University of Oregon neuroscientists have identified a group of brain cells that essentially act as a "disappointment meter," announcing when reality is falling short of expectations.
In a study published May 8 in Current Biology , the researchers describe a specific group of neurons in the mouse brain that become active when the animal anticipates a reward but earns less than expected, or nothing at all. The findings reveal that feeling let down is something that particular cells in the brain are designed to detect and record.
Mapping the cell types that show sensitivity to disappointment might someday lead to a new class of medications that better treat neuropsychiatric disorders like depression and addiction, said Emily Sylwestrak , an assistant biology professor in the UO College of Arts and Sciences .
"If you're looking at a neuropsychiatric disease, you need to know which knobs to turn to set things right," said Sylwestrak, senior author of the paper. "So, if we know that a particular cell type is compromised in depression, for example, scientists might be able to design drugs that specifically target it and avoid the effects of stirring others."
A team led by Sylwestrak investigated the lateral habenula, a small and evolutionarily ancient structure wedged deep in the brain. Previous studies have shown that the region becomes more active in response to unexpected negative events, such as a punishment out of the blue or a reward no longer granted. This has led to the lateral habenula being known colloquially as the brain's "anti-reward center."
But the region contains many kinds of neurons, and scientists have yet to isolate the roles of individual cell types within it.
"What we're trying to understand is how those different cell types are mapped to particular behaviors," Sylwestrak said. "This new paper is a look at a cell type that we think is doing something very specific in the reward system."
Scientists have previously described the distinct cell type that Sylwestrak's lab investigated, but they lacked a way to directly access it. Sylwestrak accidentally stumbled into those cells when studying a nearby brain region. During an experiment, she noticed stray signals from neighboring cells that crept into the brain recordings whenever a mouse seemed to expect a reward, checked for it, but left empty-handed.
That observation led to this current work, in which Sylwestrak and colleagues recorded neural activity in mice trained to poke their noses into a port to earn sugar water. But after the mice had learned to expect a sweet sip when approaching the spot, the reward was sometimes smaller than expected or withheld entirely.
Not only did the neurons suddenly burst into activity in those moments, but that activity scaled with the degree of disappointment. In other words, the researchers could infer how much sugar water the animal received based on the strength of the neural response.
"It's like being able to record the activity in your neurons and tell whether you were given one, two or three Skittles when you expected five," Sylwestrak said. "The activity in these cells is such a reliable reporter of the difference between expectation and outcome that it essentially acts as a disappointment meter."
The researchers also compared brain activity in other worse-than-expected contexts, such as when the mice encountered a sudden puff of air. The neurons were relatively quiet during those surprise unpleasant events, suggesting they're not merely "bad news" detectors.
Rather, they're tuned to a particular kind of negative experience — when an expected reward falls short — and that specificity is central for learning from mistakes, changing behaviors and perseverance, said Kana Suzuki, a doctoral student in Sylwestrak's lab.
"We don't necessarily want to register or interpret all negative outcomes as the same because you can imagine there are different negative experiences that require distinct behavioral responses," said Suzuki, lead author of the study.
The study suggests that the brain may rely on distinct neural circuits to tell different kinds of negative situations apart and shape what happens next.
"Every day we're making decisions and neural computations on how to pursue things that are favorable, like rewards, and avoid things that are not so favorable, like punishments," Suzuki said. "You're inevitably going to use the history of your successes and failures the next time you need to make a decision or make a different choice."
Our brains are looping prediction machines, and knowing when you're wrong is critical for adjusting your behavior to increase your chances of being right, Sylwestrak said.
But those cognitive processes can be disrupted in neuropsychiatric disorders. To uncover new clues to what goes awry in neurological conditions, Sylwestrak and Suzuki plan to shift from eavesdropping on neural activity to orchestrating those conversations. By inhibiting or tinkering with the neurons during similar reward-seeking experiments, they hope to glean insights into how particular cell types guide healthy reward seeking, as well as how their dysfunction may underlie neuropsychiatric disorders such as addiction and depression.
Existing drugs tend to affect many neurons in the brain, which contributes to an array of side effects, Sylwestrak said. Identifying the relevant cell types gives scientists a more specific "knob" to study — and one they may someday be able to target for therapeutic interventions.
"If you look up a neuron online or in a textbook, you usually see the same simplified caricature, but this belies a great diversity in the genetics, structure and function of neurons," Sylwestrak said. "This is just one vignette on a cell type that we think is encoding something very specific about reward, and we see great promise in understanding the roles of different cell types in healthy brain function and in disease."
— By Leila Okahata, University Communications
