# Determining the Functional Brain Networks that Underlie Children’s Overeating and Adiposity Gain

> **NIH NIH F31** · PENNSYLVANIA STATE UNIVERSITY, THE · 2022 · $37,548

## Abstract

Project Summary
Childhood obesity is a global pandemic associated with negative physical and psychosocial health outcomes4,
and behavioral interventions to prevent childhood obesity produce small and variable effects5. Increased eating
in the absence of hunger (EAH) has been identified as an obesogenic eating phenotype in children6, but the
mechanisms that contribute to increased EAH prior to the development of obesity are unclear. A better
understanding of the mechanisms that engender increased EAH and weight gain in children is critical to the
development of more effective obesity prevention programs. Overeating is posited to result from an imbalance
in brain regions involved in food cue reactivity and reward processing (i.e., a reactive system) with those
involved in inhibition and cognitive control (i.e., a regulatory system)7–12. However, the patterns of functional
connectivity between these neural systems which increase overeating and risk for obesity are unclear. Building
on my sponsor’s R01 study, which is designed to examine neural and cognitive predictors of adiposity gain in
children 7-8 years old who vary by familial risk for obesity, this proposal aims to identify the functional
connectivity patterns (i.e., neural network properties) between reactive and regulatory brain systems that
underlie EAH and adiposity gain. It is hypothesized that weaker connectivity between the reactive and
regulatory system, and stronger connectivity within the reactive system, will be related to greater EAH and
adiposity gain in children. To test these hypotheses, neuroimaging (fMRI) data collected during exposure to
food cues will be used alongside food intake data from a laboratory assessment of EAH, during which children
are offered a variety of palatable snack foods after eating a standard meal to fullness. Anthropomorphic
assessments of adiposity will be collected at baseline and 1-year follow-up using dual x-ray absorptiometry
(DXA). Innovative network analyses and advanced statistical methods will be used to identify and characterize
child-specific neural networks from a priori “reactive” and “regulatory” brain regions of interest. Innovations
offered by this proposal are (1) the use of sophisticated quantitative techniques to examine children’s neural
networks during exposure to food cues and (2) the integration of network analyses with objectively-assessed
hedonic eating and longitudinal measures of adiposity, which together will provide novel insight into the neural
factors that promote overeating and risk for weight gain during the vulnerable pre-adolescent period. In
addition, the inter-disciplinary mentorship team assembled in this proposal will provide rigorous training in
experimental design for ingestive behavior research, neural network analyses, and scientific communication
that will help advance my career as an independent researcher. The proposed study will enhance our
understanding of the neural mechanisms supporting overeating and ad...

## Key facts

- **NIH application ID:** 10538052
- **Project number:** 1F31DK131868-01A1
- **Recipient organization:** PENNSYLVANIA STATE UNIVERSITY, THE
- **Principal Investigator:** Bari Allison Fuchs
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $37,548
- **Award type:** 1
- **Project period:** 2022-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10538052

## Citation

> US National Institutes of Health, RePORTER application 10538052, Determining the Functional Brain Networks that Underlie Children’s Overeating and Adiposity Gain (1F31DK131868-01A1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10538052. Licensed CC0.

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