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Default Mode Network Structural Integrity and Cerebellar Connectivity Predict Information Processing Speed Deficit in

Giovanni Savini1, Matteo Pardini2,3, Gloria Castellazzi4,5

  • 1Department of Physics, University of Milan, Milan, Italy.

Frontiers in Cellular Neuroscience
|March 12, 2019
PubMed
Summary
This summary is machine-generated.

Cognitive impairment in multiple sclerosis (MS) is linked to default mode network (DMN) and cerebellum connectivity. Impaired DMN and cerebellum network efficiency strongly correlates with slower processing speed in MS patients.

Keywords:
cerebellumconnectomicsdefault mode network (DMN)diffusion weighted imaging (DWI)magnetic resonance imaging (MRI)multiple sclerosis (MS)symbol digit modalities test (SDMT)tractography

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Area of Science:

  • Neuroscience
  • Radiology
  • Cognitive Science

Background:

  • Cognitive impairment affects approximately 50% of multiple sclerosis (MS) patients, with unclear underlying mechanisms.
  • The default mode network (DMN) is implicated in cognition, but its role in MS and the contribution of the cerebellum (CBL) remain poorly understood.
  • Cortico-cerebellar connectivity within the extended DMN (CBL-DMN) has not been explored concerning cognitive performance in MS.

Purpose of the Study:

  • To investigate the associations between DMN and CBL-DMN structural connectivity and cognitive processing speed in MS patients.
  • To compare these associations in cognitively impaired MS (CIMS) and cognitively preserved MS (CPMS) patients.
  • To explore the role of the cerebellum's structural connectivity within the DMN in MS-related cognitive decline.

Main Methods:

  • 68 MS patients and 22 healthy controls (HCs) underwent 3T MRI scans, including diffusion-weighted imaging.
  • Cognitive processing speed was assessed using the Symbol Digit Modalities Test (SDMT).
  • DMN and CBL-DMN tracts were reconstructed using probabilistic tractography, and network efficiency was modeled using graph theory with fractional anisotropy (FA) weighting. Brain parenchymal fraction (BPF) was also calculated.

Main Results:

  • In CIMS, SDMT scores strongly correlated with FA-weighted global efficiency (GE) of the CBL-DMN (ρ = 0.87) and DMN (ρ = 0.82).
  • In CPMS, correlations between SDMT scores and FA-weighted GE were weaker, with SDMT most strongly correlating with BPF (ρ = 0.57).
  • Multivariable regression showed FA-weighted GE was the sole significant explanatory variable for SDMT in CIMS, while BPF and disability status were significant in CPMS. No correlations were found in HCs.

Conclusions:

  • Default mode network structural global efficiency is associated with cognitive performance in multiple sclerosis.
  • The cerebellum's structural connectivity to the DMN plays a significant role in processing speed decline in MS.
  • These findings highlight the importance of exploring extended brain networks, including the cerebellum, to understand MS-related cognitive impairment.