SmartPhantom--an fMRI simulator.

Many informatics tools have emerged to process the voluminous and complex data generated by functional magnetic resonance imaging (fMRI). The interpretation of fMRI exams is largely determined by these tools. However, their performance is hard to evaluate because there is no independent means of calibration. A novel fMRI calibration system called SmartPhantom has been developed to simulate functional blood oxygen level dependent (BOLD) imaging. SmartPhantom contains a quadrature radio frequency coil, comprising two perpendicular planar loops that can be externally activated or deactivated. The system is able to produce reasonably uniform signal enhancements in a calibration sample surrounded by the two loops during an MRI scan. The enhancement is controlled well in both magnitude and predefined timing and produces BOLD-like signals. Characteristics of SmartPhantom are discussed in detail, followed by a comparison of fMRI informatics tools. Two fMRI data sets are acquired with the SmartPhantom. One with high signal-to-noise ratio provides the calibration. Another with lower SNR is input into three software packages (BrainVoyager, FSL and Statistical Parametric Mapping 2) for data preprocessing and statistical analysis. Results from the three packages are compared in both sensitivity of detecting the activation and correlation between the predicted activation and calibration.

An evaluation of the Motion Picture Association of America's treatment of violence in PG-, PG-13-, and R-rated films.

OBJECTIVE: The purpose of this study was to determine whether the Motion Picture Association of America's ratings system distinguishes among the 3 primary rating categories (PG, PG-13, and R) with respect to violence based on a study of the 100 top-grossing films of 1994. METHODS: The Motion Picture Association of America assigns age-based ratings for every film that is released in the United States accompanied by the reasons for the rating. A data abstraction instrument was designed to code each act of violence within the sample of 100 films. A series of Poisson regression models were used to examine the association among rating, seriousness of violence, and primary reason for the rating assignment. RESULTS: The total average number of violent acts within each film by rating category increased from PG (14) to PG-13 (20) to R (32). However, using results from the Poisson models, it is clear that the rating does not predict the frequency of violence in films. For all 3 rating categories, the predicted number of violent acts is almost identical for films with violence as a primary descriptor and films with the highest level of seriousness (R = 62.4 acts, PG-13 = 55.2 acts, and PG = 56.1 acts). The regression analysis shows that the rating does not predict the frequency of violence that occurs in films. CONCLUSIONS: Frequency of violence alone is not the most important criterion for the assignment of rating. The content descriptors and average seriousness of films are better measures of the violence than rating assignment.