Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED)

  1. Andreas M Brandmaier  Is a corresponding author
  2. Elisabeth Wenger
  3. Nils C Bodammer
  4. Simone Kühn
  5. Naftali Raz
  6. Ulman Lindenberger
  1. Max Planck Institute for Human Development, Germany
  2. University Clinic Hamburg-Eppendorf, Germany

Abstract

Magnetic resonance imaging has become an indispensable tool for studying associations between structural and functional properties of the brain and behavior in humans. However, generally recognized standards for assessing and reporting the reliability of these techniques are still lacking. Here, we introduce a new approach for assessing and reporting reliability, termed intra-class effect decomposition (ICED). ICED uses structural equation modeling of data from a repeated-measures design to decompose reliability into orthogonal sources of measurement error that are associated with different characteristics of the measurements, for example, session, day, or scanning site. This allows researchers to describe the magnitude of different error components, make inferences about error sources, and inform them in planning future studies. We apply ICED to published measurements of myelin content and resting state functional connectivity. These examples illustrate how longitudinal data can be leveraged separately or conjointly with cross-sectional data to obtain more precise estimates of reliability.

Data availability

The dataset on myelin water fraction measurements is freely available at https://osf.io/t68my/ and the link-wise resting state functional connectivity data is available at https://osf.io/8n24x/.

The following previously published data sets were used
    1. Arshad M
    2. Stanley J A
    3. Raz
    4. N
    (2018) Reliability of Myelin Water Fraction in ALIC
    Publicly available at Open Science Framework.

Article and author information

Author details

  1. Andreas M Brandmaier

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    For correspondence
    brandmaier@mpib-berlin.mpg.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8765-6982
  2. Elisabeth Wenger

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Nils C Bodammer

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Simone Kühn

    Clinic and Policlinic for Psychiatry and Psychotherapy, University Clinic Hamburg-Eppendorf, Hamburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Naftali Raz

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Ulman Lindenberger

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (R01-AG011230)

  • Naftali Raz

Horizon 2020 Framework Programme (732592)

  • Andreas M Brandmaier
  • Simone Kühn
  • Ulman Lindenberger

Max-Planck-Gesellschaft (Open-access funding)

  • Andreas M Brandmaier
  • Elisabeth Wenger
  • Nils C Bodammer
  • Naftali Raz
  • Ulman Lindenberger

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Heidi Johansen-Berg, University of Oxford, United Kingdom

Publication history

  1. Received: February 6, 2018
  2. Accepted: July 1, 2018
  3. Accepted Manuscript published: July 2, 2018 (version 1)
  4. Version of Record published: July 13, 2018 (version 2)

Copyright

© 2018, Brandmaier et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,038
    Page views
  • 239
    Downloads
  • 29
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Andreas M Brandmaier
  2. Elisabeth Wenger
  3. Nils C Bodammer
  4. Simone Kühn
  5. Naftali Raz
  6. Ulman Lindenberger
(2018)
Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED)
eLife 7:e35718.
https://doi.org/10.7554/eLife.35718

Further reading

    1. Neuroscience
    Yonatan Sanz Perl, Sol Fittipaldi ... Enzo Tagliazucchi
    Research Article

    The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of reproducing whole-brain functional connectivity in patients diagnosed with Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD- and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neurodegeneration.

    1. Neuroscience
    Andrea Alamia, Lucie Terral ... Rufin VanRullen
    Research Article Updated

    Previous research has associated alpha-band [8–12 Hz] oscillations with inhibitory functions: for instance, several studies showed that visual attention increases alpha-band power in the hemisphere ipsilateral to the attended location. However, other studies demonstrated that alpha oscillations positively correlate with visual perception, hinting at different processes underlying their dynamics. Here, using an approach based on traveling waves, we demonstrate that there are two functionally distinct alpha-band oscillations propagating in different directions. We analyzed EEG recordings from three datasets of human participants performing a covert visual attention task (one new dataset with N = 16, two previously published datasets with N = 16 and N = 31). Participants were instructed to detect a brief target by covertly attending to the screen’s left or right side. Our analysis reveals two distinct processes: allocating attention to one hemifield increases top-down alpha-band waves propagating from frontal to occipital regions ipsilateral to the attended location, both with and without visual stimulation. These top-down oscillatory waves correlate positively with alpha-band power in frontal and occipital regions. Yet, different alpha-band waves propagate from occipital to frontal regions and contralateral to the attended location. Crucially, these forward waves were present only during visual stimulation, suggesting a separate mechanism related to visual processing. Together, these results reveal two distinct processes reflected by different propagation directions, demonstrating the importance of considering oscillations as traveling waves when characterizing their functional role.