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000911393 1001_ $$0P:(DE-HGF)0$$aOldham, Stuart$$b0$$eCorresponding author
000911393 245__ $$aModeling spatial, developmental, physiological, and topological constraints on human brain connectivity
000911393 260__ $$aWashington, DC [u.a.]$$bAssoc.$$c2022
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000911393 520__ $$aThe complex connectivity of nervous systems is thought to have been shaped by competitive selection pressures to minimize wiring costs and support adaptive function. Accordingly, recent modeling work indicates that stochastic processes, shaped by putative trade-offs between the cost and value of each connection, can successfully reproduce many topological properties of macroscale human connectomes measured with diffusion magnetic resonance imaging. Here, we derive a new formalism that more accurately captures the competing pressures of wiring cost minimization and topological complexity. We further show that model performance can be improved by accounting for developmental changes in brain geometry and associated wiring costs, and by using interregional transcriptional or microstructural similarity rather than topological wiring rules. However, all models struggled to capture topographical (i.e., spatial) network properties. Our findings highlight an important role for genetics in shaping macroscale brain connectivity and indicate that stochastic models offer an incomplete account of connectome organization.
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000911393 7001_ $$00000-0002-3003-4055$$aFulcher, Ben D.$$b1
000911393 7001_ $$00000-0002-7435-0236$$aAquino, Kevin$$b2
000911393 7001_ $$00000-0003-4098-7084$$aArnatkevičiūtė, Aurina$$b3
000911393 7001_ $$0P:(DE-Juel1)187055$$aPaquola, Casey$$b4
000911393 7001_ $$00000-0003-4636-8145$$aShishegar, Rosita$$b5
000911393 7001_ $$00000-0001-9134-480X$$aFornito, Alex$$b6
000911393 773__ $$0PERI:(DE-600)2810933-8$$a10.1126/sciadv.abm6127$$gVol. 8, no. 22, p. eabm6127$$n22$$peabm6127$$tScience advances$$v8$$x2375-2548$$y2022
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