Controlling your brain activity in real-time —
when neuroimaging and therapy converge

Imagine being able to see and then control your brain activity consciously in real-time. For example, when thinking about a positive life event like your birthday, you would see the activity of your brain’s limbic system — core structures involved in processing emotions and memory— increase on a thermometer-like gauge on a screen. Simply seeing this change could further boost your morale: This is the goal of neurofeedback training, which is getting its own boost from a recent research project called BRAINTRAIN.

Neurofeedback is a promising new technique for psychiatry and neurology. Like any new medical approach, clinical trials are the gold standard in providing evidence for efficacy. BRAINTRAIN is a consortium of European researchers studying the clinical potential of using functional magnetic imaging (fMRI) for neurofeedback training. Now in its fourth year, the project is working on clinical trials to test the technique’s efficacy for several focus areas, including alcohol addiction (Cardiff, UK), anxiety in teenagers (Oxford, UK), autism spectrum disorder (Coimbra, Portugal), obesity (Tuebingen, Germany), and post-traumatic stress disorder (Tel Aviv, Israel).

With neurofeedback, scientists can potentially help patients increase “healthy” brain signatures, or decrease brain signals associated with negative symptoms, like cravings in addiction. In the training process, patients learn to explore different mental strategies and the effects they have in self-regulating the fMRI brain signal that they can see in real time. In doing so, the brain activity associated with a certain thought process determines the feedback the person sees. This feedback acts like a teaching signal to learn optimal mental strategies. Real-time fMRI neurofeedback is thus an intervention that puts the individual at the core of the experiment.

real-time fMRI neurofeedback setup to treat alcohol dependence. Image credit: Cox et al. Trials. 2016; 17: 480.

For example, David Linden and colleagues at Cardiff University Brain Research Imaging Centre (CUBRIC) are investigating if neurofeedback training helps patients with alcohol addiction to stay sober. The protocol uses personalized images to provide immersive visual feedback to patients. In one such training session, while in the fMRI scanner, pictures of their favorite drinks are projected on a screen for the patient to view. During a first so called “localizer scan”, researchers determine a target brain area, e.g. the insular cortex, that is activated while viewing the pictures of the drinks and thus, is likely involved in the craving sensation. During neurofeedback training scans, the size of those pictures scales with the activation level of the target brain area. The patient’s goal is to use mental strategies that work well in reducing the craving — for example, remembering situations in which they remained abstinent. The idea is to pair successful reduction of the feeling with less activation in the respective brain area and reduce the size of the shown picture (see Figure, adapted from Cox et. al 2016). Based on a very similar principle, colleagues at the University of Tuebingen in Germany use food stimuli to test if neurofeedback training can help obese patients control their eating behavior and reduce weight.

Linking up new technologies with the human brain has real future promise for rehabilitative medicine in psychiatry and neurology. Neurofeedback is a way to bridge the mind and brain. As with every new technology, neurofeedback is still largely under development with many new methods being introduced and challenges that need to be addressed. For instance, it is not clear which training protocol is most efficient for a specific condition. One technical challenge for fMRI neurofeedback training are head movements — even relatively small but sudden movements can comprise the signal quality significantly. Also, fMRI does not directly measure the response of neural activity but reflects the ratio of oxygenated over deoxygenated blood. These relative levels depend on energy consumption of local neural populations, and also on other physiological factors such as heartbeat and respiration, which adds further noise. Future studies will need to assess the effects of these sources of noise and explore remedies that improve the method.

As the outcomes of more BRAINTRAIN trials become available, the potential of real-time fMRI as a clinical tool for treating patients will become clearer. But one thing is already crystal clear: learning to control the activity of a specific brain region in your brain in real time is no longer a pipe dream. The method shows promise for many clinical applications.

Further Reading:

Sitaram et al., 2016

Stoeckl et al., 2014

Cox et al., 2016