ArticleNetwork neuroscience (Cambridge, Mass.)2021
A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks.
Article in Network neuroscience (Cambridge, Mass.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed.
- Dynamic Co-Modulation (DyCoM): A Unified Operator Framework for Dynamic Connectivity in Neuroimaging.bioRxiv : the preprint server for biology · 2026Article
- Aberrant recovery of timescale-aligned amplitude balance links to symptoms and cognition in schizophrenia.Translational psychiatry · 2026Article
- Group Joint ICA (gjICA): A Method for Multimodal Fusion of Concurrent EEG and fMRI Data.Human brain mapping · 2026Article
- Aberrant Recovery of Timescale-Aligned Amplitude Balance Links to Symptoms and Cognition in Schizophrenia.Research square · 2026Article
- CCPD under sparsity and low-rank constraints: multi-frequency dynamic functional network connectivity analysis in schizophrenia.Frontiers in neuroscience · 2026Article
- Functional Inertia Index of Memory-Retaining Brain Dynamics: A Measure of Large-Scale Brain Adaptability.bioRxiv : the preprint server for biology · 2025Article
- st-DenseViT: A Weakly Supervised Spatiotemporal Vision Transformer for Dense Prediction of Dynamic Brain Networks.Human brain mapping · 2025Article
- Studying Time-Resolved Functional Connectivity via Communication Theory: On the Complementary Nature of Phase Synchronization and Sliding Window Pearson Correlation.Brain connectivity · 2025Article
- Neural flexibility in metabolic demand dynamics reveals sex-specific differences and supports cognition in late childhood.bioRxiv : the preprint server for biology · 2025Article
- Timescale-normalized fMRI reveals disrupted dynamic signal-energy balance in schizophrenia.bioRxiv : the preprint server for biology · 2025Article
- COMPLEX-VALUED PHASE SYNCHRONY REVEALS DIRECTIONAL COUPLING IN FMRI AND TRACKS MEDICATION EFFECTS.ArXiv · 2025Article
- Functionally Adaptive Structural Basis Sets of the Brain: A Dynamic Fusion Approach.Human brain mapping · 2025Article
- Studying time-resolved functional connectivity via communication theory: on the complementary nature of phase synchronization and sliding window Pearson correlation.bioRxiv : the preprint server for biology · 2025Article
- Alterations in Gray Matter Structure Linked to Frequency-Specific Cortico-Subcortical Connectivity in Schizophrenia via Multimodal Data Fusion.Neuroinformatics · 2025Article
- A multi-frequency ICA-based approach for estimating voxelwise frequency difference patterns in fMRI data.Aperture neuro · 2025Article
- The overlap across psychotic disorders: A functional network connectivity analysis.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2024Article
- A method for capturing dynamic spectral coupling in resting fMRI reveals domain-specific patterns in schizophrenia.Frontiers in neuroscience · 2023Article
- Edge-centric analysis of time-varying functional brain networks with applications in autism spectrum disorder.NeuroImage · 2022Article
- Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia.Network neuroscience (Cambridge, Mass.) · 2022Article
- Multiframe Evolving Dynamic Functional ConnectivityFrontiers in neuroscience · 2022Article
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5 authors.
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Abstract
Static and dynamic functional network connectivity (FNC) are typically studied separately, which makes us unable to see the full spectrum of connectivity in each analysis. Here, we propose an approach called filter-banked connectivity (FBC) to estimate connectivity while preserving its full frequency range and subsequently examine both static and dynamic connectivity in one unified approach. First, we demonstrate that FBC can estimate connectivity across multiple frequencies missed by a sliding-window approach. Next, we use FBC to estimate FNC in a resting-state fMRI dataset including schizophrenia patients (SZ) and typical controls (TC). The FBC results are clustered into different network states. Some states showed weak low-frequency strength and as such were not captured in the window-based approach. Additionally, we found that SZs tend to spend more time in states exhibiting higher frequencies compared with TCs who spent more time in lower frequency states. Finally, we show that FBC enables us to analyze static and dynamic connectivity in a unified way. In summary, FBC offers a novel way to unify static and dynamic connectivity analyses and can provide additional information about the frequency profile of connectivity patterns.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.