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(https://www.psypost.org/225574-2/) High-dose caffeine improves reaction time but increases nervousness
Dec 22nd 2024, 08:00

A recent study in Spain found that an intake of 6 mg/kg of caffeine improved participants’ reaction times in a series of reaction tasks. It also made participants more nervous, alert, and active. The research was published in the (https://doi.org/10.1007/s00394-024-03486-9) European Journal of Nutrition.
Caffeine is a natural stimulant found in coffee, tea, chocolate, and many energy drinks. It works by blocking adenosine, a neurotransmitter that promotes sleep, leading to increased alertness and wakefulness. Caffeine is absorbed quickly into the bloodstream and typically begins affecting the body within minutes.
Caffeine is widely used to improve focus, reaction time, and reduce fatigue. In moderate doses, caffeine is considered safe, but excessive intake can cause side effects such as jitteriness, increased heart rate, and insomnia. It is one of the most widely consumed psychoactive substances globally. Consequently, caffeine plays a significant role in cultural practices worldwide and the daily routines of many people.
Study author María Ramírez-delaCruz and her colleagues aimed to determine the acute effects of different doses of caffeine (0, 3, or 6 mg/kg) on cognitive performance in physically active, healthy individuals. They hypothesized that caffeine would increase cognitive performance and that 3 mg/kg would be the optimal dose to achieve this effect.
The study participants included 29 healthy young adults, 15 of whom were men. The participants’ average age was 22 years. All participants completed three trials. In each trial, they received a capsule with a different dose of caffeine adjusted to their body weight. In one trial, the dose was 3 mg/kg; in another, it was 6 mg/kg; and in the third, the capsule contained no caffeine. Participants did not know which dose was in the capsule they consumed, and this information was also unavailable to the researchers working with them during the experimental sessions. The order of doses (which dose was given in each trial) was randomized.
In each session, after consuming their designated capsule, participants completed tests of reaction time (on the Dynavision™ D2 Visuomotor Device), visual acuity related to hand-eye coordination and anticipation (the Bassin Anticipation Timer), sustained attention (the “Go/No-Go Test” and “Eriksen Flanker Test”), and memory (using lists of words created by the study authors for participants to memorize).
The results showed that reaction time improved after the intake of 6 mg/kg of caffeine, while the 3 mg/kg dose had no effect. Additionally, there were no effects of caffeine on anticipation, sustained attention, or memory performance.
After receiving the 6 mg/kg dose, participants also exhibited increased nervousness and activeness (i.e., they were more alert, had higher energy levels, and became more active).
“The acute intake of 6 mg/kg of caffeine was effective in improving RT [reaction time] in the test used on the Dynavision™ D2 visuomotor device. In addition, the 6 mg/kg dose of caffeine augmented the occurrence of side effects, mainly increased activeness and nervousness,” the study authors concluded.
The study sheds light on the effects of caffeine on cognitive performance. However, it should be noted that the study was conducted on a very small group of participants, all of whom were young adults. Effects on other demographic groups might not be identical.
The paper, “(https://doi.org/10.1007/s00394-024-03486-9) Effects of different doses of caffeine on cognitive performance in healthy physically active individuals,” was authored by María Ramírez-delaCruz, Paula Esteban-García, Pablo Abián, Alfredo Bravo-Sánchez, Inés Piñas-Bonilla, and Javier Abián-Vicén.

(https://www.psypost.org/artificial-intelligence-decodes-the-brains-intelligence-pathways/) Artificial intelligence decodes the brain’s intelligence pathways
Dec 22nd 2024, 06:00

In a new study published in (https://doi.org/10.1093/pnasnexus/pgae519) PNAS Nexus, scientists have demonstrated that artificial intelligence can predict different types of human intelligence by analyzing connections in the brain. Using neuroimaging data from hundreds of healthy adults, they found that predictions were most accurate for general intelligence, followed by crystallized intelligence, and then fluid intelligence. The findings shed light on the distributed and dynamic nature of intelligence, demonstrating that it arises from the global interplay of brain networks rather than isolated regions.
While prior research has established that intelligence is not localized to a single brain region but rather involves distributed networks, many studies have relied on traditional methods that focus on isolated brain features. These approaches have offered limited insights into how intelligence arises from the interplay of brain structure and function. By employing machine learning to analyze brain connectivity, the researchers aimed to overcome these limitations.
A key focus of the study was the distinction between three major forms of intelligence: general, fluid, and crystallized. General intelligence, often referred to as “g,” is a broad measure of cognitive ability that encompasses reasoning, problem-solving, and learning across a variety of contexts. It serves as an overarching factor, capturing shared elements between specific cognitive skills.
Fluid intelligence, a subset of general intelligence, refers to the capacity to reason and solve novel problems without relying on prior knowledge or experience. This type of intelligence is often associated with abstract thinking, pattern recognition, and adaptability. In contrast, crystallized intelligence represents the ability to use knowledge and skills acquired through education, culture, and experience. It includes abilities such as vocabulary, reading comprehension, and factual knowledge.
“Our research group aimed to investigate how individual differences in intelligence, or general cognitive ability, are manifested in the human brain. We are convinced that the interconnections between different brain regions—believed to reflect communication pathways—play a particularly critical role,” said study author (https://www.psychologie.uni-wuerzburg.de/bioklin/arbeitsgruppen/netzwerke-fuer-verhalten-und-kognition/) Kirsten Hilger, the head of the Networks of Behavior and Cognition research group at Julius-Maximilians-Universität Würzburg.
“Many studies published in recent years have predicted individual differences in intelligence based on these communication pathways, known as functional brain connectivity. However, the primary goal of these studies has often been to achieve the highest possible prediction performance, while insights into the concept of intelligence and the question of how intelligence may arise from these communication pathways were largely absent.”
“With our study, we aim to address this limitation by providing methods and approaches to gain interpretable insights into the concept of intelligence, i.e., to actually learn something about how intelligence evolves from the brain,” she explained.
To predict intelligence, the researchers used data from the Human Connectome Project. Their analysis included 806 participants aged 22 to 37, who were free of cognitive impairments. Brain connectivity was assessed using functional magnetic resonance imaging (fMRI) during resting states and seven tasks designed to activate different cognitive processes, such as working memory, language, and emotional recognition. Fluid intelligence was measured using tests independent of prior knowledge. Crystallized intelligence was assessed with vocabulary and reading tasks. General intelligence, combining elements of both, was calculated as a composite score.
The researchers trained machine learning models to analyze connections between 100 defined brain regions across eight cognitive states. They compared models using connections proposed by leading intelligence theories with those trained on randomly chosen connections. Additionally, they applied a technique called relevance propagation to identify which brain connections most contributed to the predictions.
Among the different types of intelligence examined, general intelligence was the most accurately predicted by the machine learning models. This finding suggests that general intelligence, as an overarching cognitive ability, may be associated with more consistent or prominent patterns of brain connectivity compared to the other types. Crystallized intelligence was also predicted with considerable accuracy, while predictions for fluid intelligence were less precise.
One of the key insights was that brain activity during cognitively demanding tasks yielded more accurate predictions of intelligence than activity during resting states. Tasks that required working memory or language processing, for instance, significantly improved the models’ ability to predict fluid and general intelligence. This finding highlights the dynamic nature of brain connectivity and its importance in supporting higher-level cognitive processes.
In contrast, crystallized intelligence, which is tied to long-term knowledge and skills, appeared to rely more on stable, task-independent brain networks. The use of latent connectivity measures, which integrate information across multiple brain states, further enhanced predictions of crystallized intelligence, suggesting that this form of intelligence may emerge from widespread, stable communication patterns in the brain.
The researchers also found that models that incorporated connections between brain regions highlighted by theories like the parieto-frontal integration theory outperformed those trained on randomly selected regions. This reinforces the idea that certain brain networks, particularly those involving the prefrontal and parietal areas, are integral to cognitive functioning. However, whole-brain models consistently outperformed theory-driven models, indicating that intelligence likely arises from a more extensive and distributed network of connections than previously understood.
“Individual differences in intelligence are not manifested in few circumscribed regions in the brain, but instead in a communication mechanism involving the whole brain,” Hilger told PsyPost. “Previous neurocognitive models of intelligence are not wrong, but need to be extended towards the inclusion of the whole brain and more focus on the mechanisms instead of specific brain regions.”
The analysis identified approximately 1,000 specific brain connections as being most predictive of intelligence. These connections were not confined to isolated regions but were distributed across the brain, involving major networks such as the default mode network, the frontoparietal control network, and the attention networks. These findings underscore the idea that intelligence is a global property of the brain rather than the product of activity within a single region or system.
Interestingly, the researchers found that the brain’s ability to compensate for missing connections was remarkably high. Even when entire networks were excluded from the models, predictions of intelligence were only minimally affected.
“Artificial removal of complete large-scale functional brain systems affects predictive performance surprisingly little,” Hilger said. “Thus, there seem to be some redundancy in the neural code of intelligence differences.”
While the study provided significant insights into the neural underpinnings of intelligence, it is not without limitations. One notable constraint is the narrow age range of participants, which included only healthy adults aged 22 to 37. This limits the generalizability of the findings across the lifespan, particularly for children and older adults.
In addition, although the study identified approximately 1,000 brain connections as most predictive of intelligence, the exact nature of these connections and their functional roles remain unclear. Investigating the specific processes these connections support—such as memory, attention, or executive control—could help clarify how they contribute to different types of intelligence. Furthermore, exploring individual differences in neural strategies for problem-solving and knowledge application might illuminate why some connections are more predictive than others.
“In sum, our results suggest intelligence as emerging from global brain characteristics, rather than from isolated brain regions or single neural networks,” the researchers concluded. “In a broader context, our study offers a framework for future predictive modeling studies that prioritize meaningful insights into human complex traits over the mere maximization of prediction performance.”
The study, “(https://academic.oup.com/pnasnexus/article/3/12/pgae519/7915712) Choosing explanation over performance: Insights from machine learning-based prediction of human intelligence from brain connectivity,” was authored by Jonas A. Thiele, Joshua Faskowitz, Olaf Sporns, and Kirsten Hilger.

(https://www.psypost.org/individuals-with-dark-traits-have-a-heightened-connection-to-certain-types-of-fictional-characters/) Individuals with dark traits have a heightened connection to certain types of fictional characters
Dec 21st 2024, 14:00

A new study published in (https://psycnet.apa.org/record/2025-39699-001) Psychology of Popular Media sheds light on why some people are drawn to morally ambiguous fictional characters, such as villains and antiheroes. The research suggests that antagonistic personality traits like Machiavellianism, narcissism, psychopathy, and everyday sadism—collectively known as Dark Tetrad traits—are associated with admiring and identifying with these types of characters. This association appears to reflect how individuals view their own values, motivations, and personalities in relation to these fictional figures.
Fictional heroes, antiheroes, and villains play a central role in popular media, captivating audiences with their moral clarity, ambiguity, or outright malice. Previous studies have established that people are often drawn to characters who share traits with themselves, but much of this research has focused narrowly on single types of characters or excluded key personality traits like everyday sadism. This study sought to expand on that foundation.
“Fiction is a big part of a lot of people’s lives, and a lot of people have pretty personal relationships with their favorite fictional characters. What draws certain individuals to certain characters?” said study author Eliott K. Doyle, a PhD candidate at the University of Oregon.
“Antiheroes and villains are exciting parts of stories, but for some of the people who like them, the appeal might be deeper than that. Personally, I’m often intrigued by villains in fiction; I have some guesses about why that is for me, but what about for consumers of fictional media more generally? Some past research has found that people tend to like characters who behave in a way that is moral according to the culture they live in, but not everybody from a given culture is necessarily in total agreement about what ‘good’ values and behaviors actually are. So, we wanted to look at the variability in character preferences based on individual differences in these kinds of attitudes.”
To explore this question, researchers recruited 473 undergraduate students from a university in the Pacific Northwest. The participants, mostly women with an average age of 19.78, completed a survey assessing their personality traits and preferences for various fictional characters.
The researchers used a dual approach to evaluate character preferences. First, participants rated 25 popular fictional characters, including heroes like Disney’s Mulan, antiheroes like DC Comics’ Harley Quinn, and villains like Dolores Umbridge from Harry Potter. Participants rated their familiarity with each character, and responses for characters they were unfamiliar with were excluded. For each character, participants rated how admirable they found the character and how similar they felt to them.
In the second approach, participants evaluated brief written descriptions of archetypal heroes, antiheroes, and villains. These descriptions were stripped of specific narrative contexts, focusing solely on the values and motivations associated with each archetype. This allowed the researchers to assess whether the appeal of these archetypes extended beyond familiarity with specific characters.
To measure antagonistic personality traits, participants completed several validated questionnaires. These included measures of Machiavellianism (manipulativeness and cynicism), narcissism (self-centeredness and grandiosity), psychopathy (impulsivity and lack of remorse), and everyday sadism (enjoyment of cruelty).
The researchers found that individuals with more antagonistic traits were more likely to admire and view themselves as similar to antiheroes. Psychopathy and everyday sadism demonstrated the strongest correlations, indicating that individuals high in these traits are particularly drawn to antiheroes, who often operate in moral gray areas and exhibit a mix of virtuous and questionable behaviors. Machiavellianism and narcissism were also linked to positive evaluations of antiheroes, but the associations were somewhat weaker. These findings align with the idea that antiheroes embody complex, multifaceted personalities that resonate with those who exhibit similarly complex antagonistic traits.
Villains showed a similar pattern, with antagonistic traits positively correlated with both admiration and perceived similarity. However, the associations with villains were generally weaker than with antiheroes, especially for traits like Machiavellianism. This may reflect the fact that, while villains often share traits like cunning and self-interest, their overtly malevolent actions and lack of redeeming qualities make them less relatable than antiheroes. Nonetheless, individuals high in psychopathy and everyday sadism were more likely to admire and feel similar to villains, suggesting that these traits may amplify the appeal of characters who embrace chaos or cruelty.
“The biggest takeaway from the study was that all of the antagonistic traits were linked to admiring and feeling similar to fictional villains and antiheroes,” Doyle told PsyPost. “This was the case for both antiheroes and villains from popular culture, and for descriptions of archetypal antiheroes and villains. The link was the strongest for psychopathy and everyday sadism.”
In contrast, heroes were rated as the most admirable overall, but they were not strongly associated with antagonistic traits. Participants high in Machiavellianism, psychopathy, and everyday sadism often rated heroes as less similar to themselves, reflecting a mismatch between their own personality characteristics and the virtuous, altruistic qualities typically associated with heroes. The only exception was narcissism, which showed a weak positive correlation with similarity to heroes, potentially reflecting narcissistic individuals’ admiration for heroic qualities like leadership and recognition.
“The associations between fictional heroes and narcissism were somewhat surprising,” Doyle said. “We found that three of the four antagonistic traits (Machiavellianism, psychopathy, and everyday sadism) were negatively associated with both similarity to/admiration for heroes, but the trait of grandiose narcissism was positively associated with similarity to heroes from popular culture.”
“Interestingly, this wasn’t the case for narcissism and descriptions of archetypal heroes, just heroes from popular culture, which might suggest that higher narcissism is related to feeling similar to fictional heroes’ presentations in stories more than relating to archetypal heroic attitudes.”
The study sheds light on the psychological factors that drive admiration for morally ambiguous fictional characters. But the researchers warn against overinterpreting the results: “I would mostly caution people not to use these findings diagnostically in daily life,” Doyle said. “Someone who likes fictional villains isn’t necessarily high in antagonistic traits, and someone high in antagonistic traits won’t necessarily behave like a fictional villain!”
Future research could explore other characteristics of antiheroes and villains that contribute to their appeal. For example, some characters may resonate with audiences due to shared experiences of marginalization. Investigating how these factors interact with personality traits could deepen our understanding of why people are drawn to certain fictional figures.
“I would like to investigate other features of antiheroes and villains that a subset of fiction consumers latch onto,” Doyle said. “Our study demonstrates that some of the appeal of antiheroes and villains is attributable to those characters’ archetypal traits, but there might be other features that are probably appealing in different ways. For example, some subtypes of antiheroes and villains might have had experiences of marginalization (e.g., disability, economic disadvantage, minoritized identities) that are less common to find in heroic characters. It’s possible people who have also had those kinds of marginalizing experiences end up admiring/feeling similar to antihero and villain characters for those reasons, regardless of personality.”
“I am also interested in seeing how these perceptions of characters hold up contextually. How people tend to perceive character archetypes is probably heavily informed by stereotypes they’ve formed based on other similar characters they’ve encountered in the past. Even though our archetypal hero/antihero/villain descriptions weren’t presented in the context of stories, the participants in the study might have been making assumptions that the villain description, for example, would be in an antagonistic role.”
“But what if a character who seemed like an archetypal villain did something most people would agree was good?” Doyle continued. “What if a character who seemed like an archetypal hero did something most people would agree was bad? I’m interested in complicating these findings — and potentially also investigating how they apply to perceptions of figures from popular media who aren’t fictional, like celebrities and political figures.”
The study, “(https://psycnet.apa.org/doi/10.1037/ppm0000571) Rating Heroes, Antiheroes, and Villains: Machiavellianism, Grandiose Narcissism, Psychopathy, and Sadism Predict Admiration for and Perceived Similarity to Morally Questionable Characters,” was authored by Eliott K. Doyle, Cameron S. Kay, and Holly Arrow.

(https://www.psypost.org/individuals-with-core-knowledge-confusions-are-more-likely-to-believe-in-the-paranormal/) Individuals with core knowledge confusions are more likely to believe in the paranormal
Dec 21st 2024, 12:00

A meta-analytic study involving over 16,000 participants from 11 countries found that individuals with stronger core knowledge confusions are more likely to believe in the paranormal. The association was particularly pronounced among participants from Finland. The research was published in (https://doi.org/10.1016/j.paid.2024.112780) Personality and Individual Differences.
The concept of core knowledge confusions, proposed by Lindeman and Aarnio, describes how our brains sometimes mix up different types of basic knowledge, leading to incorrect explanations. Our minds have evolved to handle specific tasks, such as understanding how objects move, recognizing living things, or interpreting why people act in certain ways. However, these natural ways of thinking can sometimes be misapplied. For instance, people might treat objects as if they are alive or believe that natural events occur due to invisible forces or spirits.
This confusion may also lead to beliefs in phenomena such as ghosts, magical powers, or other supernatural ideas. It occurs because our brains rely on intuitive shortcuts that feel correct but are not based on science or facts. Sometimes, individuals might attribute intentions or knowledge to inanimate objects, like stars, during their reasoning. Yet, when explicitly asked, they may clearly state they do not believe that stars have intentions. Some researchers propose that this happens because humans use two reasoning systems: one that is intuitive and automatic, employed for rapid decision-making, and another that is more deliberate and logical.
Study author Albina Gallyamova and her colleagues aimed to integrate findings from previously published research on the links between core knowledge confusions and belief in the paranormal. They sought to verify whether individuals with stronger core knowledge confusions are indeed more likely to hold paranormal beliefs.
The researchers searched scientific article databases for texts containing the keywords “core knowledge” or “ontological confusion” and “paranormal” or “supernatural.” This search yielded 25 results from 22 studies published between 2010 and 2024, encompassing data from 16,129 participants. The participants’ average age was 28 years, and 66% were female. The studies represented findings from 11 countries: Australia, Canada, Finland, Germany, Japan, Romania, Russia, Slovakia, Spain, the United Kingdom, and the United States. Notably, 10 of the 25 results came from Finland.
The studies varied in the strength of the reported association between core knowledge confusions and belief in the paranormal. Some studies reported relatively weak associations, while others found very strong associations. However, all studies concluded that these two psychological characteristics are linked.
On average, the association between core knowledge confusions and belief in the paranormal was moderate in magnitude across all studies. When researchers focused on data from Finland, they found that the associations reported by Finnish studies were stronger than those from the rest of the group.
“Despite considerable heterogeneity and potential influences of unexamined moderators, the results suggest a universal cognitive pattern linking paranormal beliefs with certain types of ontological confusion. This meta-analysis underscores the need for further exploration into contextual variations in understanding the complex relationship between paranormal beliefs and ontological errors,” the study authors concluded.
The study sheds light on the links between core knowledge confusions and belief in the paranormal. However, it is important to note that the study design does not allow for causal conclusions to be drawn from the results.
The paper, “(https://doi.org/10.1016/j.paid.2024.112780) Paranormal beliefs and core knowledge confusions: A meta-analysis,” was authored by Albina Gallyamova, Elizaveta Komyaginskaya, and Dmitry Grigoryev.

(https://www.psypost.org/scientists-reveal-dopamine-and-serotonins-opposing-roles-in-fascinating-neuroscience-breakthrough/) Scientists reveal dopamine and serotonin’s opposing roles in fascinating neuroscience breakthrough
Dec 21st 2024, 10:00

A recent study from Stanford’s Wu Tsai Neurosciences Institute has shed light on the interplay between two key brain chemicals, dopamine and serotonin, revealing their opposing roles in shaping our decisions and learning processes. Published in (https://doi.org/10.1038/s41586-024-08412-x) Nature, the research demonstrates for the first time that dopamine and serotonin operate as a “gas and brake” system, jointly influencing how we learn from rewards. The findings have broad implications, from understanding everyday decision-making to developing treatments for neurological and psychiatric conditions such as addiction, depression, and Parkinson’s disease.
Dopamine and serotonin are crucial to many aspects of human behavior, including reward processing and decision-making. Both neurotransmitters are also implicated in a variety of mental health disorders. While previous research has established their individual roles—dopamine is linked to reward prediction and seeking, while serotonin promotes long-term thinking and patience—the precise nature of their interaction has remained unclear.
Two competing theories have sought to explain their dynamic: the “synergy hypothesis,” which posits that dopamine focuses on immediate rewards and serotonin on long-term benefits, and the “opponency hypothesis,” suggesting the two act in opposition, with dopamine encouraging impulsive action and serotonin promoting restraint. The Stanford researchers aimed to directly test these theories using advanced experimental methods.
“We’ve known for decades that dopamine and serotonin serve reward-related functions, and that they do so by acting on a common set of target brain regions. This implies that dopamine and serotonin systems work together to drive learning, but exactly how works remained hotly debated in the field,” explained study author (https://www.linkedin.com/in/danielcardozopinto/) Daniel F. Cardozo Pinto ((https://bsky.app/profile/dcardozopinto.bsky.social) @dcardozopinto), a postdoctoral scholar in the Department of Psychiatry & Behavioral Sciences at Stanford University.
When we kicked off this project around 2018, it was the first time that our genetic tools were advanced enough for us to attempt studying the dopamine and serotonin systems simultaneously. Once we got that to work, we knew we had the right new tool to break open an old and fascinating question.”
The team engineered a group of mice that allowed them to observe and manipulate dopamine and serotonin activity simultaneously. These mice were designed with specialized genetic modifications that enabled researchers to control the neurotransmitters using light, a technique known as optogenetics.
The experiments focused on a brain region called the nucleus accumbens, which is critical for motivation, emotion, and reward processing. Researchers trained the mice to associate specific cues—such as a tone and flashing light—with a sweet reward. During this learning process, the researchers recorded dopamine and serotonin signals and observed how they changed in response to rewards and cues.
They found that dopamine and serotonin activity shifted in opposite directions: dopamine increased with reward signals, while serotonin decreased. This supported the opponency hypothesis, indicating that the two neurotransmitters act as opposing forces during decision-making and learning.
To further test this dynamic, the team used optogenetics to selectively block or restore dopamine and serotonin activity during the learning tasks. Mice were unable to learn reward cues when both dopamine and serotonin signaling were suppressed. Surprisingly, neither neurotransmitter alone was sufficient to restore learning. Only when both systems were active could the mice effectively associate the cues with rewards.
In a related experiment, researchers tested the mice’s preferences for different brain states induced by manipulating dopamine and serotonin. Mice consistently preferred experiences that combined dopamine boosts and serotonin reductions—providing direct behavioral evidence of the opponency model.
“In short, we discovered that dopamine and serotonin signals form a gas-brake system for reward in the mammalian brain,” Cardozo Pinto told PsyPost. “More specifically, we found that when mice consume a sugar reward, dopamine in a key reward center goes up and serotonin goes down. In follow-up experiments, we then showed that artificially recreating both reward signals – a dopamine boost and a serotonin dip – drives reward learning more powerfully than either signal alone. To the best of our knowledge, this study is the first direct demonstration of an opponent relationship between dopamine and serotonin.”
These results have significant implications for understanding disorders that involve dopamine and serotonin dysfunction. For instance, addiction is associated with excessive dopamine activity, leading to compulsive reward-seeking. Depression, meanwhile, is linked to reduced serotonin activity, which may impair behavioral flexibility and long-term planning.
The researchers believe that future treatments for these conditions could target the balance between dopamine and serotonin. For example, therapies for addiction might aim to reduce dopamine activity while enhancing serotonin signaling, while depression treatments might focus on strengthening both systems to restore motivation and decision-making.
While the findings are compelling, the study has limitations. The experiments were conducted in mice, which, though a valuable model for neuroscience, may not fully capture the complexity of human brain function.
Future studies could investigate how these neurotransmitter systems function in different contexts, such as social behavior or stress. The tools developed for this study, which allow precise control and observation of multiple neurotransmitters, could also be applied to other brain chemicals and circuits.
Ultimately, the study underscores the importance of dopamine and serotonin balance in shaping behavior and decision-making. By uncovering how these neurotransmitters work in opposition, researchers have opened new avenues for understanding the brain and addressing the disorders that arise when this balance is disrupted.
“One major goal is to gain a better understanding of the underlying causes of disorders of reward processing – like depression and addiction – and our finding of dopamine and serotonin opponency is exciting because it opens important new research avenues in those fields,” Cardozo Pinto explained. “For example, our work could help explain why drugs that produce both dopamine and serotonin release tend to have lower abuse potential than drugs that primarily release dopamine alone. In general, our work suggests that the relative balance between dopamine and serotonin may play a crucial and previously underappreciated role in the etiology of these disorders.”
The study, “(https://www.nature.com/articles/s41586-024-08412-x) Opponent control of reinforcement by striatal dopamine and serotonin,” was authored by Daniel F. Cardozo Pinto, Matthew B. Pomrenze, Michaela Y. Guo, Gavin C. Touponse, Allen P. F. Chen, Brandon S. Bentzley, Neir Eshel, and Robert C. Malenka.

Forwarded by:
Michael Reeder LCPC
Baltimore, MD

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