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  4. Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression

Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression

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Author(s)
Hirshfeld-Becker, Dina
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Biederman, Joseph
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Uchida, Mai
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Kenworthy, Tara
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Brown, Ariel
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Kagan, Elana
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Chai, Xiaoqian
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Doehrmann, Oliver
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Leonard, Julia
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Salvatore, John J.
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Date Issued
December 2015
Journal
Biological Psychiatry
Publisher
Elsevier
Citation
Chai, Xiaoqian J. et al. “Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression.” Biological Psychiatry 80, 11 (December 2016): 849–858 © 2016 Society of Biological Psychiatry
Version
Author's final manuscript
Abstract
Background Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression. Methods We compared resting-state functional connectivity, measured with functional magnetic resonance imaging, between unaffected children of parents who had documented histories of major depression (at-risk, n = 27; 8–14 years of age) and age-matched children of parents with no lifetime history of depression (control subjects, n = 16). Results At-risk children exhibited hyperconnectivity between the default mode network and subgenual anterior cingulate cortex/orbital frontal cortex, and the magnitude of connectivity positively correlated with individual symptom scores. At-risk children also exhibited 1) hypoconnectivity within the cognitive control network, which also lacked the typical anticorrelation with the default mode network; 2) hypoconnectivity between left dorsolateral prefrontal cortex and subgenual anterior cingulate cortex; and 3) hyperconnectivity between the right amygdala and right inferior frontal gyrus, a key region for top-down modulation of emotion. Classification between at-risk children and control subjects based on resting-state connectivity yielded high accuracy with high sensitivity and specificity that was superior to clinical rating scales. Conclusions Children at familial risk for depression exhibited atypical functional connectivity in the default mode, cognitive control, and affective networks. Such task-independent functional brain measures of risk for depression in children could be used to promote early intervention to reduce the likelihood of developing depression.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/112654
DOI of Published Version
https://doi.org/10.1016/J.BIOPSYCH.2015.12.003
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