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Cereb Cortex. 2019 Feb 1;29(2):852-862. doi: 10.1093/cercor/bhy287.

Person-Based Brain Morphometric Similarity is Heritable and Correlates With Biological Features.

Author information

1
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
2
Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
3
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
4
Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
5
Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
6
Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
7
Olin Neuropsychiatric Institute, Institute of Living, Hartford Hospital, Hartford, CT, USA.

Abstract

The characterization of the functional significance of interindividual variation in brain morphometry is a core aim of cognitive neuroscience. Prior research has focused on interindividual variation at the level of regional brain measures thus overlooking the fact that each individual brain is a person-specific ensemble of interdependent regions. To expand this line of inquiry we introduce the person-based similarity index (PBSI) for brain morphometry. The conceptual unit of the PBSI is the individual person's brain structural profile which considers all relevant morphometric measures as features of a single vector. In 2 independent cohorts (total of 1756 healthy participants), we demonstrate the foundational validity of this approach by affirming that the PBSI scores for subcortical volume and cortical thickness in healthy individuals differ between men and women, are heritable, and robust to variation in neuroimaging parameters, sample composition, and regional brain morphometry. Moreover, the PBSI scores correlate with age, body mass index, and fluid intelligence. Collectively, these results suggest that the person-based measures of brain morphometry are biologically and functionally meaningful and have the potential to advance the study of human variation in multivariate brain imaging phenotypes in healthy and clinical populations.

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