Literature DB >> 28549797

Cortico-amygdalar maturational coupling is associated with depressive symptom trajectories during adolescence.

Nandita Vijayakumar1, Nicholas B Allen2, Meg Dennison3, Michelle L Byrne4, Julian G Simmons5, Sarah Whittle5.   

Abstract

BACKGROUND: Adolescence is characterized by increasing prevalence of depressive symptomatology, along with significant structural brain development. While much research has examined focal abnormalities in gray matter structure underlying depression, we employed a structural coupling approach to examine whether longitudinal associations between amygdala and cortical development (referred to as maturational coupling) was related to concurrent changes in depressive symptomatology during adolescence.
METHOD: 166 participants underwent up to three MRI scans (367 scans) between 11 and 20 years of age. Depressive symptoms were measured at three coinciding time points using the Center for Epidemiological Studies-Depression scale. Linear mixed models were employed to identify whether change in amygdala volume was related to development of cortical thickness, and if maturational coupling of these regions was related to changes in depressive symptomatology.
RESULTS: Positive maturational coupling was identified between the right amygdala and (predominantly anterior) prefrontal cortex, as well as parts of the temporal cortices. Greater positive coupling of these regions was associated with reductions in depressive symptoms over time.
CONCLUSIONS: Findings highlight significant associations between cortico-amygdalar maturational coupling and the emergence of depressive symptoms during adolescence, suggesting that synchronous development of these regions might support more adaptive affect regulation and functioning.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Adolescence; Affective functioning; Brain development; Depressive symptomatology; Structural coupling

Mesh:

Year:  2017        PMID: 28549797      PMCID: PMC5554433          DOI: 10.1016/j.neuroimage.2017.05.051

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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