Preprint

FZJ-2021-05137

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.

2021

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Please use a persistent id in citations: http://hdl.handle.net/2128/29434  doi:10.1101/2021.09.29.462379

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 with the aim to more accurately capture 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 inter-regional transcriptional or microstructural similarity rather than topological wiring-rules. However, all models struggled to capture topologies spatial embedding. 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 2021

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