Summary: New research has revealed that norepinephrine is a significant factor in how the brain anticipates potential outcomes, revealing some strange behavior in response to both pleasure and pain. Researchers discovered that norepinephrine neurons encode a “prospective script for value” that indicates expectations for upcoming outcomes and how quickly those expectations are evolving.
This aids in the brain’s daily decision-making by allowing it to assess the value of potential activities in shifting conditions. The findings challenge outdated notions about dopamine and provide a foundation for research in AI, biology, psychology, and psychotherapy.
Important Information
- Potential Forecasting: Serotonin cells encapsulate anticipations for upcoming rewards and punishments.
- Depending on expected benefit, these neurons respond to wonder, pain, and pleasure.
- Head vs. Machine: There are significant differences between the brain’s serotonin-based value-signaling system and unnatural systems.
University of Ottawa Cause
We make a slew of choices in our day-to-day life, from the simplest to the most likely options.
The biological nuts and bolts of how our neurons weigh these many daily choices and what function does the neurotransmitter serotonin play have been obscured.
A new study led by an inter-university faculty of medicine  group, led by an inter-disciplinary team, has recently revealed exciting findings on this significant subject and may shed light on a sizable aspect of what our anxious system’s exceptionally complex serotonin system is actually doing inside the mysterious organ in our skulls.
One of the professional reviewers who evaluated the work, which was published in the journal Nature, took into account the study’s “broad implications across biology, psychology, and psychiatry, enhancing our understanding of serotonin’s role in mood regulation, learning, and determined behavior” as well as the findings of a very effective global collaboration.
The team’s cutting-edge research combines recent hard-won insights into the dorsal raphe nucleus’ filtering properties with ideas from reinforcement learning ( RL ) theory, which is used in neuroscience to better understand learning, behavior, and decision-making. That area of the mammal brain is full of serotonin-producing neurons.
Dopamine is frequently portrayed as the “pleasure chemical” of the brain. Antidepressant medications like selective serotonin reuptake inhibitors ( SSRIs ) are well known for their ability to target the serotonin system as part of a multi-billion-dollar industry.
Serotonin’s specific role in the nerve system is unclear and perplexing, covering everything from mood and movement legislation to taste and sleep-wake processes. A mind research issue has long been the fact that it is activated by problems, pleasure, and surprise.
The uOttawa-led researchers present a cohesive viewpoint on serotonin with this study, which they call a “prospective script for value” – a genetic code for how the brain assigns a value for potential rewards.
In essence, this script explains why serotonin neurons in the brain are activated in response to both rewards and punishments, with a taste for unexpected benefits.
What does happy show the brain, according to our research? Our research, in essence, demonstrates that its information is in line with what is expected in the near future, according to senior author Dr. Richard Naud, interact professor at the University of Medicine’s Department of Cellular and Molecular Medicine and University of Ottawa’s Department of Physics.
The main findings are summarized in this article by co-author Dr. Jean-Claude Béque,  , professor in the Department of Cellular and Molecular Medicine.” Your brain needs to determine the expected value of the actions you contemplate and take as you connect with a changing earth, asking,” What’s the value of this choice versus that decision in that particular environment?”
That’s a challenging issue. So what we believe serotonin does in the brain is encode the expected value of a particular environment or course of action in order to ultimately influence daily decisions.
Drs. Both Bouque and Naud are affiliated with the Centre for Neural Dynamics and Artificial Intelligence at the University of Ottawa Brain and Mind Research Institute.
The Initial Spark
When Emerson Harkin, the first author, and Dr. Naud’s lab started developing the idea while researching the biophysical properties of serotonin neurons, the idea got off the ground at the University of Toronto Faculty of Medicine.
Dr. Harkin, who completed his PhD at uOttawa in late 2023 and received his degree in March 2024, claims the fundamental idea” came half-serendipitously.”
He and his uOttawa Faculty of Medicine supervisors began looking closely at findings from other labs that focused on measuring the activity of serotonin neurons in animals that were subject to rewards and punishments after dedicating a lot of time and effort to studying the electrical properties of the brain cells that produce serotonin.
He claims that they realized they might be pursuing something promising after the overall picture became incredibly perplexing.
According to Dr. Harkin, who referred to lab experiments with mouse models, “nobody seemed to have taken into account the possibility that serotonin neurons might be activated by , changes , in the animal’s surroundings, like the start of a signal that reward will arrive soon or the end of a punishment.”
A lot of results that had previously seemed puzzling or contradictory suddenly started to fit together when we looked at these previous results through the lens of what we had seen under our microscopes and with our electrodes.
Dr. Harkin, who is currently working as a postdoc in Germany at the Max Planck Institute for Biological Cybernetics, claims that the research shows that a significant portion of what the serotonin system does is send a “best guess” to the rest of the brain, stating” Here’s our best guess about how good your near future will be, and here’s how quickly that guess is improving.”
Dr. Naud, a computational neuroscience expert who deciphered the theory’s incredibly complex math, explains that the initial concept changed a lot over the course of the work as the collaborative team worked through “lots of reading, lots of discussion, lots of thinking.”
Next Steps
The research team wants to find out what the rest of the brain does with the neurotransmitter’s messages in order to understand how serotonin affects behavior. Dr. Naud suggests that they might find ways to use reinforcement-learning theory on frameworks to accomplish this.
According to Dr. Naud, whose research in neuroscience frequently has implications for theories of learning and memory that could influence future developments in artificial intelligence ( AI), the team’s recent study, which was just published in Nature , appears to demonstrate how unique the nervous system actually is.
The team’s findings, in my opinion, demonstrate that the brain does not function in the same way as machines do. He claims that if we disrupt the signaling of rewards in the machine, it would do many things that the brain’s perturbation doesn’t do.
About this news about neuroscience research
Author: Paul Logothetis
Source: University of Ottawa
Contact: Paul Logothetis – University of Ottawa
Image: The image is credited to Neuroscience News
Original research has been made private.
” A serotonin system value-related prospective code” by Richard Naud and al. Nature
Abstract
A serotonin system value-related prospective code
A puzzle surrounds the dorsal raphe nucleus serotonin neurons ‘ in-vivo responses to emotionally relevant stimuli. Some aspects of serotonergic activity are accounted for by existing theories that center on reward, surprise, salience, and uncertainty, but not others.
Here, we present a unified perspective on a prospective code for value by combining concepts from reinforcement learning theory with recent research into the dorsal raphe nucleus’ filtering properties.
This biological code for near-future reward explains why serotonin neurons are activated by both rewards and punishments, and why these neurons are more strongly activated by unexpected rewards without having such surprise preference for punishments, observations that previous theories have failed to reconcile.
Finally, our model accurately predicts in-vivo population activity than previous hypotheses.
Our research makes a significant step forward in understanding the role of serotonin in learning and behavior by resolving previous theories and making a precise connection with reinforcement learning.
