ArticleNetwork neuroscience (Cambridge, Mass.)2022
Constraining functional coactivation with a cluster-based structural connectivity network.
Article in Network neuroscience (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- The relationship between recreational cannabis use, psychotic-like experiences, and the salience network in adolescent and young adult twins.Psychological medicine · 2025Article
- A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity.Nature communications · 2024Article
- The thresholding problem and variability in the EEG graph network parameters.Scientific reports · 2022Article
- Editorial: Focus feature on consciousness and cognition.Network neuroscience (Cambridge, Mass.) · 2022Article
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3 authors.
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Abstract
In this article, we propose a two-step pipeline to explore task-dependent functional coactivations of brain clusters with constraints from the structural connectivity network. In the first step, the pipeline employs a nonparametric Bayesian clustering method that can estimate the optimal number of clusters, cluster assignments of brain regions of interest (ROIs), and the strength of within- and between-cluster connections without any prior knowledge. In the second step, a factor analysis model is applied to functional data with factors defined as the obtained structural clusters and the factor structure informed by the structural network. The coactivations of ROIs and their clusters can be studied by correlations between factors, which can largely differ by ongoing cognitive task. We provide a simulation study to validate that the pipeline can recover the underlying structural and functional network. We also apply the proposed pipeline to empirical data to explore the structural network of ROIs obtained by the Gordon parcellation and study their functional coactivations across eight cognitive tasks and a resting-state condition.
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