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PubMed2000

Nonlinear Markov process amplitude EEG model for nonlinear coupling interaction of spontaneous EEG.

To develop an appropriate model for representing spontaneous electroencephalography (EEG) is an important and necessary work in the field of neuroscience. The Markov process amplitude (MPA) EEG model has been proposed in our previous work for representing the features of the EEG in terms of a few parameters. However, being a linear model, the linear MPA EEG model cannot perfectly describe the spontaneous EEG that displays nonlinear phenomena. In this paper, the nonlinear Markov process amplitude (nonlinear MPA) EEG model that includes nonlinear components is introduced. The consistent consideration of the nonlinear features of the EEG investigated by N. Wiener and P. L. Nunez can be seen from the nonlinear MPA EEG model. The similarity in the time domain and the goodness of fitting in the frequency domain with respect to the ongoing EEG are shown. As a result, the EEG power spectrum can be decomposed into the spontaneous components and the nonlinearly coupled components by use of the nonlinear MPA EEG model, which is useful for a better understanding the mechanism of the EEG generation.

Biomedical Engineering↗
PubMed2000

Multivariate continuation ratio models: connections and caveats.

We develop semiparametric estimation methods for a pair of regressions that characterize the first and second moments of clustered discrete survival times. In the first regression, we represent discrete survival times through univariate continuation indicators whose expectations are modeled using a generalized linear model. In the second regression, we model the marginal pairwise association of survival times using the Clayton-Oakes cross-product ratio (Clayton, 1978, Biometrika 65, 141-151; Oakes, 1989, Journal of the American Statistical Association 84, 487-493). These models have recently been proposed by Shih (1998, Biometrics 54, 1115-1128). We relate the discrete survival models to multivariate multinomial models presented in Heagerty and Zeger (1996, Journal of the American Statistical Society 91, 1024-1036) and derive a paired estimating equations procedure that is computationally feasible for moderate and large clusters. We extend the work of Guo and Lin (1994, Biometrics 50, 632-639) and Shih (1998) to allow covariance weighted estimating equations and investigate the impact of weighting in terms of asymptotic relative efficiency. We demonstrate that the multinomial structure must be acknowledged when adopting weighted estimating equations and show that a naive use of GEE methods can lead to inconsistent parameter estimates. Finally, we illustrate the proposed methodology by analyzing psychological testing data previously summarized by TenHave and Uttal (1994, Applied Statistics 43, 371-384) and Guo and Lin (1994).

Analysis of Variance↗
PubMed2004

Genetic analysis of non-essential amino acid contents in rice (Oryza sativa L.) across environments.

Genetic main effects and genotype x environment (GE) interaction effects for 7 non-essential amino acids in milled rice were analyzed for two year data by using the genetic models based on mixed linear model approaches for quantitative traits of triploid endosperm. Nine cytoplasmic, male sterile lines as females and five restoring lines as males were introduced in a diallel cross in two environments. It was found that the content of non-essential amino acids including Asp, Ser, Glu, Gly and Tyr were mainly controlled by genetic main effects, whereas the content of Ala or Pro was mainly affected by GE effects. In genetic main effects, the cytoplasmic and maternal genetic effects were preponderant for all traits of non-essential amino acids, indicating that selection for improving these traits based on the maternal plant would be more effective than on seeds. The total narrow-sense heritabilities for non-essential amino acids were 70.9-85.9%. By predicating the genetic effects of parents, the total genetic effects from Xieqingzao, V20, Zuo 5 and Zhenshan 97 were mainly negative and these parents would decrease the content of most essential amino acids. Since parents of Zhenan 3, Yinchao 1, T49, 26715, 102 and 1391 had possessed a positive value of most total genetic effects, these parents could be chosen as optimal parents for increasing the content of most non-essential amino acids.

Amino Acids↗
PubMed1999

Application of linear circuit models to impedance spectra in irradiated muscle.

We have applied a number of modeling schemes to previously reported in vivo electrical impedance measurements on irradiated and normal muscle in the hind legs of rats. Specifically, seven-parameter parallel pathways and embedded membrane circuit models have been fit to group averages of impedance spectra measured at different doses and time points. Correlations between histologically scored tissue sections and model parameters have also been determined. The results show that both models produce good fits to the experimental observations, especially in the case of the irradiated tissues. The correlations between histology scores and circuit parameters were, however, higher with the embedded model. Trends in the spectra and the model parameters were found to agree with the expected changes in tissue pathophysiology associated with the progression of tissue injury from radiation exposure. Quantitative correlations with specific histological criteria were less conclusive, suggesting that more information may be needed to refine the model architecture if model parameters are to be explicitly related to the types and extent of tissue damage induced by radiation treatments.

Animals↗