NSF-BSF: Elucidating the functional and microstructural development of the human visual system across the lifespan

Children's brains grow and change in ways that help them understand what they see. Over development, babies and children learn to recognize familiar faces and places, make sense of words on a page, and make visual decisions such as "Is this my mother?" or "What word am I reading?" This project explains how children develop visual intelligence by studying how brain structure and brain function change together from infancy to young adulthood. The research may help scientists create earlier ways to detect when development is going off track, so children and families can receive earlier support and have better long-term outcomes. The project may also inspire new kinds of biologically inspired artificial intelligence (AI). Most AI systems have a fixed design, but children's brain tissue grows as visual abilities develop. Understanding how changes in brain tissue and visual abilities are linked may help engineers build biologically inspired AI systems with adaptable designs that can grow and become more efficient over time. The project studies how brain activity and brain tissue change together in the ventral visual stream, a major brain pathway that supports visual understanding, including face recognition, place recognition, reading, and visual decision-making. The research team uses functional magnetic resonance imaging (fMRI) to measure brain responses to visual inputs and quantitative MRI (qMRI) to measure brain tissue properties in the same children. The project tests when and how brain responses and tissue develop across infancy and childhood, and whether these developmental changes are linked. This work will provide brain charts of the development of the visual system. Because qMRI reflects brain tissue properties indirectly, the project also combines qMRI with direct measurements of biological features from rare pediatric brain tissue samples, as well as with MRI phantoms. MRI phantoms are lab-designed objects that mimic brain tissue and allow researchers to precisely control specific features, such as the amount of myelin or iron. The project will test biological features that change during development, including myelin, a fatty membrane that wraps around nerve fibers and helps brain signals travel efficiently, and iron, which supports brain function. Computational modeling will connect qMRI measures to these biological features, which will make it possible to use qMRI data from infants and children to infer which features of brain tissue are developing. Understanding how brain responses and brain tissue develop together may support earlier detection of atypical neurodevelopment and inform new types of AI systems whose architecture can adapt over time and become more efficient. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2547344 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Kalanit Grill-Spector | Institution: Stanford University, STANFORD, CA | Award Amount: $795,439 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2547344 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2547344.html