Abstract
Depression is a common psychiatric illness that often begins in youth, and is sometimes associated with cognitive deficits. However, there is significant variability in cognitive dysfunction, likely reflecting biological heterogeneity. We sought to identify neurocognitive subtypes and their neurofunctional signatures in a large cross-sectional sample of depressed youth. Participants were drawn from the Philadelphia Neurodevelopmental Cohort, including 712 youth with a lifetime history of a major depressive episode and 712 typically developing (TD) youth matched on age and sex. A subset (MDD n = 368, TD n = 200) also completed neuroimaging. Cognition was assessed with the Penn Computerized Neurocognitive Battery. A recently developed semi-supervised machine learning algorithm was used to delineate neurocognitive subtypes. Subtypes were evaluated for differences in both clinical psychopathology and brain activation during an n-back working memory fMRI task. We identified three neurocognitive subtypes in the depressed group. Subtype 1 was high-performing (high accuracy, moderate speed), Subtype 2 was cognitively impaired (low accuracy, slow speed), and Subtype 3 was impulsive (low accuracy, fast speed). While subtypes did not differ in clinical psychopathology, they diverged in their activation profiles in regions critical for executive function, which mirrored differences in cognition. Taken together, these data suggest disparate mechanisms of cognitive vulnerability and resilience in depressed youth, which may inform the identification of biomarkers for prognosis and treatment response.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.