Displaying 1 - 10 of 10
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Amelink, J., Postema, M., Kong, X., Schijven, D., Carrion Castillo, A., Soheili-Nezhad, S., Sha, Z., Molz, B., Joliot, M., Fisher, S. E., & Francks, C. (2024). Imaging genetics of functional connectivity within the language network reveals links with language-related abilities, dyslexia, and handedness. Poster presented at the IMPRS Conference 2024, Nijmegen, the Netherlands.
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Amelink, J., Postema, M., Kong, X., Schijven, D., Carrion Castillo, A., Soheili-Nezhad, S., Sha, Z., Molz, B., Joliot, M., Fisher, S. E., & Francks, C. (2024). Imaging genetics of language network functional connectivity reveals links with language-related abilities, dyslexia and handedness. Talk presented at the third conference of the European Social Science Genetics Network (ESSGN III). Rotterdam, The Netherlands. 2024-05-29 - 2024-05-30.
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Amelink, J., Postema, M., Kong, X., Schijven, D., Carrion Castillo, A., Soheili-Nezhad, S., Sha, Z., Molz, B., Joliot, M., Fisher, S. E., & Francks, C. (2024). Imaging genetics of language network functional connectivity reveals links with language-related abilities, dyslexia and handedness. Poster presented at the 57th Annual European Human Genetics Conference (ESHG 2024), Berlin, Germany.
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Amelink, J., Postema, M., Kong, X., Schijven, D., Carrion Castillo, A., Soheili-Nezhad, S., Sha, Z., Molz, B., Joliot, M., Fisher, S. E., & Francks, C. (2024). Imaging genetics of language network functional connectivity reveals links with language-related abilities, dyslexia and handedness. Poster presented at the Dutch Neuroscience Meeting (DNM 24), Tiel, The Netherlands.
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Amelink, J., Postema, M., Kong, X., Schijven, D., Carrion Castillo, A., Soheili-Nezhad, S., Sha, Z., Molz, B., Joliot, M., Fisher, S. E., & Francks, C. (2024). Imaging genetics of language network functional connectivity reveals links with language-related abilities, dyslexia and handedness. Poster presented at the Highlights in the Language Sciences Conference 2024, Nijmegen, The Netherlands.
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Amelink, J., Postema, M., Kong, X., Schijven, D., Carrion Castillo, A., Soheili-Nezhad, S., Sha, Z., Molz, B., Joliot, M., Fisher, S. E., & Francks, C. (2024). Imaging genetics of language network functional connectivity reveals links with language-related abilities, dyslexia and handedness. Poster presented at the Donders Poster Session 2024, Nijmegen, The Netherlands.
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Wong, M. M. K., Sha, Z., Luetje, L., Kong, X., Velthuijs, N., Van Heukelum, S., Schijven, D., Mhlanga, M., Van de Berg, W., Jonkman, L., Fisher, S. E., & Francks, C. (2024). The neocortical infrastructure for language involves region-specific patterns of laminar gene expression. Poster presented at the Highlights in the Language Sciences Conference 2024, Nijmegen, The Netherlands.
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Huang, L., Yang, Z., Zhou, G., Liu, Z., Dang, X., Kong, X., Wang, X., Zhen, Z., & Liu, J. (2014). FreeROI: an integrated toolbox for region of interest definition and visualization. Poster presented at The 17th National Academic Congress of Psychology, China.
Abstract
With the increasing knowledge for the topography of brain function, neuroimaging studies are moving away from traditional brain mapping towards investigating the response properties of specific brain regions. As a result, region of interest (ROI) approach, which allows one to ask how a region responds to a range of situations and tasks, become an important methodology in neuroimaging. The FreeROI is designed to help ROI analysis by providing versatile tools for defining/manipulating ROIs and calculating a summary time course from the region data. A pipeline for handling big dataset is also included. -
Kong, X., Zhen, Z., & Liu, J. (2014). Measuring Regional Diffusivity Dependency via Mutual Information. Poster presented at IEEE International Symposium on Biomedical Imaging, Beijing.
Abstract
We proposed an improved approach to measuring regional diffusivity dependency with diffusion MRI. Unlike the original approach, the improved metric can detect all types of regional dependencies. Systematical comparison was done. -
Kong, X., Dang, X., & Liu, J. (2014). Large-scale anatomical networks: does node refining matter?. Poster presented at 20th Annual Meeting of the Organization for Human Brain Mapping (OHBM), Hamburg.
Abstract
We evaluated the affects of node refining on the topological properties of constructed large-scale anatomical networks. Significant effects of node-refining on topological metrics in large-scale anatomical network analysis were found, suggesting that node-refining does matter in quantifying anatomical topological properties.
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