Distributed analysis of simultaneous EEG-fMRI time-series: modeling and interpretation issues

Area of Science:

• Neuroscience
• Cognitive Science
• Biophysics

Background:

• Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) offer complementary insights into neural processes.
• Integrating EEG and fMRI is challenging due to the different physical natures of their signals and varying temporal scales.

Purpose of the Study:

• To illustrate a framework for combining simultaneously recorded EEG and fMRI signals.
• To enable spatial and temporal comparative analysis of neural activity using EEG distributed source modeling.

Main Methods:

• Defined a common source space for projecting EEG and fMRI signals.
• Developed a framework for integrated spatial and temporal analysis.
• Applied the framework to a graded-load working memory experiment using the n-back task.

Main Results:

• Demonstrated colocalization of sustained blood-oxygenation-level-dependent (BOLD) signal changes and parametric EEG theta synchronization in midline frontal regions.
• Showcased the ability to observe phenomena at different temporal scales within a unified framework.
• Validated the approach in two single-subject cases.

Conclusions:

• The presented framework effectively integrates simultaneous EEG-fMRI data.
• This approach enhances the interpretation of cognitive experiments by linking signals across different temporal scales.
• Addresses key modeling and interpretation challenges in combined EEG-fMRI studies.