Instantaneous fluctuations in brain activity can reliably predict outcomes of psychiatric treatment

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It remains a central challenge in psychiatry to reliably judge whether a patient will respond to treatment. In a new study published in the journal Biological Psychiatry, researchers at Karolinska Institutet in Sweden and the Max Planck Institute for Human Development in Germany show that moment-to-moment fluctuations in brain activity can reliably predict whether patients with dementia Social anxiety will be receptive to cognitive behavioral therapy (CBT).

Viable predictors of response to psychiatric treatment are often sought, but remain elusive. Brain imaging techniques such as functional magnetic resonance imaging (fMRI) have shown promise, but their low reliability has limited the utility of typical fMRI measurements as early warning signs of treatment success. Although historically considered to be a marker of “noise” in the brain, moment-to-moment variability in brain signal continues to gain traction as a sensitive and reliable indicator of individual differences in the effectiveness of brain therapy. neuronal function. However, neuronal variability had not yet been examined in relation to the outcome of psychiatric treatment.

To do this, the research team designed a unique study; 45 patients with social anxiety disorder had their brains imaged during passive rest and emotional facial visualization (a task related to social anxiety) in two sessions (11 weeks apart) to capture neural variability from one moment to the next. Then, the patients underwent a 9-week cognitive behavioral therapy delivered via the Internet. The researchers showed that the variability of the brain signal measured during the emotional task was the strongest and most reliable predictor of treatment outcome, although the task only took patients three minutes.

The variability in brain signals is often thought of as measurement “noise”, something to be eliminated before further analysis. We show the first evidence that neuronal variability can be a reliable and effective predictor of psychiatric treatment outcomes, particularly when task designs relevant to the disorder are used. We simply need to rethink our standard approaches in psychiatric neuroimaging to maximize clinical impact. “

Dr Kristoffer MÃ¥nsson, senior author, clinical psychologist and researcher, Department of Clinical Neurosciences, Karolinska Institutet

In the next phase of their research, the authors will collect larger samples to examine whether the variability of the brain signal can predict what specific treatment a patient should undergo.

“If moment-to-moment neural variability is to be worth its weight in gold as a clinically useful predictor of treatment outcome, it should tell clinicians not only how well a patient will respond to a given treatment, but also if treatment A or B is better. Establishing this will be our long term goal. In the meantime, our methods are immediately and openly available to any researcher interested in whether neural variability offers clinical utility within and beyond patients with social anxiety disorders, ”says lead author Dr. Douglas Garrett, leader of the Lifespan Neural Dynamics group at the Max Planck UCL Center for Computational Psychiatry and Aging Research in Berlin.

The study was conducted in close collaboration with the Max Planck UCL Center for Computational Psychiatry and Aging Research and the Max Planck Institute for Human Development in Berlin, Germany, and Stockholm University, Uppsala University and the Umeå Functional Brain Imaging Center in Sweden. It was funded by the Swedish Research Council, the Swedish Brain Foundation and the German Research Foundation. No conflict of interest was reported.

Source:

Journal reference:

MÃ¥nsson, KNT, et al. (2021) The variability of the brain signal from one moment to another reliably predicts the outcome of psychiatric treatment. Biological Psychiatry. doi.org/10.1016/j.biopsych.2021.09.026.


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