Network Neuroscience

Papers
(The H4-Index of Network Neuroscience is 18. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Dynamic expression of brain functional systems disclosed by fine-scale analysis of edge time series63
Combining network topology and information theory to construct representative brain networks58
Parcels and particles: Markov blankets in the brain47
Graph convolutional network for fMRI analysis based on connectivity neighborhood44
Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia36
Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle36
Allostasis as a core feature of hierarchical gradients in the human brain32
Controversies and progress on standardization of large-scale brain network nomenclature27
Edges in brain networks: Contributions to models of structure and function26
A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks24
Differential contributions of static and time-varying functional connectivity to human behavior23
Parcellation-induced variation of empirical and simulated brain connectomes at group and subject levels23
Latent functional connectivity underlying multiple brain states23
Efficient coding in the economics of human brain connectomics21
It’s about time: Linking dynamical systems with human neuroimaging to understand the brain21
The ascending arousal system promotes optimal performance through mesoscale network integration in a visuospatial attentional task20
A natural cortical axis connecting the outside and inside of the human brain18
Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity18
Predicting MEG resting-state functional connectivity from microstructural information18
Gradients of connectivity as graph Fourier bases of brain activity18
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