Hayward, CJ orcid.org/0000-0001-5563-8296, Huo, S, Chen, X et al. (1 more author) (2023) Nonoptimal component placement of the human connectome supports variable brain dynamics. Network Neuroscience, 7 (1). pp. 254-268. ISSN 2472-1751
Abstract
Neural systems are shaped by multiple constraints, balancing region communication with the cost of establishing and maintaining physical connections. It has been suggested that the lengths of neural projections be minimized, reducing their spatial and metabolic impact on the organism. However, long-range connections are prevalent in the connectomes across various species, and thus, rather than rewiring connections to reduce length, an alternative theory proposes that the brain minimizes total wiring length through a suitable positioning of regions, termed component placement optimization. Previous studies in nonhuman primates have refuted this idea by identifying a nonoptimal component placement, where a spatial rearrangement of brain regions in silico leads to a reduced total wiring length. Here, for the first time in humans, we test for component placement optimization. We show a nonoptimal component placement for all subjects in our sample from the Human Connectome Project (N = 280; aged 22–30 years; 138 females), suggesting the presence of constraints—such as the reduction of processing steps between regions—that compete with the elevated spatial and metabolic costs. Additionally, by simulating communication between brain regions, we argue that this suboptimal component placement supports dynamics that benefit cognition.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license |
Keywords: | Component placement optimization; Spatial networks; Wiring minimization; Structural connectivity; Macroconnectome; Metastability; Cognition |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Feb 2023 10:42 |
Last Modified: | 25 Jun 2023 23:16 |
Status: | Published |
Publisher: | MIT Press |
Identification Number: | 10.1162/netn_a_00282 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:196648 |