scholarly journals Alternations of interhemispheric functional connectivity in children with strabismus and amblyopia: a resting-state fMRI study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiaxin Peng ◽  
Fan Yao ◽  
Qiuyu Li ◽  
Qianmin Ge ◽  
Wenqing Shi ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Pearson Correlation ◽  
Gaussian Random Field ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Random Field Theory ◽  
Fmri Study ◽  
Brain Changes ◽  
Normal Controls

AbstractPrevious neuroimaging studies demonstrated that patients with strabismus or amblyopia can show significant functional and anatomical changes in the brain, but alterations of interhemispheric functional connectivity (FC) have not been well studied in this population. The current study analyzed whole-brain changes of interhemispheric FC in children with strabismus and amblyopia (CSA) using voxel-mirrored homotopic connectivity (VMHC).A total of 24 CSA (16 males and 8 females) and 24 normal controls (NCs) consisting of 16 and 8 age-, sex, and education-matched males and females, respectively, underwent functional magnetic resonance imaging (fMRI) scans in the resting state. According to Gaussian random field theory, changes in the resting state FC (rsFC) between hemispheres were evaluated using the VMHC method. The relationships between mean VMHC values in multiple brain regions and behavioral performance were evaluated by Pearson correlation analysis. In contrast to NCs, the CSA group showed significantly decreased VMHC values in the bilateral cerebellum, bilateral frontal superior orbital (frontal sup orb), bilateral temporal inferior(temporal inf),and bilateral frontal superior(frontal sup). CSA have abnormal interhemispheric FC in many brain regions, which may reflect dysfunction of eye movements and visual fusion. These findings might provide insight into the underlying pathogenetic mechanisms of CSA.

scholarly journals Dynamic Expression of Brain Functional Systems Disclosed by Fine-Scale Analysis of Edge Time Series

2020 ◽  
Author(s):  
Olaf Sporns ◽  
Joshua Faskowitz ◽  
Andreia Sofia Teixera ◽  
Richard F. Betzel
Keyword(s):  
Time Series ◽  
Functional Connectivity ◽  
Resting State ◽  
Pearson Correlation ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Statistical Dependence ◽  
Fine Scale ◽  
Time Step ◽  
Functional Systems

AbstractFunctional connectivity (FC) describes the statistical dependence between brain regions in resting-state fMRI studies and is usually estimated as the Pearson correlation of time courses. Clustering reveals densely coupled sets of regions constituting a set of resting-state networks or functional systems. These systems manifest most clearly when FC is sampled over longer epochs lasting many minutes but appear to fluctuate on shorter time scales. Here, we propose a new approach to track these temporal fluctuations. Un-wrapping FC signal correlations yields pairwise co-fluctuation time series, one for each node pair/edge, and reveals fine-scale dynamics across the network. Co-fluctuations partition the network, at each time step, into exactly two communities. Sampled over time, the overlay of these bipartitions, a binary decomposition of the original time series, very closely approximates functional connectivity. Bipartitions exhibit characteristic spatiotemporal patterns that are reproducible across participants and imaging sessions and disclose fine-scale profiles of the time-varying levels of expression of functional systems. Our findings document that functional systems appear transiently and intermittently, and that FC results from the overlay of many variable instances of system expression. Potential applications of this decomposition of functional connectivity into a set of binary patterns are discussed.

scholarly journals Altered functional connectivity of brain regions based on a meta‐analysis in patients with T2DM: A resting‐state fMRI study

2020 ◽  
Vol 10 (8) ◽  
Author(s):  
Dongsheng Zhang ◽  
Jie Gao ◽  
Xuejiao Yan ◽  
Min Tang ◽  
Xia Zhe ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Meta Analysis ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Fmri Study

scholarly journals Dynamic expression of brain functional systems disclosed by fine-scale analysis of edge time series

2021 ◽  
pp. 1-34
Author(s):  
Olaf Sporns ◽  
Joshua Faskowitz ◽  
Andreia Sofia Teixeira ◽  
Sarah A Cutts ◽  
Richard F. Betzel
Keyword(s):  
Time Series ◽  
Functional Connectivity ◽  
Resting State ◽  
Pearson Correlation ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Statistical Dependence ◽  
Fine Scale ◽  
Time Step ◽  
Functional Systems

Functional connectivity (FC) describes the statistical dependence between neuronal populations or brain regions in resting-state fMRI studies and is commonly estimated as the Pearson correlation of time courses. Clustering or community detection reveals densely coupled sets of regions constituting resting-state networks or functional systems. These systems manifest most clearly when FC is sampled over longer epochs but appear to fluctuate on shorter time scales. Here, we propose a new approach to reveal temporal fluctuations in neuronal time series. Un-wrapping FC signal correlations yields pairwise co-fluctuation time series, one for each node pair or edge, and allows tracking of fine-scale dynamics across the network. Co-fluctuations partition the network, at each time step, into exactly two communities. Sampled over time, the overlay of these bipartitions, a binary decomposition of the original time series, very closely approximates functional connectivity. Bipartitions exhibit characteristic spatiotemporal patterns that are reproducible across participants and imaging runs, capture individual differences, and disclose fine-scale temporal expression of functional systems. Our findings document that functional systems appear transiently and intermittently, and that FC results from the overlay of many variable instances of system expression. Potential applications of this decomposition of functional connectivity into a set of binary patterns are discussed.

scholarly journals Decreased Functional Connectivity of Homotopic Brain Regions in Chronic Stroke Patients: A Resting State fMRI Study

PLoS ONE ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. e0152875 ◽  
Author(s):  
Chaozheng Tang ◽  
Zhiyong Zhao ◽  
Chuang Chen ◽  
Xiaohui Zheng ◽  
Fenfen Sun ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Chronic Stroke ◽  
Stroke Patients ◽  
Fmri Study
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