The study developed a memory task training system using functional near-infrared spectroscopy(fNIRS)and neurofeedback mechanisms,and acquired and analyzed subjects'EEG signals.The results showed that subjects participating in the neurofeedback task had higher correlated brain network node degrees and average cluster coefficients in the right hemisphere brain region of the prefrontal lobe,with relatively lower dispersion of mediator centrality.In addition,the subjects'left hemisphere brain region of the prefrontal lobe section had increased centrality in the neurofeedback task.Classification of brain data by the channel network model and the support vector machine model showed that the classification accuracy of both models was higher in the task state and resting state than in the feedback task and the control task,and the classification accuracy of the channel network model was higher.The results suggested that subjects in the neurofeedback task had distinct brain data features and that these features could be effectively recognized.
关键词
功能性近红外光谱技术/神经反馈/脑网络/通道网络模型
Key words
functional near-infrared spectroscopy/neurofeedback/brain network/channel network model
维普
万方数据