Skip to Content

Brain Waves Predict Suicide Risk

A new technique might help doctors foresee suicidal thoughts before a patient even has them.

Over the past five years, an increasing number of studies have pointed to the rare but serious risk of suicidal thoughts that can accompany new antidepressant treatments. Close monitoring is currently the only clinical option, but a new technique–one that measures and analyzes electrical activity of the brain–could one day predict which people might be most susceptible to antidepressant-induced suicide.

Suicidal thoughts: This image shows brain activity measured using quantitative EEG (blue indicates a decrease in activity, red an increase). Patients who experienced suicidal thoughts at any time during the eight-week study showed a sixfold greater drop in brain activity within 48 hours of beginning treatment (top) compared to patients who showed no increase in suicidal thoughts (bottom).

While uncommon, the gravity of suicide risk was enough to prompt the U.S. Food and Drug Administration to place a “black box” warning on multiple antidepressant labels. So in order to tease out those individuals at highest risk, researchers at the University of California at Los Angeles’s Laboratory of Brain, Behavior, and Pharmacology are using an approach called quantitative EEG (QEEG).

Electroencephalography (EEG) uses a cap of electrodes placed at multiple locations across the scalp, each of which measures electrical activity coming from the brain at that particular spot. Neurologists frequently use EEG readouts to diagnose conditions such as epilepsy or brain injury. But instead of using the raw data–a set of jerky, squiggly lines, with each line corresponding to a single electrode–UCLA researchers employ an algorithm that mathematically analyzes data from all of the electrodes to transform the results into a map of brain activity.

The lab is using this quantitative EEG to determine how different individuals’ brains respond to different antidepressants, trying to find early markers that indicate whether a new therapy will be effective. But in addition to efficacy, research psychologist Aimee Hunter is also interested in side effects, since those often appear long before any improvement in mood. “And with all the increased press about antidepressants causing suicidal ideation, I began looking for brain changes that might specifically be related to that,” says Hunter, who is the lead author of a paper about the research, which was published in the April issue of Acta Psychiatrica Scandinavica.

An earlier study by Hunter and her colleagues, in which healthy volunteers were placed on either placebo or antidepressants, pinpointed the midline-and-right-frontal (MRF) portion of the brain as a region of interest. Those on medication showed moderately decreased activity in this area after just a week, while placebo-takers exhibited a slight increase. Focusing on the MRF region, Hunter then examined QEEGs from 72 adult patients who had been randomly assigned to take either medication or placebo for eight weeks. At multiple time points–48 hours, one week, two weeks, four weeks, and eight weeks after starting their therapy–the patients returned for QEEG measurements and a mood-assessment questionnaire.

When Hunter examined the results, she found a striking effect: Those patients on antidepressants who indicated any increase in suicidal thoughts also showed a drastic decrease in activity in their MRF region just 48 hours after starting their meds–six times the decrease shown in subjects with no change in suicidal thoughts. But after one week, the two groups were nearly identical again.

“It was very strange: There was a very large downward spike, and then … nothing,” Hunter says. “But the suicidal worsening isn’t happening at 48 hours–it’s happening at some later point over the next eight weeks.” She was seeing what appeared to be a harbinger of future response.

“They’re onto something important,” says Barry Lebowitz, a professor of psychiatry at the University of California at San Diego, who was not involved with the research. “This is clearly a first step in trying to personalize antidepressant treatment.”

Lebowitz, who has worked with the UCLA group on prior projects, notes that other techniques that could potentially predict a patient’s response to antidepressants are incredibly expensive, and not practical for widespread use. “But the kind of physiological measure this group is talking about is something people can use. An EEG machine is something that every doctor could have in the office for relatively small amounts of money.”

The results may also prove helpful in determining underlying physiology, says Ira Lesser, a professor of psychiatry at the Harbor-UCLA Medical Center who was not involved in the current work. “It begins to let people think neurochemically about what might be involved in the genesis of suicidal thinking. Heuristically, it could lead to whole other areas of study.”

Dan Iosifescu, who directs the translational neuroscience program at Boston’s Massachusetts General Hospital, performed similar QEEG experiments with similar results in 2008. “I think it’s interesting, but it’s too early to tell whether [the effect] is real or whether it’s an artifact,” he says. “Worsening of suicidal ideation is not a frequent event, and it happens in less than 10 percent of people. So you typically need very large data sets to study it adequately.”

Hunter’s next step is to determine whether a similar effect can be seen using abbreviated EEG monitors, which require far fewer electrodes and can be completed in just 10 minutes (as opposed to the hour required with the full electrode array), and she’ll be examining this using a much larger group of patients. “Further development needs to be done, but we’re hoping this would allow us to provide a tool that could make antidepressant use happen in a safer way,” she says.

Keep Reading

Most Popular

DeepMind’s cofounder: Generative AI is just a phase. What’s next is interactive AI.

“This is a profound moment in the history of technology,” says Mustafa Suleyman.

What to know about this autumn’s covid vaccines

New variants will pose a challenge, but early signs suggest the shots will still boost antibody responses.

Human-plus-AI solutions mitigate security threats

With the right human oversight, emerging technologies like artificial intelligence can help keep business and customer data secure

Next slide, please: A brief history of the corporate presentation

From million-dollar slide shows to Steve Jobs’s introduction of the iPhone, a bit of show business never hurt plain old business.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at with a list of newsletters you’d like to receive.