Combining independent component analysis and correlation analysis to probe interregional connectivity in fMRI task activation datasets
Abstract
A new approach in studying interregional functional connectivity using functional magnetic resonance imaging (fMRI) is presented. Functional connectivity may be detected by means of cross correlating time course data from functionally related brain regions. These data exhibit high temporal coherence of low frequency fluctuations due to synchronized blood flow changes. In the past, this fMRI technique for studying functional connectivity has been applied to subjects that performed no prescribed task ("resting" state). This paper presents the results of applying the same method to task-related activation datasets. Functional connectivity analysis is first performed in areas not involved with the task. Then a method is devised to remove the effects of activation from the data using independent component analysis (ICA) and functional connectivity analysis is repeated. Functional connectivity, which is demonstrated in the "resting brain," is not affected by tasks which activate unrelated brain regions. In addition, ICA effectively removes activation from the data and may allow us to study functional connectivity even in the activated regions.
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Protective factors increase a person's resilience, i.e. the ability to maintain or regain mental health in the face of adversity or to bounce back from hardship and trauma.
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“Second, coherent spontaneous fluctuations have been observed within systems associated with specific behavior in the absence of that behavior such as in the motor system in the absence of movement (30,40,42).”
From Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems (2006) · cites this paper as [40]
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- Authors
- Arfanakis, K., Cordes, D., Haughton, V. M., Moritz, C. H., Quigley, M. A., & Meyerand, M. E.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Arfanakis, Konstantinos
- Venue
- Magnetic Resonance Imaging
- Publisher
- Elsevier BV
- Published
- 2000-10
- Volume
- 18
- Issue
- 8
- Pages
- 921-930
- ISSN
- 0730-725X (ISSN-L)
- OpenAlex
- W2066906403
- Cited by
- 191
- References
- 30
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 4 · 2020: 3 · 2019: 2 · 2018: 6 · 2017: 3 · 2016: 4 · 2015: 7 · 2014: 15 · 2013: 16 · 2012: 9
- FWCI
- 2.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Magnetic Resonance Imaging (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- independent component analysis, correlation analysis, task-related brain activation, resting state, low-frequency fluctuations
- MeSH terms
- Adult, Auditory Cortex, Brain, Brain Mapping, Hemodynamics, Humans, Magnetic Resonance Imaging, Models, Neurological, Motor Cortex, Research, Time Factors, Visual Cortex, Databases as Topic
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