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Related Experiment Video

Updated: Aug 27, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

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Sensorimotor network dynamics predict decline in upper and lower limb function in people with multiple sclerosis.

Myrte Strik¹, Anand Jc Eijlers², Iris Dekker³

¹Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Melbourne, VIC, Australia/MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.

Multiple Sclerosis (Houndmills, Basingstoke, England)

|September 30, 2022

Summary

Functional network efficiency predicts multiple sclerosis (MS) limb disability progression. Unique predictors for upper and lower limbs suggest distinct network disturbances in MS patients.

Keywords:

Functional magnetic resonance imaging disability progression longitudinal network dynamics network efficiency upper and lower limbs

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Area of Science:

Neuroscience
Medical Imaging
Neurology

Background:

Multiple sclerosis (MS) is hypothesized to involve independent network disturbances affecting upper and lower limbs.
Understanding these distinct network alterations is crucial for predicting MS progression.

Purpose of the Study:

To investigate functional network predictors of upper and lower limb disability progression in MS.
To examine longitudinal changes in functional networks related to limb function over time.

Main Methods:

Functional magnetic resonance imaging (fMRI) was used to assess functional network efficiency (static and dynamic) in 214 MS patients and 58 controls.
Dexterity and mobility were measured at baseline and 5 years, with patients stratified into progressors and non-progressors.
Baseline network measures predicted progression, and significant predictors were analyzed longitudinally.

Main Results:

Both upper and lower limb progression were associated with supplementary motor area and caudate efficiency.
Unique predictors were identified for each limb, including grey matter volume and various cortical and subcortical network efficiencies.
Only the caudate showed a decline in efficiency over time in non-progressors.

Conclusions:

Sensorimotor network measures can predict disability progression in MS.
Distinct predictors for upper and lower limb progression suggest underlying differences in network disturbances.
This highlights the potential for targeted interventions based on specific limb involvement.