<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02228187</url>
  </required_header>
  <id_info>
    <org_study_id>B-14-099</org_study_id>
    <nct_id>NCT02228187</nct_id>
  </id_info>
  <brief_title>Brain-Computer Interface System for Training Memory and Attention in Elderly</brief_title>
  <official_title>Brain-computer Interface System for Training Memory and Attention in Elderly With Subjective Memory Deficits and Age Related Cognitive Decline (ARCD)</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Duke-NUS Graduate Medical School</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Agency for Science, Technology and Research</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>National University of Singapore</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Singapore Clinical Research Institute</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Singapore General Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Tan Tock Seng Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Duke-NUS Graduate Medical School</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The primary objective is to examine the efficacy of 8-weeks of a locally developed&#xD;
      brain-computer interface based system intervention for improving attention and memory in&#xD;
      healthy elderly and those with age related cognitive decline. We hypothesize that elderly who&#xD;
      have completed the training program will have significant improvement in their attention and&#xD;
      memory compared to the controls, based on the Repeatable Battery for the Assessment of&#xD;
      Neuropsychological Status.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The world population has reached an unprecedented seven billion, with global population&#xD;
      ageing increasing at a greater rate than total population growth. Between 1998 and 2030, the&#xD;
      proportion of persons aged 65 years and over in Singapore will grow by about 3% annually&#xD;
      compared to 1.0-1.3% in some developed nations. Specific cognitive deficits like inattention,&#xD;
      dysexecutive functioning, and processing speed decline may affect a number of quality of life&#xD;
      domains. Concurrent with these statistics, the maintenance of the highest possible level of&#xD;
      cognitive functioning for as long as possible has become an important goal of aging&#xD;
      successfully.&#xD;
&#xD;
      To contribute to the realization of this goal we propose to conduct a wait-list control trial&#xD;
      to examine the efficacy of this brain-computer interface based intervention for cognitive&#xD;
      enhancement in elderly. This intervention uses a technology which analyzes brain waves&#xD;
      captured through an electroencephalogram to determine the participants' state of attention.&#xD;
      The training program developed using this patented technology may be useful for individuals&#xD;
      who experience difficulty with memory and sustaining their attention.&#xD;
&#xD;
      This intervention may represent one alternative means to enhance cognitive abilities and to&#xD;
      slow down cognitive decline in the normal elderly. If demonstrated to be efficacious, this&#xD;
      therapy may even help to delay the onset of dementia.&#xD;
&#xD;
      In addition, the rate of cognitive decline during the course of AD is possibly influenced by&#xD;
      not only environmental but also genetic factors. To date, several genes, such as&#xD;
      apolipoprotein E (APOE) and TOMM40 (translocase of outer mitochondrial membrane 40&#xD;
      homologue), have been identified to be probable genetic risk markers for AD. These genes have&#xD;
      been shown to play a role in disease onset as well as rates of cognitive decline. For&#xD;
      instance, studies have shown APOEε4 allele carriers to be associated with earlier and faster&#xD;
      cognitive decline.&#xD;
&#xD;
      Therefore, we propose to analyse if there is any relationship between the genetic profiles of&#xD;
      our participants and their performance in the training program.&#xD;
&#xD;
      There are no published studies that look at how cognitive training may be associated with&#xD;
      changes in the metabolism and functional connectivity of the brain. Therefore, our study also&#xD;
      aims to carry out functional MRI of the brain before and after training to gain a finer&#xD;
      understanding of the changes associated with our BCI-based cognitive training.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>July 2015</start_date>
  <completion_date type="Actual">June 2017</completion_date>
  <primary_completion_date type="Actual">June 2017</primary_completion_date>
  <phase>Phase 2</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Crossover Assignment</intervention_model>
    <primary_purpose>Prevention</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Total Score of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)</measure>
    <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</time_frame>
    <description>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.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Sum of Scaled Score of the Rivermead Behavioral Memory Test-II</measure>
    <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</time_frame>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Number of Adverse Events/Serious Adverse Events Reported</measure>
    <time_frame>Throughout the intervention period (Up to 20 weeks) for both groups</time_frame>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Usability Measure of the Brain-Computer Interface training system</measure>
    <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)</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <other_outcome>
    <measure>Relationship between genetic profile of participants and their performance on the training program</measure>
    <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)</time_frame>
    <description>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.</description>
  </other_outcome>
  <other_outcome>
    <measure>Changes in functional MRI</measure>
    <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</time_frame>
    <description>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.</description>
  </other_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">240</enrollment>
  <condition>Alzheimer's Disease</condition>
  <condition>Mild Cognitive Impairment</condition>
  <condition>Age-Related Cognitive Decline</condition>
  <condition>Dementia</condition>
  <arm_group>
    <arm_group_label>BCI Intervention</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>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.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Waitlist Control Group</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>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.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Brain-Computer Interface</intervention_name>
    <description>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.</description>
    <arm_group_label>BCI Intervention</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Age 60-80 years old&#xD;
&#xD;
          -  Clinical Dementia Rating (CDR) of 0-0.5&#xD;
&#xD;
          -  Mini Mental State Examination (MMSE) of 24 and above&#xD;
&#xD;
          -  Geriatric Depression Scale (GDS) of 4 and below&#xD;
&#xD;
          -  Chinese Ethnicity&#xD;
&#xD;
          -  Literate in English&#xD;
&#xD;
          -  Able to travel to study site independently&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Any known neuropsychiatric disorders (such as epilepsy or mental retardation)&#xD;
&#xD;
          -  Involvement in another research study (aside from the Singapore Longitudinal Ageing&#xD;
             Study)&#xD;
&#xD;
          -  Gross hearing, visual or speech impairment that are uncorrected&#xD;
&#xD;
          -  Color Blindness&#xD;
&#xD;
          -  Intake of the following medications: Rivastigmine, Donepezil, Galantamine or&#xD;
             Memantine.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>60 Years</minimum_age>
    <maximum_age>80 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Tih Shih Lee, MD, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Duke-NUS Medical School, Duke University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Duke-NUS Medical School</name>
      <address>
        <city>Singapore</city>
        <zip>169857</zip>
        <country>Singapore</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Singapore</country>
  </location_countries>
  <verification_date>July 2017</verification_date>
  <study_first_submitted>August 27, 2014</study_first_submitted>
  <study_first_submitted_qc>August 27, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">August 28, 2014</study_first_posted>
  <last_update_submitted>July 31, 2017</last_update_submitted>
  <last_update_submitted_qc>July 31, 2017</last_update_submitted_qc>
  <last_update_posted type="Actual">August 2, 2017</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Duke-NUS Graduate Medical School</investigator_affiliation>
    <investigator_full_name>Lee Tih Shih</investigator_full_name>
    <investigator_title>Associate Professor</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Alzheimer Disease</mesh_term>
    <mesh_term>Cognitive Dysfunction</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02228187
org study id: B-14-099
nct id: NCT02228187
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
has dmc: No
The primary objective is to examine the efficacy of 8-weeks of a locally developed
      brain-computer interface based system intervention for improving attention and memory in
      healthy elderly and those with age related cognitive decline. We hypothesize that elderly who
      have completed the training program will have significant improvement in their attention and
      memory compared to the controls, based on the Repeatable Battery for the Assessment of
      Neuropsychological Status.
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.
allocation: Randomized
intervention model: Crossover Assignment
primary purpose: Prevention
masking: None (Open Label)
measure: 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
description: 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.
measure: 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
measure: Number of Adverse Events/Serious Adverse Events Reported
time frame: Throughout the intervention period (Up to 20 weeks) for both groups
measure: 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)
description: 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.
measure: 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)
description: 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.
measure: 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
description: 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.
arm group label: BCI Intervention
arm group type: Active Comparator
description: 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.
arm group label: Waitlist Control Group
arm group type: No Intervention
description: 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.
intervention type: Device
intervention name: Brain-Computer Interface
description: 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.
arm group label: BCI Intervention
criteria: 
gender: All
minimum age: 60 Years
maximum age: 80 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Tih Shih Lee, MD, PhD
role: Principal Investigator
affiliation: Duke-NUS Medical School, Duke University
facility: 
country: Singapore
responsible party type: Principal Investigator
investigator affiliation: Duke-NUS Graduate Medical School
investigator full name: Lee Tih Shih
investigator title: Associate Professor
mesh term: Alzheimer Disease
mesh term: Cognitive Dysfunction