ArticleScientific reports2019
A Comparison of Static and Dynamic Functional Connectivities for Identifying Subjects and Biological Sex Using Intrinsic Individual Brain Connectivity.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- Dynamic Co-Modulation (DyCoM): A Unified Operator Framework for Dynamic Connectivity in Neuroimaging.bioRxiv : the preprint server for biology · 2026Article
- Brain dynamics of attentional, default-mode and limbic networks are disrupted at rest in post-COVID-19 syndrome.Brain, behavior, & immunity - health · 2026Article
- Hypercapnia dissociates neuronal and hemodynamic responses impairing neurovascular coupling and functional brain connectivity.Nature communications · 2026Article
- Sex differences in dynamic and static measures of brain integration derived from resting-state functional magnetic resonance imaging.Biology of sex differences · 2026Article
- μ Opioid Modulation of Sensorimotor Functional Connectivity in Autism: Insights From a Pharmacological Neuroimaging Investigation Using Tianeptine.Biological psychiatry global open science · 2026Article
- The individuality of single-frame functional brain connectivity.bioRxiv : the preprint server for biology · 2026Article
- Integration of Multi-Modal Biosensing Approaches for Depression: Current Status, Challenges, and Future Perspectives.Sensors (Basel, Switzerland) · 2025Review
- Topological and geometric signatures of brain network dynamics in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- A Method for Estimating Dynamic Functional Network Connectivity Gradients (dFNGs) From ICA Captures Smooth Inter-Network Modulation.Human brain mapping · 2025Article
- Revealing morphological fingerprints in perinatal brains using quasi-conformal mapping: occurrence and neurodevelopmental implications.Brain imaging and behavior · 2025Article
- Observational
- Precision non-invasive brain stimulation: anJournal of neural engineering · 2025Article
- Efficacy of functional connectome fingerprinting using tangent-space brain networks.Network neuroscience (Cambridge, Mass.) · 2025Article
- Individual connectivity-based parcellations reflect functional properties of human auditory cortex.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Generation of surrogate brain maps preserving spatial autocorrelation through random rotation of geometric eigenmodes.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Multilayer network analysis across cortical depths in 7-T resting-state fMRI.Network neuroscience (Cambridge, Mass.) · 2025Article
- A Graph-Based Statistical Approach to Identifying Functional Connectivity Networks in Patients with Traumatic Brain Injury.Iranian journal of child neurology · 2025Article
- Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI.bioRxiv : the preprint server for biology · 2024Article
- Synesthesia is linked to large and extensive differences in brain structure and function as determined by whole-brain biomarkers derived from the HCP (Human Connectome Project) cortical parcellation approach.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Characterization of the temporal stability of ToM and pain functional brain networks carry distinct developmental signatures during naturalistic viewing.Scientific reports · 2024Article
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2 authors.
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Abstract
Functional magnetic resonance imaging has revealed correlated activities in brain regions even in the absence of a task. Initial studies assumed this resting-state functional connectivity (FC) to be stationary in nature, but recent studies have modeled these activities as a dynamic network. Dynamic spatiotemporal models better model the brain activities, but are computationally more involved. A comparison of static and dynamic FCs was made to quantitatively study their efficacies in identifying intrinsic individual connectivity patterns using data from the Human Connectome Project. Results show that the intrinsic individual brain connectivity pattern can be used as a 'fingerprint' to distinguish among and identify subjects and is more accurately captured with partial correlation and assuming static FC. It was also seen that the intrinsic individual brain connectivity patterns were invariant over a few months. Additionally, biological sex identification was successfully performed using the intrinsic individual connectivity patterns, and group averages of male and female FC matrices. Edge consistency, edge variability and differential power measures were used to identify the major resting-state networks involved in identifying subjects and their sex.
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