Evidence for embracing normative modeling
- Radboud University Nijmegen Medical Centre, Netherlands
- Radboud University Nijmegen, Netherlands
- University of Michigan-Ann Arbor, United States
Abstract
In this work, we expand the normative model repository introduced in (Rutherford, Fraza, et al., 2022) to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability). Across all benchmarks, we show the advantage of using normative modeling features, with the strongest statistically significant results demonstrated in the group difference testing and classification tasks. We intend for these accessible resources to facilitate wider adoption of normative modeling across the neuroimaging community.
Data availability
Pre-trained normative models are available on GitHub (https://github.com/predictive-clinical-neuroscience/braincharts) and Google Colab (https://colab.research.google.com/github/predictive-clinical-neuroscience/braincharts/blob/master/scripts/apply_normative_models_yeo17.ipynb). Scripts for running the benchmarking analysis and visualizations are available on GitHub (https://github.com/saigerutherford/evidence_embracing_nm). An online portal for running models without code is available (https://pcnportal.dccn.nl).
Article and author information
Author details
Funding
European Research Council (10100118)
- Andre F Marquand
European Research Council (802998)
- Andre F Marquand
Wellcome Trust (215698/Z/19/Z)
- Andre F Marquand
Wellcome Trust (098369/Z/12/Z)
- Andre F Marquand
National Institute of Mental Health (R01MH122491)
- Ivy F Tso
National Institute of Mental Health (R01MH123458)
- Chandra Sripada
National Institute of Mental Health (R01MH130348)
- Chandra Sripada
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Secondary data analysis was conducted in this work. Data were pooled from multiple data sources described in the supplemental tables. All subjects provided informed consent. Subject recruitment procedures and informed consent forms, including consent to share de-identified data, were approved by the corresponding university institutional review board where data were collected. Human subjects: Ethical approval for the public data were provided by the relevant local research authorities for the studies contributing data. For full details, see the main study publications in the main text. For all clinical studies, approval was obtained via the local ethical review authorities, i.e., Delta: The local ethics committee of the Academic Medical Center of the University of Amsterdam (AMC-METC) Nr.:11/050, UMich_IMPS: University of Michigan Institution Review Board HUM00088188, UMich_SZG: University of Michigan Institution Review Board HUM00080457.
Copyright
© 2023, Rutherford 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.
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