A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information Flow

IEEE Trans Biomed Eng. 2016 Dec;63(12):2525-2539. doi: 10.1109/TBME.2016.2600637. Epub 2016 Aug 16.

Abstract

We introduce a method for analyzing dynamically changing functional magnetic resonance imaging (fMRI) network connectivity estimates as they vary within and between broad functional domains. The method captures evidence of intertemporal directionality in cross joint functional-domain influence and extends standard whole-brain dynamic network connectivity approaches into additional functionally meaningful dimensions by evaluating transition probabilities between clustered intradomain and interdomain connectivity patterns. Results: In applying this method to a large (N = 314) multisite resting-state fMRI dataset balanced between schizophrenia patients and healthy controls, we find evidence of joint functional domains that are global catalyzers, broadly shaping downstream functional relationships throughout the brain. Multiple interesting differences between patients and controls in both time-varying joint functional-domain connectivity patterns and in cross joint functional-domain intertemporal information flow were identified. Conclusion and Significance: Our proposed approach, thus, unifies the concepts of brain connectivity and interdomain connectivity and provides a powerful new way to evaluate functional connectivity data in the context of both the healthy and diseased brain.

Publication types

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

MeSH terms

  • Adolescent
  • Adult
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Nerve Net / physiopathology*
  • Schizophrenia / physiopathology*
  • Signal Processing, Computer-Assisted
  • Young Adult