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Cortical Morphological Networks Difer Between Gyri and Sulci
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作者 Qingchun lin Suhui Jin +4 位作者 Guole Yin junle li Umer Asgher Shijun Qiu Jinhui Wang 《Neuroscience Bulletin》 2025年第1期46-60,共15页
This study explored how the human cortical folding pattern composed of convex gyri and concave sulci afected single-subject morphological brain networks,which are becoming an important method for studying the human br... This study explored how the human cortical folding pattern composed of convex gyri and concave sulci afected single-subject morphological brain networks,which are becoming an important method for studying the human brain connectome.We found that gyri-gyri networks exhibited higher morphological similarity,lower small-world parameters,and lower long-term test-retest reliability than sulci-sulci networks for cortical thickness-and gyrifcation index-based networks,while opposite patterns were observed for fractal dimension-based networks.Further behavioral association analysis revealed that gyri-gyri networks and connections between gyral and sulcal regions signifcantly explained inter-individual variance in Cognition and Motor domains for fractal dimension-and sulcal depth-based networks.Finally,the clinical application showed that only sulci-sulci networks exhibited morphological similarity reductions in major depressive disorder for cortical thickness-,fractal dimension-,and gyrifcation index-based networks.Taken together,these fndings provide novel insights into the constraint of the cortical folding pattern to the network organization of the human brain. 展开更多
关键词 Morphological connectivity Magnetic resonance imaging Test-retest reliability Cortical folding Graph theory
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Taxonomic status of Chinese blue sheep(Pseudois nayaur):new evidence of a distinct subspecies 被引量:2
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作者 Hui GAO Nannan li +7 位作者 Yongjie HUANG Fujie QIAO junle li Zongzhi li Yanxiang li Zhenghuan WANG liwei TENG Zhensheng liU 《Integrative Zoology》 SCIE CSCD 2020年第3期202-212,共11页
The blue sheep is an endemic species to the Qinghai-Tibet Plateau and surrounding regions.It has been regarded as having 2 subspecies:Pseudois nayaur nayaur and P.n.szechuanensis.However,such a classification remains ... The blue sheep is an endemic species to the Qinghai-Tibet Plateau and surrounding regions.It has been regarded as having 2 subspecies:Pseudois nayaur nayaur and P.n.szechuanensis.However,such a classification remains controversial.Herein,we analyze 10 microsatellite loci and part of the mitochondrial control region for clarification in such taxonomic debates.We use samples from 168 individuals from 6 geographic populations covering almost all the distribution areas of the species in China to carry out comparisons.Phylogenetic trees derived from both the microsatellite and mitochondrial markers combined with the discriminant analysis of principal components(DAPC)and the STRUCTURE analysis reveal that the individuals in the Helan Mountains are well grouped with a distinct evolutionary lineage and are significantly different from the other populations of P.n.szechuanensis according to Fst values,implying that this isolated population should be categorized as a valid subspecies;namely,Pseudois nayaur alashanicus.The isolation-by-distance(IBD)analysis shows a significant positive relationship between genetic and geographical distances among the populations. 展开更多
关键词 blue sheep isolation by distance MICROSATELLITE mtDNA control region TAXONOMY
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Aberrant single-subject morphological brain networks in first-episode,treatment-naive adolescents with major depressive disorder
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作者 Xiaofan Qiu junle li +8 位作者 Fen Pan Yuping Yang Weihua Zhou Jinkai Chen Ning Wei Shaojia Lu Xuchu Weng Manli Huang Jinhui Wang 《Psychoradiology》 2023年第1期220-231,共12页
Background:Neuroimaging-based connectome studies have indicated that major depressive disorder(MDD)is associated with dis-rupted topological organization of large-scale brain networks.However,the disruptions and their... Background:Neuroimaging-based connectome studies have indicated that major depressive disorder(MDD)is associated with dis-rupted topological organization of large-scale brain networks.However,the disruptions and their clinical and cognitive relevance are not well established for morphological brain networks in adolescent MDD.Objective:To investigate the topological alterations of single-subject morphological brain networks in adolescent MDD.Methods:Twenty-five first-episode,treatment-naive adolescents with MDD and 19 healthy controls(HCs)underwent T1-weighted magnetic resonance imaging and a battery of neuropsychological tests.Single-subject morphological brain networks were constructed separately based on cortical thickness,fractal dimension,gyrification index,and sulcus depth,and topologically characterized by graph-based approaches.Between-group differences were inferred by permutation testing.For significant alterations,partial correla-tions were used to examine their associations with clinical and neuropsychological variables in the patients.Finally,a support vector machine was used to classify the patients from controls.Results:Compared with the HCs,the patients exhibited topological alterations only in cortical thickness-based networks character-ized by higher nodal centralities in parietal(left primary sensory cortex)but lower nodal centralities in temporal(left parabelt complex,right perirhinal ectorhinal cortex,right area PHT and right ventral visual complex)regions.Moreover,decreased nodal centralities of some temporal regions were correlated with cognitive dysfunction and clinical characteristics of the patients.These results were largely reproducible for binary and weighted network analyses.Finally,topological properties of the cortical thickness-based net-works were able to distinguish the MDD adolescents from HCs with 87.6%accuracy.Conclusion:Adolescent MDD is associated with disrupted topological organization of morphological brain networks,and the disrup-tions provide potential biomarkers for diagnosing and monitoring the disease. 展开更多
关键词 adolescent major depressive disorder structural MRI morphological brain network cortical thickness support vector machine
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