ArticleJournal of neuroscience methods2020
Determining the number of states in dynamic functional connectivity using cluster validity indexes.
Article in Journal of neuroscience methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- UltraFast Layer-Resolved Encoding (uFLARE) functional MRI deciphers bidirectional signaling from spontaneous activity.Nature communications · 2026Article
- Channel Capacity for Time-Resolved Effective Connectivity in Functional Neuroimaging.bioRxiv : the preprint server for biology · 2026Article
- Neurocognitive characterization of behaviour and mental illness through time-varying brain network analysis.Nature communications · 2026Article
- fNIRS-Based characterization of adolescent depression using dynamic functional connectivity biomarkers in a verbal fluency task.BMC psychiatry · 2026Article
- Characterizing the relationship between functional network dynamics and the body mass index.Frontiers in nutrition · 2026Article
- State-base dynamic functional connectivity analysis of fMRI data during facial emotional processing.Brain imaging and behavior · 2025Article
- Aberrant brain dynamics in major depressive disorder during working memory task.European archives of psychiatry and clinical neuroscience · 2025Article
- Review
- Human brain state dynamics are highly reproducible and associated with neural and behavioral features.PLoS biology · 2024Article
- Human brain state dynamics reflect individual neuro-phenotypes.bioRxiv : the preprint server for biology · 2024Article
- Article
- Revisiting delusion subtypes in schizophrenia based on their underlying structures.Journal of psychiatric research · 2024Article
- Aberrant Brain Dynamics in Schizophrenia During Working Memory Task: Evidence From a Replication Functional MRI Study.Schizophrenia bulletin · 2024Article
- Article
- Dynamic alterations of spontaneous neural activity in post-stroke aphasia: a resting-state functional magnetic resonance imaging study.Frontiers in neuroscience · 2023Article
- Dynamic phase-locking states and personality in sub-acute mild traumatic brain injury: An exploratory study.PloS one · 2023Article
- Conceptualizing problems with symptoms, function, health behavior, health-seeking skills, and financial strain in breast cancer survivors using hierarchical clustering.Journal of cancer survivorship : research and practice · 2022Article
- Time-varying dynamic network model for dynamic resting state functional connectivity in fMRI and MEG imaging.NeuroImage · 2022Article
- Racial and Ethnic Differences in Genomic Profiling of Early Onset Colorectal Cancer.Journal of the National Cancer Institute · 2022Article
- Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease.Frontiers in computational neuroscience · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundClustering analysis is employed in brain dynamic functional connectivity (dFC) to cluster the data into a set of dynamic states. These states correspond to different patterns of functional connectivity that iterate through time. Although several cluster validity index (CVI) methods to determine the best clustering partition exists, the appropriateness of methods to apply in the case of dynamic connectivity analysis has not been determined. NEW
methodCurrently employed indexes do not provide a crisp answer on what is the best number of clusters. In addition, there is a lack of CVI testing in the context of dFC data. This work tests a comprehensive set of twenty four cluster validity indexes applied to addiction data and suggest the best ones for clustering dynamic functional connectivity.
resultsOut of the twenty four considered CVIs, Davies-Bouldin and Ray-Turi were the most suitable methods to find the number of clusters in both simulation and real data. The solution for these two CVIs is to find a local minimum critical point, which can be automated using computational algorithms. COMPARISON WITH EXISTING
methodsElbow-Criterion, Silhouette and GAP-Statistic methods have been widely used in dFC studies. These methods are included among the tested CVIs where the performances of all twenty four CVIs are compared.
conclusionsDavies-Bouldin and Ray-Turi CVIs showed better performance among a group of twenty four CVIs in determining the number of clusters to use in dFC analysis.
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