Thanks so much Grace 😊

A huge thanks to Manasa Kalanadhabhatta and Adam Grabell their mentorship and support on this project!

View full preprint 👉 doi.org/10.31234/osf...

… this approach may hold promise for personalized, neuroscience-informed treatment routing and response monitoring in early childhood.

We show that naturalistic, brain-based measures via fNIRS, analyzed using simple and interpretable machine learning models, can detect psychotherapy-like states in young children, although modestly. While larger replications with external datasets are required …

📊Feature analysis revealed that lower mean activity and variability in the left ventrolateral PFC while engaging in calm-emotion😌 reflection increased the likelihood of being classified into the therapy-like condition.

… whereas post-hoc exploratory models (using the four most frequently selected features across 1,000 folds from the a-priori models) yielded improved and consistently significant performance (mean AUC=0.72 - 0.76, p=0.005) 🎯

📊Across 200 iterations of 5-fold cross-validation, logistic regression models accurately classified whether a child was engaged in the therapy-like task (mean AUC=0.60-0.76). Performance in a-priori models was modest against a permutation null (AUC=0.60-0.63, p=0.044-0.13)…

🧠fNIRS was used to record activity of the bilateral dorsolateral and ventrolateral prefrontal cortex (PFC) throughout the entire duration of the task.

78 preschool children were randomly assigned to:
- a dyadic coloring task prompting awareness and reflection of 😡angry and😌calm emotions, designed to mimic a therapy-like interaction, or
- identically structured interpersonal control condition with no emotion-related prompts🚫