Reliability of Magnetoencephalography and High-Density Electroencephalography Resting-State Functional Connectivity Metrics

Marquetand, Justus; Vannoni, Silvia; Carboni, Margherita; Hegner, Yiwen Li; Stier, Christina; Braun, Christoph; Focke, Niels K.

doi:10.1089/brain.2019.0662

Cited by 38 publications

(56 citation statements)

References 34 publications

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“…However, in contrast to the previous paper, we found that pli had excellent reliability in beta, gamma, and broadband across 1 week. Another previous study examining MEG global whole brain reliability found that coh and wpli had good to excellent reliability in delta-gamma bands (4). In contrast to this, the present study found that imcoh and wpli generally had poor reliability in all frequencies with a few exceptions, such as fair to good reliability for imcoh during an eyes closed state in beta, gamma, and broadband and fair to excellent reliability for wpli across 1 week.…”

Section: Discussioncontrasting

confidence: 99%

“…For example, the reliability of phase-locking value (plv) in alpha, beta, and gamma bands average between ICCs = 0.74-0.82, but dip to ICCs < 0.1 when phase-lag index (pli) is used (2). Conversely, other studies have reported weighted phase-lag index (wpli) and the imaginary part of coherency had excellent to good reliability of global connectivity over 30 trials in alpha and theta bands, but often fair to poor reliability in other frequency bands and in vertex-based connectivity (4). It is clear given the variability of previous MEG functional connectivity findings that more research is needed to reach a consensus on which functional connectivity metric is best suited for MEG resting-state studies.…”

Section: Introductionmentioning

confidence: 90%

“…Previous resting-state MEG test-retest reliability has been evaluated in healthy controls (HC) (1)(2)(3)(4)(5), patients with depression (6), and patients with SZ (5). Most test-retest studies use intraclass correlation coefficients (ICCs) or Spearman correlations to report and categorize degree of reliability.…”

Section: Introductionmentioning

confidence: 99%

“…In HC, MEG spectral power has good reliability in theta, alpha, and beta bands (ICCs > 0.6) over a 7 day testretest interval (3) and excellent reliability in theta-gamma bands (ICCs > 0.86) in global and regional spectral measures over both 1 hour and 1 week test-retest intervals (5). The reliability of MEG functional connectivity has varied greatly in HC depending on the connectivity metric used (1,2,5) and frequency band studied (4). For example, the reliability of phase-locking value (plv) in alpha, beta, and gamma bands average between ICCs = 0.74-0.82, but dip to ICCs < 0.1 when phase-lag index (pli) is used (2).…”

Section: Introductionmentioning

confidence: 99%

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Test–Retest Reliability of Magnetoencephalography Resting-State Functional Connectivity in Schizophrenia

Candelaria‐Cook

Stephen

2020

Front. Psychiatry

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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.

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Section: Discussioncontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Test–Retest Reliability of Magnetoencephalography Resting-State Functional Connectivity in Schizophrenia

Candelaria‐Cook

Stephen

2020

Front. Psychiatry

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“…This pattern of increased reliability for first-order graph metrics compared to second-order metrics may arise from differences in variances in connectivity matrices where second-order graph theory metrics are more sensitive to variability in the connectivity matrices than first-order graph theory metrics 35 . Furthermore, it is possible that graph theory metrics cannot be reliably measured within these data segments, and more data (longer than 2 min in total) is needed to reliably measure graph metrics 42,80 .…”

Section: Reliability Of Network Characteristics Across a Constant Amomentioning

confidence: 99%

Using multiple short epochs optimises the stability of infant EEG connectivity parameters

Haartsen

Velde

Jones

et al. 2020

Sci Rep

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Atypicalities in connectivity between brain regions have been implicated in a range of neurocognitive disorders. We require metrics to assess stable individual differences in connectivity in the developing brain, while facing the challenge of limited data quality and quantity. Here, we examine how varying core processing parameters can optimise the test-retest reliability of eeG connectivity measures in infants. EEG was recorded twice with a 1-week interval between sessions in 10-month-olds. EEG alpha connectivity was measured across different epoch lengths and numbers, with the phase lag index (PLI) and debiased weighted PLI (dbWPLI), for both whole-head connectivity and graph theory metrics. We calculated intra-class correlations between sessions for infants with sufficient data for both sessions (N's = 19-41, depending on the segmentation method). Reliability for the whole brain dbWPLI was higher across many short epochs, whereas reliability for the whole brain PLI was higher across fewer long epochs. However, the PLI is confounded by the number of available segments. Reliability was higher for whole brain connectivity than graph theory metrics. thus, segmenting available data into a high number of short epochs and calculating the dbWPLI is most appropriate for characterising connectivity in populations with limited availability of eeG data.

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The effects of spatial leakage correction on the reliability ofEEG‐based functional connectivity networks

Nagy,

Tóth,

Winkler

et al. 2024

Human Brain Mapping

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Electroencephalography (EEG) functional connectivity (FC) estimates are confounded by the volume conduction problem. This effect can be greatly reduced by applying FC measures insensitive to instantaneous, zero‐lag dependencies (corrected measures). However, numerous studies showed that FC measures sensitive to volume conduction (uncorrected measures) exhibit higher reliability and higher subject‐level identifiability. We tested how source reconstruction contributed to the reliability difference of EEG FC measures on a large (n = 201) resting‐state data set testing eight FC measures (including corrected and uncorrected measures). We showed that the high reliability of uncorrected FC measures in resting state partly stems from source reconstruction: idiosyncratic noise patterns define a baseline resting‐state functional network that explains a significant portion of the reliability of uncorrected FC measures. This effect remained valid for template head model‐based, as well as individual head model‐based source reconstruction. Based on our findings we made suggestions how to best use spatial leakage corrected and uncorrected FC measures depending on the main goals of the study.

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Reliability of Magnetoencephalography and High-Density Electroencephalography Resting-State Functional Connectivity Metrics

Cited by 38 publications

References 34 publications

Test–Retest Reliability of Magnetoencephalography Resting-State Functional Connectivity in Schizophrenia

Test–Retest Reliability of Magnetoencephalography Resting-State Functional Connectivity in Schizophrenia

Using multiple short epochs optimises the stability of infant EEG connectivity parameters

The effects of spatial leakage correction on the reliability ofEEG‐based functional connectivity networks

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