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Functional alteration due to structural damage is network dependent: insight from multiple sclerosis.

Alexander Bartnik1,2, Tom A Fuchs1,2, Kira Ashton1,2

  • 1Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, NY 14203, United States.

Cerebral Cortex (New York, N.Y. : 1991)
|December 31, 2022
PubMed
Summary
This summary is machine-generated.

Brain networks adapt differently to structural damage. Higher-order networks show greater functional connectivity changes in multiple sclerosis, unlike lower-order sensory networks, suggesting adaptability depends on processing complexity.

Keywords:
connectomefunctional connectivitymultiple sclerosisresting-state networkstructural connectivity

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Area of Science:

  • Neuroscience
  • Neuroimaging
  • Systems Neuroscience

Background:

  • Understanding brain functional organization changes with structural damage is crucial.
  • Multiple sclerosis (MS) provides a model to study structural damage's impact on brain function.
  • Current knowledge on how functional connectivity (FC) responds to structural disruption is limited.

Purpose of the Study:

  • To assess changes in functional connectivity within and between resting-state networks (RSNs) in multiple sclerosis patients.
  • To investigate the relationship between structural disruption (SD) and changes in FC.
  • To determine if higher-order or lower-order networks are more affected by structural damage.

Main Methods:

  • Acquired structural, diffusion, and functional MRI data from 122 subjects (72 MS, 50 controls).
  • Computed functional connectomes and structural disconnectivity profiles using MRI data.
  • Utilized ordinary least squares regression to predict FC changes from SD across 9 common RSNs.

Main Results:

  • Identified significant differences in RSN functional response to structural damage.
  • Higher-order networks exhibited greater FC changes in response to SD compared to lower-order networks.
  • Default mode network showed significant FC changes (R2=0.160-0.207, P<0.001), while visual network 1 showed minimal changes (R2=0.001-0.007, P=0.157-0.387).

Conclusions:

  • Functional adaptability to structural damage varies across brain networks.
  • Higher-order processing networks are more susceptible to functional alterations following structural damage.
  • The degree of involvement in higher-order processing influences a network's functional resilience to structural damage.