Phase- and amplitude-coupling are tied by an intrinsic spatial organization but show divergent stimulus-related changes

Mostame, Parham; Sadaghiani, Sepideh

doi:10.1016/j.neuroimage.2020.117051

Cited by 24 publications

(29 citation statements)

References 71 publications

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“…Further work is needed to better understand the contribution of veridic neuronal connectivity at zero lag (Engel et al, 1991) that is suppressed by either using orthogonalization or iCoh. As the magnitude of the crossmodal correlation of iCoh lies between the values for orthogonalized and non-orthognalized AEC, we conclude that our results provide further evidence for the overall concordance of amplitude-based and phase-based static connectivity during resting-state (Mostame and Sadaghiani, 2020; Sadaghiani and Wirsich, 2020). Beyond the measurement of undirected connectivity, EEG has been shown to be able to extract the directional connectivity of ICN organization (Coito et al, 2019).…”

Section: Discussionsupporting

confidence: 68%

“…It has been argued that phase coupling might be closer to the underlying SC dMRI and amplitude coupling is proposed to be more related to FC fMRI (Engel et al, 2013). Nevertheless, most of the literature suggests a rather similar connectivity pattern of intrinsic brain activity on the whole brain scale when averaging over resting-state recordings lasting several minutes (Colclough et al, 2016; Mostame and Sadaghiani, 2020; Sadaghiani and Wirsich, 2020). Siems and Siegel (2020) observed highly correlated, but not identical connectivity between both types of measures, and the neurobiological interpretation of those differences have yet to be explored.…”

Section: Introductionmentioning

confidence: 99%

“…Siems and Siegel (2020) observed highly correlated, but not identical connectivity between both types of measures, and the neurobiological interpretation of those differences have yet to be explored. Recently those changes have been linked to task-specific connectivity (Mostame and Sadaghiani, 2020), but ultimately the relevance of different connectivity measures for brain behavior and pathology is still an open question.…”

Section: Introductionmentioning

confidence: 99%

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The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T

Wirsich

Jorge

Iannotti

et al. 2020

Preprint

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Both electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite their differences in probing brain activity, both electrophysiology and BOLD signal can map the underlying functional connectivity structure at the whole brain scale at different timescales. Previous work demonstrated a moderate but significant correlation between resting-state functional connectivity of both modalities, however there is a wide range of technical setups to measure simultaneous EEG-fMRI and the reliability of those measures between different setups remains unknown. This is true notably with respect to different magnetic field strengths (low and high field) and different spatial sampling of EEG (medium to high-density electrode coverage).Here, we investigated the reliability of the bimodal EEG-fMRI functional connectome in the most comprehensive resting-state simultaneous EEG-fMRI dataset compiled to date including a total of 72 subjects from four different imaging centers. Data was acquired from 1.5T, 3T and 7T scanners with simultaneously recorded EEG using 64 or 256 electrodes. We demonstrate that the whole-brain monomodal connectivity reliably correlates across different datasets and that the crossmodal correlation between EEG and fMRI connectivity of r≈0.3 can be reliably extracted in low and high-field scanners. The crossmodal correlation was strongest in the EEG-β frequency band but exists across all frequency bands. Both homotopic and withing intrinsic connectivity network (ICN) connections contributed the most to the crossmodal relationship.This study confirms, using a considerably diverse range of recording setups, that simultaneous EEG-fMRI offers a consistent estimate of multimodal functional connectomes in healthy subjects being organized into reliable ICNs across different timescales. This opens new avenues for estimating the dynamics of brain function and provides a better understanding of interactions between EEG and fMRI measures. Alterations of this coupling could be explored as a potential clinical marker of pathological brain function.

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Section: Discussionsupporting

confidence: 68%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T

Wirsich

Jorge

Iannotti

et al. 2020

Preprint

Self Cite

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“…In contrast to task-based phase coupling, commonly estimated as phase-lag consistency over trials (Lachaux et al 1999), continuous phase coupling was estimated as phase-lag consistency over time (Mostame and Sadaghiani 2020;Sadaghiani et al 2012). The above-defined PLV measure adjusted to continuous data is defined as:…”

Section: Dynamic Functional Connectivitymentioning

confidence: 99%

“…Palva and Palva 2007;Sadaghiani and Kleinschmidt 2016) and language processing (Rimmele et al 2018). Oscillation-based FC can be conceptualized in terms of two major modes (Engel et al 2013;Mostame and Sadaghiani 2020): (1) phase coupling denoting synchronization of the phase of neural activity of distinct brain regions over multiple consecutive oscillation cycles (Lachaux et al 1999;Nolte et al 2004), and (2) amplitude coupling denoting synchronization of the magnitude of neural oscillations between regions (Brookes et al 2011). These FC modes have traditionally been evaluated across a small set of brain regions, and temporally confined to relatively brief task-related processes (Singer, 1999;Uhlhaas et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Oscillation-based connectivity architecture is dominated by an intrinsic spatial organization, not cognitive state or frequency

Mostame

Sadaghiani

2020

Preprint

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Functional connectivity (FC) of neural oscillations (~1-150Hz) is thought to facilitate neural information exchange across brain areas by forming malleable neural ensembles in the service of cognitive processes. However, neural oscillations and their FC are not restricted to certain cognitive demands and continuously unfold in all cognitive states. To what degree is the spatial organization of oscillation-based FC affected by cognitive state or governed by an intrinsic architecture? And what is the impact of oscillation frequency and FC mode (phase-versus amplitude coupling)? Using ECoG recordings of 18 presurgical patients, we quantified the state-dependency of oscillation-based FC in five canonical frequency bands and across an array of 6 task states. For both phase- and amplitude coupling, static FC analysis revealed a spatially largely state-invariant (i.e. intrinsic) component in all frequency bands. Further, the observed intrinsic FC pattern was spatially similar across all frequency bands. However, temporally independent FC dynamics in each frequency band allow for frequency-specific malleability in information exchange. In conclusion, the spatial organization of oscillation-based FC is largely stable over cognitive states, i.e. primarily intrinsic in nature, and shared across frequency bands. The state-invariance is in line with prior findings at the other temporal extreme of brain activity, the infraslow range (~<0.1Hz) observed in fMRI. Our observations have implications for conceptual frameworks of oscillation-based FC and the analysis of task-related FC changes.

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How Can iEEG Be Used to Study Inter-Individual and Developmental Differences?

Johnson

Knight

2023

Studies in Neuroscience, Psychology and Behavioral Economics

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Phase- and amplitude-coupling are tied by an intrinsic spatial organization but show divergent stimulus-related changes

Cited by 24 publications

References 71 publications

The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T

The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T

Oscillation-based connectivity architecture is dominated by an intrinsic spatial organization, not cognitive state or frequency

How Can iEEG Be Used to Study Inter-Individual and Developmental Differences?

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