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.
Metrics
-
- 6,000
- views
-
- 644
- downloads
-
- 73
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
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)
Evidence for embracing normative modeling
eLife 12:e85082.
https://doi.org/10.7554/eLife.85082
Further reading
-
- Neuroscience
Dense core vesicles (DCVs) transport and release various neuropeptides and neurotrophins that control diverse brain functions, but the DCV secretory pathway remains poorly understood. Here, we tested a prediction emerging from invertebrate studies about the crucial role of the intracellular trafficking GTPase Rab10, by assessing DCV exocytosis at single-cell resolution upon acute Rab10 depletion in mature mouse hippocampal neurons, to circumvent potential confounding effects of Rab10’s established role in neurite outgrowth. We observed a significant inhibition of DCV exocytosis in Rab10-depleted neurons, whereas synaptic vesicle exocytosis was unaffected. However, rather than a direct involvement in DCV trafficking, this effect was attributed to two ER-dependent processes, ER-regulated intracellular Ca2+ dynamics, and protein synthesis. Gene Ontology analysis of differentially expressed proteins upon Rab10 depletion identified substantial alterations in synaptic and ER/ribosomal proteins, including the Ca2+ pump SERCA2. In addition, ER morphology and dynamics were altered, ER Ca2+ levels were depleted, and Ca2+ homeostasis was impaired in Rab10-depleted neurons. However, Ca2+ entry using a Ca2+ ionophore still triggered less DCV exocytosis. Instead, leucine supplementation, which enhances protein synthesis, largely rescued DCV exocytosis deficiency. We conclude that Rab10 is required for neuropeptide release by maintaining Ca2+ dynamics and regulating protein synthesis. Furthermore, DCV exocytosis appeared more dependent on (acute) protein synthesis than synaptic vesicle exocytosis.
-
- Neuroscience
By influencing calcium homeostasis, local protein synthesis and the endoplasmic reticulum, a small protein called Rab10 emerges as a crucial cytoplasmic regulator of neuropeptide secretion.
