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EEG identifies brain signal that correlates with depression and anxiety

Cell Press

Researchers have long known that two brain structures, the amygdala and hippocampus, are involved with processing of emotion and mood--but not exactly how. Now, researchers from the University of California at San Francisco have identified a unique frequency of brainwaves associated with communication between these two brain structures that can be predictive of worsening mood related to depression and anxiety. Their findings appear November 8 in the journal Cell.

The investigators used intracranial electroencephalography (EEG) to measure the brainwave activity of 21 in-hospital epilepsy patients awaiting brain surgery for seizure localization. The patients self-reported their mood during the same period. After comparing the brainwave activity to the self-reported mood diaries, 13 of 21 patients showed fluctuations in electrical activity, or communication, at a brainwave frequency in the range of 13-30 cycles/second between the amygdala and hippocampus that correlated with depressed mood. Many of these patients did have notable pre-existing anxiety before the study.

"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."

To measure brainwave activity, 40-70 intracranial electrodes were placed on and within the brains of the 21 patients as part of treatment to identify and treat the source of epileptic seizure activity. The electrodes remained in place for 7-10 days and captured brainwave activity without interruption. The investigators reviewed the self-reported mood surveys for correlations with between mood and brain activity.

Previous attempts to correlate brain function with mood have relied on functional MRI (fMRI) studies in which an individual's brain activity is typically scanned for an hour or two. Subjects are prompted for mood changes during that time and results are correlated between the two. "But with fMRI, it is difficult to measure changes that happen over hours to days," says Sohal. "You are also looking at blood oxygenation levels, which measure something very different from electrical activity within the brain. Plus, you cannot detect fluctuations in electrical activity that go up and down 20 times per second with fMRI like you can with this method."

"We are excited to find out how the communication between the amygdala and hippocampus, which are very near to each other, contributes to emotional processing and how this signal correlates with peoples' changes in mood state," says co-lead author Edward Chang, a neurosurgeon and neuroscientist at UCSF. "This research is the first step in letting us look how the brain operates at different frequencies of brain activity, and it opens a lot of research and clinical questions."

Scientifically, researchers may choose to study the cells that generate that particular brain activity, factors that stimulate the pattern's activity to increase or decrease, and what that activity influences elsewhere in the brain. "What is exciting to me is that this may give us a new set of tools and a new way of looking at people who may be suffering from very severe mood disorders--perhaps even patients who are suffering much more than those we were looking at," says Chang. "If we can understand how that communication works, we may be able to come up with ways to very selectively treat that part of the brain."

The authors emphasize that they do not know if the signal identified in this study causes the mood shift or if it is a result of an altered mood. This is one of the questions the team plans on pursuing.

Clinically, the researchers suggest that this research may lead to new devices, such as those used in epilepsy and Parkinson's disease, that measure brain activity and deliver stimulation at a specific moment to treat brain symptoms. "Now that we know this is the neural signature, maybe we could find some non-invasive way to measure it without electrodes in the brain," Sohal says. "Once the signature is detected, patients might perform meditation or some other biofeedback-based approach to control that neural signature."

The team believes this discovery could help reduce the fear and stigma of mood disorders. "It's really powerful to say to subjects that when you're feeling down it's due to communication between these two brain structures at a particular frequency," says Sohal. "It helps everybody think about these things in a way that is destigmatizing and empowering."

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This research was funded by the Systems-Based Neurotechnology for Emerging Therapies (SUBNETS) program of the Defense Advanced Research Projects Agency (DARPA).

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

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