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question:Could you recommend some other works by chiyoko? I really enjoyed the cut paper style of the illustration and would like to see more done by the same artist.
answer:Sure, here are some works done by Chiyoko that you might enjoy: - "The Mermaid's Lament" - "Underwater Wonderland" - "Nighttime Adventure" - "Feline Friends" - "Wildflower Garden" You can find more of Chiyoko's work on their website or social media pages.
question:Longchuan Li, PhD, received his doctorate in biomedical engineering from the University of Alabama at Birmingham in 2007. Upon his graduation, Dr. Li joined the Department of Biomedical Engineering at Emory University and Georgia Institute of Technology for his post-doctoral and research associate training, which focused on methods and applications of diffusion MRI and network theory. Dr. Li has previously studied brain evolution, aging and abnormalities associated with prenatal alcohol exposure using advanced MRI techniques and graph theory. At Marcus Autism Center, Dr. Li codirects pediatric neuroimaging research. Currently, his research is centered on three areas: understanding spatio-temporal patterns of early brain development using MRI, network theory and statistical modeling; identifying imaging-based biomarkers of autism spectrum disorder (ASD) in early infancy and adolescence; and developing state-of-the-art analytical tools to facilitate the study of complex brain developmental processes. Ji, B., Li, Z., Li, K., Li, L., Langley, J., Shen, H., Nie, S., Zhang, R., & Hu, X. (2015). Dynamic thalamus parcellation from resting-state fMRI data. Human brain mapping, 37(3), 954-967. Jing, K., Zhang, T., Lu, J., Chen, H., Jiang, X., Guo, L., Li, L., Hu, X., Lv, J., & Ge, B. (2015). Multiscale and multimodal fusion of tract-tracing and DTI-derived fibers in macaque brains, 2015. 938-942. Li, L., Bachevalier, J., Hu, X., Klin, A., Preuss, T. M., Shultz, S., & Jones, W. (2018). Topology of the Structural Social Brain Network in Typical Adults. Brain connectivity, 8(9), 537-548. Li, X., Chen, H., Zhang, T., Yu, X., Jiang, X., Li, K., Li, L., Razavi, M. J., Wang, X., Hu, X., Han, J., Guo, L., Hu, X., & Liu, T. (2016). Commonly preserved and species-specific gyral folding patterns across primate brains. Brain structure and function, 222(5), 2127-2141. Meng, Y., Payne, C., Li, L., Hu, X., Zhang, X., & Bachevalier, J. (2014). Alterations of hippocampal projections in adult macaques with neonatal hippocampal lesions: a Diffusion Tensor Imaging study. NeuroImage, 102 Pt. 2, 828-837. Na, S., Li, L., Crosson, B., Dotson, V., MacDonald, T. J., Mao, H., & King, T. Z. (2018). White matter network topology relates to cognitive flexibility and cumulative neurological risk in adult survivors of pediatric brain tumors. NeuroImage. Clinical, 20, 485-497. Van den Heuvel, M. P., de Reus, M. A., Feldman Barrett, L., Scholtens, L. H., Coopmans, F. M., Schmidt, R., Preuss, T. M., Rilling, J. K., & Li, L. (2015). Comparison of diffusion tractography and tract-tracing measures of connectivity strength in rhesus macaque connectome. Human brain mapping, 36(8), 3064-3075. Yan, Y., Li, L., Preuss, T. M., Hu, X., Herndon, J. G., & Zhang, X. (2014). In vivo evaluation of optic nerve aging in adult rhesus monkey by diffusion tensor imaging. Quantitative imaging in medicine and surgery, 4(1), 43-49. Zhang, T., Razavi, M. J., Chen, H., Li, Y., Li, X., Li, L., Guo, L., Hu, X., Liu, T., & Wang, X. (2017). Mechanisms of circumferential gyral convolution in primate brains. Journal of Computational Neuroscience, 42(3), 217-229. Zhang, J. Q., Ji, B., Zhou, C. Y., Li, L. C., Li, Z. H., Hu, X. P., & Hu, J. (2016). Differential Impairment of Thalamocortical Structural Connectivity in Amyotrophic Lateral Sclerosis. CNS neuroscience and therapeutics, 23(2), 155-161. Zhang, T., Kong, J., Jing, K., Chen, H., Jiang, X., Li, L., Guo, L., Lu, J., Hu, X., & Liu, T. (2015). Multi-scale and Multimodal Fusion of Tract-tracing, Myelin Stain and DTI-derived Fibers in Macaque Brains. Medical image computing and computer-assisted intervention, 9350, 246-254. Based on the passage above, Can you provide a list of publications by Dr. Li and his research team and briefly describe their findings?
answer:Publications: 1. Jing, K., Zhang, T., Lu, J., Chen, H., Jiang, X., Guo, L., Li, L., Hu, X., Lv, J., & Ge, B. (2015). Multiscale and multimodal fusion of tract-tracing and DTI-derived fibers in macaque brains, 2015. 938-942. The study focused on investigating multiscale and multimodal fusion of tract-tracing and DTI-derived fibers in macaque brains. 2. Li, L., Bachevalier, J., Hu, X., Klin, A., Preuss, T. M., Shultz, S., & Jones, W. (2018). Topology of the Structural Social Brain Network in Typical Adults. Brain connectivity, 8(9), 537-548. The research team explored the topology of the Structural Social Brain Network in Typical Adults using fMRI data. 3. Li, X., Chen, H., Zhang, T., Yu, X., Jiang, X., Li, K., Li, L., Razavi, M. J., Wang, X., Hu, X., Han, J., Guo, L., Hu, X., & Liu, T. (2016). Commonly preserved and species-specific gyral folding patterns across primate brains. Brain structure and function, 222(5), 2127-2141. The study aimed at identifying commonly preserved and species-specific gyral folding patterns across primate brains using MRI data. 4. Meng, Y., Payne, C., Li, L., Hu, X., Zhang, X., & Bachevalier, J. (2014). Alterations of hippocampal projections in adult macaques with neonatal hippocampal lesions: a Diffusion Tensor Imaging study. NeuroImage, 102 Pt. 2, 828-837. The research team examined alterations of hippocampal projections in adult macaques with neonatal hippocampal lesions using Diffusion Tensor Imaging data. 5. Na, S., Li, L., Crosson, B., Dotson, V., MacDonald, T. J., Mao, H., & King, T. Z. (2018). White matter network topology relates to cognitive flexibility and cumulative neurological risk in adult survivors of pediatric brain tumors. NeuroImage. Clinical, 20, 485-497. The study explored the relationship between white matter network topology, cognitive flexibility, and cumulative neurological risk in adult survivors of pediatric brain tumors using MRI data. 6. Van den Heuvel, M. P., de Reus, M. A., Feldman Barrett, L., Scholtens, L. H., Coopmans, F. M., Schmidt, R., Preuss, T. M., Rilling, J. K., & Li, L. (2015). Comparison of diffusion tractography and tract-tracing measures of connectivity strength in rhesus macaque connectome. Human brain mapping, 36(8), 3064-3075. The study compared diffusion tractography and tract-tracing measures of connectivity strength in the rhesus macaque connectome. 7. Yan, Y., Li, L., Preuss, T. M., Hu, X., Herndon, J. G., & Zhang, X. (2014). In vivo evaluation of optic nerve aging in adult rhesus monkey by diffusion tensor imaging. Quantitative imaging in medicine and surgery, 4(1), 43-49. The research team evaluated optic nerve aging in adult rhesus monkeys using Diffusion Tensor Imaging. 8. Zhang, T., Razavi, M. J., Chen, H., Li, Y., Li, X., Li, L., Guo, L., Hu, X., Liu, T., & Wang, X. (2017). Mechanisms of circumferential gyral convolution in primate brains. Journal of Computational Neuroscience, 42(3), 217-229. The study aimed to understand the mechanisms of circumferential gyral convolution in primate brains. 9. Zhang, J. Q., Ji, B., Zhou, C. Y., Li, L. C., Li, Z. H., Hu, X. P., & Hu, J. (2016). Differential Impairment of Thalamocortical Structural Connectivity in Amyotrophic Lateral Sclerosis. CNS neuroscience and therapeutics, 23(2), 155-161. The study focused on investigating the differential impairment of thalamocortical structural connectivity in amyotrophic lateral sclerosis. 10. Zhang, T., Kong, J., Jing, K., Chen, H., Jiang, X., Li, L., Guo, L., Lu, J., Hu, X., & Liu, T. (2015). Multi-scale and Multimodal Fusion of Tract-tracing, Myelin Stain and DTI-derived Fibers in Macaque
question:Can you provide a summary of Dr. Li's current research and the focus of his work?
answer:Dr. Longchuan Li's current research focuses on three areas: understanding spatio-temporal patterns of early brain development using MRI, network theory, and statistical modeling; identifying imaging-based biomarkers of autism spectrum disorder (ASD) in early infancy and adolescence; and developing state-of-the-art analytical tools to facilitate the study of complex brain developmental processes. Specifically, his team is exploring the topology of the structural social brain network, investigating white matter network topology in relation to cognitive flexibility and cumulative neurological risk in adult survivors of pediatric brain tumors, and studying the mechanisms of circumferential gyral convolution in primate brains, among other topics related to brain development and disorders. Overall, Dr. Li's work is focused on advancing our understanding of the brain's development and functioning, with a particular emphasis on ASD and related neurological conditions.
question:Can you provide more information about Dr. Li's research on imaging-based biomarkers of autism spectrum disorder?
answer:Dr. Li's research on imaging-based biomarkers of autism spectrum disorder (ASD) aims to identify objective and reliable markers that can aid in the diagnosis and early detection of ASD, which is currently diagnosed based on behavioral observations. He and his team are using various neuroimaging techniques, such as magnetic resonance imaging (MRI), to examine differences in brain structure, connectivity, and function between individuals with ASD and typically developing individuals. Specifically, his team is studying the structural and functional connectivity within and across brain networks, as well as the patterns of brain activity, in order to identify potential biomarkers of ASD. Dr. Li and his team are using a longitudinal approach to study brain development in individuals with ASD, from early infancy to adolescence, with the goal of identifying biomarkers that can provide early predictions of ASD diagnosis or the likelihood of developing ASD later in life. By developing reliable and objective markers of ASD, Dr. Li's research on imaging-based biomarkers has the potential to improve our understanding of the condition, facilitate early diagnosis and intervention, and ultimately improve the long-term outcomes for individuals with ASD.