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A seed-based cross-modal comparison of brain connectivity measures

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Abstract

Human neuroimaging methods have provided a number of means by which the connectivity structure of the human brain can be inferred. For instance, correlations in blood-oxygen-level-dependent (BOLD) signal time series are commonly used to make inferences about “functional connectivity.” Correlations across samples in structural morphometric measures, such as voxel-based morphometry (VBM) or cortical thickness (CT), have also been used to estimate connectivity, putatively through mutually trophic effects on connected brain areas. In this study, we have compared seed-based connectivity estimates obtained from four common correlational approaches: resting-state functional connectivity (RS-fMRI), meta-analytic connectivity modeling (MACM), VBM correlations, and CT correlations. We found that the two functional approaches (RS-fMRI and MACM) had the best agreement. While the two structural approaches (CT and VBM) had better-than-random convergence, they were no more similar to each other than to the functional approaches. The degree of correspondence between modalities varied considerably across seed regions, and also depended on the threshold applied to the connectivity distribution. These results demonstrate some degrees of similarity between connectivity inferred from structural and functional covariances, particularly for the most robust functionally connected regions (e.g., the default mode network). However, they also caution that these measures likely capture very different aspects of brain structure and function.

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Authors and Affiliations

  1. Institute for Neuroscience and Medicine (INM-1), Jülich Research Center, Wilhelm-Johnen-Straße, 52428, Jülich, Germany

    Andrew T. Reid, Felix Hoffstaedter, Katrin Amunts & Simon B. Eickhoff

  2. Department of Clinical Neuroscience and Medicine, Heinrich Heine University, Düsseldorf, Germany

    Felix Hoffstaedter & Simon B. Eickhoff

  3. School of Brain and Cognitive Sciences, National Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China

    Gaolang Gong

  4. Department of Physics, Florida International University, Miami, FL, USA

    Angela R. Laird

  5. University of Texas Health Sciences Center at San Antonio, San Antonio, TX, USA

    Peter Fox

  6. South Texas Veterans Health Care System, San Antonio, TX, USA

    Peter Fox

  7. McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Canada

    Alan C. Evans

  8. C. & O. Vogt Institute for Brain Research, Heinrich Heine University, Düsseldorf, Germany

    Katrin Amunts

  9. Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands

    Andrew T. Reid

Authors
  1. Andrew T. Reid
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  2. Felix Hoffstaedter
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  3. Gaolang Gong
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  4. Angela R. Laird
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  5. Peter Fox
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  6. Alan C. Evans
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  7. Katrin Amunts
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  8. Simon B. Eickhoff
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Corresponding author

Correspondence to Andrew T. Reid.

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Funding

This study was supported by the Deutsche Forschungsgemeinschaft (DFG, EI 816/4-1; EI 816/6-1 and LA 3071/3-1.), the National Institute of Mental Health (R01-MH074457) and the European EFT program (Human Brain Project).

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Reid, A.T., Hoffstaedter, F., Gong, G. et al. A seed-based cross-modal comparison of brain connectivity measures. Brain Struct Funct 222, 1131–1151 (2017). https://doi.org/10.1007/s00429-016-1264-3

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  • DOI: https://doi.org/10.1007/s00429-016-1264-3

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