Closed-loop individual EEG neurofeedback of appetite interventions: a conceptual framework

An increasingly influential perspective conceptualizes both obesity and overeating accompanied by corresponding brain changes, generating interest in treatment options targeting these neural activities. As a promising noninvasive treatment method, EEG neurofeedback technology is widely used for self-regulation of brain activity by subjects. Given individual variations and other factors, the outcomes of feedback regulation training using standard protocols have not been optimal. Here, we propose an appetite intervention system framework of individual EEG neurofeedback, especially for obese people caused by poor dietary habits. An individual appetite classification model based on the EEG signal induced by the food cue reactivity task is the highlighted foundation, which can be used for food craving recognition and quantification in real-time neurofeedback. Furthermore, in this framework, to adapt to personal preferences, the visual signal feedback materials were individually selected by the subjects to match the degree of food craving, providing reward and punishment feedback signals to guide individualized appetite regulation.