ArticleHuman brain mapping2019
Spatial dynamics within and between brain functional domains: A hierarchical approach to study time-varying brain function.
Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.
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Who cites it
46 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Aberrant cortical-subcortical-cerebellar connectivity in resting-state fMRI as an imaging marker of schizophrenia and psychosis: a systematic review of data-driven whole-brain functional connectivity analyses.Frontiers in neuroimaging · 2025Pooled it
- Spatiotemporal asymmetries on brain energy landscape uncover system entrapment related to depression severity.Nature communications · 2026Article
- Neurocognitive characterization of behaviour and mental illness through time-varying brain network analysis.Nature communications · 2026Article
- Deciphering multiway multiscale brain network connectivity from birth to 6 months.Communications biology · 2026Article
- NeuroMark-DyFICA: NeuroMark dynamic frequency-informed ICA with high-frequency spatial filtering for windowed fMRI analysis.Network neuroscience (Cambridge, Mass.) · 2026Article
- Spatial development of brain networks during the first six postnatal months.Communications 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
- A Method for Estimating Dynamic Functional Network Connectivity Gradients (dFNGs) From ICA Captures Smooth Inter-Network Modulation.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
- Time-Varying Spatial Propagation of Brain Networks in fMRI Data.Human brain mapping · 2025Article
- Deciphering Multiway Multiscale Brain Network Connectivity: Insights from Birth to 6 Months.bioRxiv : the preprint server for biology · 2025Article
- Deep linear matrix approximate reconstruction with integrated BOLD signal denoising reveals reproducible hierarchical brain connectivity networks from multiband multi-echo fMRI.Frontiers in neuroscience · 2025Article
- Time-resolved instantaneous functional loci estimation (TRIFLE): Estimating time-varying allocation of spatially overlapping sources in functional magnetic resonance imaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Dynamic fluctuations of intrinsic brain activity are associated with consistent topological patterns in puberty and are biomarkers of neural maturation.Network neuroscience (Cambridge, Mass.) · 2025Article
- A multi-frequency ICA-based approach for estimating voxelwise frequency difference patterns in fMRI data.Aperture neuro · 2025Article
- Sequential patterning of dynamic brain states distinguish Parkinson's disease patients with mild cognitive impairments.NeuroImage. Clinical · 2025Article
- Addressing Inconsistency in Functional Neuroimaging: A Replicable Data-Driven Multi-Scale Functional Atlas for Canonical Brain Networks.bioRxiv : the preprint server for biology · 2024Article
- Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and Their Links to Genetic Risk.Biological psychiatry · 2024Article
- A method for estimating dynamic functional network connectivity gradients (dFNG) from ICA captures smooth inter-network modulation.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
19 authors.
Funding
Abstract
The analysis of time-varying activity and connectivity patterns (i.e., the chronnectome) using resting-state magnetic resonance imaging has become an important part of ongoing neuroscience discussions. The majority of previous work has focused on variations of temporal coupling among fixed spatial nodes or transition of the dominant activity/connectivity pattern over time. Here, we introduce an approach to capture spatial dynamics within functional domains (FDs), as well as temporal dynamics within and between FDs. The approach models the brain as a hierarchical functional architecture with different levels of granularity, where lower levels have higher functional homogeneity and less dynamic behavior and higher levels have less homogeneity and more dynamic behavior. First, a high-order spatial independent component analysis is used to approximate functional units. A functional unit is a pattern of regions with very similar functional activity over time. Next, functional units are used to construct FDs. Finally, functional modules (FMs) are calculated from FDs, providing an overall view of brain dynamics. Results highlight the spatial fluidity within FDs, including a broad spectrum of changes in regional associations, from strong coupling to complete decoupling. Moreover, FMs capture the dynamic interplay between FDs. Patients with schizophrenia show transient reductions in functional activity and state connectivity across several FDs, particularly the subcortical domain. Activity and connectivity differences convey unique information in many cases (e.g., the default mode) highlighting their complementarity information. The proposed hierarchical model to capture FD spatiotemporal variations provides new insight into the macroscale chronnectome and identifies changes hidden from existing approaches.
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