Dataset Information

Test-retest reliability of graph metrics in high-resolution functional connectomics: a resting-state functional MRI study.

ABSTRACT:

Background

The combination of resting-state functional MRI (R-fMRI) technique and graph theoretical approaches has emerged as a promising tool for characterizing the topological organization of brain networks, that is, functional connectomics. In particular, the construction and analysis of high-resolution brain connectomics at a voxel scale are important because they do not require prior regional parcellations and provide finer spatial information about brain connectivity. However, the test-retest reliability of voxel-based functional connectomics remains largely unclear.

Aims

This study tended to investigate both short-term (?20 min apart) and long-term (6 weeks apart) test-retest (TRT) reliability of graph metrics of voxel-based brain networks.

Methods

Based on graph theoretical approaches, we analyzed R-fMRI data from 53 young healthy adults who completed two scanning sessions (session 1 included two scans 20 min apart; session 2 included one scan that was performed after an interval of ?6 weeks).

Results

The high-resolution networks exhibited prominent small-world and modular properties and included functional hubs mainly located at the default-mode, salience, and executive control systems. Further analysis revealed that test-retest reliabilities of network metrics were sensitive to the scanning orders and intervals, with fair to excellent long-term reliability between Scan 1 and Scan 3 and lower reliability involving Scan 2. In the long-term case (Scan 1 and Scan 3), most network metrics were generally test-retest reliable, with the highest reliability in global metrics in the clustering coefficient and in the nodal metrics in nodal degree and efficiency.

Conclusion

We showed high test-retest reliability for graph properties in the high-resolution functional connectomics, which provides important guidance for choosing reliable network metrics and analysis strategies in future studies.

SUBMITTER: Du HX

PROVIDER: S-EPMC6493187 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Publications

Test-retest reliability of graph metrics in high-resolution functional connectomics: a resting-state functional MRI study.

Du Hai-Xiao HX Liao Xu-Hong XH Lin Qi-Xiang QX Li Gu-Shu GS Chi Yu-Ze YZ Liu Xiang X Yang Hua-Zhong HZ Wang Yu Y Xia Ming-Rui MR

CNS neuroscience & therapeutics 20150727 10

<h4>Background</h4>The combination of resting-state functional MRI (R-fMRI) technique and graph theoretical approaches has emerged as a promising tool for characterizing the topological organization of brain networks, that is, functional connectomics. In particular, the construction and analysis of high-resolution brain connectomics at a voxel scale are important because they do not require prior regional parcellations and provide finer spatial information about brain connectivity. However, the ...[more]

PMID: 26212146

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Project description:Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ?20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (?90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52?0.84; efficiency: 0.50?0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28?0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience.

Project description:The reliability of magnetoencephalography (MEG) resting-state functional connectivity in schizophrenia (SZ) is unknown as previous research has focused on healthy controls (HC). Here, we examined reliability in 26 participants (13-SZ, 13-HC). Eyes opened and eyes closed resting-state data were collected on 4 separate occasions during 2 visits, 1 week apart. For source modeling, we used minimum norm software to apply dynamic statistical parametric mapping. Source analyses compared the following functional connectivity metrics from each data run: coherence (coh), imaginary coherence (imcoh), pairwise phase consistency (ppc), phase-locking value (plv), phase lag index (pli), weighted phase lag index (wpli), and weighted phase lag index debiased (wpli2). Intraclass correlation coefficients (ICCs) were calculated for whole brain, network, and network pair averages. For reliability, ICCs above 0.75 = excellent, above 0.60 = good, above 0.40 = fair, and below 0.40 = poor reliability. We found the reliability of these metrics varied greatly depending on frequency band, network, network pair, and participant group examined. Broadband (1-58 Hz) whole brain averages in both HC and SZ showed excellent reliability for wpli2, and good to fair reliability for ppc, plv, and coh. Broadband network averages showed excellent to good reliability across 1 hour and 1 week for coh, imcoh, ppc, plv, wpli within default mode, cognitive control, and visual networks in HC, while the same metrics had excellent to fair reliability in SZ. Regional network pair averages showed good to fair reliability for coh, ppc, plv within default mode, cognitive control and visual network pairs in HC and SZ. In general, HC had higher reliability compared to SZ, and the default mode, cognitive control, and visual networks had higher reliability compared to somatosensory and auditory networks. Similar reliability levels occurred for both eyes opened and eyes closed resting-states for most metrics. The functional connectivity metrics of coh, ppc, and plv performed best across 1 hour and 1 week in HC and SZ. We also found that SZ had reduced coh, plv, and ppc in the dmn average and pair values indicating dysconnectivity in SZ. These findings encourage collecting both eyes opened and eyes closed resting-state MEG, while demonstrating that clinical populations may differ in reliability.

Project description:Resting-state functional MRI (rs-fMRI) has emerged as a powerful tool for investigating brain functional connectivity (FC). Research in recent years has focused on assessing the reliability of FC across younger subjects within and between scan-sessions. Test-retest reliability in resting-state functional connectivity (RSFC) has not yet been examined in older adults. In this study, we investigated age-related differences in reliability and stability of RSFC across scans. In addition, we examined how global signal regression (GSR) affects RSFC reliability and stability. Three separate resting-state scans from 29 younger adults (18-35 yrs) and 26 older adults (55-85 yrs) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available as part of the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 92 regions of interest (ROIs) with 5 cubic mm radius, derived from the default, cingulo-opercular, fronto-parietal and sensorimotor networks, were previously defined based on a recent study. Mean time series were extracted from each of the 92 ROIs from each scan and three matrices of z-transformed correlation coefficients were created for each subject, which were then used for evaluation of multi-scan reliability and stability. The young group showed higher reliability of RSFC than the old group with GSR (p-value = 0.028) and without GSR (p-value <0.001). Both groups showed a high degree of multi-scan stability of RSFC and no significant differences were found between groups. By comparing the test-retest reliability of RSFC with and without GSR across scans, we found significantly higher proportion of reliable connections in both groups without GSR, but decreased stability. Our results suggest that aging is associated with reduced reliability of RSFC which itself is highly stable within-subject across scans for both groups, and that GSR reduces the overall reliability but increases the stability in both age groups and could potentially alter group differences of RSFC.

Project description:BackgroundFunctional MRI (fMRI) tasks are increasingly being used to advance knowledge of the etiology and maintenance of obesity and eating disorders. Thus, understanding the test-retest reliability of BOLD signal contrasts from these tasks is important.ObjectivesTo evaluate test-retest reliability of responses in reward-related brain regions to food receipt paradigms (palatable tastes, anticipated palatable tastes), food picture paradigms (high-calorie food pictures), a monetary reward paradigm (winning money and anticipating winning money), and a thin female model picture paradigm (thin female model pictures).MethodWe conducted secondary univariate contrast-based analyses in data drawn from 4 repeated-measures fMRI studies. Participants (Study 1: N = 60, mean [M] age = 15.2 ± 1.1 y; Study 2: N = 109, M age = 15.1 ± 0.9 y; Study 3: N = 39, M age = 21.2 ± 3.7 y; Study 4: N = 62, M age = 29.7 ± 6.2 y) completed the same tasks over 3-wk to 3-y test-retest intervals. Studies 3 and 4 included participants with eating disorders and obesity, respectively.ResultsTest-retest reliability of the food receipt and food picture paradigms was poor, with average ICC values ranging from 0.07 to 0.20. The monetary reward paradigm and the thin female model picture paradigm also showed poor test-retest reliability: average ICC values 0.21 and 0.12, respectively. Although several regions demonstrated moderate to good test-retest reliability, these results did not replicate across studies using similar paradigms. In Studies 3 and 4, but not Study 1, test-retest reliability in visual processing regions was moderate to good when contrasting single conditions with a low-level baseline.ConclusionsResults underscore the importance of examining the temporal reliability of fMRI tasks and call for the development and use of well-validated standardized fMRI tasks in eating- and obesity-related studies that can provide more reliable measures of neural activation. The trials were registered at clinicaltrials.gov as NCT02084836, NCT01949636, NCT03261050, and NCT03375853.

Dataset Information

Test-retest reliability of graph metrics in high-resolution functional connectomics: a resting-state functional MRI study.

Background

Aims

Methods

Results

Conclusion

Publications

Test-retest reliability of graph metrics in high-resolution functional connectomics: a resting-state functional MRI study.

Similar Datasets

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