Patterns of individual differences in fiber tract integrity of the face processing brain network support neurofunctional models

Xinyang Liu, Andrea Hildebrandt, Kristina Meyer, Werner Sommer*, Changsong Zhou*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

11 Citations (Scopus)


Face cognition, the ability to perceive faces and interpret facial information, is a crucial skill in human social interactions. At the neurobiological level, several functionally specialized brain regions constitute a network of face processing. However, the evidence whether functional specialization within the face network is also reflected in the white matter structural connectivity patterns is yet limited. Based on imaging data from 1051 young healthy adult women and men, we investigated individual differences in the integrity of fibre tracts connecting face-processing regions relative to brain-general tract integrity. We analyzed individual tract-averaged fractional anisotropy (FA) values with structural equation modeling (SEM). Our results show that beyond the variance explained by a general factor indicating the quality of global tracts, the specificity of white matter integrity within the face network can be accounted for by additional factors. These factors correspond to the core and extended networks suggested in classic neuro-functional models of face processing. The right-hemisphere dominance, as commonly found in face cognition studies, is also reflected in this factorial structure. Overall, our results extend the structural brain substrate of the classic functional face processing system to the network of fibre tracts connecting these brain areas, and shed light on a structure-function correspondence from the perspective of individual differences.

Original languageEnglish
Article number116229
Publication statusPublished - 1 Jan 2020

Scopus Subject Areas

  • Neurology
  • Cognitive Neuroscience

User-Defined Keywords

  • Face processing network
  • Individual differences
  • Structural equation modeling
  • Structural-functional correspondence
  • White matter integrity


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