A method for making group inferences from functional MRI data using independent component analysis
Open accessAbstract
Independent component analysis (ICA) is a promising analysis method that is being increasingly applied to fMRI data. A principal advantage of this approach is its applicability to cognitive paradigms for which detailed models of brain activity are not available. Independent component analysis has been successfully utilized to analyze single‐subject fMRI data sets, and an extension of this work would be to provide for group inferences. However, unlike univariate methods (e.g., regression analysis, Kolmogorov–Smirnov statistics), ICA does not naturally generalize to a method suitable for drawing inferences about groups of subjects. We introduce a novel approach for drawing group inferences using ICA of fMRI data, and present its application to a simple visual paradigm that alternately stimulates the left or right visual field. Our group ICA analysis revealed task‐related components in left and right visual cortex, a transiently task‐related component in bilateral occipital/parietal cortex, and a non‐task‐related component in bilateral visual association cortex. We address issues involved in the use of ICA as an fMRI analysis method such as: (1) How many components should be calculated? (2) How are these components to be combined across subjects? (3) How should the final results be thresholded and/or presented? We show that the methodology we present provides answers to these questions and lay out a process for making group inferences from fMRI data using independent component analysis. Hum. Brain Mapping 14:140–151, 2001. © 2001 Wiley‐Liss, Inc.
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The independent components which resembled the default mode network most were spatially sorted using the DMN template built-in in GIFT and then further identified by visual inspection by two different raters for resting state and meditation state separately.
“The ICs which resembled the DMN most were firstly spatially sorted by using the DMN template built-in in GIFT [57] and then further identified by visual inspection by two different raters for RS and MS separately.”
From State and training effects of mindfulness meditation on brain networks reflect neuronal mechanisms of its antidepressant effect (2016) · cites this paper as [57]
The adult language network is lateralized and includes the inferior frontal gyrus and superior temporal gyrus; these regions begin to show asymmetry in functional connectivity with the contralateral homotopic region at about age two.
“The language network, in adults is lateralized and encompasses the inferior frontal gyrus (IFG) and the superior temporal gyrus (STG); these regions begin to exhibit asymmetry in functional connectivity with the homotopic region on the contralateral hemisphere at about age 2 years 102.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [102]
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Self-citationAltered resting state connectivity of the default mode network in alexithymia
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Functional connectivity and cannabis use in high-risk adolescents
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- Authors
- Calhoun, V. D., Adali, T., Pearlson, G. D., & Pekar, J. J.
- Affiliations
- Johns Hopkins University (US)
- Kennedy Krieger Institute (US)
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2001-08-27
- Volume
- 14
- Issue
- 3
- Pages
- 140-151
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- PMC
- PMC6871952
- OpenAlex
- W1985327120
- Cited by
- 2,994
- References
- 18
- Citations by year
- 2026: 96 · 2025: 158 · 2024: 128 · 2023: 158 · 2022: 190 · 2021: 223 · 2020: 201 · 2019: 217 · 2018: 186 · 2017: 195 · 2016: 174 · 2015: 143 · 2014: 181 · 2013: 173 · 2012: 153
- FWCI
- 15.08
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Human Brain Mapping (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Johns Hopkins University
- Topics
- Physical Sciences › Computer Science › Signal Processing › Blind Source Separation Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Mathematics › Computational Mathematics › Tensor decomposition and applications
- Keywords
- independent component analysis, visual cortex, visual field stimulation, component selection, statistical thresholding, visual association cortex
- MeSH terms
- Algorithms, Brain Mapping, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Models, Neurological, Signal Processing, Computer-Assisted, Visual Cortex
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