Scan Your Brain, Predict and Prevent Depression?

A recent study in PLoS One about predicting and preventing depression by using functional brain imaging as a tool [1]. The study abstract can be viewed at link

The possibility of preventing depression by looking for changes in neuroimaging is a relatively novel idea and would be a big step forward in preventing one of the biggest public health burdens facing the nation and the world. I like the idea of using evidence-based psychotherapy to help protect young people against depression, especially since we already know that psychotherapy changes the brain, according to Karlsson from a recent Psychiatric Times article [2]. An excerpt from my recent post of January 29, 2012 about this:

Did you also know that psychotherapy can change the brain? A recently published article in Psychiatric Times discussed the recent research also going on that show psychotherapy itself can change brain function, demonstrable in functional brain MRI, positron emission tomography (PET), and single photon emission CT (SPECT). About 20 studies have been done in the last two decades demonstrating that talk therapy can induce changes in the brain similar to antidepressant. Different types of psychotherapy such as Cognitive Behavioral Therapy (CBT) and Interpersonal Psychotherapy (IPT) can alter brain function in a variety of psychiatric disorders including but not limited to depression, obsessive compulsive disorder, posttraumatic stress disorder, and panic disorder.

Many psychotherapies attempt to engage and enhance the ability of patients to problem-solve and regulate their own emotions. One of the brain areas that play a role in functions like these is the medial prefrontal cortex among many other areas, many of them in the frontal lobe.

This strategy could help young people develop resiliency to prevent depression and add a valuable self-help tool for those at risk for developing mood disorders, which can lead to other vulnerabilities to additional medical problems such as coronary artery disease.

1. Mourão-Miranda, J., L. Oliveira, et al. (2012). “Pattern Recognition and Functional Neuroimaging Help to Discriminate Healthy Adolescents at Risk for Mood Disorders from Low Risk Adolescents.” PLoS ONE 7(2): e29482.

Introduction: There are no known biological measures that accurately predict future development of psychiatric disorders in individual at-risk adolescents. We investigated whether machine learning and fMRI could help to: 1. differentiate healthy adolescents genetically at-risk for bipolar disorder and other Axis I psychiatric disorders from healthy adolescents at low risk of developing these disorders; 2. identify those healthy genetically at-risk adolescents who were most likely to develop future Axis I disorders. Methods:16 healthy offspring genetically at risk for bipolar disorder and other Axis I disorders by virtue of having a parent with bipolar disorder and 16 healthy, age- and gender-matched low-risk offspring of healthy parents with no history of psychiatric disorders (12–17 year-olds) performed two emotional face gender-labeling tasks (happy/neutral; fearful/neutral) during fMRI. We used Gaussian Process Classifiers (GPC), a machine learning approach that assigns a predictive probability of group membership to an individual person, to differentiate groups and to identify those at-risk adolescents most likely to develop future Axis I disorders. Results: Using GPC, activity to neutral faces presented during the happy experiment accurately and significantly differentiated groups, achieving 75% accuracy (sensitivity = 75%, specificity = 75%). Furthermore, predictive probabilities were significantly higher for those at-risk adolescents who subsequently developed an Axis I disorder than for those at-risk adolescents remaining healthy at follow-up. Conclusions: We show that a combination of two promising techniques, machine learning and neuroimaging, not only discriminates healthy low-risk from healthy adolescents genetically at-risk for Axis I disorders, but may ultimately help to predict which at-risk adolescents subsequently develop these disorders.

2. Karlsson, H., MA, MD, PhD (2011). How Psychotherapy Changes the Brain: Understanding the Mechanisms. Psychiatric Times, UBM Medica. 28.