Unpacking the functional heterogeneity of the Emotional Face Matching Task: a normative modelling approach Article Swipe
Hannah S. Savage
,
Peter Mulders
,
Philip van Eijndhoven
,
Jasper van Oort
,
Indira Tendolkar
,
Janna N. Vrijsen
,
Christian F. Beckmann
,
André F. Marquand
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.03.27.534351
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.03.27.534351
Functional neuroimaging has contributed substantially to understanding brain function but is dominated by group analyses that index only a fraction of the variation in these data. It is increasingly clear that parsing the underlying heterogeneity is crucial to understand individual differences and the impact of different task manipulations. We estimate large-scale (N=7728) normative models of task-evoked activation during the Emotional Face Matching Task, which enables us to bind heterogeneous datasets to a common reference and dissect heterogeneity underlying group-level analyses. We apply this model to a heterogenous patient cohort, to map individual differences between patients with one or more mental health diagnoses relative to the reference cohort and determine multivariate associations with transdiagnostic symptom domains. For the face>shapes contrast, patients have a higher frequency of extreme deviations which are spatially heterogeneous. In contrast, normative models for faces>baseline have greater predictive value for individuals’ transdiagnostic functioning.
Related Topics
Concepts
Normative
Task (project management)
Psychology
Multivariate statistics
Correlation
Neuroimaging
Cognitive psychology
Cohort
Contrast (vision)
Matching (statistics)
Computer science
Artificial intelligence
Machine learning
Statistics
Neuroscience
Mathematics
Philosophy
Economics
Management
Epistemology
Geometry
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.03.27.534351
- https://www.biorxiv.org/content/biorxiv/early/2023/04/21/2023.03.27.534351.full.pdf
- OA Status
- green
- Cited By
- 9
- References
- 36
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4360991065
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4360991065Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.03.27.534351Digital Object Identifier
- Title
-
Unpacking the functional heterogeneity of the Emotional Face Matching Task: a normative modelling approachWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-27Full publication date if available
- Authors
-
Hannah S. Savage, Peter Mulders, Philip van Eijndhoven, Jasper van Oort, Indira Tendolkar, Janna N. Vrijsen, Christian F. Beckmann, André F. MarquandList of authors in order
- Landing page
-
https://doi.org/10.1101/2023.03.27.534351Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2023/04/21/2023.03.27.534351.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2023/04/21/2023.03.27.534351.full.pdfDirect OA link when available
- Concepts
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Normative, Task (project management), Psychology, Multivariate statistics, Correlation, Neuroimaging, Cognitive psychology, Cohort, Contrast (vision), Matching (statistics), Computer science, Artificial intelligence, Machine learning, Statistics, Neuroscience, Mathematics, Philosophy, Economics, Management, Epistemology, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 4, 2023: 3Per-year citation counts (last 5 years)
- References (count)
-
36Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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