Test-retest reliability of dynamic functional connectivity parameters for a two-state model.
Xiaojing Fang1, Michael Marxen1
1Department of Psychiatry, Technische Universität Dresden, Dresden, Germany.
Network Neuroscience (Cambridge, Mass.)
|March 31, 2025
Summary
Investigating dynamic functional connectivity (dFC) reliability revealed that state prevalence is the most stable parameter across sessions. Shorter scans and within-subject centering decrease reliability, impacting brain connectivity analyses.
Area of Science:
- Neuroscience
- Brain Imaging
- Network Science
Background:
- Reliability of neuroimaging parameters is crucial for accurate correlation analyses.
- Dynamic functional connectivity (dFC) offers insights into brain function over time.
- Understanding the stability of dFC measures is essential for robust research findings.
Purpose of the Study:
- To assess the test-retest reliability of dynamic functional connectivity (dFC) brain states and associated parameters.
- To evaluate the impact of scan length, atlas size, and data centering on dFC reliability.
- To identify the most reliable dFC parameters for future research, particularly in correlational studies.
Main Methods:
- Investigated test-retest reliability of two dFC brain states in 23 participants, replicated in 501 subjects (Human Connectome Project).
- Examined variations in reliability based on scan duration, atlas resolution (116 vs. 442 regions), and data centering techniques.
- Calculated intraclass correlation coefficients (ICCs) to quantify the reliability of dFC states and parameters.
Main Results:
- Identified two distinct dFC states (integrated and segregated) with high inter-session reliability (ICC ≥ 0.67).
- State prevalence demonstrated the highest reliability (ICC ≈ 0.5) for approximately 15 minutes of uncentered data.
- Shorter scan durations and within-subject data centering significantly reduced parameter reliability, while atlas choice had no discernible effect.
Conclusions:
- State prevalence is recommended as the most reliable dFC parameter for cross-sectional studies and correlational analyses with other subject-specific measures.
- Findings underscore the importance of considering scan length and data centering when interpreting dFC results.
- The study provides practical recommendations for optimizing the reliability of dFC measures in neuroscience research.
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