Coupling structure and function in early MS: How a less diverse repertoire of brain function could lead to clinical progression

Dam, Maureen van; Hulst, Hanneke E.; Schoonheim, Menno M.

doi:10.1177/1352458520987798

Cited by 5 publications

(7 citation statements)

References 11 publications

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“…structure–function coupling. Such coupling of direct connections was found to be increased during the first stages of MS, and greater coupling was related to worse cognitive performance ( Koubiyr et al, 2021 , van Dam et al, 2021 ). This suggests that the functional network becomes more strongly constrained by the structural network in cognitively impaired patients.…”

Section: Structure-function Relationships In Ms: Are Functional and S...mentioning

confidence: 99%

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

Schoonheim

Broeders

Geurts

2022

NeuroImage: Clinical

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Section: Structure-function Relationships In Ms: Are Functional and S...mentioning

confidence: 99%

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

Schoonheim

Broeders

Geurts

2022

NeuroImage: Clinical

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“…This specific effect in CI could be explained by the higher density of short-range compared to long-range structural connections in the brain, leading to an increased vulnerability of long-range connections ( Park & Friston, 2013 ). Thus, alterations to long-range connections may have larger consequences on the functional network, limiting the repertoire of functional possibilities when these connections are damaged ( van Dam et al, 2021 ). This limited repertoire would then result in stronger coupling, which has longitudinally been observed in a previous MS study ( Koubiyr et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…While intuitively one might expect that FC would be severely constrained by the presence of direct structural connections, previous work found strong FC without a direct structural connection ( Honey et al, 2009 ; Robinson, 2012 ). Overall, in the healthy situation, the functional repertoire seems extensive despite a limited structural backbone, indicating a potentially low overlap between structure and function ( van Dam, Hulst, & Schoonheim, 2021 ). Indeed, it has become clear that there are regional variations in SC-FC correspondence, which relate to cognition in healthy controls (HCs) ( Gu, Jamison, Sabuncu, & Kuceyeski, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis

Kulik

Nauta

Tewarie

et al. 2022

Network Neuroscience

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Multiple sclerosis (MS) features extensive connectivity changes, but how structural and functional connectivity relate, and whether this relation could be a useful biomarker for cognitive impairment in MS is unclear. This study included 79 MS patients and 40 healthy controls (HCs). Patients were classified as cognitively impaired (CI) or cognitively preserved (CP). Structural connectivity was determined using diffusion MRI and functional connectivity using resting-state magnetoencephalography (MEG) data (theta, alpha1 and alpha2 bands). Structure-function coupling was assessed by correlating modalities, and further explored in frequency bands that significantly correlated with whole-brain structural connectivity. Functional correlates of short- and long-range structural connections (based on tract length) were then specifically assessed. ROC analyses were performed on coupling values to identify biomarker potential. Only the theta band showed significant correlations between whole-brain structural and functional connectivity (rho = −0.26, p = 0.023, only in MS). Long-range structure-function coupling was higher in CI patients compared to HCs (p = 0.005). Short-range coupling showed no group differences. Structure-function coupling was not a significant classifier of cognitive impairment for any tract length (short-range AUC = 0.498, p = 0.976, long-range AUC = 0.611, p = 0.095). Long-range structure-function coupling was higher in CI-MS compared to HC, but more research is needed to further explore this measure as biomarkers in MS.

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“…A healthy brain exhibits a rich repertoire of dynamical configurations, which is revealed in the low similarity between structural and functional connectivity (Braun et al, 2015). At the onset of MS, the similarity between structural and functional connectivity is low, but as the disease progresses disconnecting structural pathways, they become highly similar, indicating reduced range of dynamical configurations (van Dam et al, 2021). Persson et al (2006) investigated cognitive decline in aging and reported structural and functional alterations associated with declining memory performance in older subjects.…”

Section: Macroscopic Relationships Between Structural and Functional Connectivitymentioning

confidence: 99%

Integrative Models of Brain Structure and Dynamics: Concepts, Challenges, and Methods

Venkadesh

Horn

2021

Front. Neurosci.

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The anatomical architecture of the brain constrains the dynamics of interactions between various regions. On a microscopic scale, neural plasticity regulates the connections between individual neurons. This microstructural adaptation facilitates coordinated dynamics of populations of neurons (mesoscopic scale) and brain regions (macroscopic scale). However, the mechanisms acting on multiple timescales that govern the reciprocal relationship between neural network structure and its intrinsic dynamics are not well understood. Studies empirically investigating such relationships on the whole-brain level rely on macroscopic measurements of structural and functional connectivity estimated from various neuroimaging modalities such as Diffusion-weighted Magnetic Resonance Imaging (dMRI), Electroencephalography (EEG), Magnetoencephalography (MEG), and functional Magnetic Resonance Imaging (fMRI). dMRI measures the anisotropy of water diffusion along axonal fibers, from which structural connections are estimated. EEG and MEG signals measure electrical activity and magnetic fields induced by the electrical activity, respectively, from various brain regions with a high temporal resolution (but limited spatial coverage), whereas fMRI measures regional activations indirectly via blood oxygen level-dependent (BOLD) signals with a high spatial resolution (but limited temporal resolution). There are several studies in the neuroimaging literature reporting statistical associations between macroscopic structural and functional connectivity. On the other hand, models of large-scale oscillatory dynamics conditioned on network structure (such as the one estimated from dMRI connectivity) provide a platform to probe into the structure-dynamics relationship at the mesoscopic level. Such investigations promise to uncover the theoretical underpinnings of the interplay between network structure and dynamics and could be complementary to the macroscopic level inquiries. In this article, we review theoretical and empirical studies that attempt to elucidate the coupling between brain structure and dynamics. Special attention is given to various clinically relevant dimensions of brain connectivity such as the topological features and neural synchronization, and their applicability for a given modality, spatial or temporal scale of analysis is discussed. Our review provides a summary of the progress made along this line of research and identifies challenges and promising future directions for multi-modal neuroimaging analyses.

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Coupling structure and function in early MS: How a less diverse repertoire of brain function could lead to clinical progression

Cited by 5 publications

References 11 publications

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis

Integrative Models of Brain Structure and Dynamics: Concepts, Challenges, and Methods

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