Abstract
Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting
clinical symptoms, while demonstrating substantial heterogeneity within diagnostic
categories. Notably, many of these psychiatric disorders first manifest in youth.
We review progress and next steps in efforts to parse heterogeneity in psychiatric
symptoms in youths by identifying abnormalities within neural circuits. To address
this fundamental challenge in psychiatry, a number of methods have been proposed.
We provide an overview of these methods, broadly organized into dimensional versus
categorical approaches and single-view versus multiview approaches. Dimensional approaches
including factor analysis and canonical correlation analysis aim to capture dimensional
associations between psychopathology and brain measures across a continuous spectrum
from health to disease. In contrast, categorical approaches, such as clustering and
community detection, aim to identify subtypes of individuals within a class of symptoms
or brain features. We highlight several studies that apply these methods to samples
of youths and discuss issues to consider when using these approaches. Finally, we
end by highlighting avenues for future research.
Keywords
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Article info
Publication history
Published online: December 21, 2019
Accepted:
December 11,
2019
Received in revised form:
November 7,
2019
Received:
July 8,
2019
Identification
Copyright
© 2019 Society of Biological Psychiatry.
