Partial correlation for functional brain interactivity investigation in functional MRI
Abstract
Examination of functional interactions through effective connectivity requires the determination of three distinct levels of information: (1) the regions involved in the process and forming the spatial support of the network, (2) the presence or absence of interactions between each pair of regions, and (3) the directionality of the existing interactions. While many methods exist to select regions (Step 1), very little is available to complete Step 2. The two main methods developed so far, structural equation modeling (SEM) and dynamical causal modeling (DCM), usually require precise prior information to be used, while such information is sometimes lacking. Assuming that Step 1 was successfully completed, we here propose a data-driven method to deal with Step 2 and extract functional interactions from fMRI datasets through partial correlations. Partial correlation is more closely related to effective connectivity than marginal correlation and provides a convenient graphical representation for functional interactions. As an instance of brain interactivity investigation, we consider how simple hand movements are processed by the bihemispheric cortical motor network. In the proposed framework, Bayesian analysis makes it possible to estimate and test the partial statistical dependencies between regions without any prior model on the underlying functional interactions. We demonstrate the interest of this approach on real data.
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Correlation cannot reveal anything about causality, or even whether connectivity is direct versus indirect.
“Furthermore, correlation cannot reveal anything about causality, or even whether connectivity is direct vs indirect [49].”
From Functional connectomics from resting-state fMRI (2013) · cites this paper as [49]
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- Authors
- Marrelec, G., Krainik, A., Duffau, H., Pélégrini-Issac, M., Lehéricy, S., Doyon, J., & Benali, H.
- Affiliations
- Inserm (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Corresponding author
- Marrelec, Guillaume
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2006-08
- Volume
- 32
- Issue
- 1
- Pages
- 228-237
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2033881971
- Cited by
- 488
- References
- 67
- Citations by year
- 2026: 11 · 2025: 23 · 2024: 28 · 2023: 16 · 2022: 19 · 2021: 22 · 2020: 43 · 2019: 48 · 2018: 40 · 2017: 30 · 2016: 37 · 2015: 36 · 2014: 31 · 2013: 30 · 2012: 16
- FWCI
- 4.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- partial correlation, effective connectivity, brain network topology, functional MRI
- MeSH terms
- Cerebral Cortex, Humans, Functional Laterality, Magnetic Resonance Imaging, Models, Neurological, Motor Cortex, Nerve Net
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