Balancing act: Neural correlates of affect dysregulation in youth depression and substance use – A systematic review of functional neuroimaging studies
Author(s) -
Divyangana Rakesh,
Nicholas B. Allen,
Sarah Whittle
Publication year - 2020
Publication title -
developmental cognitive neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.662
H-Index - 64
eISSN - 1878-9307
pISSN - 1878-9293
DOI - 10.1016/j.dcn.2020.100775
Subject(s) - psychology , amygdala , functional magnetic resonance imaging , neuroimaging , prefrontal cortex , neuroscience , functional neuroimaging , neural correlates of consciousness , depression (economics) , resting state fmri , functional connectivity , affect (linguistics) , brain structure and function , developmental psychology , cognition , communication , economics , macroeconomics
Both depression and substance use problems have their highest incidence during youth (i.e., adolescence and emerging adulthood), and are characterized by emotion regulation deficits. Influential neurodevelopmental theories suggest that alterations in the function of limbic and frontal regions render youth susceptible to these deficits. However, whether depression and substance use in youth are associated with similar alterations in emotion regulation neural circuitry is unknown. In this systematic review we synthesized the results of functional magnetic resonance imaging (fMRI) studies investigating the neural correlates of emotion regulation in youth depression and substance use. Resting-state fMRI studies focusing on limbic connectivity were also reviewed. While findings were largely inconsistent within and between studies of depression and substance use, some patterns emerged. First, youth depression appears to be associated with exaggerated amygdala activity in response to negative stimuli; second, both depression and substance use appear to be associated with lower functional connectivity between the amygdala and prefrontal cortex during rest. Findings are discussed in relation to support for existing neurodevelopmental models, and avenues for future work are suggested, including studying neurodevelopmental trajectories from a network perspective.
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