Brain Structure and Function

, Volume 224, Issue 4, pp 1489–1503 | Cite as

Phase fMRI informs whole-brain function connectivity balance across lifespan with connection-specific aging effects during the resting state

  • Zikuan ChenEmail author
  • Qing Zhou
  • Vince Calhoun
Original Article


A functional magnetic resonance imaging (fMRI) experiment produces complex-valued images consisting of pairwise magnitude and phase images. As different perspective on the same magnetic source, fMRI magnitude and phase data are complementary for brain function analysis. We collected 600-subject fMRI data during rest, decomposed via group-level independent component analysis (ICA) (mICA and pICA for magnitude and phase respectively), and calculated brain functional network connectivity matrices (mFC and pFC). The pFC matrix shows a fewer of significant connections balanced across positive and negative relationships. In comparison, the mFC matrix contains a positively-biased pattern with more significant connections. Our experiment data analyses also show that human brain maintains a whole-brain connection balance in resting state across an age span from 10 to 76 years, however, phase and magnitude data analyses reveal different connection-specific age effects on significant positive and negative subnetwork couplings.


BOLD fMRI Independent component analysis (ICA) Functional network connectivity (FC) Resting state Functional connectivity balance Age effect 



Blood oxygenation level dependent


Functional magnetic resonance imaging


False discovery rate


Magnitude-data independent component analysis (ICA)


Phase-data ICA


Magnitude-depicted function network connectivity (FC)


Phase-depicted FC



The authors would like to acknowledge the funding support of NIH Grant P20GM103472. The authors declare no competing financial interest.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Informed consent

All the human subjects provided written consent for MRI scanning under the approval of IRB at the University of New Mexico.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.The Mind Research Network and LBERIAlbuquerqueUSA
  2. 2.School of Physics and AstronomyYunnan UniversityKunmingChina
  3. 3.Department of Electrical and Computer EngineeringUniversity of New MexicoAlbuquerqueUSA

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