Generative models of the human connectome.
Generative models of the human connectome.
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DOI:
10.1016/j.neuroimage.2015.09.041
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发表时间:
2016-01-01
期刊:
影响因子:
5.7
通讯作者:
Sporns O
中科院分区:
文献类型:
--
作者:
Betzel RF;Avena-Koenigsberger A;Goñi J;He Y;de Reus MA;Griffa A;Vértes PE;Mišic B;Thiran JP;Hagmann P;van den Heuvel M;Zuo XN;Bullmore ET;Sporns O
The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan. We systematically compare thirteen generative models for the human connectome. The best-fitting model combines a distance penalty with homophily. Our results are consistent across three datasets comprising 380 total participants. The distance penalty weakens monotonically across the human lifespan.