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Updated: Feb 24, 2026
Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
Published on: June 30, 2018
Complementary contributions of concurrent EEG and fMRI connectivity for predicting structural connectivity.
Jonathan Wirsich1, Ben Ridley2, Pierre Besson2
1Aix Marseille Université, CNRS, CRMBM 7339, 13385 Marseille, France; AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, 13385 Marseille, France; Aix Marseille Université, Inserm, UMR_S 1106, INS, Institut de Neurosciences des Systèmes, 13385 Marseille, France.
Combining electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) significantly improves understanding of brain structure-function relationships compared to fMRI alone. This integrated approach offers a more complete picture of neural activity in resting-state networks.
Area of Science:
- Neuroscience
- Network Neuroscience
- Brain Imaging
Background:
- The relationship between large-scale brain function and structure is a key unsolved problem in network neuroscience.
- Functional brain dynamics (EEG, fMRI) are hypothesized to arise from an underlying structural architecture (dMRI).
- The independent or complementary contributions of EEG and fMRI to this function-structure relationship are not well understood.
Purpose of the Study:
- To explore the function-structure correlation using simultaneous resting-state EEG-fMRI and dMRI.
- To determine if combined EEG-fMRI provides a better explanation of dMRI connectivity than fMRI alone.
- To investigate how different connectivity metrics and network scales influence the function-structure relationship.
Main Methods:
- Simultaneous resting-state EEG-fMRI and dMRI were acquired from fourteen healthy subjects.
- Function-structure correlation was analyzed using connectivity matrices.
- Model improvement was assessed by comparing fMRI-only models with combined EEG-fMRI models.
Main Results:
- The combination of EEG and fMRI connectivity significantly improved the explanation of dMRI connectivity compared to fMRI-only models.
- This model improvement was observed at both group-averaged and individual levels.
- The best model fit involved fMRI and EEG-δ connectivity, influenced by Euclidean distance and interhemispheric connectivity, with local EEG-γ contributions.
Conclusions:
- Combined EEG-fMRI provides a more comprehensive understanding of the brain's structure-function relationship.
- The factors mediating this relationship are context- and scale-dependent, involving topological, geometric, and architectural features.
- Simultaneous EEG measures in fMRI studies capture essential resting-state neuronal activity, valuable for clinical and research applications.
