FIT’NG & FLUX Poster

Citations for FIT’NG & FLUX 2024 Poster
- Innocenti, G. M., & Price, D. J. (2005). Exuberance in the development of cortical networks. Nature reviews. Neuroscience, 6(12), 955–965. https://doi.org/10.1038/nrn1790
- Haynes, L., Ip, A., Cho, I. Y. K., Dimond, D., Rohr, C. S., Bagshawe, M., Dewey, D., Lebel, C., & Bray, S. (2020). Grey and white matter volumes in early childhood: A comparison of voxel-based morphometry pipelines. Developmental Cognitive Neuroscience, 46, 100875. https://doi.org/10.1016/j.dcn.2020.100875
- Holland, D., Chang, L., Ernst, T. M., Curran, M., Buchthal, S. D., Alicata, D., Skranes, J., Johansen, H., Hernandez, A., Yamakawa, R., Kuperman, J. M., & Dale, A. M. (2014). Structural Growth Trajectories and Rates of Change in the First 3 Months of Infant Brain Development. JAMA Neurology, 71(10), 1266. https://doi.org/10.1001/jamaneurol.2014.1638
- Knickmeyer, R. C., Gouttard, S., Kang, C., Evans, D., Wilber, K., Smith, J. K., Hamer, R. M., Lin, W., Gerig, G., & Gilmore, J. H. (2008). A Structural MRI Study of Human Brain Development from Birth to 2 Years. The Journal of Neuroscience, 28(47), 12176–12182. https://doi.org/10.1523/JNEUROSCI.3479-08.2008
- Beuriat, P.-A., Cristofori, I., Richard, N., Bardi, L., Loriette, C., Szathmari, A., Di Rocco, F., Leblond, P., Frappaz, D., Faure-Conter, C., Claude, L., Mottolese, C., & Desmurget, M. (2020). Cerebellar lesions at a young age predict poorer long-term functional recovery. Brain Communications, 2(1). https://doi.org/10.1093/braincomms/fcaa027
- Sathyanesan, A., Zhou, J., Scafidi, J., Heck, D. H., Sillitoe, R. V., & Gallo, V. (2019). Emerging connections between cerebellar development, behaviour and complex brain disorders. Nature reviews. Neuroscience, 20(5), 298–313. https://doi.org/10.1038/s41583-019-0152-2
- Wee, C., Tuan, T. A., Broekman, B. F. P., Ong, M. Y., Chong, Y., Kwek, K., Shek, L. P., Saw, S., Gluckman, P. D., Fortier, M. V., Meaney, M. J., & Qiu, A. (2017). Neonatal neural networks predict children behavioral profiles later in life. Human Brain Mapping, 38(3), 1362–1373. https://doi.org/10.1002/hbm.23459
- Ullman, H., Almeida, R., & Klingberg, T. (2014). Structural Maturation and Brain Activity Predict Future Working Memory Capacity during Childhood Development. The Journal of Neuroscience, 34(5), 1592–1598. https://doi.org/10.1523/JNEUROSCI.0842-13.2014
- Kuhl, P. K., Coffey-Corina, S., Padden, D., Munson, J., Estes, A., & Dawson, G. (2013). Brain Responses to Words in 2-Year-Olds with Autism Predict Developmental Outcomes at Age 6. PLoS ONE, 8(5), e64967. https://doi.org/10.1371/journal.pone.0064967
- McNorgan, C., Alvarez, A., Bhullar, A., Gayda, J., & Booth, J. R. (2011). Prediction of Reading Skill Several Years Later Depends on Age and Brain Region: Implications for Developmental Models of Reading. Journal of Neuroscience, 31(26), 9641–9648. https://doi.org/10.1523/JNEUROSCI.0334-11.2011
- Fenchel, D., Dimitrova, R., Robinson, E. C., Batalle, D., Chew, A., Falconer, S., Kyriakopoulou, V., Nosarti, C., Hutter, J., Christiaens, D., Pietsch, M., Brandon, J., Hughes, E. J., Allsop, J., O’Keeffe, C., Price, A. N., Cordero-Grande, L., Schuh, A., Makropoulos, A., … O’Muircheartaigh, J. (2022). Neonatal multi-modal cortical profiles predict 18-month developmental outcomes. Developmental Cognitive Neuroscience, 54, 101103. https://doi.org/10.1016/j.dcn.2022.101103
- Edwards, A. D., Rueckert, D., Smith, S. M., Abo Seada, S., Alansary, A., Almalbis, J., Allsop, J., Andersson, J., Arichi, T., Arulkumaran, S., Bastiani, M., Batalle, D., Baxter, L., Bozek, J., Braithwaite, E., Brandon, J., Carney, O., Chew, A., Christiaens, D., … Hajnal, J. V. (2022). The Developing Human Connectome Project Neonatal Data Release. Frontiers in Neuroscience, 16. https://doi.org/10.3389/fnins.2022.886772
- Andersson, J. L. R., Skare, S., & Ashburner, J. (2003). How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. NeuroImage, 20(2), 870–888. https://doi.org/10.1016/S1053-8119(03)00336-7
- Christiaens, D., Cordero-Grande, L., Pietsch, M., Hutter, J., Price, A. N., Hughes, E. J., Vecchiato, K., Deprez, M., Edwards, A. D., Hajnal, J. V., & Tournier, J.-D. (2021). Scattered slice SHARD reconstruction for motion correction in multi-shell diffusion MRI. NeuroImage, 225, 117437. https://doi.org/10.1016/j.neuroimage.2020.117437
- Daducci, A., Canales-Rodríguez, E. J., Zhang, H., Dyrby, T. B., Alexander, D. C., & Thiran, J.-P. (2015). Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data. NeuroImage, 105, 32–44. https://doi.org/10.1016/j.neuroimage.2014.10.026
- Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012). NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage, 61(4), 1000–1016. https://doi.org/10.1016/j.neuroimage.2012.03.072
- Kamiya, K., Hori, M., & Aoki, S. (2020). NODDI in clinical research. Journal of Neuroscience Methods, 346, 108908. https://doi.org/10.1016/j.jneumeth.2020.108908
- Wang, Y., Chen, L., Wu, Z., Li, T., Sun, Y., Cheng, J., Zhu, H., Lin, W., Wang, L., Huang, W., & Li, G. (2023). Longitudinal development of the cerebellum in human infants during the first 800 days. Cell Reports, 42(4), 112281. https://doi.org/10.1016/j.celrep.2023.112281
- Diedrichsen, J., Balsters, J. H., Flavell, J., Cussans, E., & Ramnani, N. (2009). A probabilistic MR atlas of the human cerebellum. NeuroImage, 46(1), 39–46. https://doi.org/10.1016/j.neuroimage.2009.01.045
- Diedrichsen, J., Maderwald, S., Küper, M., Thürling, M., Rabe, K., Gizewski, E. R., Ladd, M. E., & Timmann, D. (2011). Imaging the deep cerebellar nuclei: A probabilistic atlas and normalization procedure. NeuroImage, 54(3), 1786–1794. https://doi.org/10.1016/j.neuroimage.2010.10.035
- Bayley, N. (2012). Bayley Scales of Infant and Toddler Development, Third Edition. https://doi.org/10.1037/t14978-000
- Allison, C., Matthews, F. E., Ruta, L., Pasco, G., Soufer, R., Brayne, C., Charman, T., & Baron-Cohen, S. (2021). Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population screening study with follow-up: the case for multiple time-point screening for autism. BMJ Paediatrics Open, 5(1), e000700. https://doi.org/10.1136/bmjpo-2020-000700
- Wood, S. N. (2017). Generalized Additive Models: An Introduction with R (2nd ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781315370279
- Marvel, C. L., & Desmond, J. E. (2010). Functional Topography of the Cerebellum in Verbal Working Memory. Neuropsychology Review, 20(3), 271–279. https://doi.org/10.1007/s11065-010-9137-7
- Saadon-Grosman, N., Angeli, P. A., DiNicola, L. M., & Buckner, R. L. (2022). A third somatomotor representation in the human cerebellum. Journal of Neurophysiology, 128(4), 1051–1073. https://doi.org/10.1152/jn.00165.2022
- Stephen, R., Elizabeth, Y., & Christophe, H. (2018). Participation of the caudal cerebellar lobule IX to the dorsal attentional network. Cerebellum & ataxias, 5, 9. https://doi.org/10.1186/s40673-018-0088-8
- Olson, I. R., Hoffman, L. J., Jobson, K. R., Popal, H. S., & Wang, Y. (2023). Little brain, little minds: The big role of the cerebellum in social development. Developmental cognitive neuroscience, 60, 101238. https://doi.org/10.1016/j.dcn.2023.101238
- Popa, L.S., Ebner, T.J. (2022). Cerebellum and Internal Models. In: Manto, M.U., Gruol, D.L., Schmahmann, J.D., Koibuchi, N., Sillitoe, R.V. (eds) Handbook of the Cerebellum and Cerebellar Disorders. Springer, Cham. https://doi.org/10.1007/978-3-030-23810-0_56