The Effect of Neurofeedback on Eating Behaviour

Modulating Functional Connectivity Between Eating-related Brain Areas by Neurofeedback

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.

Study Overview

• Status: Unknown
• Conditions: Obesity; Eating Behaviour
• Intervention / Treatment: Device: Neurofeedback

Detailed 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.

• Study Type: Interventional
• Enrollment (Anticipated): 50
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Manfred Hallschmid, PhD; Phone Number: +49 7071 29-8825; Email: Manfred.Hallschmid@uni-tuebingen.de
• Study Contact Backup: Name: Maartje Spetter, PhD; Phone Number: +49 7071 29-81193; Email: Maartje.Spetter@uni-tuebingen.de

Study Locations

• Germany
  • Tuebingen, Germany, 72076
    • Recruiting
    • UKT and MPI
    • Contact: Manfred Hallschmid, PhD; Phone Number: +49 7071 29-8825; Email: Manfred.Hallschmid@uni-tuebingen.de
    • Sub-Investigator: Maartje Spetter, PhD
    • Principal Investigator: Manfred Hallschmid, PhD
    • Sub-Investigator: Ralf Veit, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 65 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

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 Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Neurofeedback; Neurofeedback training: Up-regulation of DLPFC.	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.; Other Names: Neurofeedback training; fMRI-based Brain Computer Interface (BCI); rtfMRI
Sham Comparator: Neurofeedback SHAM; Neurofeedback training: Sham-regulation of DLPFC.	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.; Other Names: Neurofeedback training; fMRI-based Brain Computer Interface (BCI); rtfMRI

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Food intake	Snack consumption during the snack test, comparing pre vs post neurofeedback session, and between the two groups (ANCOVA approach).	4 weeks
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
Weight	Difference in weight before and after training	4 weeks

Collaborators and Investigators

• Sponsor: University Hospital Tuebingen
• Investigators: Principal Investigator: Manfred Hallschmid, PhD, University Tuebingen

Publications and helpful links

General Publications

• 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.

Helpful Links

• Overview of main EU-project.

Study record dates

Study Major Dates

• Study Start: November 1, 2014
• Primary Completion (Anticipated): May 1, 2017
• Study Completion (Anticipated): May 1, 2017

Study Registration Dates

• First Submitted: May 14, 2014
• First Submitted That Met QC Criteria: May 27, 2014
• First Posted (Estimate): May 28, 2014

Study Record Updates

• Last Update Posted (Estimate): May 30, 2016
• Last Update Submitted That Met QC Criteria: May 27, 2016
• Last Verified: June 1, 2015

More Information

Terms related to this study

• Keywords: neurofeedback; overweight; self-control; rt-fmri; eating behaviour
• Other Study ID Numbers: 646/2013BO2

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: Yes
• IPD Plan Description: We will share the data inside the EU-consortium