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. Further, we then used these tract differences to investigate their association with performance on a memory test. When comparing our high versus low anxiety groups, we observed a positive association between the left uncinate fasciculus and memory overgeneralization for negatively valenced stimuli. This same association was not evident in the right uncinate or anterior forceps. These findings illustrate that GAMs are well-suited for modeling diffusion data while accounting for various aspects of the data, and suggest that the adoption of GAMs will be a powerful investigatory tool for diffusion-weighted analyses.

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. We tested the influence of a short-term experimental stressor on behavioral and event-related potential (ERP; N2 and P3 components) measures of food-related inhibitory control. Ninety-seven healthy participants were randomly assigned to complete the Trier Social Stress Test (TSST) (n = 48, 27 females [52.9%]) or a neutral control condition (n = 49, 35 females [70%]) immediately followed by food-specific go/no-go and neutral go/no-go tasks while electroencephalogram (EEG) data were recorded. Stress levels were successfully manipulated, with heightened self-report and physiological measures (heart rate and systolic blood pressure) of the stress response in individuals who completed the TSST compared to control. As expected, the high calorie food-specific go/no-go task elicited larger N2 amplitude than the neutral task. N2 component amplitude was also significantly larger following the TSST relative to the control task. There were no significant between-group or task differences for P3 amplitude or behavioral measures. Findings suggest heightened N2 amplitude following psychological stress that is not specific to food or inhibition processes and may reflect heightened arousal following stress. Future research in individuals with overweight/obesity or experiencing chronic stress will further clarify the role of stress in 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. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing.