Unexpected hubness: a proof-of-concept study of the human connectome using pagerank centrality and implications for intracerebral neurosurgery

J Neurooncol. 2021 Jan;151(2):249-256. doi: 10.1007/s11060-020-03659-6. Epub 2020 Nov 10.

Abstract

Introduction: Understanding the human connectome by parcellations allows neurosurgeons to foretell the potential effects of lesioning parts of the brain during intracerebral surgery. However, it is unclear whether there exist variations among individuals such that brain regions that are thought to be dispensable may serve as important networking hubs.

Methods: We obtained diffusion neuroimaging data from two healthy cohorts (OpenNeuro and SchizConnect) and applied a parcellation scheme to them. We ranked the parcellations on average using PageRank centrality in each cohort. Using the OpenNeuro cohort, we focused on parcellations in the lower 50% ranking that displayed top quartile ranking at the individual level. We then queried whether these select parcellations with over 3% prevalence would be reproducible in the same manner in the SchizConnect cohort.

Results: In the OpenNeuro (n = 68) and SchizConnect cohort (n = 195), there were 27.9% and 43.1% of parcellations, respectively, in the lower half of all ranks that displayed top quartile ranks. We noted three outstanding parcellations (L_V6, L_a10p, and L_7PL) in the OpenNeuro cohort that also appeared in the SchizConnect cohort. In the larger Schizconnect cohort, L_V6, L_a10p, and L_7PL had unexpected hubness in 3.08%, 5.13%, and 8.21% of subjects, respectively.

Conclusions: We demonstrated that lowly-ranked parcellations may serve as important hubs in a subset of individuals, highlighting the importance of studying parcellation ranks at the personalized level in planning supratentorial neurosurgery.

Keywords: Centrality; Connectome; Connectomics; Hubs; Unexpected hubness.

MeSH terms

  • Algorithms*
  • Brain / anatomy & histology
  • Brain / surgery*
  • Connectome*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Neural Pathways*
  • Neuroimaging / methods*
  • Neurosurgical Procedures / statistics & numerical data*
  • Proof of Concept Study