ArticleScientific reports2023
Exploring the latent structure of behavior using the Human Connectome Project's data.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Multivariate brain-behaviour associations in psychiatric disorders.Translational psychiatry · 2024Pooled it
- Spectral organization of individualized connectome harmonics across brain structure, function and cognition.bioRxiv : the preprint server for biology · 2026Article
- Robust but independent sex differences in human brain function, structure, and behavior.Nature communications · 2026Article
- Cognition emerges from phase dynamics of intrinsic coordination.bioRxiv : the preprint server for biology · 2026Article
- Brain structures and their association with executive and attentional abilities in very preterm 8-year-old children.Brain structure & function · 2025Article
- Reconfiguration of functional brain hierarchy in schizophrenia.Translational psychiatry · 2025Article
- A mega-analysis of low frequency resting-state measures in mood and psychosis-spectrum disorders.medRxiv : the preprint server for health sciences · 2025Article
- Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task.Communications biology · 2025Article
- Comparing and scaling fMRI features for brain-behavior prediction.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Article
- Unveiling the Core Functional Networks of Cognition: An Ontology-Guided Machine Learning Approach.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
6 authors.
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Abstract
How behavior arises from brain physiology has been one central topic of investigation in neuroscience. Considering the recent interest in predicting behavior from brain imaging using open datasets, there is the need for a principled approach to the categorization of behavioral variables. However, this is not trivial, as the definitions of psychological constructs and their relationships-their ontology-are not always clear. Here, we propose to use exploratory factor analysis (EFA) as a data-driven approach to find robust and interpretable domains of behavior in the Human Connectome Project (HCP) dataset. Additionally, we explore the clustering of behavioral variables using consensus clustering. We find that four and five factors offer the best description of the data, a result corroborated by the consensus clustering. In the four-factor solution, factors for Mental Health, Cognition, Processing Speed, and Substance Use arise. With five factors, Mental Health splits into Well-Being and Internalizing. Clustering results show a similar pattern, with clusters for Cognition, Processing Speed, Positive Affect, Negative Affect, and Substance Use. The factor structure is replicated in an independent dataset using confirmatory factor analysis (CFA). We discuss how the content of the factors fits with previous conceptualizations of general behavioral domains.
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