Measuring robustness of brain networks in autism spectrum disorder with Ricci curvature

Sci Rep. 2020 Jul 2;10(1):10819. doi: 10.1038/s41598-020-67474-9.

Abstract

Ollivier-Ricci curvature is a method for measuring the robustness of connections in a network. In this work, we use curvature to measure changes in robustness of brain networks in children with autism spectrum disorder (ASD). In an open label clinical trials, participants with ASD were administered a single infusion of autologous umbilical cord blood and, as part of their clinical outcome measures, were imaged with diffusion MRI before and after the infusion. By using Ricci curvature to measure changes in robustness, we quantified both local and global changes in the brain networks and their potential relationship with the infusion. Our results find changes in the curvature of the connections between regions associated with ASD that were not detected via traditional brain network analysis.

Trial registration: ClinicalTrials.gov NCT02176317.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Autism Spectrum Disorder / diagnostic imaging*
  • Autism Spectrum Disorder / physiopathology*
  • Autism Spectrum Disorder / therapy
  • Blood Transfusion, Autologous
  • Child, Preschool
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Fetal Blood / transplantation*
  • Humans
  • Male
  • Nerve Net / diagnostic imaging*
  • Nerve Net / physiology*
  • White Matter / diagnostic imaging*
  • White Matter / physiology*

Associated data

  • ClinicalTrials.gov/NCT02176317