Journal
HUMAN BRAIN MAPPING
Volume 39, Issue 4, Pages 1796-1804Publisher
WILEY
DOI: 10.1002/hbm.23955
Keywords
adolescents; Bulimia Nervosa; conflict resolution; fronto-striatal circuits; functional magnetic resonance imaging; self-regulatory control; Simon task; machine learning; multi-voxel pattern analysis
Funding
- National Institute of Mental Health [K23MH101637, R01MH090062]
- NATIONAL INSTITUTE OF MENTAL HEALTH [K23MH101637, R01MH090062] Funding Source: NIH RePORTER
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This study aimed to determine whether functional disturbances in fronto-striatal control circuits characterize adolescents with Bulimia Nervosa (BN) spectrum eating disorders regardless of clinical severity. FMRI was used to assess conflict-related brain activations during performance of a Simon task in two samples of adolescents with BN symptoms compared with healthy adolescents. The BN samples differed in the severity of their clinical presentation, illness duration and age. Multi-voxel pattern analyses (MVPAs) based on machine learning were used to determine whether patterns of fronto-striatal activation characterized adolescents with BN spectrum disorders regardless of clinical severity, and whether accurate classification of less symptomatic adolescents (subthreshold BN; SBN) could be achieved based on patterns of activation in adolescents who met DSM5 criteria for BN. MVPA classification analyses revealed that both BN and SBN adolescents could be accurately discriminated from healthy adolescents based on fronto-striatal activation. Notably, the patterns detected in more severely ill BN compared with healthy adolescents accurately discriminated less symptomatic SBN from healthy adolescents. Deficient activation of fronto-striatal circuits can characterize BN early in its course, when clinical presentations are less severe, perhaps pointing to circuit-based disturbances as useful biomarker or risk factor for the disorder, and a tool for understanding its developmental trajectory, as well as the development of early interventions.
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