Method for spatial overlap estimation of electroencephalography and functional magnetic resonance imaging responses

Neural correlates of individual differences in moral identity and its positive moral function

Moral identity is an important moral variable which has positive moral functions, such as contributing to prosocial behaviours, reducing antisocial behaviours, and resisting the risk factors of antisocial behaviours. However, little is known about the neural correlates of moral identity and the neural basis of the effect of moral identity on the risk factors of antisocial behaviours, including moral disengagement. In this study, we explored these issues in 142 college students by estimating the regional homogeneity (ReHo) through resting-state functional magnetic resonance imaging (fMRI). The whole-brain correlation analyses found that higher internalized moral identity was correlated with higher ReHo in the precuneus. Furthermore, the ReHo in the precuneus was negatively correlated with moral disengagement, suggesting positive moral functions of the neural mechanisms of moral identity. These findings deepen our understanding of individual differences in moral identity and provide inspiration for the education of moral identity and the intervention for moral disengagement from the perspective of the brain.

EEG and fMRI coupling and decoupling based on joint independent component analysis (jICA)

BACKGROUND

Meaningful integration of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) requires knowing whether these measurements reflect the activity of the same neural sources, i.e., estimating the degree of coupling and decoupling between the neuroimaging modalities.

NEW METHOD

This paper proposes a method to quantify the coupling and decoupling of fMRI and EEG signals based on the mixing matrix produced by joint independent component analysis (jICA). The method is termed fMRI/EEG-jICA.

RESULTS

fMRI and EEG acquired during a syllable detection task with variable syllable presentation rates (0.25-3 Hz) were separated with jICA into two spatiotemporally distinct components, a primary component that increased nonlinearly in amplitude with syllable presentation rate, putatively reflecting an obligatory auditory response, and a secondary component that declined nonlinearly with syllable presentation rate, putatively reflecting an auditory attention orienting response. The two EEG subcomponents were of similar amplitude, but the secondary fMRI subcomponent was ten folds smaller than the primary one.

COMPARISON TO EXISTING METHOD

FMRI multiple regression analysis yielded a map more consistent with the primary than secondary fMRI subcomponent of jICA, as determined by a greater area under the curve (0.5 versus 0.38) in a sensitivity and specificity analysis of spatial overlap.

CONCLUSION

fMRI/EEG-jICA revealed spatiotemporally distinct brain networks with greater sensitivity than fMRI multiple regression analysis, demonstrating how this method can be used for leveraging EEG signals to inform the detection and functional characterization of fMRI signals. fMRI/EEG-jICA may be useful for studying neurovascular coupling at a macro-level, e.g., in neurovascular disorders.