Brain ‘noise’ key to successful psychotherapy

In psychiatry, it is difficult to assess whether a patient will improve with treatment. Fluctuations in brain activity, from second to second, can reliably predict whether patients with social anxiety will improve with cognitive behavioral therapy (CBT). This was shown by a study conducted by researchers from the Karolinska Institutet and the Max Planck Institute for Human Development in Germany.

Fluctuations in brain activity have long been considered a sign of unwanted “noise” in the brain. But this asymmetry or variance, second to second, in brain signals has been shown to be a sign of individual differences and competence in neuron function.

Researchers have long wanted to find useful ways to predict success in psychotherapy, but it has proven to be a difficult challenge.

Reliable diagnosis using brain signals

To be able to do this, the research group designed a unique study; 45 patients with social anxiety had their brains scanned using fMRI during passive rest and when they looked at other people’s faces (a relevant task in social anxiety patients). Brain imaging was performed twice every 11 weeks.

After the examination, patients received online cognitive-behavioral therapy for nine weeks. The variance measured when people looked at other people’s faces was the strongest and most reliable predictor of treatment outcome, even though the task took less than three minutes to complete.

Variation in brain signals is often seen as noise that should be minimized before further analysis. We show that this variance can be a reliable measure for predicting success in psychotherapy, especially if one analyzes second-to-second brain fluctuations. We must reconsider the usual measurement methods in fMRI to maximize the clinical utility of brain imaging, says Christopher Monson, a psychologist and researcher in the Department of Clinical Neuroscience at Karolinska Institutet.

It is possible to predict a specific treatment

In the next stage, the researchers will collect more data and investigate whether it is possible to predict what specific treatment a patient should undergo, by measuring brain diversity.

For the measurement to be clinically useful, it not only needs to know how well a patient will improve with a particular treatment, but it must also predict the most appropriate treatment for the patient. He says defining this is our long-term goal Douglas Jarrett , search leader for Lifespan Neural Dynamics Group vid The UCL Max Planck Center for Computational Psychiatry and Research on Aging I am Berlin.

Scientific Publication:

The fluctuation of instantaneous brain signals reliably predicts psychotherapy outcomesAnd Christopher NT Manson, Leonard Waschke, Amir Hossein Mansouri, Thomas Formark, Hakan Fischer, Douglas de Garrett. Biological Psychiatry