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Investigating the Intersession Reliability of Dynamic Brain-State Properties
Derek M Smith1, Yrian Zhao2, Shella D Keilholz2
11 School of Psychology, Georgia Institute of Technology , Atlanta, Georgia .
Brain Connectivity
|June 21, 2018
Summary
Reliability of dynamic functional connectivity in the brain was assessed using resting-state fMRI. Brain state patterns showed good test-retest reliability, suggesting promise for individual differences research.
Area of Science:
- Neuroscience
- Cognitive Science
- Neuroimaging
Background:
- Dynamic functional connectivity (dFC) offers insights into individual differences in cognition.
- Research on the reliability of dFC measures is limited.
- Understanding dFC reliability is crucial for advancing cognitive neuroscience.
Purpose of the Study:
- To assess the test-retest reliability of dynamic functional connectivity metrics.
- To investigate the impact of global signal regression (GSR) on dFC reliability.
- To explore changes in brain states over the course of a scan.
Main Methods:
- Resting-state fMRI data from 100 Human Connectome Project subjects were analyzed across two scan days.
- Brain states were identified using k-means clustering on time frames, with and without global signal regression (GSR).
- Multiple reliability metrics were employed to evaluate consistency.
Main Results:
- Dynamic functional connectivity measures demonstrated adequate test-retest reliability across scan days.
- Global signal regression (GSR) was found to attenuate the reliability of brain states.
- Changes in brain state properties over time were also investigated.
Conclusions:
- Summary metrics of brain state clustering exhibit sufficient reliability for individual-difference research.
- Dynamic functional connectivity patterns hold potential for understanding cognitive variations.
- The findings underscore the importance of considering GSR's impact on dFC reliability.
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