General additive models address statistical issues in diffusion MRI: An example with clinically anxious adolescents.

Statistical models employed to test for group differences in quantized diffusion-weighted MRI white matter tracts often fail to account for the large number of data points per tract in addition to the distribution, type, and interdependence of the data. To address these issues, we propose the use of Generalized Additive Models (GAMs) and supply code and examples to aid in their implementation. Specifically, using diffusion data from 73 periadolescent clinically anxious and no-psychiatric-diagnosis control participants, we tested for group tract differences and show that a GAM allows for the identification of differences within a tract while accounting for the nature of the data as well as covariates and group factors.

The relationship between acute stress and neurophysiological and behavioral measures of food-related inhibitory control: An event-related potential (ERP) study.

Stress influences many health-related behaviors including diet and nutrition intake, often resulting in increased calorie intake, fewer healthy eating behaviors, and poorer nutrition. Food intake is modulated by inhibitory control and has important implications for our physical, mental, and emotional health. Yet, little is known about the relationship between stress and food-related inhibitory control.

Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images.

Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown.