We present an approach to analyzing fMRI timetrends from volumes-of-interest (VOI) within and between subject groups using repeated measures analysis of variance (RMANOVA), which allows temporal patterns to be examined without an model of expected timing or pattern of response. The method serves a priori as a complement to whole-brain voxel-based analyses, and is useful for detecting complex r...

STUDY DESIGN This study is a repeated measures design to measure the lumbar spine response to typical school backpack loads in healthy children. The lumbar spine in this setting was measured for the first time by an upright magnetic resonance imaging (MRI) scanner. OBJECTIVE The purpose of this study is to measure the lumbar spine response to typical school backpack loads in healthy children....

BACKGROUND Using covariance or mean estimates from previous data introduces randomness into each power value in a power curve. Creating confidence intervals about the power estimates improves study planning by allowing scientists to account for the uncertainty in the power estimates. Driving examples arise in many imaging applications. METHODS We use both analytical and Monte Carlo simulation...

We present an approach to analyzing fMRI timetrends from volumes-of-interest (VOI) within and between subject groups using repeated measures analysis of variance (RMANOVA), which allows temporal patterns to be examined without an a priori model of expected timing or pattern of response. The method serves as a complement to whole-brain voxel-based analyses, and is useful for detecting complex re...

We present an approach to analyzing physiologic timetrends recorded during a stimulus by comparing means at each time point using repeated measures analysis of variance (RMANOVA). The approach allows temporal patterns to be examined without an model of expected timing or pattern of response. a priori The approach was originally applied to signals recorded from functional magnetic resonance ima...