Impact of sample size and regression of tissue‐specific signals on effective connectivity within the core default mode network
Alexander N. Silchenko, Felix Hoffstaedter, Simon Bodo Eickhoff
Human Brain Mapping September 15, 2023 DOI: 10.1002/hbm.26481 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational neuroimaging study Peer reviewed |
|---|---|
| Sample size | 330 |
| Population | Unrelated Human Connectome Project participants with resting-state fMRI data |
| Topics | Default mode network |
| Citations | 5 |
| Key findings | The stability of spectral DCM model selection and connectivity parameter inference depends strongly on sample size, with approximately 50 subjects as the minimum for stable estimates. A stable effective connectivity pattern within the core default mode network emerges at large sample sizes, and subject-specific thresholded whole-brain masks for tissue-specific signal regression enhance detection of weak connections. |
Abstract
Interactions within brain networks are inherently directional, which are inaccessible to classical functional connectivity estimates from resting-state functional magnetic resonance imaging (fMRI) but can be detected using spectral dynamic causal modeling (DCM). The sample size and unavoidable presence of nuisance signals during fMRI measurement are the two important factors influencing the stability of group estimates of connectivity parameters. However, most recent studies exploring effective connectivity (EC) have been conducted with small sample sizes and minimally pre-processed datasets. We explore the impact of these two factors by analyzing clean resting-state fMRI data from 330 unrelated subjects from the Human Connectome Project database. We demonstrate that both the stability of the model selection procedures and the inference of connectivity parameters are highly dependent on the sample size. The minimum sample size required for stable DCM is approximately 50, which may explain the variability of the DCM results reported so far. We reveal a stable pattern of EC within the core default mode network computed for large sample sizes and demonstrate that the use of subject-specific thresholded whole-brain masks for tissue-specific signals regression enhances the detection of weak connections.
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 |
Citations in the library
Cites 6
- The Brain's Default Mode Network Annual Review of Neuroscience May 4, 2015
- The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis Neuroimage June 13, 2008
- The Default Mode Network in Healthy Individuals: A Systematic Review and Meta-Analysis Brain Connectivity December 5, 2016
- Variability and reliability of effective connectivity within the core default mode network: A multi-site longitudinal spectral DCM study. Neuroimage December 2018
- Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data Frontiers in Human Neuroscience February 1, 2016
and 1 more in the library