xml: <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/NCT05987865</url>
    </required_header>
    <id_info>
      <org_study_id>249990</org_study_id>
      <nct_id>NCT05987865</nct_id>
    </id_info>
    <brief_title>Neurofeedback Training for PD</brief_title>
    <official_title>EEG- or STN LFP-based Neurofeedback Training for Improving Motor Functions in Parkinson's Disease</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>University of Oxford</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>St George's London University Hospitals NHS Foundation Trust</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>King's College Hospital NHS Trust</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>University of Oxford</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        The goal of this clinical trial is to test neurofeedback training in both people with&#xD;
        Parkinson's disease and healthy control.&#xD;
  &#xD;
        The main questions it aims to answer are:&#xD;
  &#xD;
          -  To demonstrate that EEG based or STN LFP based neurofeedback can help patients with&#xD;
             Parkinson's disease to volitionally modulate pathological brain activities measured&#xD;
             non-invasively;&#xD;
  &#xD;
          -  To evaluate the learning effect of the neurofeedback training with multiple training&#xD;
             sessions&#xD;
  &#xD;
        Patient participants will be asked to receive the research intervention called neurofeedback&#xD;
        training for maximal three separate sessions. During the intervention, the participants will&#xD;
        also be asked to press a pinch meter as fast as possible in order to measure the reaction&#xD;
        time, meanwhile, different type of brain signals will be recorded.&#xD;
  &#xD;
        . This will be a within-subject cross-over study contrasting the effect of the neurofeedback&#xD;
        training and no training.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">September 1, 2023</start_date>
    <completion_date type="Anticipated">August 30, 2026</completion_date>
    <primary_completion_date type="Anticipated">February 28, 2026</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>N/A</allocation>
      <intervention_model>Single Group Assignment</intervention_model>
      <primary_purpose>Basic Science</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>The feasibility of using EEG-based neurofeedback to help patients with Parkinson's disease to volitionally modulate pathological brain activities measured non-invasively.</measure>
      <time_frame>10 days</time_frame>
      <description>The final position of the cursor and beta power changes after neurofeedback training will be measured and reported.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Learning effect of the neurofeedback training with multiple training sessions</measure>
      <time_frame>10 days</time_frame>
      <description>The final positions of the cursor and the changes in beta power will be measured and compared across different training sessions.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>The effect of EEG-based neurofeedback on motor performance quantified as reaction time in patients with Parkinson's disease</measure>
      <time_frame>10 days</time_frame>
      <description>The reaction time following cued motor task will be measured, and compared between training and no-training conditions.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>The effect of EEG-based neurofeedback on motor performance quantified as peak movement velocity in patients with Parkinson's disease</measure>
      <time_frame>10 days</time_frame>
      <description>The peak movement velocity during the cued motor task will be measured, and compared between training and no-training conditions.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>The effect of EEG-based neurofeedback on parkinsonian tremor</measure>
      <time_frame>10 days</time_frame>
      <description>The acceleration data will be measured from patient's arms during neurofeedback training, which will be used to quantity the tremor severity by looking at the power at patient specific tremor frequency band. The comparison on tremor severity between training and no-training conditions will be reported.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>The effect of EEG-based neurofeedback on motor Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score</measure>
      <time_frame>10 days</time_frame>
      <description>MDS-UPDRS is a comprehensive 50 question assessment of both motor and non-motor symptoms associated with Parkinson's. Each question will be scored between 0 and 5, with a higher value indicates more severe assessment. In this study, the motor part of UPDRS scores on the patients will be measured, and compared before and after neurofeedback training.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>The effect of EEG-based neurofeedback on motor performance quantified as reaction time in healthy age-matched control</measure>
      <time_frame>10 days</time_frame>
      <description>The reaction time following cued motor task will be measured, and compared between training and no-training conditions in healthy age-matched control group.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>The peak movement velocity during the cued motor task will be measured, and compared between training and no-training conditions in healthy age-matched control group.</measure>
      <time_frame>10 days</time_frame>
      <description>This will be assessed by comparing the peak movement velocity during the cued motor task between training and no-training conditions.</description>
    </secondary_outcome>
    <number_of_arms>1</number_of_arms>
    <enrollment type="Anticipated">40</enrollment>
    <condition>Parkinson Disease</condition>
    <condition>Healthy</condition>
    <arm_group>
      <arm_group_label>People with Parkinson's disease or Healthy Control</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>The experimental arm involves either patients with PD or healthy control, who will receive both experimental or non-experimental (control) intervention conditions.</description>
    </arm_group>
    <intervention>
      <intervention_type>Behavioral</intervention_type>
      <intervention_name>Neurofeedback training</intervention_name>
      <description>Features related to PD symptoms will be extracted from the brain recordings in real-time and used to drive a visual cursor on a computer screen placed in front of the participant, while the participant will be asked to try to control the cursor by regulating their brain signals.</description>
      <arm_group_label>People with Parkinson's disease or Healthy Control</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Participants with symptomatic Parkinson's disease or age-matched healthy control&#xD;
  &#xD;
            -  Adequate understanding of verbal explanation or written information given in English&#xD;
  &#xD;
            -  Able and willing to give informed consent.&#xD;
  &#xD;
            -  Normal or corrected-to-normal vision&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Lack of capacity to consent (judged by the researcher taking consent as not having&#xD;
               sufficient mental capacity to understand the study and its requirements)&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>75 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_contact>
      <last_name>Huiling Tan</last_name>
      <phone>01865 572483</phone>
      <phone_ext>44</phone_ext>
      <email>huiling.tan@ndcn.ox.ac.uk</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Shenghong He</last_name>
      <phone>01865 572483</phone>
      <phone_ext>44</phone_ext>
      <email>shenghong.he@ndcn.ox.ac.uk</email>
    </overall_contact_backup>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>July 26, 2023</study_first_submitted>
    <study_first_submitted_qc>August 3, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 14, 2023</study_first_posted>
    <last_update_submitted>August 14, 2023</last_update_submitted>
    <last_update_submitted_qc>August 14, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 18, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Parkinson Disease</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>Undecided</sharing_ipd>
      <ipd_description>The investigators will share the fully anonymized brain recordings and behavioural data on the Oxford Research Archives or the MRC Brain Network Dynamics Unit Data Sharing platform.</ipd_description>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT05987865
  org study id: 249990
  nct id: NCT05987865
  lead sponsor: 
  collaborator: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  The goal of this clinical trial is to test neurofeedback training in both people with
        Parkinson's disease and healthy control.
  
        The main questions it aims to answer are:
  
          -  To demonstrate that EEG based or STN LFP based neurofeedback can help patients with
             Parkinson's disease to volitionally modulate pathological brain activities measured
             non-invasively;
  
          -  To evaluate the learning effect of the neurofeedback training with multiple training
             sessions
  
        Patient participants will be asked to receive the research intervention called neurofeedback
        training for maximal three separate sessions. During the intervention, the participants will
        also be asked to press a pinch meter as fast as possible in order to measure the reaction
        time, meanwhile, different type of brain signals will be recorded.
  
        . This will be a within-subject cross-over study contrasting the effect of the neurofeedback
        training and no training.
  allocation: N/A
  intervention model: Single Group Assignment
  primary purpose: Basic Science
  masking: None (Open Label)
  measure: The feasibility of using EEG-based neurofeedback to help patients with Parkinson's disease to volitionally modulate pathological brain activities measured non-invasively.
  time frame: 10 days
  description: The final position of the cursor and beta power changes after neurofeedback training will be measured and reported.
  measure: Learning effect of the neurofeedback training with multiple training sessions
  time frame: 10 days
  description: The final positions of the cursor and the changes in beta power will be measured and compared across different training sessions.
  measure: The effect of EEG-based neurofeedback on motor performance quantified as reaction time in patients with Parkinson's disease
  time frame: 10 days
  description: The reaction time following cued motor task will be measured, and compared between training and no-training conditions.
  measure: The effect of EEG-based neurofeedback on motor performance quantified as peak movement velocity in patients with Parkinson's disease
  time frame: 10 days
  description: The peak movement velocity during the cued motor task will be measured, and compared between training and no-training conditions.
  measure: The effect of EEG-based neurofeedback on parkinsonian tremor
  time frame: 10 days
  description: The acceleration data will be measured from patient's arms during neurofeedback training, which will be used to quantity the tremor severity by looking at the power at patient specific tremor frequency band. The comparison on tremor severity between training and no-training conditions will be reported.
  measure: The effect of EEG-based neurofeedback on motor Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score
  time frame: 10 days
  description: MDS-UPDRS is a comprehensive 50 question assessment of both motor and non-motor symptoms associated with Parkinson's. Each question will be scored between 0 and 5, with a higher value indicates more severe assessment. In this study, the motor part of UPDRS scores on the patients will be measured, and compared before and after neurofeedback training.
  measure: The effect of EEG-based neurofeedback on motor performance quantified as reaction time in healthy age-matched control
  time frame: 10 days
  description: The reaction time following cued motor task will be measured, and compared between training and no-training conditions in healthy age-matched control group.
  measure: The peak movement velocity during the cued motor task will be measured, and compared between training and no-training conditions in healthy age-matched control group.
  time frame: 10 days
  description: This will be assessed by comparing the peak movement velocity during the cued motor task between training and no-training conditions.
  arm group label: People with Parkinson's disease or Healthy Control
  arm group type: Experimental
  description: The experimental arm involves either patients with PD or healthy control, who will receive both experimental or non-experimental (control) intervention conditions.
  intervention type: Behavioral
  intervention name: Neurofeedback training
  description: Features related to PD symptoms will be extracted from the brain recordings in real-time and used to drive a visual cursor on a computer screen placed in front of the participant, while the participant will be asked to try to control the cursor by regulating their brain signals.
  arm group label: People with Parkinson's disease or Healthy Control
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: 75 Years
  healthy volunteers: Accepts Healthy Volunteers
  last name: Huiling Tan
  phone: 01865 572483
  phone ext: 44
  email: huiling.tan@ndcn.ox.ac.uk
  last name: Shenghong He
  phone: 01865 572483
  phone ext: 44
  email: shenghong.he@ndcn.ox.ac.uk
  responsible party type: Sponsor
  mesh term: Parkinson Disease
  sharing ipd: Undecided
  ipd description: The investigators will share the fully anonymized brain recordings and behavioural data on the Oxford Research Archives or the MRC Brain Network Dynamics Unit Data Sharing platform.