Combined distributed source and single-trial EEG-fMRI modeling: application to effortful decision making processes

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Psychophysiology

Background:

• Simultaneously recorded EEG and fMRI data enable high-resolution brain activity mapping.
• Previous research linked early anterior cingulate cortex (ACC) activation to effortful decision-making using single-trial EEG-fMRI coupling.

Purpose of the Study:

• To identify effort-specific electroencephalography (EEG) event-related potential (ERP) sources, specifically the N1 component.
• To explore single-trial EEG-fMRI correlations for source-specific inter-modality coupling effects related to cognitive effort.

Main Methods:

• Whole-cortex distributed EEG analysis was performed.
• Trial-by-trial variation in local source power was used for single-trial EEG-fMRI coupling analysis.
• A forced choice reaction task with varying effort levels was employed.

Main Results:

• A high-effort-specific ERP-N1 source was localized in the ACC.
• Statistically significant differential EEG-fMRI coupling was observed in five cortical regions, including the ACC.
• Results highlight the neural origins of effort-specific EEG and fMRI modulations.

Conclusions:

• Early ACC activation plays a central role in motivation-related decision-making.
• Combining distributed source modeling with single-trial coupling enriches the interpretation of EEG-fMRI data.
• This approach provides deeper insights into the neural mechanisms underlying cognitive effort.