The normative modeling framework for computational psychiatry.
Journal
Nature protocols
ISSN: 1750-2799
Titre abrégé: Nat Protoc
Pays: England
ID NLM: 101284307
Informations de publication
Date de publication:
07 2022
07 2022
Historique:
received:
16
08
2021
accepted:
17
03
2022
pubmed:
2
6
2022
medline:
12
7
2022
entrez:
1
6
2022
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 35650452
doi: 10.1038/s41596-022-00696-5
pii: 10.1038/s41596-022-00696-5
pmc: PMC7613648
mid: EMS154602
doi:
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1711-1734Subventions
Organisme : Wellcome Trust
ID : 098369/Z/12/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 215698/Z/19/Z
Pays : United Kingdom
Organisme : ZonMw
ID : ZONMW_91716415
Pays : Netherlands
Organisme : Wellcome Trust
ID : 215698
Pays : United Kingdom
Organisme : European Research Council
ID : 101001118
Pays : International
Informations de copyright
© 2022. Springer Nature Limited.
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