Neuroimaging Depression Risk in a Sample of Never-Depressed Children

Children of mothers with a history of depression are at significantly higher risk for developing depression themselves. Although numerous mechanisms explaining this relationship have been proposed (Goodman & Gotlib, 1999), relatively little is known about the neural substrates of never-depressed children’s depression risk. Of the few studies that have used neuroimaging techniques to characterize risk-based differences in children’s neural structure, function, and functional connectivity, most have used samples that include participants with a personal history of depression or older samples (i.e., past the typical age of onset for depressive disorders). These approaches limit what can be determined regarding whether findings are true markers of risk (and potential etiological mechanisms) or better reflect resilience to depression or brain-based sequelae of depression. There is a clear need to better characterize children’s neuroimaging-based markers of depression risk by focusing on samples with clear statistical risk (i.e., a maternal history of depression or early emerging depression symptoms) prior to their own onset of disorder. This dissertation addresses this gap in the literature by characterizing the association between a sample (Ns = 80-85) of never-depressed children’s risk for depression and magnetic resonance imaging (MRI) markers of children’s brain structure (Study 1), functional response to maternal feedback (Study 2), and resting-state functional connectivity (Study 3). Main findings included never-depressed children’s self-reported depression symptoms being negatively associated with grey matter volume in regions relevant to reward processing (i.e., orbitofrontal cortex; Study 1), functional activity in salience processing regions (i.e., anterior insula) and reward processing (i.e., putamen) during critical maternal feedback (Study 2), and resting-state functional connectivity within the Central Executive Network and Salience Network (Study 3). I also demonstrated that children with high maternal risk for depression (i.e., a maternal history of depression) had significantly increased resting-state functional connectivity within the default mode network. Results indicate that brain-based associates of depression risk (i.e., maternal history of depression and children’s depression symptoms) pre-exist the development of depression, potentially contributing to the etiology of depression. Future directions for the emerging field of neuroimaging children’s risk for depression are discussed