The normative modeling framework for computational psychiatry
Rutherford,Saige Kia,Seyed Mostafa Wolfers,Thomas Fraza,Charlotte Zabihi,Mariam Dinga,Richard Berthet,Pierre Worker,Amanda Verdi,Serena Ruhe,Henricus G.
Rutherford,Saige
Kia,Seyed Mostafa
Wolfers,Thomas
Fraza,Charlotte
Zabihi,Mariam
Dinga,Richard
Berthet,Pierre
Worker,Amanda
Verdi,Serena
Ruhe,Henricus G.
Abstract
Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior, which can then be used to make statistical inferences at the level of the individual. The fields of computational psychiatry and clinical neuroscience have been slow to transition away from patient versus ‘healthy’ control analytic approaches, probably owing to a lack of tools designed to properly model biological heterogeneity of mental disorders. Normative modeling provides a solution to address this issue and moves analysis away from case–control comparisons that rely on potentially noisy clinical labels. Here we define a standardized protocol to guide users through, from start to finish, normative modeling analysis using the Predictive Clinical Neuroscience toolkit (PCNtoolkit). We describe the input data selection process, provide intuition behind the various modeling choices and conclude by demonstrating several examples of downstream analyses that the normative model may facilitate, such as stratification of high-risk individuals, subtyping and behavioral predictive modeling. The protocol takes ~1–3 h to complete.
Description
Funding Information: This research was supported by grants from the European Research Council (ERC, grant ‘MENTALPRECISION’ 10100118 and ‘BRAINMINT’ 802998), the Wellcome Trust under an Innovator award (‘BRAINCHART’, 215698/Z/19/Z) and a Strategic Award (098369/Z/12/Z), the Dutch Organisation for Scientific Research (VIDI grant 016.156.415). T.W. also gratefully acknowledges the Niels Stensen Fellowship as well as the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant agreement no. 895011. Publisher Copyright: © 2022, Springer Nature Limited.
Date
2022-06-01
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Keywords
Case-Control Studies, Computational Biology/methods, Humans, Mental Disorders, Neurosciences, Psychiatry/methods
Citation
Rutherford, S, Kia, S M, Wolfers, T, Fraza, C, Zabihi, M, Dinga, R, Berthet, P, Worker, A, Verdi, S, Ruhe, H G, Beckmann, C F & Marquand, A F 2022, 'The normative modeling framework for computational psychiatry', Nature Protocols, vol. 17, no. 7, pp. 1711-1734. https://doi.org/10.1038/s41596-022-00696-5