Back

Functional connectome through the human life span

Sun, L.; Zhao, T.; Liang, X.; Xia, M.; Li, Q.; Liao, X.; Gong, G.; Wang, Q.; Pang, C.; Yu, Q.; Bi, Y.; Chen, P.; Chen, R.; Chen, Y.; Chen, T.; Cheng, J.; Cheng, Y.; Cui, Z.; Dai, Z.; Deng, Y.; Ding, Y.; Dong, Q.; Duan, D.; Gao, J.-H.; Gong, Q.; Han, Y.; Han, Z.; Huang, C.-C.; Huang, R.; Li, L.; Lin, C.-P.; Lin, Q.; Liu, B.; Liu, C.; Liu, N.; Liu, Y.; Lu, J.; Ma, L.; Men, W.; Qin, S.; Qiu, J.; Qiu, S.; Si, T.; Tan, S.; Tang, Y.; Tao, S.; Wang, D.; Wang, F.; Wang, J.; Wang, P.; Wang, X.; Wang, Y.; Wei, D.; Wu, Y.; Xie, P.; Xu, X.; Xu, Y.; Xu, Z.; Yang, L.; Zeng, Z.; Zhang, H.; Zhang, X.; Zhao, G

2023-09-13 neuroscience
10.1101/2023.09.12.557193 bioRxiv
Show abstract

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.