<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/NCT03297437</url>
  </required_header>
  <id_info>
    <org_study_id>PsychiatricUHZPUK</org_study_id>
    <nct_id>NCT03297437</nct_id>
  </id_info>
  <brief_title>Predictors for Successful Neurofeedback Training</brief_title>
  <acronym>Predictors</acronym>
  <official_title>Predictors for Successful Neurofeedback Training</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Frank Scharnowski</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Psychiatric University Hospital, Zurich</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 primary objective of this study is to identify predictors of neurofeedback training&#xD;
      success.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      In the last decades, neurofeedback has been established as a promising scientific tool.&#xD;
      Learning voluntary control over their own brain activity allows for establishing causal links&#xD;
      between brain activity and mental functions. However, patients participants differ in their&#xD;
      ability to learn control over their own brain activity with neurofeedback. It is thus crucial&#xD;
      to understand why some participants are more successful in regulating their own brain&#xD;
      activity than others. The objective of the present study is thus to identify predictors for&#xD;
      successful learning self-regulation with real-time fMRI neurofeedback. To achieve this goal,&#xD;
      we will evaluate the introspection ability of healthy participants using standardized&#xD;
      psychological questionnaires and tasks. These scores will then be correlated with how well&#xD;
      they learned self-regulation skills using established real-time fMRI neurofeedback protocols.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Anticipated">October 1, 2017</start_date>
  <completion_date type="Anticipated">September 30, 2021</completion_date>
  <primary_completion_date type="Anticipated">September 30, 2021</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Basic Science</primary_purpose>
    <masking>Triple (Participant, Investigator, Outcomes Assessor)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>correlation between introspection scores and learning success</measure>
    <time_frame>48 months</time_frame>
    <description>The primary outcome measure is a correlation between introspection scores and neurofeedback learning success across all subjects.</description>
  </primary_outcome>
  <enrollment type="Anticipated">192</enrollment>
  <condition>Healthy</condition>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Neurofeedback training</intervention_name>
    <description>In a neurofeedback setting, brain activity is measured non-invasively, the brain imaging data is analyzed in real-time, and then feedback regarding the current level of brain activity is provided to the subject.</description>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        Age 18 - 65 years. Magnetic resonance imaging compatibility.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
        Physical or psychiatric disorders (DSM-V diagnosis). Current substance abuse. Exclusion&#xD;
        criteria applicable to MRI (metallic implants, claustrophobia, epilepsy).&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>65 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Frank Scharnowski, Prof. Dr.</last_name>
    <phone>+41443842953</phone>
    <email>Frank.Scharnowski@uzh.ch</email>
  </overall_contact>
  <location>
    <facility>
      <name>Hospital of Psychiatry, University of Zurich</name>
      <address>
        <city>Zürich</city>
        <state>Zürich-</state>
        <zip>8032</zip>
        <country>Switzerland</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Frank Scharnowski, Prof. Dr.</last_name>
      <phone>+41443842953</phone>
      <email>Frank.Scharnowski@uzh.ch</email>
    </contact>
    <contact_backup>
      <last_name>Ronald Sladky, PD Dr.</last_name>
      <phone>+41443842667</phone>
      <email>ronald.sladky@uzh.ch</email>
    </contact_backup>
  </location>
  <location_countries>
    <country>Switzerland</country>
  </location_countries>
  <verification_date>September 2017</verification_date>
  <study_first_submitted>September 26, 2017</study_first_submitted>
  <study_first_submitted_qc>September 26, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">September 29, 2017</study_first_posted>
  <last_update_submitted>September 28, 2017</last_update_submitted>
  <last_update_submitted_qc>September 28, 2017</last_update_submitted_qc>
  <last_update_posted type="Actual">October 2, 2017</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor-Investigator</responsible_party_type>
    <investigator_affiliation>Psychiatric University Hospital, Zurich</investigator_affiliation>
    <investigator_full_name>Frank Scharnowski</investigator_full_name>
    <investigator_title>Prof. Dr.</investigator_title>
  </responsible_party>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- 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/NCT03297437
org study id: PsychiatricUHZPUK
nct id: NCT03297437
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The primary objective of this study is to identify predictors of neurofeedback training
      success.
In the last decades, neurofeedback has been established as a promising scientific tool.
      Learning voluntary control over their own brain activity allows for establishing causal links
      between brain activity and mental functions. However, patients participants differ in their
      ability to learn control over their own brain activity with neurofeedback. It is thus crucial
      to understand why some participants are more successful in regulating their own brain
      activity than others. The objective of the present study is thus to identify predictors for
      successful learning self-regulation with real-time fMRI neurofeedback. To achieve this goal,
      we will evaluate the introspection ability of healthy participants using standardized
      psychological questionnaires and tasks. These scores will then be correlated with how well
      they learned self-regulation skills using established real-time fMRI neurofeedback protocols.
allocation: Randomized
intervention model: Single Group Assignment
primary purpose: Basic Science
masking: Triple (Participant, Investigator, Outcomes Assessor)
measure: correlation between introspection scores and learning success
time frame: 48 months
description: The primary outcome measure is a correlation between introspection scores and neurofeedback learning success across all subjects.
intervention type: Other
intervention name: Neurofeedback training
description: In a neurofeedback setting, brain activity is measured non-invasively, the brain imaging data is analyzed in real-time, and then feedback regarding the current level of brain activity is provided to the subject.
criteria: 
gender: All
minimum age: 18 Years
maximum age: 65 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Frank Scharnowski, Prof. Dr.
phone: +41443842953
email: Frank.Scharnowski@uzh.ch
facility: 
status: Recruiting
contact: 
contact backup: 
country: Switzerland
responsible party type: Sponsor-Investigator
investigator affiliation: Psychiatric University Hospital, Zurich
investigator full name: Frank Scharnowski
investigator title: Prof. Dr.
sharing ipd: No