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Geometric eigenmode brain fingerprinting and its longitudinal associations with adolescent mental health and wellbeing

  • Amanda Boyes
  • , Paul E. Schwenn
  • , Zack Y. Shan
  • , Maryuresh Korgaonkar
  • , James Pang
  • , Taliah Prince
  • , Lia Mills
  • , Michelle F. Kennedy
  • , Daniel F. Hermens

Research output: Contribution to specialist publicationArticleResearch

Abstract

Background: ‘Brain fingerprinting’ research posits that individual uniqueness can be identified by structural and functional features that may also be linked to mental health outcomes. Global structural features of the brain can be succinctly and directly captured from magnetic resonance imaging (MRI) via the eigenmodes of the cortical surface - known as geometric eigenmodes. This research investigates how the uniqueness of geometric eigenmodes changes across adolescence and their longitudinal relation to mental health and wellbeing.
Methods: The current study utilised n=613 MRI, self-report and demographic datasets from N=116 community-recruited adolescents enrolled in the Longitudinal Adolescent Brain Study (LABS), between the ages of 12-17 years. MPRAGE scans at each participant’s visit were used to derive 225 left-hemisphere geometric eigenmodes. Eigenmodes were clustered into 14 eigengroups and developmental trajectories of their uniqueness and longitudinal associations with mental wellbeing and psychological distress were examined.
Results: All eigengroups become significantly more unique longitudinally, and higher mode (shorter wavelength) eigengroups were more unique than lower mode groups in adolescence. Less uniqueness in ‘eigengroup 6’ was significantly associated with higher psychological distress and lower mental wellbeing at concurrent and future timepoints.
Conclusion: Geometric eigengroup brain fingerprinting offers a novel way to examine neurodevelopment. This study provides evidence that eigengroups have distinct trajectories from adolescence to adulthood, consistent with other imaging studies demonstrating increasing uniqueness in this period. Importantly, they are associated with mental health state and thus may represent neurobiological markers for mental illness onset, building on previous LABS research demonstrating that the functional uniqueness of the ‘cognitive control network’ predicts psychological distress four months later.
Original languageEnglish
Number of pages36
Volume2024
Specialist publicationbioRxiv
DOIs
Publication statusPublished - 9 Aug 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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