# A data-driven approach to identify the neural and cognitive basis of social functioning in health and first episode psychosis

> **NIH NIH F31** · UNIVERSITY OF MINNESOTA · 2021 · $41,879

## Abstract

Project Summary/Abstract: The research and training plan for this Fellowship will provide the applicant with
significant and foundational training in cognitive neuroscience, advanced computational approaches and
neuroimaging analysis to support her long-term career goal of becoming an independent researcher dedicated
to enhancing functional recovery in schizophrenia. A core feature of schizophrenia is severe disability in social
functioning, which places a high burden on individuals and society. Effective treatment development for social
functioning deficits is hindered by the lack of well-defined neural and cognitive treatment targets. Recent
advances suggest cortical loss in prefrontal and cingulate cortices may be linked to poor functioning in chronic
schizophrenia, however the relationship between specific neural targets and social functioning in first episode
psychosis (FEP), when individuals may have greater ability to engage in substantial recovery, is largely
unknown. Further, social cognition deficits are strongly linked to poor functioning, but the relationship between
cortical loss in social cognitive brain regions and social functioning remains to be established. The purpose of
this study is to employ data-driven approaches to identify neural and social cognitive markers of social
functioning in health and FEP to inform treatment target identification. This cross-sectional, secondary
analysis leverages two unique datasets – a large sample of healthy young adults from the Human Connectome
Project (n=1113), and a sample of FEP participants enrolled in an ongoing clinical trial at the University of
Minnesota (n=40). Specific Aim 1 - examine the relationships between gray matter volume and cortical
thickness, social cognition and social functioning in healthy young adults using data driven approaches - will
answer two research questions: 1a) what brain regions estimate better social functioning in healthy young
adults, using regression-based machine learning analysis? and 1b) Is the relationship between social
functioning and measures of gray matter volume and cortical thickness mediated by social cognition? We will
then translate these findings to an FEP sample in Aim 2 - characterize the relationship between gray matter
volume and cortical thickness and social functioning in FEP. This research will be supported by the applicant’s
comprehensive training plan, her interdisciplinary mentoring team, and an ideal training environment due to its
sophisticated neuroimaging and health informatics resources. This research is expected to advance our
understanding of the complex relationships between the brain, social cognition and social functioning, which
could lead to more targeted interventions for functional deficits in schizophrenia, alleviating suffering and
addressing a critical public health need. The training will position the applicant to continue her trajectory to an
independent career in translational cognitive neuroscience to enhance...

## Key facts

- **NIH application ID:** 10153037
- **Project number:** 1F31MH124278-01A1
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Kathleen Miley
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $41,879
- **Award type:** 1
- **Project period:** 2021-01-22 → 2022-01-21

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10153037

## Citation

> US National Institutes of Health, RePORTER application 10153037, A data-driven approach to identify the neural and cognitive basis of social functioning in health and first episode psychosis (1F31MH124278-01A1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10153037. Licensed CC0.

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