emotional states
Research Papers
Neurofeedback Training With an Electroencephalogram-Based Brain-Computer Interface Enhances Emotion Regulation
Emotion regulation plays a vital role in human beings daily lives by helping them deal with social problems and protects mental and physical health. However, objective evaluation of the efficacy of emotion regulation and assessment of the improvement in emotion regulation ability at the individual level remain challenging. In this study, we leveraged neurofeedback training to design a real-time EEG-based brain-computer interface (BCI) system for users to effectively regulate their emotions. Twenty healthy subjects performed 10 BCI-based neurofeedback training sessions to regulate their emotion towards a specific emotional state (positive, negative, or neutral), while their EEG signals were analyzed in real time via machine learning to predict their emotional states. The prediction results were presented as feedback on the screen to inform the subjects of their immediate emotional state, based on which the subjects could update their strategies for emotion regulation. The experimental results indicated that the subjects improved their ability to regulate these emotions through our BCI neurofeedback training. Further EEG-based spectrum analysis revealed how each emotional state was related to specific EEG patterns, which were progressively enhanced through long-term training. These results together suggested that long-term EEG-based neurofeedback training could be a promising tool for helping people with emotional or mental disorders.
View Full Paper →Musical neurofeedback for treating depression in elderly people
We introduce a new neurofeedback approach, which allows users to manipulate expressive parameters in music performances using their emotional state, and we present the results of a pilot clinical experiment applying the approach to alleviate depression in elderly people. Ten adults (9 female and 1 male, mean = 84, SD = 5.8) with normal hearing participated in the neurofeedback study consisting of 10 sessions (2 sessions per week) of 15 min each. EEG data was acquired using the Emotiv EPOC EEG device. In all sessions, subjects were asked to sit in a comfortable chair facing two loudspeakers, to close their eyes, and to avoid moving during the experiment. Participants listened to music pieces preselected according to their music preferences, and were encouraged to increase the loudness and tempo of the pieces, based on their arousal and valence levels. The neurofeedback system was tuned so that increased arousal, computed as beta to alpha activity ratio in the frontal cortex corresponded to increased loudness, and increased valence, computed as relative frontal alpha activity in the right lobe compared to the left lobe, corresponded to increased tempo. Pre and post evaluation of six participants was performed using the BDI depression test, showing an average improvement of 17.2% (1.3) in their BDI scores at the end of the study. In addition, an analysis of the collected EEG data of the participants showed a significant decrease of relative alpha activity in their left frontal lobe (p = 0.00008), which may be interpreted as an improvement of their depression condition.
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