Researchers using an EEG have found a common pattern of brain activity connected to feelings of depression. This could serve as an early diagnosis mechanism, particularly indicating how severe a person’s symptoms are.
The World Health Organization estimates that there are over 300 million people suffering from depression worldwide, yet the condition is poorly understood and can be difficult to diagnose. Previous studies have generally had participants lie in a fMRI scanner and look at upsetting images or listen to sad stories. These studies have been able to highlight areas of the brain associated with emotion in healthy and depressed individuals, but they still don’t reveal much about natural mood fluctuations and the mechanisms which cause these fluctuations.
In order to shed some light on these processes, researchers at the University of California San Francisco (UCSF) recruited 21 patients, installing 40-70 intracranial electrodes for 7-10 days. This was not done for this study, but was rather as part of treatment to identify and treat the source of epileptic seizure activity — the new study harmlessly took advantage of the opportunity.
The electrodes measured brain activity in the patients and compared the brainwave activity to the self-reported mood diaries, finding that 13 of 21 patients showed fluctuations in electrical activity between the amygdala and hippocampus that correlated with depressed mood. These are two areas that have long been associated with memory and negative emotion.
“This study showed that there is a naturally occurring network that seems to consistently predict changes in mood among the majority of subjects,” says co-senior author Vikaas Sohal (@sohallab), a psychiatrist and neuroscientist at UCSF. “We were surprised to find such a clear and consistent signal, made up of interactions between the amygdala and hippocampus at a specific frequency, which matched changes in the mood seen in these 13 patients.”
This is a remarkable find which could, ultimately, enable doctors to prescribe better treatments. While it likely won’t be as a direct diagnose tool, it could assess symptoms linked with depression and highlight brain patterns associated with them. Vikaas told ZME Science that the brain communication they measured, while not perfect, yielded telling results:
“Our main result is that changes in the activity of a specific network in the brain correlate with changes in self-reported mood, measured using a tablet-based questionnaire. This would not be used to diagnose whether or not an individual has a specific psychiatric condition, but could potentially be used to measure the severity of an individual’s symptoms at a particular point in time. This is an idea that we and others may pursue in the future to develop new treatments for severe cases of depression or anxiety, which do not respond well to current treatments. Overall, the brain activity we measured was sufficient to predict about 40-50% of the variation in an individual’s mood in approximately 2/3 of subjects.”
This study essentially offers a new set of tools and a new way to look at how the brain works, and how it is connected to mood shifts and potentially, some mental disease. Understanding how this communication works could allow researchers to develop ways to selectively treat these parts of the brain.
The study does have some limitations, however, as the patterns were not apparent for all the patients. The authors emphasize that they do not know if the signal identified causes the mood shift or if it is a result of an altered mood. However, where there is a difference, anxiety seems to be an excellent predictor of success.
“We found that this particular form of brain activity (beta-frequency communication between the amygdala and hippocampus) predicted mood in about 2/3 of the subjects in our study. Interestingly, this was true for all subjects who had clinically meaningful levels of anxiety. For subjects without clinically meaningful levels of anxiety, sometimes this method was informative and sometimes it was not.”
Overall, this is still only a first step in what has the potential to be a long (and very rewarding) road. Vikaas and several other researchers are honing in on the biological (and neurological) activity that corresponds to our mood, which would be a huge achievement.
“There are many outstanding questions. For example, we do not know whether this brain activity causes depressed mood, or whether it is an indicator of when mood is low. We and others are thinking about how to study brain mechanisms which generate this brain activity in order to get more insight into the biology of mood. We would also like to understand how to influence this brain activity in order to identify potential new treatments for mood and anxiety disorders.”
Journal Reference: Cell, Kirkby et al.: “An amygdala-hippocampus subnetwork that encodes natural variation in human mood” https://www.cell.com/cell/fulltext/S0092-8674(18)31313-8