Brain Scans Could Reveal The Likelihood Of Depression Treatment Success


Stephen Luntz

Stephen has a science degree with a major in physics, an arts degree with majors in English Literature and History and Philosophy of Science and a Graduate Diploma in Science Communication.

Freelance Writer

Electroencephalography measurements of the rostral anterior cingulate cortex could help predict how well someone will respons to antidepressants. YAKOBCHUK VIACHESLAV 


Strong activity in a specific section of the brain can help predict the success of antidepressant drugs, a study has found. The work could make it easier to choose the right therapy for people with serious depression, and possibly even improve our understanding of the causes of the condition.

One of the reasons depression remains so widespread, and so destructive, is that it's hard to establish the best approach for an individual. Some people benefit from pharmacological options – such as selective serotonin reuptake inhibitors (SSRIs) – others from psychotherapy, and others from changes in lifestyle. We desperately need ways to match the treatment to the patient that aren't just a doctor's preference.


Harvard's Dr Diego Pizzagalli has previously shown that people with high activity on brain scans of the rostral anterior cingulate cortex (rACC) are more likely to benefit from antidepressant drugs. The rACC is particularly active when we feel we've made a mistake. This predictive capacity hadn't been compared with existing, fairly unreliable measures.

In Jama Psychiatry, Pizzagalli and co-authors report on a sample of 296 patients given either the antidepressant sertraline (Zoloft) or a placebo, of whom 248 had an electroencephalogram (EEG) to measure their brain activity in the rACC. Greater rACC activity, both prior to the start of medication and a week after treatment, was found to be a statistically significant predictor of how well people's depression responded eight weeks into treatment. This value remained after controlling for clinical and demographic data sometimes used to predict treatment outcomes.

So far, the predictive power is limited. Even combined with existing tests, Pizzgalli could predict less than 40 percent of the variation in treatment responses, but this was still 8.5 percent higher than could be done without using the EEGs. Co-author Dr Christian Webb said in a statement that the work “demonstrate[s] the 'incremental predictive validity'” of rACC activity.

Despite being far from perfect, Pizzagalli proposes: "For those with the marker of good response, a clinician could tell patients that they have a high chance of benefiting from the intervention, and they should stay engaged in treatment." Where rACC activity is lower, doctors might propose psychotherapy, alone or in combination with antidepressants, and also monitor responses more closely.


Besides avoiding the four to eight weeks it takes to learn that someone is not responding to SSRIs, a test like the one Pizzagalli is proposing could spare people from experiencing the often serious side-effects of these drugs if they wouldn't benefit. More ambitiously, the authors hope future studies will find ways to match EEG activity to specific treatment options, for example which antidepressants are most likely to suit individual patients. They also hope to find ways to boost rACC activity to increase the prospects for a response.


  • tag
  • depression,

  • SSRIs,

  • electroencephalography,

  • rostral anterior cingulate cortex,

  • treatment predictions