Variability and reliability of effective connectivity within the core default mode network: A longitudinal spectral DCM study
Hannes Almgren, Frederik van de Steen, Simone Kühn, Adeel Razi, Karl Friston, Daniele Marinazzo
Study at a glance
AI-extracted from the abstract| Characteristics | Observational longitudinal neuroimaging study |
|---|---|
| Sample size | 20 |
| Population | Human participants with longitudinal resting-state fMRI data across four datasets |
| Topics | Default mode network |
| Key findings | Effective connectivity estimates from spectral DCM were reliable within subjects and similar between subjects once systematic hemispheric asymmetry was taken into account. Processing choices such as global signal regression and ROI size had little effect on inference or reliability for most subjects, and Bayesian model reduction increased within-subject reliability and between-subject stability. |
Abstract
Abstract: Dynamic causal modelling (DCM) for resting state fMRI – namely spectral DCM – is a recently developed and widely adopted method for inferring effective connectivity in intrinsic brain networks. Most research applying spectral DCM has focused on group-averaged connectivity within large-scale intrinsic brain networks; however, the consistency of subject- and session-specific estimates of effective connectivity has not been evaluated. Establishing reliability (within subjects) is crucial for its clinical use; e.g., as a neurophysiological phenotype of disease progression. Effective connectivity during rest is likely to vary due to changes in cognitive, behavioural, and physical states. Determining the sources of fluctuations in effective connectivity may yield greater understanding of brain processes and inform clinical applications about potential confounds. In the present study, we investigated the consistency of effective connectivity within and between subjects, as well as potential sources of variability (e.g., hemispheric asymmetry). We further investigated how standard procedures for data processing and signal extraction affect this consistency. DCM analyses were applied to four longitudinal resting state fMRI datasets. Our sample consisted of 20 subjects with 653 resting state fMRI sessions in total. These data allowed to quantify the robustness of connectivity estimates for each subject, and to draw conclusions beyond specific data features. We found that subjects contributing to all datasets showed systematic and reliable patterns of hemispheric asymmetry. When asymmetry was taken into account, subjects showed very similar connectivity patterns. We also found that various processing procedures (e.g. global signal regression and ROI size) had little effect on inference and reliability of connectivity for the majority of subjects. Bayesian model reduction increased reliability (within-subjects) and stability (between-subjects) of connectivity patterns.
Comparable studies
Other experimental studies on default mode network, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Functional connectivity of default mode network components: Correlation, anticorrelation, and causality Healthy subjects | 2008 | Observational study using resting-state fMRI and seed correlation analysis | |
| Patterns of Brain Activity Supporting Autobiographical Memory, Prospection, and Theory of Mind, and Their Relationship to the Default Mode Network Healthy subjects | 2009 | Experimental study using fMRI | |
| Dynamic reconfiguration of the default mode network during narrative comprehension Human subjects | 2016 | Experimental study | |
| Broadband Cortical Desynchronization Underlies the Human Psychedelic State Healthy human participants | 2013 | Experimental study | |
| The brain on art: intense aesthetic experience activates the default mode network Human observers | 2012 | Observational study with fMRI and behavioral analysis |