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Author Notes:

Correspondence: Ganesh B. Chand ganesh.chand@emory.edu; ganeshchand@gmail.com

Designed the experiment: IH and DQ.

Performed the experiment: GC, JW, DQ, and IH.

Analyzed the data: GC, DQ, and IH.

Wrote the paper: GC, DQ, and IH.

Participated in the discussion and provided the comments: GC, JW, DQ, and IH.

All authors have approved the manuscript and agree with submission to this journal.

We have read and have abided by the statement of ethical standards for manuscripts submission.

The authors would like to thank the members of our team and the volunteers for their participation in the present study.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Research Funding:

Funding. NIA/NIH grants RF1AG051633 and R01AG042127 supported to IH. NIH grants AG25688, AG42127, AG49752, AG51633 supported to DQ.


  • Science & Technology
  • Life Sciences & Biomedicine
  • Geriatrics & Gerontology
  • Neurosciences
  • Neurosciences & Neurology
  • central-executive network
  • dynamical causal modeling
  • default mode network
  • insula subdivisions
  • insula-based network
  • FMRI

Interactions of Insula Subdivisions-Based Networks with Default-Mode and Central-Executive Networks in Mild Cognitive Impairment


Journal Title:

Frontiers in Aging Neuroscience


Volume 9


Type of Work:

Article | Final Publisher PDF


Interactions between the brain networks and subnetworks are crucial for active and resting cognitive states. Whether a subnetwork can restore the adequate function of the parent network whenever a disease state affects the parent network is unclear. Investigations suggest that the control of the anterior insula-based network (AIN) over the default-mode network (DMN) and central-executive network (CEN) is decreased in individuals with mild cognitive impairment (MCI). Here, we hypothesized that the posterior insula-based network (PIN) attempts to compensate for this decrease. To test this, we compared a group of MCI and normal cognitive individuals. A dynamical causal modeling method has been employed to investigate the dynamic network controls/modulations. We used the resting state functional MRI data, and assessed the interactions of the AIN and of the PIN, respectively, over the DMN and CEN. We found that the greater control of AIN than that of DMN (Wilcoxon rank sum: Z = 1.987; p = 0.047) and CEN (Z = 3.076; p = 0.002) in normal group and the lower (impaired) control of AIN than that of CEN (Z = 8.602; p = 7.816 × 10-18). We further revealed that the PIN control was significantly higher than that of DMN (Z = 6.608; p = 3.888 × 10-11) and CEN (Z = 6.429; p = 1.278 × 10-10) in MCI group where the AIN was impaired, but that control was significantly lower than of DMN (Z = 5.285; p = 1.254 × 10-7) and CEN (Z = 5.404; p = 6.513 × 10-8) in normal group. Finally, the global cognitive test score assessed using Montreal cognitive assessment and the network modulations were correlated (Spearman’s correlation: r = 0.47; p = 3.76 × 10-5 and r = -0.43; p = 1.97 × 10-4). These findings might suggest the flexible functional profiles of AIN and PIN in normal aging and MCI.

Copyright information:

© 2017 Chand, Wu, Hajjar and Qiu.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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