ArticleFrontiers in human neuroscience2023
Individual differences in the language task-evoked and resting-state functional networks.
Article in Frontiers in human neuroscience, 2023. 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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Who cites it
6 citing papers in PubMed.
- Beyond GLM: Inter-Subject Variability as a Complementary Approach to Detect Longitudinal Changes in Emotion Processing in Multiple Sclerosis.Journal of imaging · 2026Article
- Resting-State and Task Functional Magnetic Resonance Imaging Network Topology Metrics With no Threshold Selection to Predict Cognition.Human brain mapping · 2026Article
- Hemispheric Network Dynamics During Auditory Language Comprehension and Its Clinical Implications Regarding Resting-State Functional Magnetic Resonance Imaging.Journal of speech, language, and hearing research : JSLHR · 2026Article
- Divergence unveils further distinct phenotypic traits of human brain connectomics fingerprint.iScience · 2026Article
- NEBULA101: an open dataset for the study of language aptitude in behaviour, brain structure and function.Scientific data · 2025Article
- Precision neurodiversity: personalized brain network architecture as a window into cognitive variability.Frontiers in human neuroscience · 2025Review
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Abstract
The resting state functional network is highly variable across individuals. However, inter-individual differences in functional networks evoked by language tasks and their comparison with resting state are still unclear. To address these two questions, we used T1 anatomical data and functional brain imaging data of resting state and a story comprehension task from the Human Connectome Project (HCP) to characterize functional network variability and investigate the uniqueness of the functional network in both task and resting states. We first demonstrated that intrinsic and task-induced functional networks exhibited remarkable differences across individuals, and language tasks can constrain inter-individual variability in the functional brain network. Furthermore, we found that the inter-individual variability of functional networks in two states was broadly consistent and spatially heterogeneous, with high-level association areas manifesting more significant variability than primary visual processing areas. Our results suggested that the functional network underlying language comprehension is unique at the individual level, and the inter-individual variability architecture of the functional network is broadly consistent in language task and resting state.
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