001037652 001__ 1037652
001037652 005__ 20250310131242.0
001037652 0247_ $$2doi$$a10.1523/JNEUROSCI.1510-24.2024
001037652 0247_ $$2ISSN$$a0270-6474
001037652 0247_ $$2ISSN$$a1529-2401
001037652 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-00817
001037652 0247_ $$2pmid$$a39824638
001037652 0247_ $$2WOS$$aWOS:001425206500002
001037652 037__ $$aFZJ-2025-00817
001037652 082__ $$a610
001037652 1001_ $$0P:(DE-HGF)0$$aLi, Deying$$b0
001037652 245__ $$aTopographic Axes of Wiring Space Converge to Genetic Topography in Shaping Human Cortical Layout
001037652 260__ $$aWashington, DC$$bSoc.$$c2025
001037652 3367_ $$2DRIVER$$aarticle
001037652 3367_ $$2DataCite$$aOutput Types/Journal article
001037652 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1737998342_9345
001037652 3367_ $$2BibTeX$$aARTICLE
001037652 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001037652 3367_ $$00$$2EndNote$$aJournal Article
001037652 520__ $$aGenetic information is involved in the gradual emergence of cortical areas since the neural tube begins to form, shaping the heterogeneous functions of neural circuits in the human brain. Informed by invasive tract-tracing measurements, the cortex exhibits marked interareal variation in connectivity profiles, revealing the heterogeneity across cortical areas. However, it remains unclear about the organizing principles possibly shared by genetics and cortical wiring to manifest the spatial heterogeneity across cortex. Instead of considering a complex one-to-one mapping between genetic coding and interareal connectivity, we hypothesized the existence of a more efficient way that the organizing principles are embedded in genetic profiles to underpin the cortical wiring space. Leveraging vertex-wise tractography in diffusion-weighted MRI, we derived the global connectopies in both female and male to reliably index the organizing principles of interareal connectivity variation in a low-dimensional space, which captured three dominant topographic patterns along the dorsoventral, rostrocaudal, and mediolateral axes of the cortex. More importantly, we demonstrated that the global connectopies converge with the gradients of a vertex-by-vertex genetic correlation matrix on the phenotype of cortical morphology and the cortex-wide spatiomolecular gradients. By diving into the genetic profiles, we found that the critical role of genes scaffolding the global connectopies was related to brain morphogenesis and enriched in radial glial cells before birth and excitatory neurons after birth. Taken together, our findings demonstrated the existence of a genetically determined space that encodes the interareal connectivity variation, which may give new insights into the links between cortical connections and arealization.Significance Statement Genetic factors have involved the gradual emergence of cortical areas since the neural tube begins to form, shaping the specialization of neural circuitry in the human brain. However, the mechanisms through which genetics encode the complex interareal connectivity remain a pivotal and unanswered question in the field of neuroscience. Here, we hypothesized that a genetically determined space encoding the interareal connectivity variation exists, which may give new insights into the links between cortical connections and arealization. We combined diffusion tractography with a dimension reduction framework to unravel the underlying global topographic principle revealed by the anatomical connections.
001037652 536__ $$0G:(DE-HGF)POF4-5253$$a5253 - Neuroimaging (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001037652 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001037652 7001_ $$0P:(DE-HGF)0$$aWang, Yufan$$b1
001037652 7001_ $$0P:(DE-HGF)0$$aMa, Liang$$b2
001037652 7001_ $$0P:(DE-HGF)0$$aWang, Yaping$$b3
001037652 7001_ $$0P:(DE-HGF)0$$aCheng, Luqi$$b4
001037652 7001_ $$0P:(DE-HGF)0$$aLiu, Yinan$$b5
001037652 7001_ $$0P:(DE-HGF)0$$aShi, Weiyang$$b6
001037652 7001_ $$0P:(DE-HGF)0$$aLu, Yuheng$$b7
001037652 7001_ $$0P:(DE-HGF)0$$aWang, Haiyan$$b8
001037652 7001_ $$0P:(DE-HGF)0$$aGao, Chaohong$$b9
001037652 7001_ $$0P:(DE-HGF)0$$aErichsen, Camilla T.$$b10
001037652 7001_ $$0P:(DE-HGF)0$$aZhang, Yu$$b11
001037652 7001_ $$0P:(DE-HGF)0$$aYang, Zhengyi$$b12
001037652 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon B$$b13$$ufzj
001037652 7001_ $$0P:(DE-HGF)0$$aChen, Chi-Hua$$b14
001037652 7001_ $$0P:(DE-HGF)0$$aJiang, Tianzi$$b15
001037652 7001_ $$0P:(DE-HGF)0$$aChu, Congying$$b16
001037652 7001_ $$0P:(DE-HGF)0$$aFan, Lingzhong$$b17$$eCorresponding author
001037652 773__ $$0PERI:(DE-600)1475274-8$$a10.1523/JNEUROSCI.1510-24.2024$$gp. e1510242024 -$$pe1510242024 -$$tThe journal of neuroscience$$v.$$x0270-6474$$y2025
001037652 8564_ $$uhttps://juser.fz-juelich.de/record/1037652/files/Topographic%20Axes%20of%20Writing%20Space%20..pdf$$yOpenAccess
001037652 909CO $$ooai:juser.fz-juelich.de:1037652$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
001037652 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131678$$aForschungszentrum Jülich$$b13$$kFZJ
001037652 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)131678$$a HHU Düsseldorf$$b13
001037652 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China$$b17
001037652 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Lingzhong Fan at lingzhong.fan@ia.ac.cn $$b17
001037652 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5253$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001037652 9141_ $$y2025
001037652 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bJ NEUROSCI : 2022$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001037652 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bJ NEUROSCI : 2022$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-14
001037652 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-14
001037652 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0
001037652 980__ $$ajournal
001037652 980__ $$aVDB
001037652 980__ $$aUNRESTRICTED
001037652 980__ $$aI:(DE-Juel1)INM-7-20090406
001037652 9801_ $$aFullTexts