Alterations of Dynamic Regional Homogeneity in Trigeminal Neuralgia: A Resting-State fMRI Study

Yan, Ji; Li, Meng; Fu, Shishun; Li, Guomin; Wang, Tianyue; Yin, Yi; Jiang, Guihua; Lin, Jin; Li, Wuming; Jin, Fang; Jian-guo, Tian

doi:10.3389/fneur.2019.01083

Cited by 20 publications

(22 citation statements)

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“…It is the uncovering of dynamics in FC across time scales and its interaction with external factors that helps improve the understanding of the central pain processes [ 20 ]. Recently, one dynamic regional homogeneity study detected temporal alteration about spontaneous neural activity in TN patients [ 21 ], but did not focus on changes in dynamic FC. However, dynamic functional network connectivity (dFNC) analysis can not only provide time-varying information of FC between resting-state connectivity networks (RSNs )[ 13 ], but also capture reproducible connectivity states and calculate temporal properties.…”

Section: Introductionmentioning

confidence: 99%

Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study

et al. 2021

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Background Accumulating studies have indicated a wide range of brain alterations with respect to the structure and function of classic trigeminal neuralgia (CTN). Given the dynamic nature of pain experience, the exploration of temporal fluctuations in interregional activity covariance may enhance the understanding of pain processes in the brain. The present study aimed to characterize the temporal features of functional connectivity (FC) states as well as topological alteration in CTN. Methods Resting-state functional magnetic resonance imaging and three-dimensional T1-weighted images were obtained from 41 CTN patients and 43 matched healthy controls (HCs). After group independent component analysis, sliding window based dynamic functional network connectivity (dFNC) analysis was applied to investigate specific FC states and related temporal properties. Then, the dynamics of the whole brain topological organization were estimated by calculating the coefficient of variation of graph-theoretical properties. Further correlation analyses were performed between all these measurements and clinical data. Results Two distinct states were identified. Of these, the state 2, characterized by complicated coupling between default mode network (DMN) and cognitive control network (CC) and tight connections within DMN, was expressed more in CTN patients and presented as increased fractional windows and dwell time. Moreover, patients switched less frequently between states than HCs. Regarding the dynamic topological analysis, disruptions in global graph-theoretical properties (including network efficiency and small-worldness) were observed in patients, coupled with decreased variability in nodal efficiency of anterior cingulate cortex (ACC) in the salience network (SN) and the thalamus and caudate nucleus in the subcortical network (SC). The variation of topological properties showed negative correlation with disease duration and attack frequency. Conclusions The present study indicated disrupted flexibility of brain topological organization under persistent noxious stimulation and further highlighted the important role of “dynamic pain connectome” regions (including DMN/CC/SN) in the pathophysiology of CTN from the temporal fluctuation aspect. Additionally, the findings provided supplementary evidence for current knowledge about the aberrant cortical-subcortical interaction in pain development.

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Section: Introductionmentioning

confidence: 99%

Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study

et al. 2021

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“…A sliding window approach was used to calculate the dReho by using the Dynamic Brain Connectome (DynamicBC) toolbox ( 30 ). In this study, we used a window length of 50 TRs (100 s) to calculate the temporal variability of dReho, which was accorded with the recommendation of previous studies (100 s ≥ 1/0.01) ( 31 ). The time series was comprised of 240 TRs (480 s), and the window was shifted by 1 TR (2 s).…”

Section: Methodsmentioning

confidence: 99%

Differential Dynamical Pattern of Regional Homogeneity in Bipolar and Unipolar Depression: A Preliminary Resting-State fMRI Study

et al. 2021

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Background: Bipolar depression (BD) and unipolar depression (UD) are both characterized by depressive moods, which are difficult to distinguish in clinical practice. Human brain activity is time-varying and dynamic. Investigating dynamical pattern alterations of depressed brains can provide deep insights into the pathophysiological features of depression. This study aimed to explore similar and different abnormal dynamic patterns between BD and UD.Methods: Brain resting-state functional magnetic resonance imaging data were acquired from 36 patients with BD type I (BD-I), 38 patients with UD, and 42 healthy controls (HCs). Analysis of covariance was adopted to examine the differential pattern of the dynamical regional homogeneity (dReHo) temporal variability across 3 groups, with gender, age, and education level as covariates. Post-hoc analyses were employed to obtain the different dynamic characteristics between any 2 groups. We further applied the machine-learning methods to classify BD-I from UD by using the detected distinct dReHo pattern.Results: Compared with patients with UD, patients with BD-I demonstrated decreased dReHo variability in the right postcentral gyrus and right parahippocampal gyrus. By using the dReHo variability pattern of these two regions as features, we achieved the 91.89% accuracy and 0.92 area under curve in classifying BD-I from UD. Relative to HCs, patients with UD showed increased dReHo variability in the right postcentral gyrus, while there were no dReHo variability differences in patients with BD-I.Conclusions: The results of this study mainly report the differential dynamic pattern of the regional activity between BD-I and UD, particular in the mesolimbic system, and show its promising potential in assisting the diagnosis of these two depression groups.

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“…Finally, we will smooth with a Gaussian kernel of 6 mm full-width at half-maximum (FWHM) to reduce noise. 19 , 39 …”

Section: Methodsmentioning

confidence: 99%

The Central Response of Electroacupuncture on Trigeminal Neuralgia Based on Resting-State Functional Magnetic Resonance Imaging: A Protocol for a Pre-Experimental, Single-Centre, Randomized, Controlled Trial

Tang

Zhang

et al. 2021

JPR

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Alterations of Dynamic Regional Homogeneity in Trigeminal Neuralgia: A Resting-State fMRI Study

Cited by 20 publications

References 38 publications

Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study

Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study

Differential Dynamical Pattern of Regional Homogeneity in Bipolar and Unipolar Depression: A Preliminary Resting-State fMRI Study

The Central Response of Electroacupuncture on Trigeminal Neuralgia Based on Resting-State Functional Magnetic Resonance Imaging: A Protocol for a Pre-Experimental, Single-Centre, Randomized, Controlled Trial

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