A method for making group inferences from functional MRI data using independent component analysis
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Summary
A novel approach for drawing group inferences using ICA of fMRI data is introduced, and its application to a simple visual paradigm that alternately stimulates the left or right visual field is presented.
- Type
- article
- Published
- 2001-11-01
- Cited by
- 3,087
- References
- 24
- Access
- Open access
- OpenAlex
- https://openalex.org/W1985327120
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:14617963
Keywords
Independent component analysis, Principal component analysis, Artificial intelligence, Pattern recognition (psychology), Univariate
References
- Detection of consistently task-related activations in fMRI data with hybrid independent component analysis.
- Blind source separation of multiple signal sources of fMRI data sets using independent component analysis.
- Modeling for intergroup comparisons of imaging data.
- On Neural Blind Separation with Noise Suppression and Redundancy Reduction
- Analysis of fMRI time-series revisited--again.
- Detection of signals by information theoretic criteria
- Detecting activations in PET and fMRI: levels of inference and power.
- A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH
- An Information-Maximization Approach to Blind Separation and Blind Deconvolution
- Spatially independent activity patterns in functional MRI data during the stroop color-naming task.
- Independent component analysis: algorithms and applications
- Latencies in fMRI time‐series: effect of slice acquisition order and perception
- A new look at the statistical model identification
- Spatial and temporal independent component analysis of functional MRI data containing a pair of task‐related waveforms
- INDEPENDENT COMPONENT ANALYSIS APPLIED TO FMRI DATA: A NATURAL MODEL AND ORDER SELECTION
- Analysis of fMRI data by blind separation into independent spatial components
- Independent component analysis of fMRI data: Examining the assumptions
- An information-maximization approach to blind separation and blind deconvolution
- Human Brain Mapping 6:160–188(1998) � Analysis of fMRI Data by Blind Separation Into Independent Spatial Components
- Human Brain Mapping 6:368–372(1998) � Independent Component Analysis of fMRI Data: Examining the Assumptions
Cited by
- Introducing Connectivity Analysis to NeuroIS Research
- Mind over chatter: plastic up-regulation of the fMRI alertness network by EEG neurofeedback
- A group model for stable multi-subject ICA on fMRI datasets
- Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions
- Group ICA of resting-state data: a comparison
- Group independent component analysis of resting state EEG in large normative samples.
- Cognitive rehabilitation correlates with the functional connectivity of the anterior cingulate cortex in patients with multiple sclerosis
- Prestimulus hemodynamic activity in dorsal attention network is negatively associated with decision confidence in visual perception.
- Networks involved in Olfaction and their Dynamics using Independent Component Analysis (ICA) and unified Structural Equation Modeling (uSEM)
- A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies
- Gray Matter Volume as an Intermediate Phenotype for Psychosis: Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP)
- Intranetwork and internetwork functional connectivity abnormalities in pediatric multiple sclerosis
- A Survey of the Sources of Noise in fMRI
- Altered Intrinsic Connectivity Networks in Frontal Lobe Epilepsy: A Resting-State fMRI Study
- Specific default mode subnetworks support mentalizing as revealed through opposing network recruitment by social and semantic FMRI tasks
- Left frontoparietal network activity is modulated by drug stimuli in cocaine addiction
- Adapted estimate of neural activity based on blood-oxygen-level dependent signal by a model-free spatio-temporal clustering analysis.
- Pretherapeutic Functional Imaging Allows Prediction of Head Tremor Arrest After Thalamotomy for Essential Tremor: The Role of Altered Interconnectivity Between Thalamolimbic and Supplementary Motor Circuits.
- Connectivity Dynamics in Typical Development and its Relationship to Autistic Traits and Autism Spectrum Disorder
- Non-linear ICA Analysis of Resting-State fMRI in Mild Cognitive Impairment
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