ArticleNeuroImage2012
Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study.
Article in NeuroImage, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
127 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Resting-state network alterations in depression: a comprehensive meta-analysis of functional connectivity.Psychological medicine · 2025Pooled it
- Dwelling in prolonged grief: Resting state functional connectivity during oxytocin and placebo administration.Human brain mapping · 2023Trial
- Group differences in MEG-ICA derived resting state networks: Application to major depressive disorder.NeuroImage · 2015Trial
- Dimensional change card sort performance associated with age-related differences in functional connectivity of lateral prefrontal cortex.Developmental cognitive neuroscience · 2013Trial
- A general framework for investigating neurodevelopment of brain functional networks using multisite and longitudinal neuroimaging.The annals of applied statistics · 2026Article
- A review of decomposition methods for brain states estimation.Biomedical engineering online · 2026Review
- A brain-state-informed framework for simultaneous extinction of fear and functional magnetic resonance imaging acquisition in rodents.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Personalized mapping of inhibitory spinal cord circuits in humans via noninvasive neural decoding and in silico modeling.Science advances · 2025Article
- Data-Driven Approach to Dynamic Resting State Functional Connectivity in Post-Traumatic Stress Disorder: An ENIGMA-PGC PTSD Study.Human brain mapping · 2025Article
- Unraveling the Neural Landscape of Mental Disorders Using Double Functional Independent Primitives.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Article
- Effects of an 18-month meditation training on dynamic functional connectivity states in older adults: Secondary analyses from the Age-Well randomized controlled trial.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Article
- Constrained Independent Vector Analysis With Reference for Multi-Subject fMRI Analysis.IEEE transactions on bio-medical engineering · 2024Article
- Independent Vector Analysis for Feature Extraction in Motor Imagery Classification.Sensors (Basel, Switzerland) · 2024Article
- Unraveling the Neural Landscape of Mental Disorders using Double Functional Independent Primitives (dFIPs).bioRxiv : the preprint server for biology · 2024Article
- Abnormal large-scale brain functional network dynamics in social anxiety disorder.CNS neuroscience & therapeutics · 2024Article
- Resting state network connectivity is associated with cognitive flexibility performance in youth in the Adolescent Brain Cognitive Development Study.Neuropsychologia · 2023Article
- Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets.Human brain mapping · 2023Article
- Large-scale brain functional network abnormalities in social anxiety disorder.Psychological medicine · 2023Article
- Network connectivity and structural correlates of survival in progressive supranuclear palsy and corticobasal syndrome.Human brain mapping · 2023Article
67 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
A key challenge in functional neuroimaging is the meaningful combination of results across subjects. Even in a sample of healthy participants, brain morphology and functional organization exhibit considerable variability, such that no two individuals have the same neural activation at the same location in response to the same stimulus. This inter-subject variability limits inferences at the group-level as average activation patterns may fail to represent the patterns seen in individuals. A promising approach to multi-subject analysis is group independent component analysis (GICA), which identifies group components and reconstructs activations at the individual level. GICA has gained considerable popularity, particularly in studies where temporal response models cannot be specified. However, a comprehensive understanding of the performance of GICA under realistic conditions of inter-subject variability is lacking. In this study we use simulated functional magnetic resonance imaging (fMRI) data to determine the capabilities and limitations of GICA under conditions of spatial, temporal, and amplitude variability. Simulations, generated with the SimTB toolbox, address questions that commonly arise in GICA studies, such as: (1) How well can individual subject activations be estimated and when will spatial variability preclude estimation? (2) Why does component splitting occur and how is it affected by model order? (3) How should we analyze component features to maximize sensitivity to intersubject differences? Overall, our results indicate an excellent capability of GICA to capture between-subject differences and we make a number of recommendations regarding analytic choices for application to functional imaging data.
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Registered trials
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 OpenQuestion graph.