ArticleHuman brain mapping2014
Dynamic functional connectomics signatures for characterization and differentiation of PTSD patients.
Article in Human brain mapping, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.
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Who cites it
78 citing papers in PubMed.
- Data-Driven Approach to Dynamic Resting State Functional Connectivity in Post-Traumatic Stress Disorder: An ENIGMA-PGC PTSD Study.Human brain mapping · 2025Article
- Extended nonnegative matrix factorization for dynamic functional connectivity analysis of fMRI data.Cognitive neurodynamics · 2024Article
- Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.NeuroImage · 2023Article
- Classification of Migraine Using Static Functional Connectivity Strength and Dynamic Functional Connectome Patterns: A Resting-State fMRI Study.Brain sciences · 2023Article
- Altered dynamic functional network connectivity in drug-naïve Parkinson's disease patients with excessive daytime sleepiness.Frontiers in aging neuroscience · 2023Article
- Resting-state connectivity subtype of comorbid PTSD and alcohol use disorder moderates improvement from integrated prolonged exposure therapy in Veterans.Psychological medicine · 2023Article
- Control energy assessment of spatial interactions among macro-scale brain networks.Human brain mapping · 2022Article
- Test-retest reliability of dynamic functional connectivity in naturalistic paradigm functional magnetic resonance imaging.Human brain mapping · 2022Article
- The integrative functional connectivity analysis between seafarer's brain networks using functional magnetic resonance imaging data of different states.Frontiers in neuroscience · 2022Article
- Tools of the trade: estimating time-varying connectivity patterns from fMRI data.Social cognitive and affective neuroscience · 2021Review
- Brain parcellation driven by dynamic functional connectivity better capture intrinsic network dynamics.Human brain mapping · 2021Article
- Fundamental functional differences between gyri and sulci: implications for brain function, cognition, and behavior.Psychoradiology · 2021Review
- Extraction and Analysis of Dynamic Functional Connectome Patterns in Migraine Sufferers: A Resting-State fMRI Study.Computational and mathematical methods in medicine · 2021Article
- Altered Brain Functional Network in Subtypes of Parkinson's Disease: A Dynamic Perspective.Frontiers in aging neuroscience · 2021Article
- Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder.Frontiers in human neuroscience · 2021Article
- Pelvic Pain Alters Functional Connectivity Between Anterior Cingulate Cortex and Hippocampus in Both Humans and a Rat Model.Frontiers in systems neuroscience · 2021Article
- Current methods and new directions in resting state fMRI.Clinical imaging · 2020Review
- Sparse representation and dictionary learning model incorporating group sparsity and incoherence to extract abnormal brain regions associated with schizophrenia.IEEE access : practical innovations, open solutions · 2020Article
- Multi-channel hierarchy functional integration analysis between large-scale brain networks for migraine: An fMRI study.NeuroImage. Clinical · 2020Article
- Sparse Representation-Based Denoising for High-Resolution Brain Activation and Functional Connectivity Modeling: A Task fMRI Study.IEEE access : practical innovations, open solutions · 2020Article
18 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors.
Funding
Abstract
Functional connectomes (FCs) have been recently shown to be powerful in characterizing brain conditions. However, many previous studies assumed temporal stationarity of FCs, while their temporal dynamics are rarely explored. Here, based on the structural connectomes constructed from diffusion tensor imaging data, FCs are derived from resting-state fMRI (R-fMRI) data and are then temporally divided into quasi-stable segments via a sliding time window approach. After integrating and pooling over a large number of those temporally quasi-stable FC segments from 44 post-traumatic stress disorder (PTSD) patients and 51 healthy controls, common FC (CFC) patterns are derived via effective dictionary learning and sparse coding algorithms. It is found that there are 16 CFC patterns that are reproducible across healthy controls, and interestingly, two additional CFC patterns with altered connectivity patterns [termed signature FC (SFC) here] exist dominantly in PTSD subjects. These two SFC patterns alone can successfully differentiate 80% of PTSD subjects from healthy controls with only 2% false positive. Furthermore, the temporal transition dynamics of CFC patterns in PTSD subjects are substantially different from those in healthy controls. These results have been replicated in separate testing datasets, suggesting that dynamic functional connectomics signatures can effectively characterize and differentiate PTSD patients.
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