# Functional network organization is locally atypical in children, adolescents, and young adults with congenital heart disease

## TL;DR

This study finds that children and young adults with congenital heart disease have altered brain network organization, particularly in regions linked to cognition and executive function.

## Contribution

The study introduces a cross-method network analysis to avoid arbitrary thresholds and reveals localized brain network differences in CHD.

## Key findings

- Network differences were prominent in temporal, occipital, and subcortical regions.
- Local network changes were more significant than global differences in CHD patients.
- Network metrics correlated with cognitive performance, suggesting compensatory mechanisms.

## Abstract

•CHD youth show altered brain networks linked to executive function deficits.•CHD shows temporal, occipital, and subcortical network changes tied to cognition.•Local network differences were more prominent than global differences.•This study used a cross-method network analysis to avoid reliance on arbitrary thresholds.

CHD youth show altered brain networks linked to executive function deficits.

CHD shows temporal, occipital, and subcortical network changes tied to cognition.

Local network differences were more prominent than global differences.

This study used a cross-method network analysis to avoid reliance on arbitrary thresholds.

Children, adolescents, and young adults with congenital heart disease (CHD) frequently experience disruptions in neurodevelopment affecting their executive functioning and other cognitive abilities, which in turn can impact academic performance, psychosocial adjustment, and overall quality of life. This exploratory study aims to investigate the impact of CHD on functional brain network connectivity and cognitive function, with a particular focus on executive functioning. Rather than relying on a single network construction method or arbitrary thresholds, our study methodically employed both weighted networks and binarized networks generated using absolute and proportional thresholding. This cross-method approach enables us to identify functional connectivity features that persist across heuristically and arbitrarily defined parameters, and to evaluate their association with neurocognition. Using resting-state fMRI data, we examined several network metrics across brain regions using three network construction types: weighted networks, absolute-threshold binarized networks, and proportional-threshold binarized networks. Regression models were then fit to neuropsychological test scores using metrics obtained from each network construction approach. Our results identified differences in network connectivity with a predilection for temporal, occipital, and subcortical regions, across both weighted and binarized networks. Furthermore, we identified distinct correlations between network metrics and cognitive performance, suggesting potential compensatory mechanisms within specific brain regions. These results provide an initial, methodologically transparent characterization of altered network organization in CHD and offer directions for future hypothesis-driven investigations.