NCT02148770

Brief 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.

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
50

participants targeted

Target at P25-P50 for not_applicable obesity

Timeline
Completed

Started Nov 2014

Typical duration for not_applicable obesity

Geographic Reach
1 country

1 active site

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

May 14, 2014

Completed
14 days until next milestone

First Posted

Study publicly available on registry

May 28, 2014

Completed
5 months until next milestone

Study Start

First participant enrolled

November 1, 2014

Completed
2.5 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

May 1, 2017

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

May 1, 2017

Completed
Last Updated

May 30, 2016

Status Verified

June 1, 2015

Enrollment Period

2.5 years

First QC Date

May 14, 2014

Last Update Submit

May 27, 2016

Conditions

ObesityEating Behaviour

Keywords

rt-fmriself-controleating behaviouroverweightneurofeedback

Outcome Measures

Primary Outcomes (1)

  • 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 Outcomes (3)

  • Food intake

    4 weeks

  • Preferred food (healthy or unhealthy food).

    4 weeks

  • Weight

    4 weeks

Study Arms (2)

Neurofeedback

EXPERIMENTAL

Neurofeedback training: Up-regulation of DLPFC.

Device: Neurofeedback

Neurofeedback SHAM

SHAM COMPARATOR

Neurofeedback training: Sham-regulation of DLPFC.

Device: Neurofeedback

Interventions

NeurofeedbackDEVICE

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.

Also known as: fMRI-based Brain Computer Interface (BCI), Neurofeedback training, rtfMRI
NeurofeedbackNeurofeedback SHAM

Eligibility Criteria

Age18 Years - 65 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • 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)

You may not qualify if:

  • 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
  • +9 more criteria

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

UKT and MPI

Tübingen, 72076, Germany

RECRUITING

Related Publications (3)

  • 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.

    PMID: 16289548BACKGROUND

  • 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.

    PMID: 18274615BACKGROUND

  • 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.

    PMID: 28131758DERIVED

Related Links

MeSH Terms

Conditions

ObesityFeeding BehaviorSelf-ControlOverweight

Interventions

Neurofeedback

Condition Hierarchy (Ancestors)

OvernutritionNutrition DisordersNutritional and Metabolic DiseasesBody WeightSigns and SymptomsPathological Conditions, Signs and SymptomsBehavior, AnimalBehaviorSocial Behavior

Intervention Hierarchy (Ancestors)

Biofeedback, PsychologyMind-Body TherapiesComplementary TherapiesTherapeuticsBehavior TherapyPsychotherapyBehavioral Disciplines and ActivitiesFeedback, Psychological

Study Officials

  • Manfred Hallschmid, PhD

    University Tuebingen

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Manfred Hallschmid, PhD

CONTACT

+49 7071 29-8825Manfred.Hallschmid@uni-tuebingen.de

Maartje Spetter, PhD

CONTACT

+49 7071 29-81193Maartje.Spetter@uni-tuebingen.de

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
PARTICIPANT
Purpose
TREATMENT
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

May 14, 2014

First Posted

May 28, 2014

Study Start

November 1, 2014

Primary Completion

May 1, 2017

Study Completion

May 1, 2017

Last Updated

May 30, 2016

Record last verified: 2015-06

Data Sharing

IPD Sharing
Will share

We will share the data inside the EU-consortium

Locations

DE(1)