ArticleHuman brain mapping2024
4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia.
Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Group Joint ICA (gjICA): A Method for Multimodal Fusion of Concurrent EEG and fMRI Data.Human brain mapping · 2026Article
- Dynamic Estimation of Spatially Interactive Networks (DESINE) Reveals Constrained Brain Repertoire in Schizophrenia Linked to Clinical and Cognitive Symptoms.bioRxiv : the preprint server for biology · 2026Article
- NeuroMark-DyFICA: NeuroMark dynamic frequency-informed ICA with high-frequency spatial filtering for windowed fMRI analysis.Network neuroscience (Cambridge, Mass.) · 2026Article
- Diminished spatial dynamics and maladaptive spatial complexity link resting brain network disruption to cognition in schizophrenia.bioRxiv : the preprint server for biology · 2025Article
- Integrating fMRI spatial network dynamics and EEG spectral power: insights into resting state connectivity.Frontiers in neuroscience · 2025Article
- 4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia.Human brain mapping · 2024Article
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Abstract
Despite increasing interest in the dynamics of functional brain networks, most studies focus on the changing relationships over time between spatially static networks or regions. Here we propose an approach to study dynamic spatial brain networks in human resting state functional magnetic resonance imaging (rsfMRI) data and evaluate the temporal changes in the volumes of these 4D networks. Our results show significant volumetric coupling (i.e., synchronized shrinkage and growth) between networks during the scan, that we refer to as dynamic spatial network connectivity (dSNC). We find that several features of such dynamic spatial brain networks are associated with cognition, with higher dynamic variability in these networks and higher volumetric coupling between network pairs positively associated with cognitive performance. We show that these networks are modulated differently in individuals with schizophrenia versus typical controls, resulting in network growth or shrinkage, as well as altered focus of activity within a network. Schizophrenia also shows lower spatial dynamical variability in several networks, and lower volumetric coupling between pairs of networks, thus upholding the role of dynamic spatial brain networks in cognitive impairment seen in schizophrenia. Our data show evidence for the importance of studying the typically overlooked voxel-wise changes within and between brain networks.
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