scholarly journals Altered brain network centrality in patients with retinal vein occlusion: a resting-state fMRI study

2021 ◽  
Vol 14 (11) ◽  
pp. 1741-1747
Author(s):  
Wen-Jia Dong ◽  
◽  
Chu-Qi Li ◽  
Yong-Qiang Shu ◽  
Wen-Qing Shi ◽  
...  
Keyword(s):  
Retinal Vein Occlusion ◽  
Resting State ◽  
Brain Activity ◽  
Activity Patterns ◽  
Depression Scale ◽  
Resting State Fmri ◽  
Brain Network ◽  
Middle Temporal Gyrus ◽  
Vein Occlusion ◽  
Intrinsic Brain Activity

AIM: To explore the intrinsic brain activity variations in retinal vein occlusion (RVO) subjects by using the voxel-wise degree centrality (DC) technique. METHODS: Twenty-one subjects with RVO and twenty-one healthy controls (HCs) were enlisted and underwent the resting-state functional magnetic resonance imaging (rs-fMRI) examination. The spontaneous cerebrum activity variations were inspected using the DC technology. The receiver operating characteristic (ROC) curve was implemented to distinguish the DC values of RVOs from HCs. The relationships between DC signal of definite regions of interest and the clinical characteristics in RVO group were evaluated by Pearson’s correlation analysis. RESULTS: RVOs showed notably higher DC signals in right superior parietal lobule, middle frontal gyrus and left precuneus, but decreased DC signals in left middle temporal gyrus and bilateral anterior cingulated (BAC) when comparing with HCs. The mean DC value of RVOs in the BAC were negatively correlated with the anxiety and depression scale. CONCLUSION: RVO is associated aberrant intrinsic brain activity patterns in several brain areas including pain-related as well as visual-related regions, which might assist to reveal the latent neural mechanisms.

scholarly journals Aberrant Dynamics of Regional Coherence Measured by Resting-State fMRI in Children With Benign Epilepsy With Centrotemporal Spikes (BECTS)

2021 ◽  
Vol 12 ◽  
Author(s):  
Lin Jiang ◽  
Xuejin Ma ◽  
Heng Liu ◽  
Ji Wang ◽  
Jiaren Zhang ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Middle Temporal Gyrus ◽  
Dynamic Features ◽  
Association Analyses ◽  
Global Signal ◽  
Iq Scores ◽  
Intrinsic Brain Activity ◽  
Benign Epilepsy

Objective: To explore the dynamic features of intrinsic brain activity measured by fMRI in children with benign epilepsy with centrotemporal spikes (BECTS) and examine whether these indexes were associated with behaviors.Methods: We recruited 26 children with BECTS (10.35 ± 2.91 years) and 26 sex-, and age-matched (11.35 ± 2.51 years) healthy controls (HC) and acquired resting-state functional magnetic resonance imaging (rs-fMRI) and behavioral data. Dynamic regional homogeneity (dReHo), including mean and coefficient of variation (CV) metrics derived from the rs-fMRI data, and were compared between the BECTS and the HC groups.Results: Significantly decreased mean dReHo in bilateral supramarginal gyrus, left middle temporal gyrus (MTG.L), left postcentral gyrus and superior occipital gyrus were found in children with BECTS. Meanwhile, increased CV of dReHo in MTG.L and right fusiform in children with BECTS was revealed compared with HC. Further analyses of functional connectivity revealed decreased global signal FC existed in similar regions, linked with linguistic, social cognition, and sensorimotor processes, in children with BECTS compared with HCs. Moreover, the association analyses showed that the CV of dReHo in MTG.L was positively associated with age and a negative correlation was found between mean dReHo of MTG.L and disease duration. Besides, the CV of dReHo in MTG.L was found positively associated with the intelligence quotient (IQ) language scores and full IQ scores in children with BECTS, and the CV of dReHo in the left inferior temporal gyrus and Rolandic operculum were positively correlated with IQ operation scores and full IQ scores.Conclusion: Aberrant dynamic regional coherence in sensorimotor, linguistic, and lateral temporal regions suggests dynamical interplay that underlying cognitive performance in children with BECTS, suggesting an intrinsic dynamic mechanism for BECTS.

Distinguishing hypochondriasis and schizophrenia using regional homogeneity: a resting-state fMRI study and support vector machine analysis

2021 ◽  
pp. 1-29
Author(s):  
Kangyu Jin ◽  
Zhe Shen ◽  
Guoxun Feng ◽  
Zhiyong Zhao ◽  
Jing Lu ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Resting State ◽  
Parietal Lobe ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Middle Temporal Gyrus ◽  
Support Vector ◽  
Fmri Study

Abstract Objective: A few former studies suggested there are partial overlaps in abnormal brain structure and cognitive function between Hypochondriasis (HS) and schizophrenia (SZ). But their differences in brain activity and cognitive function were unclear. Methods: 21 HS patients, 23 SZ patients, and 24 healthy controls (HC) underwent Resting-state functional magnetic resonance imaging (rs-fMRI) with the regional homogeneity analysis (ReHo), subsequently exploring the relationship between ReHo value and cognitive functions. The support vector machines (SVM) were used on effectiveness evaluation of ReHo for differentiating HS from SZ. Results: Compared with HC, HS showed significantly increased ReHo values in right middle temporal gyrus (MTG), left inferior parietal lobe (IPL) and right fusiform gyrus (FG), while SZ showed increased ReHo in left insula, decreased ReHo values in right paracentral lobule. Additionally, HS showed significantly higher ReHo values in FG, MTG and left paracentral lobule but lower in insula than SZ. The higher ReHo values in insula were associated with worse performance in MCCB in HS group. SVM analysis showed a combination of the ReHo values in insula and FG was able to satisfactorily distinguish the HS and SZ patients. Conclusion: our results suggested the altered default mode network (DMN), of which abnormal spontaneous neural activity occurs in multiple brain regions, might play a key role in the pathogenesis of HS, and the resting-state alterations of insula closely related to cognitive dysfunction in HS. Furthermore, the combination of the ReHo in FG and insula was a relatively ideal indicator to distinguish HS from SZ.

scholarly journals Dynamic Properties of Simulated Brain Network Models and Empirical Resting State Data

2018 ◽  
Author(s):  
Amrit Kashyap ◽  
Shella Keilholz
Keyword(s):  
Resting State ◽  
Dynamic Properties ◽  
Brain Activity ◽  
Temporal Structure ◽  
Structural Connectivity ◽  
Network Models ◽  
Resting State Fmri ◽  
Brain Network ◽  
Dynamical Analysis ◽  
Whole Brain

AbstractBrain Network Models have become a promising theoretical framework in simulating signals that are representative of whole brain activity such as resting state fMRI. However, it has been difficult to compare the complex brain activity between simulated and empirical data. Previous studies have used simple metrics that surmise coordination between regions such as functional connectivity, and we extend on this by using various different dynamical analysis tools that are currently used to understand resting state fMRI. We show that certain properties correspond to the structural connectivity input that is shared between the models, and certain dynamic properties relate more to the mathematical description of the Brain Network Model. We conclude that the dynamic properties that gauge more temporal structure rather than spatial coordination in the rs-fMRI signal seem to provide the largest contrasts between different BNMs and the unknown empirical dynamical system. Our results will be useful in constraining and developing more realistic simulations of whole brain activity.

scholarly journals Longitudinal Spatial Patterns of Intrinsic Brain Activity and Functional Connectivity in Upper Limb Amputees Patients

2020 ◽  
Author(s):  
bingbo bao ◽  
xuyun hua ◽  
haifeng wei ◽  
pengbo luo ◽  
hongyi zhu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Patterns ◽  
Brain Plasticity ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Network ◽  
Intrinsic Connectivity ◽  
Intrinsic Brain Activity

Abstract Background: Amputation in adults is a serious condition and most patients were associated with the remapping of representations in motor and sensory brain network. Methods: The present study includes 8 healthy volunteers and 16 patients with amputation. We use resting-state fMRI to investigate the local and extent brain plasticity in patients suffering from amputation simultaneously. Both the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) were used for the assessment of neuroplasticity in central level. Results: We described changes in spatial patterns of intrinsic brain activity and functional connectivity in amputees in the present study and we found that not only the sensory and motor cortex, but also the related brain regions involved in the functional plasticity after upper extremity deafferentation. Conclusion: Our findings showed local and extensive cortical changes in the sensorimotor and cognitive-related brain regions, which may imply the dysfunction in not only sensory and motor function, but also sensorimotor integration and motor plan. The activation and intrinsic connectivity in the brain changed a lot showed correlation with the deafferentation status.

scholarly journals Inferring multi-scale neural mechanisms with brain network modelling

2017 ◽  
Author(s):  
Michael Schirner ◽  
Anthony Randal McIntosh ◽  
Viktor K. Jirsa ◽  
Gustavo Deco ◽  
Petra Ritter
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Empirical Studies ◽  
Structural Connectivity ◽  
Resting State Fmri ◽  
Brain Network ◽  
Neural Population ◽  
Network Modelling ◽  
Multi Scale ◽  
Activity Measurements

The neurophysiological processes underlying non-invasive brain activity measurements are not well understood. Here, we developed a novel connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects’ individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) slow resting-state fMRI oscillations, (2) spatial topologies of functional connectivity networks, (3) excitation-inhibition balance, (4, 5) pulsed inhibition on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies.

scholarly journals The organization of intrinsic brain activity differs between genders: A resting-state fMRI study in a large cohort of young healthy subjects

2012 ◽  
Vol 34 (6) ◽  
pp. 1330-1343 ◽  
Author(s):  
Massimo Filippi ◽  
Paola Valsasina ◽  
Paolo Misci ◽  
Andrea Falini ◽  
Giancarlo Comi ◽  
...  
Keyword(s):  
Resting State ◽  
Healthy Subjects ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Large Cohort ◽  
Fmri Study ◽  
Intrinsic Brain Activity
Sign in / Sign up

Export Citation Format

Share Document