Ananya Padhiari of Arkansas Children’s Research Institute applies machine learning to integrate dietary patterns, growth metrics, and resting‐state fMRI data, uncovering neural connectivity signatures linked to nutrition and enabling predictive models for tailored child cognitive interventions.

Key points

• Integrates dietary patterns, growth metrics, and resting-state fMRI to map nutritional impacts on neural connectivity.
• Uses gradient boosting regression on serum ferritin and default mode network efficiency, controlling for demographic and socioeconomic variables.
• Employs reinforcement learning–based digital twin simulations to model synaptic plasticity responses to nutritional interventions.

Why it matters: AI-driven insights into nutrient–brain interactions could revolutionize early childhood interventions, offering precision strategies to enhance cognitive outcomes over one-size-fits-all guidelines.