Reproducibility and Temporal Structure in Weekly Resting-State fMRI over a Period of 3.5 Years

PLOS ONE, 2015 · DOI: 10.1371/journal.pone.0140134 · Published: October 30, 2015

Simple Explanation

This study examines brain activity using resting-state functional MRI (rs-fMRI), a technique that measures brain networks without requiring specific tasks. It aims to assess how consistent these brain network measurements are over a long period. The research involves a unique dataset where a healthy adult was scanned weekly for 3.5 years. The consistency and patterns of brain network activity were analyzed to see if rs-fMRI could be a reliable tool for monitoring long-term health or treatment effects. The study found that certain brain network measures are highly reproducible, particularly in executive function networks. However, there are also temporal patterns like annual variations that need to be considered when using rs-fMRI for long-term monitoring.

Study Duration

3.5 Years

Participants

One healthy adult subject scanned weekly plus a 21-person dataset

Evidence Level

Not specified

Key Findings

1
Resting-state functional MRI (rs-fMRI) outcome measures, specifically network spatial maps, temporal signal fluctuation magnitude, and between-network connectivity (BNC), showed high inter-session reproducibility.
2
Executive RSNs exhibited the highest reproducibility compared to other networks.
3
Many rs-fMRI outcome measures demonstrated a significant linear trend, annual periodicity, and persistence over time.

Research Summary

This study presents a unique longitudinal dataset of weekly rs-fMRI scans over 3.5 years to assess the reproducibility and temporal structure of rs-fMRI outcome measures. The research identifies 14 RSNs and finds that spatial map similarity, temporal signal fluctuation magnitude, and between-network connectivity show high reproducibility, especially in executive RSNs. Time series analysis reveals significant linear trends, annual periodicity, and persistence in the RSN outcome measures, suggesting that these temporal structures should be considered when using rs-fMRI as a biomarker in long-term clinical trials.

Practical Implications

Biomarker Potential

High reproducibility of rs-fMRI outcome measures supports their candidacy as biomarkers for monitoring clinical trials and therapeutic interventions.

Temporal Structure Considerations

Significant temporal structure in rs-fMRI outcome measures (linear trend, annual periodicity, persistence) should be accounted for when using these measures as biomarkers.

Executive Network Focus

The high reproducibility of executive RSNs suggests they may be particularly useful as biomarkers in diseases affecting executive functions, such as substance abuse and Alzheimer's disease.

Study Limitations

1
The study is limited by the fact that only one subject underwent weekly scanning for 185 weeks.
2
The report only focuses on outcome measures derived using group ICA (GICA).
3
Additional physiological or psychological measures were not obtained during the acquisition of this dataset.

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