Thalamic Network Controllability Changes and Cognitive Impairment in Multiple Sclerosis
Poster No:
1759
Submission Type:
Abstract Submission
Authors:
Yuping Yang1, Anna Woollams1, Ilona Lipp2, Zhizheng Zhuo3, Valentina Tomassini4, Yaou Liu3, Nelson Trujillo-Barreto1, Nils Muhlert5
Institutions:
1University of Manchester, Manchester, Manchester, 2Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Leipzig, 3Beijing Tiantan Hospital, Beijing, Beijing, 4G. d’Annunzio University of Chieti-Pescara, Chieti, Chieti, 5University of Manchester, Manchester, UK
First Author:
Co-Author(s):
Introduction:
Multiple sclerosis is a neuroinflammatory and neurodegenerative disease commonly associated with cognitive impairment. Understanding brain mechanisms of cognitive impairment in multiple sclerosis is crucial for early diagnosis and developing effective interventions to improve the quality of life in patients. Recent studies indicate that individuals with multiple sclerosis who develop cognitive impairment display changes in network activity in the brain, such as altered transitions between network states (activity patterns). Particularly, regions within the subcortical network, like the thalamus, show abnormalities early in multiple sclerosis, possibly driving the subsequent changes in the rest of the brain.
Methods:
In this study, we investigated whether there are brain regions specifically involved in driving network changes throughout the brain in multiple sclerosis, and assessed how this relates to cognitive impairment in patients. To this end, we constructed functional brain networks based on resting-state functional MRI data from 102 multiple sclerosis patients and 27 healthy controls. Then we applied network controllability analysis using the most commonly used controllability measures to quantify the effect that brain networks or regions have on driving network changes and state transitions in multiple sclerosis. Furthermore, we compared network controllability changes between patients with different cognitive status. Finally, we tested the reproducibility of our main results using a separate dataset of 95 multiple sclerosis patients and 45 healthy controls.
Results:
We found significant global, cortical, and subcortical controllability changes in multiple sclerosis, as indicated by increased average controllability while decreased modal controllability and decreased activation energy in patients compared to controls. These changes predominately concentrated in the subcortical network, particularly the thalamus, and were further confirmed in the replication dataset. Moreover, both cognitively impaired and cognitively preserved patients showed increased average controllability while decreased modal controllability and decreased activation energy in the subcortical network, as well as increased average controllability in the thalamus. However, cognitively impaired patients additionally showed decreased modal controllability and decreased activation energy in the thalamus compared to the healthy controls. Besides, the thalamus in cognitively impaired patients showed significantly greater increase in average controllability than cognitively preserved patients.
Conclusions:
This study shows the specific effects that the subcortical network and the thalamus have on driving network changes and their association with cognitive impairment in multiple sclerosis. Our results emphasize the crucial role of the subcortical network and the thalamus in preserving brain transitions towards easy-to-reach network states while relinquishing brain transitions towards difficult-to-reach network states in multiple sclerosis, especially in those cognitively impaired patients, suggesting a possible brain mechanism underpinning the emergence of cognitive impairment in individuals with this disease.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Cognition
Computational Neuroscience
FUNCTIONAL MRI
Modeling
MRI
Neurological
Sub-Cortical
Thalamus
Other - Multiple Sclerosis
1|2Indicates the priority used for review
Provide references using author date format
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