Journal Article

FZJ-2022-04676

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Modeling spatial, developmental, physiological, and topological constraints on human brain connectivity

Oldham, S. (Corresponding author) ; Fulcher, B. D. ; Aquino, K. ; Arnatkevičiūtė, A. ; Paquola, C.FZJ* ; Shishegar, R. ; Fornito, A.

2022
Assoc. Washington, DC [u.a.]

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Please use a persistent id in citations: http://hdl.handle.net/2128/32592  doi:10.1126/sciadv.abm6127

Abstract: The 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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Contributing Institute(s):

1. Strukturelle und funktionelle Organisation des Gehirns (INM-1)

Research Program(s):

1. 5254 - Neuroscientific Data Analytics and AI (POF4-525) (POF4-525)
2. HIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015) (InterLabs-0015)

Appears in the scientific report 2022

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