Distance disintegration characterizes node-level topological dysfunctions in cocaine addiction

Addict Biol. 2021 Nov;26(6):e13072. doi: 10.1111/adb.13072. Epub 2021 Jun 16.

Abstract

Previous investigations have used global graph theory measures in order to disentangle the complexity of the neural reorganizations occurring in cocaine use disorder (CUD). However, how these global topological alterations map into individual brain network areas remains unknown. In this study, we used resting state functional magnetic resonance imaging (fMRI) data to investigate node-level topological dysfunctions in CUD. The sample was composed of 32 individuals with CUD and 32 healthy controls, matched in age, years of education and intellectual functioning. Graph theory measures of optimal connectivity distance, node strength, nodal efficiency and clustering coefficient were estimated in each participant using voxel-wise functional connectivity connectomes. CUD individuals as compared with healthy controls showed higher optimal connectivity distances in ventral striatum, insula, cerebellum, temporal cortex, lateral orbitofrontal cortex, middle frontal cortex and left hippocampus. Furthermore, clinical measures quantifying severity of dependence were positively related with optimal connectivity distances in the right rolandic operculum and the right lateral orbitofrontal cortex, whereas length of abstinence was negatively associated with optimal connectivity distances in the right temporal pole and the left insula. Our results reveal a topological distancing of cognitive and affective related areas in addiction, suggesting an overall reduction in the communication capacity of these regions.

Keywords: addiction; cocaine; functional connectivity; graph theory; optimal connectivity distance; resting state.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain / diagnostic imaging
  • Brain / pathology*
  • Brain Mapping
  • Cocaine-Related Disorders / diagnostic imaging
  • Cocaine-Related Disorders / pathology*
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Male
  • Middle Aged
  • Patient Acuity