In a pioneering study, scientists have discovered a specific pattern of brain activity that signals anxiety levels in both humans and mice. By focusing on the synchronization of brain waves between two key areas involved in emotion processing, researchers identified a potential universal biomarker for anxiety, offering new avenues for understanding and treating anxiety disorders.
The study was published in the journal Neuron.
With anxiety disorders being one of the most prevalent psychiatric conditions worldwide, the authors of the new study sought to pinpoint reliable indicators within the brain that could advance diagnosis, prevention, and treatment. Their exploration was rooted in previous human studies that hinted at the amygdala and hippocampus’s pivotal roles in emotion regulation, prompting a closer examination of these areas to uncover the underlying neural mechanisms.
“As a psychiatrist, I have long thought that emotional states should be evident in readily observable patterns of brain activity, because our emotional state impacts so many aspects of our behavior (facial expressions, tone of voice, movements, decision making, etc.),” said study author Vikaas S. Sohal, a professor of psychiatry and behavioral sciences at the Weill Institute for Neurosciences and Kavli Institute for Fundamental Neuroscience at the University of California, San Francisco.
“Previously, in a collaboration with a neurosurgeon (Eddie Chang also at UCSF), we analyzed recordings from the human brain made while hospitalized patients periodically rated their moods, and found a pattern of activity – synchronization between rhythmic activity in the amygdala and hippocampus – that predicted changes in emotion state in about 2/3 of subjects. We wondered if this same pattern of activity could be linked to emotional state in mice, and if so, whether we could use experiments in mice to study the mechanism and function of this pattern of activity.”
How The Study Was Conducted
The initial phase of the research focused on humans, specifically 13 individuals with epilepsy who were already undergoing clinical monitoring for their condition. These participants had intracranial electrodes implanted for seizure localization, providing a unique opportunity to study brain activity directly.
Researchers utilized intracranial electroencephalogram (iEEG) recordings to monitor electrical activity between the amygdala and hippocampus. Participants rated their emotional states using a tablet-based questionnaire, allowing researchers to correlate specific patterns of brain activity with self-reported mood and anxiety levels.
Building on the findings from human participants, the researchers extended their investigation to mice, aiming to delve deeper into the cellular mechanisms that could not be explored in humans. This involved a series of sophisticated surgical and experimental techniques to monitor and manipulate brain activity in live animals. Mice were fitted with electrodes to record local field potentials (LFPs), capturing the electrical activity between the amygdala and hippocampus, similar to the iEEG recordings in humans.
The research team employed optogenetics, a method that uses light to control neurons genetically modified to be light-sensitive, allowing for precise manipulation of specific neural circuits implicated in anxiety.
To assess anxiety levels and correlate them with brain activity patterns, mice underwent behavioral tests known for their ability to evoke anxiety-related behaviors. The elevated plus maze and elevated zero maze were utilized, with the former consisting of two open arms and two closed arms elevated above the ground, and the latter being a continuous loop with sections enclosed by walls.
These assays tested the mice’s willingness to explore open, exposed areas — behaviors that are indicative of their anxiety levels. Before and after these behavioral assays, LFP recordings were taken in various contexts, including the animals’ home cages, to establish baseline brain activity patterns for comparison.
What The Study Found
After analyzing the data, the researchers identified beta-coherence bursts – brief, intense periods of synchronization between the amygdala and hippocampus – between the amygdala and hippocampus as a biomarker for emotional states, particularly anxiety.
In mice, the frequency and variance of these bursts were strongly predictive of anxiety-related behaviors, such as avoidance actions in the elevated plus maze and zero maze tests. The more frequent these bursts, the higher the level of anxiety observed in the animals.
This relationship between beta-coherence bursts and anxiety was also mirrored in humans, where periods of high coherence correlated with lower mood and higher anxiety levels, as reported through self-assessment questionnaires. Thus, these bursts serve as a real-time marker of emotional state, bridging subjective experiences of anxiety with measurable neural activity.
Diving deeper into the neural mechanisms, the researchers focused on the role of specific neuron types in generating these coherence patterns. They pinpointed somatostatin-positive (SST+) interneurons within the amygdala and hippocampus as critical contributors to the observed beta-coherence bursts.
Using optogenetics, a method that enables the control of neurons with light, they found that artificially inducing or disrupting the synchronization of these SST+ interneurons could bidirectionally modulate anxiety-related behaviors in mice.
Inducing synchronization led to increased avoidance behaviors, mimicking a state of heightened anxiety, whereas disrupting synchronization reduced such behaviors, suggesting a decrease in anxiety levels. This causal link underscores the importance of SST+ interneurons in the neural circuitry underlying anxiety.
“In the past, we have generally found that one class of inhibitory neurons (which express a protein called parvalbumin), drives rhythmic activity at high frequencies,” Sohal told PsyPost. “Here we found a role for a different class of inhibitory neurons (which express the protein somatostatin). We don’t yet know why this specific class of neurons involved. We also found direct inhibitory connections from somatostatin inhibitory neurons in the amygdala to those in the hippocampus. These sorts of long-range inhibitory connections have only recently been discovered and their function is not yet well understood.”
The study highlights the utility of cross-species research in uncovering universal mechanisms of emotional processing. The consistency of the findings across humans and mice strengthens the case for the amygdala-hippocampus axis as a key player in anxiety, providing a solid foundation for future research aimed at unraveling the complex interplay between brain activity and emotional states.
Sohal outlined two main takeaways: “First: that our emotional state can be inferred from a specific, measurable pattern of activity in the brain, and this pattern of activity strongly influences the kinds of decisions we make and behaviors we engage in. Second: that this pattern of activity is not necessarily related just to increased or decreased activity in specific parts of the brain or specific types of brain cells, but rather is defined by communication between specific types of cells in different brain regions. This communication can be quantified by measuring how well rhythmic activity (at specific frequencies) is synchronized between these cells, across regions (the amygdala and hippocampus).”
Practical Implications and Future Directions
The identification of beta-coherence bursts as a biomarker for anxiety opens up new avenues for diagnosing and potentially treating anxiety disorders. By targeting the specific neural circuits involved, such as the synchronization of SST+ interneurons, it might be possible to develop therapies that can modulate these brain activity patterns directly, offering a novel approach to managing anxiety.
While the study marks a significant leap forward in understanding anxiety’s neural basis, it also underscores the complexity of emotional states and their manifestation in the brain. The precise mechanisms by which these beta-coherence bursts influence behavior remain to be fully elucidated. Future research will need to explore how these patterns are generated and regulated within the brain and how they can be modulated to treat anxiety disorders effectively.
“Our hope is to identify the circuits which generate negative emotional states, and identify ways of curbing overactivity in these circuits in order to develop better treatments for depression and anxiety disorders,” Sohal said.
The study, “Amygdala-hippocampus somatostatin interneuron beta-synchrony underlies a cross-species biomarker of emotional state,” was authored by Adam D. Jackson, Joshua L. Cohen, Aarron J. Phensy, Edward F. Chang, Heather E. Dawes, and Vikaas S. Sohal.
