HOW TO DEVELOP A QUALITY STRATEGY TO DETECT ABNORMAL BRAIN CONNECTIVITY USING MULTIMODAL NEUROIMAGING DATA.

The objective of our study is to discern the aberrant functional and structural brain connectivity in mental disorder patients, ultimately to develop quality therapeutic strategies. We developed a bivariate mixed-effects model to ascertain the differences in brain connectivity between healthy individuals and affected patients. The model accounts for subject-specific variability and heteroscedastic errors, enabling it to handle correlations within and across different connectivity measures. Such comprehensive accounting allowed us to identify notable connectivity differences between groups. To validate the performance of our model, we conducted a simulation study. Then, we applied our method to neuroimaging data for late-life depression patients, assessing biomarker identification compared to univariate mixed-effects models. [ABSTRACT FROM AUTHOR]