Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
50 participants
INTERVENTIONAL
2014-11-30
2017-05-31
Brief Summary
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Detailed Description
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Study design: A parallel design. Half of the participants will learn to up-regulate activity of the dorsolateral prefrontal cortex (dlPFC), while the other participants will participate in sham-training sessions. Adherence to experimental conditions will be assigned randomly, based on the participants' enrolment in the study, balanced by gender and binge eating classification.
Study population: 50 overweight and obese (BMI 25-40 kg/m2), but otherwise healthy individuals, 18-65 years old.
Intervention: All participants will participate in a screening day, followed by one neurofeedback session day and a follow-up day. During the neurofeedback session, participants will undergo a 45 min real-time-fMRI-brain-computer-interface scan in order to learn to up-regulate dlPFC activation.
Main study parameters/endpoints:
1. The ability to up-regulate dlPFC activity.
2. Respective effects on eating behaviour. Nature and extent of the burden and risks associated with participation: Participants will be scanned once (fMRI). Functional MRI is a safe and non-invasive technique.
Conditions
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Keywords
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Study Design
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RANDOMIZED
PARALLEL
TREATMENT
SINGLE
Study Groups
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Neurofeedback
Neurofeedback training: Up-regulation of DLPFC.
Neurofeedback
Networks involved in eating behaviour can be modified by neurofeedback training. We will perform a neurofeedback task using the technology of fMRI-based Brain Computer Interface (BCI). BCI approaches based on real-time fMRI (rtfMRI) allow voluntary regulation of brain regions. For the rtfMRI, a well-established setup will be used which translates the blood oxygen level dependent (BOLD) signal of a specific brain region of interest into a visual signal (e.g. moving bar) in real time using brain voyager® and matlab. The study will include 1 training-sessions In the up-regulation condition subjects will learn to up regulate their dlPFC. In the sham-condition subjects are get the same instructions, however they will receive sham feedback.
Neurofeedback SHAM
Neurofeedback training: Sham-regulation of DLPFC.
Neurofeedback
Networks involved in eating behaviour can be modified by neurofeedback training. We will perform a neurofeedback task using the technology of fMRI-based Brain Computer Interface (BCI). BCI approaches based on real-time fMRI (rtfMRI) allow voluntary regulation of brain regions. For the rtfMRI, a well-established setup will be used which translates the blood oxygen level dependent (BOLD) signal of a specific brain region of interest into a visual signal (e.g. moving bar) in real time using brain voyager® and matlab. The study will include 1 training-sessions In the up-regulation condition subjects will learn to up regulate their dlPFC. In the sham-condition subjects are get the same instructions, however they will receive sham feedback.
Interventions
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Neurofeedback
Networks involved in eating behaviour can be modified by neurofeedback training. We will perform a neurofeedback task using the technology of fMRI-based Brain Computer Interface (BCI). BCI approaches based on real-time fMRI (rtfMRI) allow voluntary regulation of brain regions. For the rtfMRI, a well-established setup will be used which translates the blood oxygen level dependent (BOLD) signal of a specific brain region of interest into a visual signal (e.g. moving bar) in real time using brain voyager® and matlab. The study will include 1 training-sessions In the up-regulation condition subjects will learn to up regulate their dlPFC. In the sham-condition subjects are get the same instructions, however they will receive sham feedback.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* Age 18-65 years at start of the study
* Body Mass Index (BMI) between 25 and 40 kg/m2
* Informed consent to study protocol
* Willingness to be informed about chance findings of pathology and approval of the disclosure of this information to the general physician (see Informed Consent)
* Fulfilment of the criteria for blood donors according to the "Richtlinien zur Gewinnung von Blut und Blutbestandteilen und zur Anwendung von Blutprodukten", in particular Hb ≥ 135 g/l (8,37 mmol/l; Bundesärztekammer 2010)
Exclusion Criteria
* Heart pace-maker
* Artificial heart valve
* Metal prosthesis
* Metallic implants (screws, plates from operations, etc.)
* Metal splinters / grenade fragments
* Non-removable dental braces
* Acupuncture needles
* Insulin pump
* Intraport, etc.
* In field strengths of over 1.0 T also: tattoos, eye lid-shadow
* Current weight loss regimens
* Limited temperature perception and/or increased sensitivity to warming of the body
* Pathological hearing ability or an increased sensitivity to loud noises
* Claustrophobia
* Lack of ability to give informed consent
* Operation less than three month ago
* Simultaneous participation in other studies
* Acute illness or infection during the last 4 weeks
* Neurological disorder or injury
* Moderate or severe head injury
* Severe psychotic illness
* Intake of antidepressants / antipsychotics
* Participation in other studies with blood withdrawals or blood donation in previous and subsequent 2 months
18 Years
65 Years
ALL
Yes
Sponsors
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University Hospital Tuebingen
OTHER
Responsible Party
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Principal Investigators
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Manfred Hallschmid, PhD
Role: PRINCIPAL_INVESTIGATOR
University Tuebingen
Locations
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UKT and MPI
Tübingen, , Germany
Countries
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Central Contacts
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Facility Contacts
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Manfred Hallschmid, PhD
Role: primary
References
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Weiskopf N, Scharnowski F, Veit R, Goebel R, Birbaumer N, Mathiak K. Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI). J Physiol Paris. 2004 Jul-Nov;98(4-6):357-73. doi: 10.1016/j.jphysparis.2005.09.019. Epub 2005 Nov 10.
Sitaram R, Caria A, Veit R, Gaber T, Rota G, Kuebler A, Birbaumer N. FMRI brain-computer interface: a tool for neuroscientific research and treatment. Comput Intell Neurosci. 2007;2007:25487. doi: 10.1155/2007/25487.
Spetter MS, Malekshahi R, Birbaumer N, Luhrs M, van der Veer AH, Scheffler K, Spuckti S, Preissl H, Veit R, Hallschmid M. Volitional regulation of brain responses to food stimuli in overweight and obese subjects: A real-time fMRI feedback study. Appetite. 2017 May 1;112:188-195. doi: 10.1016/j.appet.2017.01.032. Epub 2017 Jan 25.
Related Links
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Overview of main EU-project.
Other Identifiers
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646/2013BO2
Identifier Type: -
Identifier Source: org_study_id