Topographic Axes of Wiring Space Converge to Genetic Topography in Shaping the Human Cortical Layout

D Deying Li (Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences) Y Yufan Wang (Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences) L Liang Ma Y Yaping Wang (Clinical Cancer Institute, Center for Translational Medicine, Naval Medical University) L Luqi Cheng (School of Life and Environmental Sciences, Guilin University of Electronic Technology) Y Yinan Liu W Weiyang Shi Y Yuheng Lu (School of Biomedical Engineering, Tsinghua University) H Haiyan Wang (Department of Chemistry and Biochemistry) C Chaohong Gao C Camilla T. Erichsen Y Yu Zhang (Xiangya Hospital, Central South University Changsha China) Z Zhengyi Yang S Simon B. Eickhoff C Chi-Hua Chen T Tianzi Jiang (Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences) C Congying Chu (Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences) L Lingzhong Fan (Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences)

Abstract

Genetic 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 the 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 (GCs) 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 GCs 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 GCs 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.

Article Details

Volume / Issue Vol. 45, Issue 7
Published February 12, 2025
Pages e1510242024
ISSN 0270-6474
Publisher Society for Neuroscience

Journal Info

Journal of Neuroscience

Society for Neuroscience

ISSN: 0270-6474 Life Sciences

Authors (18)

D

Deying Li

Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences

Y

Yufan Wang

Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences

L

Liang Ma

Y

Yaping Wang

Clinical Cancer Institute, Center for Translational Medicine, Naval Medical University

L

Luqi Cheng

School of Life and Environmental Sciences, Guilin University of Electronic Technology

Y

Yinan Liu

W

Weiyang Shi

Y

Yuheng Lu

School of Biomedical Engineering, Tsinghua University

H

Haiyan Wang

Department of Chemistry and Biochemistry

C

Chaohong Gao

C

Camilla T. Erichsen

Y

Yu Zhang

Xiangya Hospital, Central South University Changsha China

Z

Zhengyi Yang

S

Simon B. Eickhoff

C

Chi-Hua Chen

T

Tianzi Jiang

Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences

C

Congying Chu

Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences

L

Lingzhong Fan

Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences