Study Reveals Brain Signature of Depressed Mood

Do new findings provide an initial line of evidence indicating the feasibility of mood state decoding linked to brain signature?

For the first time, researchers have identified what appears to be a signature pattern of brain activity when people are experiencing anxiety and depressed mood. The breakthrough research was led by a team at the University of California San Francisco and included team members and technology from Posit Science Corporation — the maker of BrainHQ and other brain exercises and assessments.

Read Also: Interview with Michael McGuire, VP Research, Gartner for Marketing Leaders

According to the study report, just published online in the journal Cell, the researchers recruited 21 volunteers with epilepsy who had 40 to 70 electrodes implanted in their brains as a standard pre-surgery preparation for removing seizure-causing tissue. During a period of seven to ten days prior to surgery, the researchers recorded a wide range of brain activity, with a particular focus on certain deep brain structures previously implicated in mood regulation.

“While we have previously shown that IMS could be useful to clinicians in monitoring emotional state and in creating opportunities for earlier clinical interventions, we now see how this real-time capture of reported mood can be instrumental to researchers in unlocking the neurobiology of mood states,” observed Dr. Tom Van Vleet, a co-author of the study and a member of the research team at Posit Science.

Read Also: Interview with Alain Briancon, VP of Data Science, Cerebri AI

Tom added, “That offers new avenues to researchers in addressing a wide range of mental health conditions.”

The participants also were prompted to record their subjective mood state throughout the day using an experimental app — the Immediate Mood Scaler (IMS) — developed by Posit Science.

Read More: Walmart Turns To Genpact To Dive Into The ‘Age Of Instinct’

IMS was shown in a study published last year to highly correlate with more traditional assessments of anxiety and depressed mood, but with a better ability to capture momentary fluctuations in mood status than the traditional assessments, which typically ask patients to recall their mental state over a period of days or weeks.

In this study, the researchers used newly developed computational algorithms to match patterns of brain activity to changes in the reported moods of participants.

The researchers found a pattern in 13 of the participants characterized by beta waves — with synchronized oscillations of between 13 and 30 cycles per second — in the hippocampus and amygdala. Those brain regions are usually associated with memory and negative emotions, respectively. This pattern was entirely absent from the other eight study participants — all of whom reported comparatively low anxiety.

The authors of the study suggest that the patterns observed may be linked to recalling emotional memories and that the pathway is particularly strong in people with higher levels of anxiety.

It also may be possible to use the new techniques in this study to identify brain activity patterns that constitute additional biomarkers linked with different emotional states and issues of mental health. This could lead to new approaches for the diagnosis, monitoring, and treatment of mental disorders.

The primary funding for the study came from the Department of Defense through the Defense Advanced Research Projects Agency (DARPA).

Read Also: Cognitive AI Leader To Make Rabobank Better Deal With Unstructured Data