The Effect of Neurofeedback on Eating Behaviour

Obesity Clinical Trial

Official title:

Modulating Functional Connectivity Between Eating-related Brain Areas by Neurofeedback

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT02148770
• Other study ID #: 646/2013BO2
• Status: Recruiting
• Phase: N/A
• First received: May 14, 2014
• Last updated: May 27, 2016
• Start date: November 2014
• Est. completion date: May 2017

Study information

• Verified date: June 2015
• Source: University Hospital Tuebingen
• Contact: Manfred Hallschmid, PhD
• Phone: +49 7071 29-8825
• Email: Manfred.Hallschmid[@]uni-tuebingen.de
• Is FDA regulated: No
• Health authority: Germany: Ethics Commission
• Study type: Interventional

Clinical Trial Summary

Neuroimaging is becoming increasingly common to investigate the neural networks underlying eating behaviour and food preference in normal-weight and obese humans. It has been observed that obese in comparison to lean individuals display altered activation patterns in networks of brain areas involved in reward, emotion and cognitive control. Interestingly, obese individuals who are capable of losing weight appear to have a stronger connectivity between areas related to food value and to the control of eating behaviour. The same areas are also associated with healthy food choices. It has been suggested that activation in the prefrontal control areas indirectly modulate valuation-related activity. Based on this, brain-related intervention strategies to support weight loss and long-lasting weight maintenance are of particular interest. Hence, we first want to examine the effect on eating behaviour of neurofeedback training-induced up-regulation of functional connectivity between reward- and impulse-related brain areas as a pilot, and second we want to examine up-regulation of the activity of prefrontal control brain areas.

Description:

Primary objective: We want to investigate whether the training-induced up-regulation of the dorsal prefrontal cortex inhibits eating behaviour.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 50
• Est. completion date: May 2017
• Est. primary completion date: May 2017
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Both
• Age group: 18 Years to 65 Years

Eligibility

Inclusion Criteria:

• Healthy male and female subjects

• 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:

• Subjects who have a non-removable metal object in or at their body, such as, for ex-ample:

• 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

Study Design

Allocation: Randomized, Intervention Model: Parallel Assignment, Masking: Single Blind (Subject), Primary Purpose: Treatment

Related Conditions & MeSH terms

• Eating Behaviour
• Obesity

Intervention

Device:
• 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.

Locations

Country	Name	City	State
Germany	UKT and MPI	Tuebingen

Sponsors (1)

Lead Sponsor	Collaborator
University Hospital Tuebingen

Country where clinical trial is conducted

Germany, 

References & Publications (2)

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. 2007:25487. doi: 10.1155/2007/25487. — View Citation

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. Epub 2005 Nov 10. Review. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Activity in the dlPFC during the training-session	Differences in dlPFC activity between baseline and after up-regulation during the neurofeedback training session, as well as the difference between the treatment and the sham groups (ANCOVA approach).	1 day	No
Secondary	Food intake	Snack consumption during the snack test, comparing pre vs post neurofeedback session, and between the two groups (ANCOVA approach).	4 weeks	No
Secondary	Preferred food (healthy or unhealthy food).	Differences in food choice (healthy vs unhealthy) pre compared to post neurofeedback session and between the two groups (ANCOVA approach).	4 weeks	No
Secondary	Weight	Difference in weight before and after training	4 weeks	No

External Links

•   Overview of main EU-project.