Emotion Regulation Clinical Trial
Official title:
Affect Regulation Based on Brain-computer Interface Towards Treatment for Depression
The primary objective is to examine the feasibility and efficacy of a locally developed brain-computer interface (BCI) based system training for regulating mood in healthy elderly. The investigators hypothesize that elderly who complete the training program will be better at regulating emotions as compared to controls, based on their ratings of the primary outcome measures.
In this project, we will leverage on a locally developed electroencephalograph (EEG)-based
BCI technology for decoding affective states of the brain, and thereby develop a closed-loop
sensing and stimulation mechanism. The technology uses advanced neural signal computing on
the EEG in real-time and audio feedback using a machine learning model that associates
individual user's EEG characteristics in relation to music-emotion features. The system is
portable and will allow emotion regulation training to be done outside of hospital setting
with ease thus potentially addressing the treatment gap for MDD in the elderly.
This is a two group randomized study. One group will undergo the intervention which is 24
sessions of BCI emotion regulation training (i.e. listening to music with audio feedback to
regulate emotions towards positive affect) over an 8-week period. The control group will
undergo 8 weeks of music sessions, without any emotion regulation training. Both groups will
undergo pre- and post- psychometric assessments looking at cognition, quality of life,
functioning and emotional states. This study will also carry out functional MRI of the brain
before and after 8 weeks of either training (intervention) or music music session (control)
to examine changes associated with the affective BCI training. Study findings derived from
psychometric assessments, EEG analysis and neuroimaging will provide evidences on efficacy
and usability of this technology.
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