Self-regulating positive emotion networks by feedback of multiple emotional brain states using real-time fMRI

Disordered emotion regulation may affect work efficiency, induce social disharmony, and even cause psychiatric diseases. Despite recent neurocomputing advances, whether positive and negative emotion networks can be voluntarily modulated is still unknown. In the present study, we addressed this question through multivariate voxel pattern analysis and real-time functional MRI neurofeedback (rtfMRI-nf). During a sustained emotion regulation task, participants' emotional states (positive or negative) were given to them as feedback. Participants were able to increase the percentage of positive emotional states, enhancing emotion regulation network activities. Participants showed an improvement on the positive subscale of positive and negative affect scale that came close to significance. Furthermore, the activation of several emotion-related brain regions, including insula, amygdala, anterior cingulate cortex, and dorsomedial prefrontal cortex, was also increased during rtfMRI-nf training. These findings suggest that humans are able to voluntarily modulate positive emotion networks, leading to exciting applications in the treatment of various neurological and psychiatric disorders.