using this modified cable equation, the excitation threshold of peripheral nerves in a transverse field during MS is obtained. The modified cable equation can be used to represent the response of peripheral nerves by an arbitrary electric field.

Objective To propose an automatic framework for segmentation of brain image in this paper. Methods The brain MRI image segmentation framework consists of three-step segmentation procedures. First, Non-brain structures removal by level set method. Then, the non-uniformity correction method is based on computing estimates of tissue intensity variation. Finally, it uses a statistical model based on Markov random filed for MRI brain image segmentation. The brain tissue can be classified into cerebrospinal fluid, white matter and gray matter. Results To evaluate the proposed our method, we performed two sets of experiments, one on simulated MR and another on real MR brain data. Conclusion The efficacy of the brain MRI image segmentation framework has been demonstrated by the extensive experiments. In the future, we are also planning on a large-scale clinical evaluation of this segmentation framework.

Objective To present a novel modified level set algorithm for medical image segmentation. Methods The algorithm is developed by substituting the speed function of level set algorithm with the region and gradient information of the image instead of the conventional gradient information. This new algorithm has been tested by a series of different modality medical images. Results We present various examples and also evaluate and compare the performance of our method with the classical level set method on weak boundaries and noisy images. Conclusion Experimental results show the proposed algorithm is effective and robust.