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Reliability modelling of resting-state functional connectivity.

Jalmar Teeuw1, Hilleke E Hulshoff Pol1, Dorret I Boomsma2

  • 1Brain Center Rudolf Magnus and Department of Psychiatry, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, Netherlands.

Neuroimage
|February 13, 2021
PubMed
Summary
This summary is machine-generated.

Improving resting-state fMRI (rs-fMRI) functional connectivity (FC) reliability using a measurement model enhances trait associations and heritability estimates. This method extracts a stable FC component, crucial for accurate genetic and behavioral studies.

Keywords:
Functional connectivityHuman connectome projectMeasurement errorMeasurement modelReliability modellingTest-retest reliability

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Area of Science:

  • Neuroimaging
  • Psychometrics
  • Behavioral Genetics

Background:

  • Resting-state functional magnetic resonance imaging (rs-fMRI) suffers from low signal-to-noise ratio, impacting functional connectivity (FC) reliability and associated trait/heritability estimates.
  • Measurement error in FC attenuates its true association with behavioral and genetic factors.

Purpose of the Study:

  • To assess the benefits of a measurement model applied to split-half rs-fMRI data for improving FC reliability.
  • To evaluate the impact of this reliability modeling on FC associations with various traits and heritability estimates.
  • To examine the efficiency of the model across different sample sizes and scan durations.

Main Methods:

  • Applied a classical test theory-based measurement model to split-half FC estimates from 1003 Human Connectome Project (HCP) participants.
  • Evaluated improvements in test-retest reliability, trait association strength, and heritability estimates.
  • Replicated findings in a longitudinal adolescent twin cohort.

Main Results:

  • The split-half measurement model significantly improved FC test-retest reliability (average increase of +0.33 points).
  • Associations between FC and traits strengthened by an average of 1.2-fold.
  • Heritability estimates increased by an average of +20% points (from 39% to 59%).
  • Approximately half of the variance in split-session FC estimates represented a stable, reliable component.

Conclusions:

  • Reliability modeling using a split-half measurement approach extracts a stable FC component, mitigating random measurement error.
  • This method enhances the accuracy of genetic and behavioral studies utilizing rs-fMRI data.
  • The benefits are particularly pronounced for shorter scan durations and smaller sample sizes.