Publications

Handwriting / symbol drawing and early visual development

Vinci-Booher, S., Zemlock, D., Ju., S., & James, K.H. (in revision). Learning to produce letters and digits by hand in preschool.

Vinci-Booher, S., Shimko, G., Marshall, H., James, K.H. (2025). Brain correlates of early writing development: the foundational role of production tasks in early childhood. In Church-Lang, J., & Lockman, J. (Eds.), Advances in Child Development and Behavior (Vol 68): Foundations of Literacy in Brain and Behavior. Elsevier Press.

Vinci-Booher, S., James, K.H. (2023). The contribution of handwriting to letter processing in early reading development: evidence from behavioral and neuroimaging research. In Ye, Y., Inoue, T., Maurer, U., & McBride, C. (Eds.), Handbook of Visual-motor skills, Handwriting, and Spelling, Theory, Research, and Practice. Oxfordshire, England, UK: Routledge Taylor & Francis.

Vinci-Booher, S., & James, K.H. (2021). Protracted neural development of dorsal motor systems during handwriting and the relation to early literacy skills. Frontiers in Psychology, 12.

Vinci-Booher, S., James, T.W., & James, K.H. (2021). Visual-motor contingency during symbol production contributes to the development of the neural systems supporting symbol perception and concurrent gains in symbol recognition. Neuroimage, 227, 117554.

Vinci-Booher, S., & James, K.H. (2020). Visual experiences of letter production contribute to the development of the neural systems supporting letter perception. Developmental Science, 23(5), 1-17. (Cover article.)

Merritt, E., Swain, S., Vinci-Booher, S., & James, K.H. (2020). Constraining stroke order during manual symbol learning hinders subsequent recognition in children under 4 ½ years. Frontiers in Psychology, 11.

Vinci-Booher, S., & James, K.H. (2020). Ecological validity of experimental set-up affects parietal involvement during letter production. Neuroscience Letters, 731.

Vinci-Booher, S., Cheng, H., & James, K.H. (2019). An analysis of the brain systems involved with producing letters by hand. Journal of Cognitive Neuroscience, 31(1), 138-154.

Zemlock, D., Vinci-Booher, S., & James, K.H. (2018). Visual-motor symbol production facilitates letter knowledge in young children. Reading and Writing, 31, 1255-1271.

James, K.H., Vinci-Booher, S., & Muñoz-Rubke, F. (2017). The impact of multimodal-multisensory learning on human performance and brain activation patterns. In Oviatt, S., Schuller, B., & Cohen, P. (Eds.), Handbook of Multimodal-Multisensor Interfaces. San Rafael, CA, USA: Morgan & Claypool Publishers.

Vinci-Booher, S., & James, K. H. (2016). Neural substrates of sensorimotor processes: Letter writing and letter perception. Journal of Neurophysiology, 115(1), 1-4.

Vinci-Booher, S., James, T. W., & James, K. H. (2016). Visual-motor functional connectivity in preschool children emerges after handwriting experience. Trends in Neuroscience and Education, 5(3), 107-120.

Dense longitudinal neuroimaging

Cross, E., Compton, A., Vess, A., Booth, J.R., Kay, K., & Vinci-Booher, S. (under review). A practical guide for dense longitudinal neuroimaging: ten simple rules for frequent scanning over short time periods.

Vinci-Booher, S., Ren, X., Kay, K., Yu, C., Pestilli, F., & Booth, J. (2025). Dense longitudinal neuroimaging for evaluating trajectories and mechanisms of brain change. Trends in Cognitive Sciences 30, 464-476.

White matter development and learning

Kim, M.E., Rudravaram, G., Saunders, A., Gao, C., Ramadass, K., …, Vinci-Booher, S., …, Schilling, K.G., Moyer, D.C., & Landman, B.A. (in revision). Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts.

Schilling, K.G., Kim, E., Amandola, M., Gao, C., …, Vinci-Booher, S., …, Gore, J.C., Smith, S., & Landman, B. (in revision). Charting Cervical Spinal Cord Morphometry Across the Lifespan.

Kim, M.E., Gao, C., Ramadass, K., Newlin, N.R., Kanakaraj, P., …, Vinci-Booher, S., …, & Landman, B.A., Schilling, K.G. (2026). White matter microstructure and macrostructure brain charts across the human lifespan. Nature.

Bogdanov, S., Kanakaraj, P., Kim, M.E., …, Vinci-Booher, S., …, Landman, B.A., & Schilling, K.G. (2026). Lifespan Trajectories of Asymmetry in White Matter Tracts. Human Brain Mapping 47, no. 8: e70519.

Vinci-Booher, S., McDonald, D. J., Berquist, E., & Pestilli, F. (2024). Associative white matter tracts selectively predict sensorimotor learning. Communications Biology, 7(1), 1-11.

Vinci-Booher, S., Schlichting, M., Preston, A., & Pestilli, F. (2023). Development of human hippocampal subfield microstructure and relation to associative inference. Cerebral Cortex, 33(18), 10207–10220.

Vinci-Booher, S., Caron, B., Bullock, D., James, K.H., & Pestilli, F. (2022). Development of white matter tracts between and within the dorsal and ventral streams. Brain Structure and Function, 227(4), 1457-1477.

Technical development for pediatric MRI

Schilling, K.G., Ramadass, K., Sairanen, V., Kim, M., Rheault, F., …, Vinci-Booher, S., …, Landman, B.A. (2025). Head motion in diffusion MRI: Quantification, mitigation, and structural associations in a large, cross-sectional dataset of lifespan and special populations. Human Brain Mapping 46(3):e70143.

Hayashi, S., Caron, B., Heinsfeld, A.S., Vinci-Booher, S., … Pestilli, F. (2024). brainlife.io: A decentralized and open-source cloud platform to support neuroscience research. Nature Methods, 21, 809–813.

Levitas, D., Hayashi, S., Vinci-Booher, S., Heinsfeld, A., Guiomar, N., & Pestilli., F. (2024). ezBIDS: Guided standardization of neuroimaging data interoperable with major data platforms. Scientific Data, 11(1), 179.

Cheng, H., Vinci-Booher, S., Caron, B., Wang, J., Newman, S., & Pestilli, F. (2022). Denoising diffusion-weighted MRI data using convolutional neural networks. PLOS ONE.

Vinci-Booher, S., Sturgeon, J., James, T., & James, K.H. (2018). The MRItab: An MR-compatible touchscreen with video-display. Journal of Neuroscience Methods, 306, 10-18.

Sesame Street Image Archive

Sadkowski, K., Guo, S., Yu, C., & Vinci-Booher, S. (2025). The Sesame Street Archive: a labeled image repository of educational children’s television, 1969-2018. In Workshop on Demographic Diversity in Computer Vision at the Conference on Computer Vision and Pattern Recognition, CVPR. Institute of Electrical and Electronics Engineers.