MOTIVATION Time-course microarray experiments are designed to study biological processes in a temporal fashion. Longitudinal gene expression data arise when biological samples taken from the same subject at different time points are used to measure the gene expression levels. It has been observed that the gene expression patterns of samples of a given tumor measured at different time points are...

This study evaluates the effects of spatial smoothing on inter-subject correlation (ISC) analysis for FMRI data using the traditional model based analysis as a reference. So far within ISC analysis the effects of smoothing have not been studied systematically and linear Gaussian filters with varying kernel widths have been used without better knowledge about the effects of filtering. Instead, w...

It is proposed to identify the behavior of steel beams prior to and after the inception of local buckling by using Digital Image Correlation. Full field measurements are used to evaluate kinematic and static fields for determining constitutive laws. It enables for the detection of local buckling inception and the evaluation of the postbuckled behavior. Constitutive models are tuned by using mea...

We present an approach to integrate multiple fMRI datasets in the context of predictive fMRI data analysis. The approach utilizes canonical correlation analysis (CCA) to find common dimensions among the different datasets, and it does not require that the multiple fMRI datasets be spatially normalized. We apply the approach to the task of predicting brain activations for unseen concrete-noun wo...

Functional magnetic resonance imaging studies answer questions about activation effects in populations of subjects. To begin with, this involves appropriate modeling of the fMRI data at the within-subject level. This is followed by extending the model to multiple subjects. There have been several attempts toward this extension, all of which have focused on inference on a single effect of intere...

Careful attentions must be required for analyzing high dimensional Electroencephalographic (EEG) signals. There have many discrepancy or linearity when signals are recorded at different stimulations for a subject. When these signals are collected for different trails of a subject, there have similarity also. In this paper, we want to measure this correspondence on the basis of correlation aspec...

BACKGROUND Propofol has been widely used for an induction and/or maintenance of general anesthesia, or for sedation for various procedures. Although it has many ideal aspects, there have been several cases of drug abuse and addiction. The authors investigated whether there are abuse liable groups among the general population. METHODS We surveyed 169 patients after gastric endoscopic examinati...

To keep pace with the time, learning from printed medium alone is no longer a comprehensive approach. Fresh digital contents can definitely be the complement of printed education medium. Although timely access to fresh contents is becoming increasingly important for education and gaining such access is no longer a problem, the capacity for human teachers to assimilate such huge amounts of conte...

Within functional magnetic resonance imaging (fMRI), the use of the traditional general linear model (GLM) based analysis methods is often restricted to strictly controlled research setups requiring a parametric activation model. Instead, Inter-Subject Correlation (ISC) method is based on voxel-wise correlation between the time series of the subjects, which makes it completely non-parametric an...