Towards personalized precision functional mapping in infancy

• Published in: Imaging neuroscience (Cambridge, Mass.) Mass.), 2024-05, Vol.2, p.1-20
• Main Authors: Moore, Lucille A., Hermosillo, Robert J. M., Feczko, Eric, Moser, Julia, Koirala, Sanju, Allen, Madeleine C., Buss, Claudia, Conan, Greg, Juliano, Anthony C., Marr, Mollie, Miranda-Dominguez, Oscar, Mooney, Michael, Myers, Michael, Rasmussen, Jerod, Rogers, Cynthia E., Smyser, Christopher D., Snider, Kathy, Sylvester, Chad, Thomas, Elina, Fair, Damien A., Graham, Alice M.
• Format: Article
• Language: English
• ISSN: 2837-6056; 2837-6056
• DOI: 10.1162/imag_a_00165

The precise network topology of functional brain systems is highly specific to individuals and undergoes dramatic changes during critical periods of development. Large amounts of high-quality resting state data are required to investigate these individual differences, but are difficult to obtain in early infancy. Using the template matching method, we generated a set of infant network templates to use as priors for individualized functional resting-state network mapping in two independent neonatal datasets with extended acquisition of resting-state functional MRI (fMRI) data. We show that template matching detects all major adult resting-state networks in individual infants and that the topology of these resting-state network maps is individual-specific. Interestingly, there was no plateau in within-subject network map similarity with up to 25 minutes of resting-state data, suggesting that the amount and/or quality of infant data required to achieve stable or high-precision network maps is higher than adults. These findings are a critical step towards personalized precision functional brain mapping in infants, which opens new avenues for clinical applicability of resting-state fMRI and potential for robust prediction of how early functional connectivity patterns relate to subsequent behavioral phenotypes and health outcomes.