Detection of consistently task-related activations in fMRI data with hybrid independent component analysis.
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Summary
A hybrid technique, HYBICA, is described, which uses the initial characterization of the fMRI data from Independent Component Analysis and allows the experimenter to sequentially combine assumed task-related components so that one can gracefully navigate from a fully data-derived approach to a fully hypothesis-driven approach.
- Type
- article
- Published
- 2000-01-01
- Cited by
- 191
- References
- 26
- OpenAlex
- https://openalex.org/W1966537304
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2747811
Keywords
Computer science, Metric (unit), A priori and a posteriori, Artificial intelligence, Component (thermodynamics)
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Cited by
- FREQUENCY DOMAIN HYBRID INDEPENDENT COMPONENT ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE IMAGING DATA
- Bibliography on Independent Component Analysis in Functional Neuroimaging
- Parcellisation et analyse multi-niveaux de données IRM fonctionnelles. Application à l'étude des réseaux de connectivité cérébrale. (Multi-level parcellation and analysis of fMRI data - Application to the study of brain functional networks)
- Exploratory analysis of fMRI data by fuzzy clustering: philosophy, strategy, tactics, implementation
- Adaptive modification of disparity vergence components: an independent component analysis study.
- Adaptive analysis of functional MRI data
- Neural correlates of behavioral variation in healthy adults' antisaccade performance.
- Source density driven adaptive independent component analysis approach for FMRI signal analysis
- INDEPENDENT COMPONENT ANALYSIS OF BIOMEDICAL SIGNALS
- An Introduction to Turbulent Flow
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- The Statistical Analysis of Functional MRI Data
- Comparison of TCA and ICA techniques in fMRI data processing
- Spatial and temporal reproducibility-based ranking of the independent components of BOLD fMRI data
- Estimation of the intrinsic dimensionality of fMRI data
- Review of fMRI Data Analysis: A Special Focus on Classification
- Independent component analysis in the presence of noise in fMRI.
- Temporal clustering analysis of cerebral blood flow activation maps measured by laser speckle contrast imaging
- Multivariate Model Specification for fMRI Data
- Removing the effects of task-related motion using independent-component analysis
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