Brain-Computer Interface System for Training Memory and Attention in Elderly
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|ClinicalTrials.gov Identifier: NCT02228187|
Recruitment Status : Completed
First Posted : August 28, 2014
Last Update Posted : August 2, 2017
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|Condition or disease||Intervention/treatment||Phase|
|Alzheimer's Disease Mild Cognitive Impairment Age-Related Cognitive Decline Dementia||Device: Brain-Computer Interface||Phase 2|
The world population has reached an unprecedented seven billion, with global population ageing increasing at a greater rate than total population growth. Between 1998 and 2030, the proportion of persons aged 65 years and over in Singapore will grow by about 3% annually compared to 1.0-1.3% in some developed nations. Specific cognitive deficits like inattention, dysexecutive functioning, and processing speed decline may affect a number of quality of life domains. Concurrent with these statistics, the maintenance of the highest possible level of cognitive functioning for as long as possible has become an important goal of aging successfully.
To contribute to the realization of this goal we propose to conduct a wait-list control trial to examine the efficacy of this brain-computer interface based intervention for cognitive enhancement in elderly. This intervention uses a technology which analyzes brain waves captured through an electroencephalogram to determine the participants' state of attention. The training program developed using this patented technology may be useful for individuals who experience difficulty with memory and sustaining their attention.
This intervention may represent one alternative means to enhance cognitive abilities and to slow down cognitive decline in the normal elderly. If demonstrated to be efficacious, this therapy may even help to delay the onset of dementia.
In addition, the rate of cognitive decline during the course of AD is possibly influenced by not only environmental but also genetic factors. To date, several genes, such as apolipoprotein E (APOE) and TOMM40 (translocase of outer mitochondrial membrane 40 homologue), have been identified to be probable genetic risk markers for AD. These genes have been shown to play a role in disease onset as well as rates of cognitive decline. For instance, studies have shown APOEε4 allele carriers to be associated with earlier and faster cognitive decline.
Therefore, we propose to analyse if there is any relationship between the genetic profiles of our participants and their performance in the training program.
There are no published studies that look at how cognitive training may be associated with changes in the metabolism and functional connectivity of the brain. Therefore, our study also aims to carry out functional MRI of the brain before and after training to gain a finer understanding of the changes associated with our BCI-based cognitive training.
|Study Type :||Interventional (Clinical Trial)|
|Actual Enrollment :||240 participants|
|Intervention Model:||Crossover Assignment|
|Masking:||None (Open Label)|
|Official Title:||Brain-computer Interface System for Training Memory and Attention in Elderly With Subjective Memory Deficits and Age Related Cognitive Decline (ARCD)|
|Study Start Date :||July 2015|
|Actual Primary Completion Date :||June 2017|
|Actual Study Completion Date :||June 2017|
Active Comparator: BCI Intervention
Subjects will undergo the Brain-Computer Interface Intervention for 24 sessions over the span of 8 weeks. Each session will take 30-minute to complete. The intervention group will undergo the intervention in the first 8 weeks of the trial.
Device: Brain-Computer Interface
Brain-computer Interface (BCI) is a direct communication pathway between a human brain and an external device. It is a technology that enables people to interact with computers through their thoughts. Electroencephalography (EEG) is the best studied non-invasive interface facilitating such communication. The BCI system will take EEG recordings from the prefrontal cortex to determine the participants' state of attention with high specificity. The training program developed using this patented technology may be useful for individuals who experience difficulty with memory and sustaining their attention.
No Intervention: Waitlist Control Group
The waitlist control will start their 8 week treatment after the completion of the intervention group from week 9 onwards. They will undergo the BCI intervention for 24 sessions over the span of 8 weeks.
- Total Score of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) [ Time Frame: Comparison in the change of RBANS total score from pre-treatment (Week 0) to post-treatment (Week 9) in Intervention Group versus Waitlist-Control group ]The Total Score on RBANS reflects the neurocognitive status of the participant by summing five index/domain scores. The domains are Immediate Memory, Visuospatial/Constructional, Language, Attention, and Delayed Memory.
- Sum of Scaled Score of the Rivermead Behavioral Memory Test-II [ Time Frame: Comparison in the change of RBMT-2 sum of scale score from pre-treatment (Week 0) to post-treatment (Week 9) in Intervention Group versus Waitlist-Control group ]
- Number of Adverse Events/Serious Adverse Events Reported [ Time Frame: Throughout the intervention period (Up to 20 weeks) for both groups ]
- Usability Measure of the Brain-Computer Interface training system [ Time Frame: At the end of the 8 weeks of treatment for both groups (Week 20 for the Intervention group, Week 29 for the Waitlist-Control group) ]Participants will rate their agreeableness on 7 statements regarding their satisfaction and ease of use of the training components on a 7-point Likert scale.
- Relationship between genetic profile of participants and their performance on the training program [ Time Frame: Blood samples will be collected pre-treatment (Week 0) and at end of study participation (Week 20 for Intervention group, Week 29 for Waitlist-Control group) ]Blood samples will be collected from each subject for DNA and RNA extraction. The samples will be used to generate a genetic profile for each subject. The presence or absence of genes of interest (i.e. TOMM40 and APOEε4) on a subject's genetic profile will then be associated with his or her corresponding performance on BCI, as measured by his or her RBANS scores.
- Changes in functional MRI [ Time Frame: Comparison in the change of fMRI during: Pre-treatment (Week 0), post-treatment (Week 9), and post booster sessions (Week 20) for the Intervention group; Baseline (Week 0), pre-treatment (Week 9), and post-treatment (Week 20) for Waitlist-control group ]Changes in the functional connectivity between the default mode network and task-positive networks (control network (dorsolateral prefrontal cortex), salience network (insula/anterior cingulate cortex)) will be compared based on observations made from fMRI scans pre-treatment versus post-treatment.
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|Ages Eligible for Study:||60 Years to 80 Years (Adult, Older Adult)|
|Sexes Eligible for Study:||All|
|Accepts Healthy Volunteers:||Yes|
- Age 60-80 years old
- Clinical Dementia Rating (CDR) of 0-0.5
- Mini Mental State Examination (MMSE) of 24 and above
- Geriatric Depression Scale (GDS) of 4 and below
- Chinese Ethnicity
- Literate in English
- Able to travel to study site independently
- Any known neuropsychiatric disorders (such as epilepsy or mental retardation)
- Involvement in another research study (aside from the Singapore Longitudinal Ageing Study)
- Gross hearing, visual or speech impairment that are uncorrected
- Color Blindness
- Intake of the following medications: Rivastigmine, Donepezil, Galantamine or Memantine.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02228187
|Duke-NUS Medical School|
|Singapore, Singapore, 169857|
|Principal Investigator:||Tih Shih Lee, MD, PhD||Duke-NUS Medical School, Duke University|
|Responsible Party:||Lee Tih Shih, Associate Professor, Duke-NUS Graduate Medical School|
|Other Study ID Numbers:||
|First Posted:||August 28, 2014 Key Record Dates|
|Last Update Posted:||August 2, 2017|
|Last Verified:||July 2017|
Central Nervous System Diseases
Nervous System Diseases