Nicotine Dependence, Depression, PTSD
Conditions
Brief summary
The objective of the present study is to identify brain networks in patients that contribute to successfully learning self-regulation with real-time fMRI.
Detailed description
Neurofeedback has been established as a promising non-pharmacological therapeutic approach. However, patients differ in their ability to learn control over their own brain activity with neurofeedback. It is thus crucial to understand the brain networks that mediate learned self-regulation with real-time fMRI. The objective of the present study is thus to identify brain networks in patients that contribute to successfully learning self-regulation with real-time fMRI. To achieve this goal, patients suffering from depression, post-traumatic stress disorder, and nicotine addiction will be trained to improve their self-regulation skills using established real-time fMRI neurofeedback protocols.
Interventions
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.
OTHERSham Feedback
Sham controlled neurofeedback training. Subjects in the sham control group will undergo the same procedure as subjects in the experimental group, but instead of being shown feedback derived from their own brain activity, they will be shown replayed feedback values from a randomly chosen subject of the experimental group.
Sponsors
Frank Scharnowski
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
BASIC_SCIENCE
Masking
TRIPLE (Subject, Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
No
Inclusion criteria
* Magnetic resonance imaging compatibility. * DSM-V diagnosis of major depressive disorder, post-traumatic stress disorder, or nicotine addiction, respectively.
Exclusion criteria
* Other physical or psychiatric disorders. * Current substance abuse. *
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| brain patterns that mediate learning self-regulation in patients with fMRI neurofeedback | 12 months | Functional MRI data will be analysed using a whole brain mixed effect analysis across all subjects that compares brain patterns during self-regulation and baseline. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| neurofeedback learning success | 12 months | Increased self-regulation skills will be assessed by a comparison of the slopes of the neurofeedback learning curves between subjects in the experimental group vs. the sham control group. |
| behavioral consequences of neurofeedback training | 12 months | Behavioral outcome measures (questionnaires, standard clinical assessments) will be compared between subjects in the experimental group vs. the sham control group. |
| maintenance of learned self-regulation | 12 months | An assessment of learned self-regulation (i.e. increase of the feedback signal in up-regulation compared to baseline blocks) in follow-up scanning sessions that will take place 6 months and 1 year after neurofeedback training. This will be a measure of how well learned self-regulation can be maintained. |
Countries
Switzerland
Contacts
Primary ContactFrank Scharnowski, Prof. Dr.
Outcome results
None listed