ArticleDevelopmental cognitive neuroscience2026
Highlights from the 2024 annual meeting of the fetal, infant, and Toddler Neuroimaging Group (FIT'NG).
Article in Developmental cognitive neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The Fetal, Infant, and Toddler Neuroimaging Group (FIT'NG) is a scientific society advancing research on fetal, perinatal, infant, and early childhood brain and behavioral development through neuroimaging, encompassing theoretical, technical, fundamental, and clinical dimensions. It unites researchers across physics, neuroscience, cognitive science, psychology, computer science, biomedical engineering, and medicine, fostering interdisciplinary collaboration among leading laboratories in the field. The annual FIT'NG conference serves as a key forum for exchanging new ideas and methods, addressing shared challenges, and promoting best practices. It supports the society's mission of connecting complementary expertise and training the next generation of scientists in the field. This special issue compiles articles highlighting work presented at the FIT'NG conference held in September 2024 in Baltimore, MD, USA, offering an overview of recent advances in fetal, neonatal, infant, and toddler neuroimaging and their applications. A central focus of the FIT'NG community is identifying early markers of atypical neurodevelopment to support translational research and inform preventive and intervention strategies. Prematurity and other perinatal adversities, including environmental factors, serve as key models of atypical cognitive and social development and strong candidates for translational work. This focus has driven notable progress in technological and analytical methods, including high-precision functional and structural connectivity imaging, statistical innovations for large cohorts supporting hypothesis-driven longitudinal designs, and integrative modeling combining physiological and metabolic data with neuroimaging. Notably, this year's meeting featured significant advances in fetal research, increasingly enabled by deep learning, which now support individual-level analyses, paving the way for precision neuroscience and clinically relevant applications.
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