scholarly journals Test–retest reliability of structural brain networks from diffusion MRI

NeuroImage ◽  
2014 ◽  
Vol 86 ◽  
pp. 231-243 ◽  
Author(s):  
Colin R. Buchanan ◽  
Cyril R. Pernet ◽  
Krzysztof J. Gorgolewski ◽  
Amos J. Storkey ◽  
Mark E. Bastin
Keyword(s):  
Diffusion Mri ◽  
Brain Networks ◽  
Retest Reliability ◽  
Test Retest Reliability ◽  
Structural Brain

scholarly journals Evaluating test-retest reliability and sex/age-related effects on temporal clustering coefficient of dynamic functional brain networks

2021 ◽  
Author(s):  
Yicheng Long ◽  
Chaogan Yan ◽  
Zhipeng Wu ◽  
Xiaojun Huang ◽  
Hengyi Cao ◽  
...  
Keyword(s):  
Intraclass Correlation ◽  
Brain Networks ◽  
Clustering Coefficient ◽  
Retest Reliability ◽  
Brain Functions ◽  
Temporal Clustering ◽  
Age Related ◽  
Human Connectome Project ◽  
Wide Range ◽  
Test Retest Reliability

The multilayer dynamic network model has been proposed as an effective method to understand how the brain functions dynamically. Specially, derived from the definition of clustering coefficient in static networks, the temporal clustering coefficient provides a direct measure of topological stability of dynamic brain networks and shows potential in predicting altered brain functions in both normal and pathological conditions. However, test-retest reliability and demographic-related effects on this measure remain to be evaluated. Using a publicly available dataset from the Human Connectome Project consisting of 337 young healthy adults (157 males/180 females; 22 to 37 years old), the present study investigated: (1) the test-retest reliability of temporal clustering coefficient across four repeated resting-state functional magnetic resonance imaging scans as measured by intraclass correlation coefficient (ICC); and (2) sex- and age-related effects on temporal clustering coefficient. The results showed that (1) the temporal clustering coefficient had overall moderate test-retest reliability (ICC > 0.40 over a wide range of densities) at both global and subnetwork levels; (2) female subjects showed significantly higher temporal clustering coefficient than males at both global and subnetwork levels, in particular within the default-mode and subcortical regions; (3) temporal clustering coefficient of the subcortical subnetwork was negatively correlated with age in young adults. Our findings suggest that temporal clustering coefficient is a reliable and reproducible approach for the identification of individual differences in brain function, and provide evidence for sex and age effects on human brain dynamic connectome.

scholarly journals Test-Retest Reliability of Graph Metrics in Functional Brain Networks: A Resting-State fNIRS Study

PLoS ONE ◽  
2013 ◽  
Vol 8 (9) ◽  
pp. e72425 ◽  
Author(s):  
Haijing Niu ◽  
Zhen Li ◽  
Xuhong Liao ◽  
Jinhui Wang ◽  
Tengda Zhao ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Networks ◽  
Retest Reliability ◽  
Functional Brain ◽  
Graph Metrics ◽  
Functional Brain Networks ◽  
Test Retest Reliability

Test-retest reliability of graph metrics of resting state MRI functional brain networks: A review

2015 ◽  
Vol 253 ◽  
pp. 183-192 ◽  
Author(s):  
Martina Andellini ◽  
Vittorio Cannatà ◽  
Simone Gazzellini ◽  
Bruno Bernardi ◽  
Antonio Napolitano
Keyword(s):  
Resting State ◽  
Brain Networks ◽  
Retest Reliability ◽  
Functional Brain ◽  
Graph Metrics ◽  
Functional Brain Networks ◽  
Test Retest Reliability

scholarly journals Deterioration in Global Organization of Structural Brain Networks in Schizophrenia: A Diffusion MRI Tractography Study

2018 ◽  
Vol 9 ◽  
Author(s):  
Seung-Hyun Shon ◽  
Woon Yoon ◽  
Harin Kim ◽  
Sung Woo Joo ◽  
Yangsik Kim ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Brain Networks ◽  
Global Organization ◽  
Structural Brain

scholarly journals Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms

2016 ◽  
Author(s):  
Jiahui Wang ◽  
Yudan Ren ◽  
Xintao Hu ◽  
Vinh Thai Nguyen ◽  
Lei Guo ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Visual Processing ◽  
Ecological Validity ◽  
Brain Networks ◽  
Viewing Condition ◽  
Retest Reliability ◽  
Fmri Session ◽  
Test Retest Reliability ◽  
Resting State Connectivity

AbstractFunctional connectivity analysis has become a powerful tool for probing the human brain function and its breakdown in neuropsychiatry disorders. So far, most studies adopted resting state paradigm to examine functional connectivity networks in the brain, thanks to its low demand and high tolerance that are essential for clinical studies. However, the test-retest reliability of resting state connectivity measures is moderate, potentially due to its low behavioral constraint. On the other hand, naturalistic neuroimaging paradigms, an emerging approach for cognitive neuroscience with high ecological validity, could potentially improve the reliability of functional connectivity measures. To test this hypothesis, we characterized the test-retest reliability of functional connectivity measures during a natural viewing condition, and benchmarked it against resting state connectivity measures acquired within the same functional magnetic resonance imaging (fMRI) session. We found that the reliability of connectivity and graph theoretical measures of brain networks is significantly improved during natural viewing conditions over resting state conditions, with an average increase of almost 50% across various connectivity measures. Not only sensory networks for audio-visual processing become more reliable, higher order brain networks, such as default mode and attention networks, also appear to show higher reliability during natural viewing. Our results support the use of natural viewing paradigms in estimating functional connectivity of brain networks, and have important implications for clinical application of fMRI.

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