Emotion Regulation
Conditions
Brief summary
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.
Detailed description
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.
Interventions
DEVICEBCI
As participants listen to the music, the EEG waves of their affective states and their variations detected in real-time is converted into an auditory signal providing direct feedback to participants about their affective states and assisting participants to learn and practice emotion regulation.
Sponsors
Agency for Science, Technology and Research
Duke-NUS Graduate Medical School
Institute of Mental Health, Singapore
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DEVICE_FEASIBILITY
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
60 Years to 85 Years
Healthy volunteers
Yes
Inclusion criteria
* English-speaking * Geriatric Depression Scale score of 4 and below * Fit to provide informed consent * Able to travel to study site independently
Exclusion criteria
* Presence of hearing impairment * Presence of any known neuropsychiatric disorders (e.g. dementia, epilepsy or mental retardation) * Contraindications for MRI such as surgical clips, cardiac pacemakers, metal implants and plates, orthodontics and claustrophobia
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Positive and Negative Affect Scale (PANAS) | Week 0 and Week 9 | To evaluate change in PANAS score |
| Emotion regulation questionnaire (ERQ) | Week 0 and Week 9 | To evaluate change in ERQ scores |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Geriatric Depression Scale (GDS) | Week 0 and Week 9 | To evaluate change in GDS score |
| Positive Mental Health (PMH) instrument | Week 0 and Week 9 | To evaluate change in PMH score |
| Body Awareness Questionnaire (BAQ) | Week 0 and Week 9 | To evaluate change in BAQ |
| Subjective Happiness Scale | Week 0 and Week 9 | To evaluate change in SHS |
| The Frenchay Activities Index (FAI) | Week 0 and Week 9 | To evaluate change in FAI scores |
| Medical Outcomes Study: 20-item short form survey instrument | Week 0 and Week 9 | — |
| Outcome rating scale | After each BCI session during Weeks 1 to 8 | — |
| Usability questionnaire | At the end of Week 8 | Participants in the intervention group will rate statements regarding their satisfaction and ease of use of the training components on a 7-point Likert scale |
| Connor-Davidson Resilience Scale 25 (CD-RISC-25) | Week 0 and Week 9 | To evaluate change in CD-RISC-25 score |
| Brief Assessment of Cognition - Short form | Week 0 and Week 9 | To evaluate changes in neurocognition |
Other
| Measure | Time frame | Description |
|---|---|---|
| Changes in functional MRI | Week 0 and Week 9 | To examine the neural mechanism underlying the intervention |
Countries
Singapore
Outcome results
None listed