Research On Emotion Network Feedback Based On Real-time FMRI Neurofeedback

With the pace of life and competition increasing,more and more people are suffering from emotional disturbance,and even neurological or mental illness,leading to the social and economic burden.The neurofeedback technique based on real-time functional magnetic resonance imaging(rt-fMRI)is an effective method and has a promising future in treatment of neurological or psychiatric disorders,having great value for the improvement of cognitive function,both clinical and social.However,most rt-fMRI neurofeedback studies for emotion regulation focus on regulation of neural activity within a single brain region.But,large-scale complex brain network is the physiological basis of information processing and expression of cognitive activities(including mood,attention,memory,etc.).Therefore,the exploration of the brain network connectivity mode and neural mechanism of emotional processing,as well as the research on rt-fMRI neurofeedback based on emotion network could provide the necessary theoretical and methodological basis for clinical application and transformation.This paper focuses on the key technical issues in rt-fMRI neurofeedback based on emotion network,including feedback target selection,feedback model building and feedback effect evaluation.The main work is as follows:1.It is difficult to describe the high-level cognitive activity of the human brain using single brain region.We proposed an emotional network analysis method based on multi-voxel function connectivity,in order to analyze and extract the key connectivity in the emotion network as the feedback target.Combining the results of neural nerve basic research and data-driven methods,we calculated the emotion network by seed point method,extracted the multi-voxel functional connectivity feature template and judged their importance according to the degree of emotional recognition.The experimental results show that the functional connectivity between the left amygdala and the right medial superior frontal gyrus in the limbic system is the key link in the emotional network,which is responsible for cognitive and emotional processing,and could be used as the feedback training target for emotion regulation.2.We proposed a feedback model based on functional connectivity and applied it to emotion regulation,for the reason that the feedback model based on neural activity within single brain region can't effectively reflect the mechanism of emotion regulation.The feedback model is constructed based on the key functional connectivity strength between the left amygdala and the right medial superior frontal gyrus,and the corresponding emotion regulation method based on the given functional connectivity is designed.The experiment results showed that brain is more sensitive to the functional regulation model than the single region model,and the neurofeedback model based on functional connectivity can reflect the mechanism of emotional cognition more effectively.3.Due to the lack of comprehensive and objective assessment of the neurofeedback effect,this paper presented an assessment method of using rest-state effective connectivity as biomarkers from the point of causality.We analyze the effective connectivity of amygdala using Granger causality model,and give the comparative analysis of the differences before and after the feedback training,and explored which effective connectivity could be biomarkers for effect evaluation.The experiment results showed that the interaction between the inner sub-region of the amygdala and the effective connectivity of the external network from the amygdala were increased after neurofeedback training,the abnormalities caused by the mood disorder is improved,and the effectiveness of the assessment method is verified.