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

Andellini, Martina; Cannatà, Vittorio; Gazzellini, Simone; Bernardi, Bruno; Napolitano, Antonio

doi:10.1016/j.jneumeth.2015.05.020

Cited by 117 publications

(116 citation statements)

References 66 publications

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“…The reliability of network definitions and other network measures has also been investigated: previous work has demonstrated good reproducibility of functional parcellation (Laumann et al, 2015), moderate to high reliability of resting brain network boundaries across techniques (Jann et al, 2015), moderate to high reliability of network membership (Zuo et al, 2010), and low to moderate reliability for network-theory metrics of functional connectivity (Braun et al, 2012; Wang et al, 2011 cf. Andellini et al, 2015; Telesford et al, 2010). In contrast, reliability of anatomical measurements via structural MRI is quite high (Cannon et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Multisite reliability of MR-based functional connectivity

et al. 2017

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Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies are an efficient way to speed up data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60–80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i.e., subject, site, and day-of-scan). Thus, for a single 5 min scan, reliability across connectivity measures was poor (ICC=0.07–0.17), but increases with increasing scan duration (ICC=0.21–0.36 at 25 min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.

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Section: Discussionmentioning

confidence: 99%

Multisite reliability of MR-based functional connectivity

et al. 2017

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“…We focused on two graph metrics that have been shown to be reliable: degree centrality and clustering coefficient (Braun et al, 2012; Guo et al, 2012; Andellini et al, 2015; Du et al, 2015; Wang et al, 2017). These graph metrics were derived from the weighted adjacency matrices using Brain Connectivity Toolbox (Rubinov et al, 2009).…”

Section: Methodsmentioning

confidence: 99%

Improving the Test-Retest Reliability of Resting State fMRI by Removing the Impact of Sleep

et al. 2017

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Resting state functional magnetic resonance imaging (rs-fMRI) provides a powerful tool to examine large-scale neural networks in the human brain and their disturbances in neuropsychiatric disorders. Thanks to its low demand and high tolerance, resting state paradigms can be easily acquired from clinical population. However, due to the unconstrained nature, resting state paradigm is associated with excessive head movement and proneness to sleep. Consequently, the test-retest reliability of rs-fMRI measures is moderate at best, falling short of widespread use in the clinic. Here, we characterized the effect of sleep on the test-retest reliability of rs-fMRI. Using measures of heart rate variability (HRV) derived from simultaneous electrocardiogram (ECG) recording, we identified portions of fMRI data when subjects were more alert or sleepy, and examined their effects on the test-retest reliability of functional connectivity measures. When volumes of sleep were excluded, the reliability of rs-fMRI is significantly improved, and the improvement appears to be general across brain networks. The amount of improvement is robust with the removal of as much as 60% volumes of sleepiness. Therefore, test-retest reliability of rs-fMRI is affected by sleep and could be improved by excluding volumes of sleepiness as indexed by HRV. Our results suggest a novel and practical method to improve test-retest reliability of rs-fMRI measures.

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“…The full cerebellum was properly scanned in the acquisition field of view. To improve test-retest reliability, no global signal regression was conducted68; no spatial smoothing was applied, in order to avoid adding spurious correlations between adjacent voxels34. Mean BOLD time series were extracted from the 116 regions of interest (ROIs) in the standard Automatic Anatomical Labeling (AAL) atlas, which comprises 90 cerebral and 26 cerebellar regions47.…”

Section: Methodsmentioning

confidence: 99%

Environmental factors linked to depression vulnerability are associated with altered cerebellar resting-state synchronization

Córdova‐Palomera

Tornador

Falcón

et al. 2016

Sci Rep

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Hosting nearly eighty percent of all human neurons, the cerebellum is functionally connected to large regions of the brain. Accumulating data suggest that some cerebellar resting-state alterations may constitute a key candidate mechanism for depressive psychopathology. While there is some evidence linking cerebellar function and depression, two topics remain largely unexplored. First, the genetic or environmental roots of this putative association have not been elicited. Secondly, while different mathematical representations of resting-state fMRI patterns can embed diverse information of relevance for health and disease, many of them have not been studied in detail regarding the cerebellum and depression. Here, high-resolution fMRI scans were examined to estimate functional connectivity patterns across twenty-six cerebellar regions in a sample of 48 identical twins (24 pairs) informative for depression liability. A network-based statistic approach was employed to analyze cerebellar functional networks built using three methods: the conventional approach of filtered BOLD fMRI time-series, and two analytic components of this oscillatory activity (amplitude envelope and instantaneous phase). The findings indicate that some environmental factors may lead to depression vulnerability through alterations of the neural oscillatory activity of the cerebellum during resting-state. These effects may be observed particularly when exploring the amplitude envelope of fMRI oscillations.

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

Cited by 117 publications

References 66 publications

Multisite reliability of MR-based functional connectivity

Multisite reliability of MR-based functional connectivity

Improving the Test-Retest Reliability of Resting State fMRI by Removing the Impact of Sleep

Environmental factors linked to depression vulnerability are associated with altered cerebellar resting-state synchronization

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