A new study suggests that psychotherapy delivered through text-based messaging can be as effective as live video sessions for treating depression. The research, which compared outcomes for hundreds of adults using a commercial mental health platform, also found that patients were less likely to drop out of message-based therapy. These findings were published in JAMA Network Open.

Depression is a leading cause of disability worldwide, and while effective psychotherapies exist, many people face barriers to accessing care. Video-based therapy has expanded access by removing geographic constraints, but it still requires patients and therapists to coordinate schedules for live appointments.

Researchers wanted to investigate a more flexible alternative: message-based psychotherapy, which allows patients and therapists to communicate asynchronously through text, audio, or video messages. This method allows for more frequent contact and creates a written record of sessions that patients can review.

A team of researchers from the University of Washington partnered with the commercial digital mental health company Talkspace to conduct a large-scale clinical trial. They aimed to directly compare the effectiveness of message-based therapy with video-based therapy and to see if combining the two approaches could help patients who did not initially respond to treatment.

To conduct the study, the research team recruited 850 adults from across the United States who were diagnosed with depression. These participants were randomly assigned to one of two treatment groups for 12 weeks. One group received message-based psychotherapy, where they could exchange messages with their therapist at any time. The other group received weekly video-based psychotherapy, which consisted of scheduled 30- to 45-minute live video sessions. The study was designed in two phases.

After the first six weeks, the researchers assessed which participants were showing improvement. Those who were not responding to their assigned treatment were then randomly assigned again to a combination of therapies. For instance, non-responders in the messaging group had either weekly or monthly video sessions added to their treatment. Similarly, non-responders in the video group had messaging added to their existing sessions.

Throughout the study, participants regularly completed questionnaires to measure the severity of their depression symptoms and their ability to participate in social roles and activities. The researchers also collected data on treatment engagement, the quality of the patient-therapist relationship, and overall satisfaction with the care they received.

The results showed no significant difference in clinical outcomes between the two methods. Both groups experienced similar reductions in depression symptoms and similar improvements in social functioning over the 12-week period. The proportion of patients who responded to treatment or achieved remission from depression was nearly identical for both message-based and video-based therapy.

A notable difference appeared in patient engagement. The study found that participants assigned to weekly video sessions were significantly more likely to disengage from treatment within the first five weeks compared to those in the messaging group.

When examining the patient-therapist relationship, known as the therapeutic alliance, the researchers observed a nuanced pattern. Among patients who were not responding well to treatment early on, those in the video therapy group tended to report a stronger bond with their therapist compared to non-responders in the messaging group. This finding suggests that live video interaction may help in building initial rapport.

However, for patients who did not improve after six weeks, adding the alternative therapy method did not lead to better outcomes. Combining messaging with video for non-responders was not more effective than continuing with a single modality. The frequency of the added video sessions, whether weekly or monthly, also did not make a difference in patient improvement. Both groups reported high levels of satisfaction, though participants who received video therapy were slightly more likely to recommend the treatment to others.

The study has several limitations. It did not include a no-treatment control group, which means the researchers cannot completely rule out the possibility that some improvement occurred naturally over time. They note, however, that the remission rates in the study were higher than the typical rates of spontaneous recovery from depression.

The research team also disclosed potential conflicts of interest, as several of the study’s authors were employees of Talkspace, the platform on which the therapy was delivered. The study was funded by the National Institute of Mental Health, which had no role in the study’s design, data analysis, or the decision to publish the results.

For future research, the authors suggest exploring ways to enhance the therapeutic alliance in message-based therapy from the outset. One possibility could be incorporating an initial video session to help establish a stronger connection between the patient and therapist. The findings support the expansion of insurance coverage for message-based psychotherapy, which would make this flexible and effective form of treatment more widely accessible.

The study, “Message-Based vs Video-Based Psychotherapy for Depression: A Randomized Clinical Trial,” was authored by Michael D. Pullmann, Julien Rouvere, Patrick J. Raue, Isabell R. Griffith Fillipo, Brittany A. Mosser, Patrick J. Heagerty, Nicole Fridling-Cook, Aarthi Padmanabhan, Thomas D. Hull, and Patricia A. Areán.

A new study reveals a psychological pathway that connects narcissistic personality traits with the tendency to engage in social media trolling. The research suggests this link is partially explained by a person’s feelings of malicious envy and their exposure to antisocial media content. The findings were published in the journal Behaviour & Information Technology.

To understand the study, it helps to first understand the concepts involved. Narcissism is a personality trait characterized by a grandiose sense of self-importance, a need for admiration, and a sense of entitlement. Trolling, in the context of social media, refers to the act of posting inflammatory or provocative messages to intentionally upset others and disrupt online conversations. The researchers, Mars A. Brown and Masahiro Toyama from the Department of Psychology at Marshall University, sought to explore the mechanisms behind the known association between these two phenomena.

Previous research has shown mixed results on the connection between narcissism and trolling, but recent studies have more consistently found a link. The Marshall University team wanted to build on this work by examining potential intermediary factors. They focused on two distinct types of envy.

The first, benign envy, is a feeling that motivates a person to improve themselves to match someone they admire. The second, malicious envy, involves hostility and a desire to see a more successful person brought down. The researchers hypothesized that malicious envy, not benign envy, might serve as a bridge between narcissism and trolling. They also investigated whether exposure to antisocial media content, such as media depicting fighting or rule-breaking, played a role in this dynamic.

To test their ideas, the researchers recruited 326 adults from the United States using an online platform called Prolific. The participants completed a detailed online questionnaire designed to measure several psychological characteristics. They answered questions that assessed their level of narcissism, their tendencies toward both malicious and benign envy, and their self-reported trolling behaviors on social media.

The survey also gauged their frequency of exposure to antisocial media content. The questionnaire included standard psychological scales for these measures, as well as questions about personality traits like agreeableness and openness to experience, and demographic information like age and gender.

The analysis of the survey data produced a clearer picture of the relationship between these factors. The first major finding confirmed a direct association: individuals with higher narcissism scores were more likely to report engaging in social media trolling. This held true even when other personality traits and demographic factors were taken into account.

The researchers then looked at the role of envy. Their analysis showed that people with higher narcissism scores also reported higher levels of malicious envy. In turn, higher levels of malicious envy were associated with more frequent trolling. This suggests that for some people with narcissistic traits, seeing others succeed online can trigger a hostile envy that leads them to lash out through trolling. Benign envy, on the other hand, was not significantly connected to either narcissism or trolling in this study.

The study also identified a more complex, multi-step pathway. Narcissism was linked to higher malicious envy, which was then linked to a greater frequency of consuming antisocial media content. This increased exposure to antisocial media was, in turn, associated with a higher likelihood of trolling. In this model, narcissistic tendencies can foster a malicious envy that makes content depicting aggression and social defiance more appealing, and consuming this content may normalize or encourage trolling behavior.

Interestingly, even when these indirect pathways through malicious envy and media consumption were accounted for, a direct link between narcissism and trolling remained. This indicates that these intermediary factors are part of the story, but not the whole explanation. Other aspects of narcissism, such as a need for attention or a desire to feel superior by provoking others, may also directly contribute to trolling. The study also noted that individuals with lower levels of the personality trait agreeableness showed patterns similar to those with high narcissism.

The researchers acknowledge several limitations to their work. The study’s design is correlational, which means it shows associations between different factors but cannot prove that one causes another. The data was collected at a single point in time, and future studies that follow participants over time could provide more insight into how these behaviors develop.

Additionally, the study’s participants were recruited from the United States and were, on average, more highly educated than the general population. This means the findings may not be applicable to people in other countries or from different backgrounds. The study also treated narcissism as a single concept, while other research suggests it is a complex trait with multiple dimensions, such as grandiose and vulnerable narcissism, which could have different relationships with trolling.

Future research could explore these different facets of narcissism and investigate other potential factors, like a lack of empathy or the pleasure derived from others’ misfortune, known as schadenfreude.

The study, “Inside the link between narcissism and social media trolling: the involvement of malicious envy and exposure to antisocial media content,” was authored by Mars A. Brown and Masahiro Toyama.

A new study published in Archives of Sexual Behavior provides the most detailed account to date of women’s experiences with orgasms that occur during physical exercise. Through in-depth interviews, researchers found that these experiences often begin in childhood, are felt as a deep, internal sensation, and can be integrated into a person’s sexual life. This work builds on more than a decade of research that challenges the common understanding of orgasm as a strictly sexual event.

The research was conducted by a team at The Center for Sexual Health Promotion at Indiana University, led by Debby Herbenick, a prominent sexuality researcher. The scientific rationale for these studies stems from a desire to understand the full spectrum of human orgasmic response. Before this work began, the phenomenon was mostly a subject of popular curiosity, often called a “coregasm” in magazines and online forums because of its frequent association with abdominal workouts.

While orgasm is almost exclusively discussed in sexual contexts, historical medical literature and early sexuality research, like the Kinsey reports, had occasionally noted orgasms occurring during non-sexual activities. However, these observations were limited, and a scientific gap remained between the popular buzz and empirical evidence. By systematically investigating this phenomenon, the researchers hoped to gain a clearer picture of the physiological and psychological processes of orgasm, independent of sexual fantasy or direct genital stimulation.

This line of inquiry began with a foundational study in 2011. The researchers conducted an anonymous, internet-based survey of 530 women who had experienced either orgasm or sexual pleasure during exercise. The goal was to systematically describe a phenomenon that had, until then, been confined to popular media articles and scattered case reports. This initial study was exploratory, aiming to identify which exercises were most commonly associated with these experiences and what the experiences felt like for the women involved.

The findings from that first survey established a baseline understanding. Among women who reported exercise-induced orgasms, the most common activities were abdominal exercises, climbing poles or ropes, and lifting weights. A large portion of these women reported feeling self-conscious about their experience, particularly when exercising in public.

The data also showed that sexual thoughts or fantasies were rarely associated with these orgasms, suggesting the experience was primarily physiological rather than psychological in origin. For women who experienced sexual pleasure without orgasm, biking or spinning was frequently identified, along with abdominal exercises and weight lifting.

Seeking to understand the prevalence of this phenomenon in the general population, the research team conducted a follow-up study using data from the 2014 National Survey of Sexual Health and Behavior. This survey involved a nationally representative probability sample of over 2,000 U.S. adolescents and adults, allowing for a much broader and more generalizable analysis. This study was the first to provide population-level estimates for exercise-induced orgasm and included men in its analysis.

The 2021 study revealed that approximately 9% of the survey respondents reported having experienced an orgasm during exercise at least once in their lifetime. There was no statistically significant difference in the prevalence between men and women. The researchers did find a gender difference in the age of first experience, with women reporting a mean age of about 23, while men reported a mean age of about 17.

The types of exercises associated with the first experience were consistent with the 2011 findings and included abdominal exercises, climbing, and weight lifting for both genders. The analysis also identified an association between having an exercise-induced orgasm and having an orgasm during sleep, but not with having an orgasm during a recent partnered sexual event.

The most recent study, published in 2025, moved from quantitative surveys to qualitative interviews to capture the rich, lived experiences of women. The research team conducted in-depth, semi-structured interviews with 21 women, ranging in age from 19 to 68, who had a history of exercise-induced orgasms. The interviews took place in a setting equipped with exercise mats and a Roman chair, allowing participants to demonstrate, if they felt comfortable, the specific movements that led to their experiences. This method allowed for a detailed exploration of their personal histories, physical sensations, and emotional responses.

A key finding from these interviews was that the first experience with exercise-induced arousal or orgasm often occurred during childhood or early adolescence. Many women recalled feeling these sensations as young as five or six years old while climbing poles on a playground, doing gymnastics, or performing sit-ups in physical education class.

At the time, they were often confused by the sensations, with several participants describing the initial feeling as a sense that they needed to urinate. They lacked a framework for understanding what was happening to their bodies, but they recognized the feeling was pleasurable and, in some cases, sought to reproduce it.

The participants often described an “aha” moment, which typically occurred later in adolescence or adulthood, when they gained more sexual knowledge from peers, media, or their own sexual experiences. It was at this point they connected their childhood sensations with the concept of arousal and orgasm. One woman recounted how making out with someone for the first time made her realize, “This is the same feeling, how strange.” This moment of recognition helped them make sense of a long-standing, and sometimes bewildering, bodily experience.

The interviews provided detailed descriptions of how an exercise-induced orgasm feels physically. Many women characterized it as a deep, internal sensation, originating in the lower abdomen between the belly button and the pelvis. They often contrasted this with orgasms from direct clitoral stimulation, which they described as more external.

Some participants noted a progression of sensations, starting with a warmth or tingling in their core that would build and radiate downward. The experience was often predictable, with women learning that orgasm would occur after a certain number of repetitions of an exercise, such as after 50 leg lifts or during the third set of pull-ups.

The emotional responses to these experiences were complex and often evolved over time. Embarrassment and shame were common, especially when the orgasms occurred in public spaces like a gym or during a group fitness class. Participants worried that others might notice their facial expressions or hear them make sounds.

Some developed strategies to mask the experience, like keeping a serious facial expression, or to avoid it altogether by choosing different exercises. These feelings were sometimes rooted in cultural or familial taboos around sexuality, which made experiencing an orgasm in a non-sexual, public setting feel inappropriate or wrong.

Despite these negative feelings, many women came to accept and even enjoy their ability to have orgasms through exercise. Some viewed it as a motivator to work out, an “added perk at the end of the 100 reps.” Others described it as an empowering experience that gave them a sense of control over their own pleasure, independent of a partner. One woman explained that if she was not getting the attention she needed from her husband, exercise was another way to achieve the stress release of an orgasm.

A significant finding was how some women integrated their knowledge of exercise-induced orgasms into their sexual lives. After learning which muscle contractions produced pleasure during exercise, they were able to apply similar movements during partnered sex. One participant explained that she could tense her core muscles to achieve a stronger or faster orgasm, sometimes allowing her to climax at the same time as her partner. For some, exercise became a form of masturbation or foreplay, and for one woman, it was the only way she had been able to experience orgasm until recently.

These studies have some limitations. The initial survey used a convenience sample, which cannot be used to determine prevalence. The new qualitative study involved a small number of participants who were mostly young, white, and living in the United States, so their experiences may not reflect those of a more diverse population. Future research is needed to explore these experiences among men, gender-diverse individuals, people from different cultural backgrounds, and older adults.

A major direction for future research is to understand the physiological mechanism behind exercise-induced orgasms. It is still not known precisely how muscle contractions during certain exercises trigger an orgasmic response.

Subsequent studies could involve biomechanical analysis, neuro-imaging, or other physiological measures to investigate the roles of muscle tension, nerve pathways, and the sympathetic nervous system. A better understanding of the mechanism could have practical applications for physical therapists, personal trainers, and even military personnel who must pass rigorous fitness tests.

The study, “Exercise-induced orgasm and pleasure among women,” was authored by Debby Herbenick and J. Dennis Fortenberry.

The study, “Exercise-Induced Orgasm and Its Association with Sleep Orgasms and Orgasms During Partnered Sex: Findings From a U.S. Probability Survey,” was authored by Debby Herbenick, Tsung-chieh Fu, Callie Patterson, and J. Dennis Fortenberry.

The study, “Women’s Experiences with Exercise-Induced Orgasm: Findings from Qualitative Interviews,” was authored by Debby Herbenick, Callie Patterson Perry, J. Dennis Fortenberry, Ruhun Wasata, Jodi Wilson, Owen Miller, Kayla Willens, Alyssa Williams, and Georgia Frey.

Researchers have developed a new type of artificial neuron that physically emulates the electrochemical processes of biological brain cells. This innovation, which relies on the movement of atoms rather than electrons, could lead to computer chips that are vastly smaller and more energy-efficient. The study was published in the journal Nature Electronics.

The primary motivation for this research stems from the immense energy demands of modern artificial intelligence. Large AI models require vast computational resources, consuming electricity on a scale comparable to that of entire communities. In contrast, the human brain performs complex tasks like learning and recognition with remarkable efficiency, operating on only about 20 watts of power.

Neuromorphic computing is a field dedicated to designing systems that replicate the brain’s principles to achieve this level of efficiency. While many existing brain-inspired chips simulate neural activity using conventional digital electronics, this new work sought to create a device that physically embodies the analog dynamics of a real neuron.

To understand the innovation, it helps to first consider how a biological neuron functions. Neurons in the brain use a combination of electrical and chemical signals. An electrical pulse travels along the neuron until it reaches a junction called a synapse, where it is converted into a chemical signal. These chemical signals, often carried by charged particles called ions like sodium and potassium, cross the gap to the next neuron, where they can trigger a new electrical pulse. This process of ion movement is fundamental to how the brain processes information and learns.

The researchers constructed an artificial neuron that mirrors this ion-based mechanism. The device is composed of just three simple components: one specialized device called a diffusive memristor, one transistor, and one resistor. This compact design allows an entire artificial neuron to occupy the footprint of a single transistor, a substantial reduction from the tens or even hundreds of transistors needed for conventional artificial neuron circuits. Instead of moving electrons, the standard for nearly all modern electronics, this system operates by controlling the movement of silver ions within a thin oxide material.

When an electrical voltage is applied to the device, it causes the silver ions to move and form a conductive channel, generating an output spike of electricity. This action is analogous to a biological neuron firing. The physics governing the motion and diffusion of these silver ions is very similar to the dynamics of ions moving across a brain cell’s membrane. By using the physical movement of atoms, the device directly replicates the hardware-based learning process of the brain, often called “wetware.”

This approach differs from traditional computing, which relies on fast but volatile electrons. Computing with electrons is well-suited for software-based learning, where algorithms are run on general-purpose hardware. The brain, however, learns by physically reconfiguring its connections through ion movement, an inherently energy-efficient method. This is why a child can learn to recognize a new object after seeing only a few examples, while a computer often needs to be trained on thousands of images. The ion-based device brings artificial systems a step closer to this efficient, hardware-based learning style.

To verify its capabilities, the team demonstrated that their artificial neuron could successfully reproduce six key characteristics observed in biological neurons. These included leaky integration, where the neuron sums incoming signals over time but with a gradual decay. It also exhibited threshold firing, meaning it produces an output spike only after its input signals accumulate past a certain point. The researchers also confirmed cascaded propagation by showing that the output from one of their artificial neurons could successfully trigger a second one in a series.

The device also displayed more complex behaviors. It showed intrinsic plasticity, a process where a neuron’s recent firing history influences its future responsiveness, making it easier to fire again after recent activity. It also had a refractory period, a brief pause after firing during which it is resistant to firing again, which helps regulate neural activity. Finally, the neuron exhibited stochasticity, an element of randomness in its firing pattern that is also found in the brain and can be beneficial for certain computational tasks and for preventing systems from getting stuck in repetitive loops.

To assess how these neurons would perform in a complex network, the researchers created a detailed computational model of their device. They used this model to simulate a type of brain-inspired network called a recurrent spiking neural network. This network was then tested on a standard benchmark task: classifying spoken digits from a dataset of audio recordings. The simulated network, built from the principles of their new neuron, achieved a classification accuracy of 91.35 percent, a result that shows its potential as a building block for powerful and efficient computing systems.

The research does face some practical hurdles before it can be widely implemented. The silver used in the proof-of-concept device is not easily integrated into standard semiconductor manufacturing processes. Future work will involve exploring alternative materials and ions that offer similar dynamic properties but are compatible with existing fabrication technologies.

The next step for the researchers is to build and integrate large numbers of these artificial neurons to test their collective ability to replicate the brain’s efficiency and capabilities on a larger scale. Beyond creating more powerful AI, such brain-faithful systems could offer a unique platform for neuroscientists, potentially revealing new insights into the workings of the human brain itself.

The study, “A spiking artificial neuron based on one diffusive memristor, one transistor and one resistor,” was authored by Ruoyu Zhao, Tong Wang, Taehwan Moon, Yichun Xu, Jian Zhao, Piyush Sud, Seung Ju Kim, Han-Ting Liao, Ye Zhuo, Rivu Midya, Shiva Asapu, Dawei Gao, Zixuan Rong, Qinru Qiu, Cynthia Bowers, Krishnamurthy Mahalingam, S. Ganguli, A. K. Roy, Qing Wu, Jin-Woo Han, R. Stanley Williams, Yong Chen & J. Joshua Yang.

A recent study provides a detailed analysis of TikTok’s popular “Bold Glamour” filter, finding that its artificial intelligence makes specific, subtle changes that often align with the goals of common cosmetic procedures. The research, published in Plastic & Reconstructive Surgery-Global Open, quantifies these modifications to better understand how such digital tools are shaping modern beauty standards and influencing patient expectations in aesthetic medicine.

The Bold Glamour filter, released on the TikTok social media platform in early 2023, quickly gained widespread attention for its remarkable realism. Unlike earlier filters that often glitch or appear as a simple layer over a person’s image, Bold Glamour uses a more advanced form of artificial intelligence to generate a new, altered version of the face in real time.

While TikTok has not revealed the specific technology, experts suggest it employs a process known as a generative adversarial network, which compares a user’s face to a vast database of other images to produce a completely remodeled, airbrushed result.

This technological sophistication means the digital enhancements remain stable even when a user moves or covers parts of their face, making the effect appear uncannily natural and often difficult to detect. Researchers undertook this study because the filter’s seamless and persuasive nature raises questions about its impact on self-perception.

Psychologists have expressed concern that such realistic filters could warp a person’s understanding of what a normal face looks like, potentially making them feel alienated from their own appearance and more interested in pursuing plastic surgery. The filter’s ability to present a glossier, more sculpted version of oneself has prompted a broad public conversation about its potential to establish new, algorithmically-defined benchmarks for beauty that could influence requests for aesthetic surgery.

To measure the filter’s effects, the research team captured images of 10 female participants using a standard smartphone camera. For each participant, they analyzed one unfiltered photograph and one image generated by the Bold Glamour filter. The analysis was conducted using two methods. First, they employed an automated software that can identify and map nearly one thousand distinct points on a human face, allowing for precise digital measurement of changes to facial features. Second, the researchers performed manual observations to identify alterations in soft tissues, such as skin texture and the appearance of makeup.

The analysis revealed a pattern of distinct and consistent modifications. On a broad scale, the filter tended to increase the face’s overall dimensions, making the jawline appear wider and the forehead taller. Many of these structural changes were proportionally small, often altering a feature by less than 10 percent. This subtlety helps the filtered image retain a natural appearance while still creating a noticeable enhancement.

When examining specific features, the researchers documented more pronounced changes. The filter algorithmically refined the nose, reducing the width of the tip and the base while increasing the upward rotation of the nasal tip. It also created substantially fuller lips, augmenting the height of the upper lip by an average of 25 percent and the lower lip by 16 percent. Other changes included a slight lift of the right eyebrow and a more defined projection of the cheekbones.

Perhaps the most significant alterations were not structural but related to the skin and soft tissues. The filter produced a dramatic smoothing effect, which reduced the appearance of wrinkles, tear troughs under the eyes, and smile lines around the mouth. It also seemed to eliminate hyperpigmentation and apply digital makeup, such as thickening and darkening the eyebrows.

These changes mimic the results of common nonsurgical rejuvenation treatments, including chemical peels, laser resurfacing, and microblading. The filter appears to blend both feminizing features, like lifted eyebrows, and masculinizing ones, such as a stronger jaw, likely to appeal to a wide range of users.

The researchers note that these findings have direct relevance to the field of aesthetic medicine. Digital tools like the Bold Glamour filter could one day serve as aids during consultations, helping surgeons and patients visualize potential outcomes of procedures. For instance, the filter’s effects correspond to the goals of treatments like lip and brow lifts, rhinoplasty, and various skin resurfacing techniques. Such technology could facilitate better communication and help establish clearer expectations between a patient and a surgeon.

At the same time, the widespread use of these filters presents challenges. The digitally perfected images may promote unrealistic beauty ideals that are difficult or impossible to achieve through surgery. This could affect the psychological well-being of users, potentially contributing to body image issues or conditions like body dysmorphic disorder, where a person becomes obsessed with perceived flaws in their appearance. The study suggests that surgeons must be mindful of these risks, balancing the potential benefits of new technologies with an ethical responsibility to prioritize the patient’s overall health and well-being.

The study was not without its limitations. The analysis was based on a small sample of 10 female participants, so the findings may not apply to men, nonbinary individuals, or a more diverse population. Additionally, the photographs were taken with a smartphone rather than under standardized studio conditions, which may have introduced minor inconsistencies in the automated measurements.

Future research could address these points by using larger and more diverse participant groups and employing professional photography to ensure greater precision. Further investigations are also needed to understand the psychological effects of prolonged interaction with AI-modified self-images, especially among younger and more vulnerable populations.

The study, “Artificial Intelligence Beauty Filters and Aesthetic Surgery: Insights from TikTok’s Bold Glamour Filter,” was authored by John A. Toms, Annie M. Fritsch, Elizabeth O’Neill, Jubril Adepoju, and Mamtha S. Raj.

An international team of scientists has developed specialized nanoparticles that can reverse the cognitive symptoms of Alzheimer’s disease in mice. The treatment works by repairing the brain’s natural filtration and waste-removal system, leading to the rapid clearance of toxic proteins and long-lasting cognitive recovery. This research, published in Signal Transduction and Targeted Therapy, suggests that targeting the brain’s protective barrier could be a powerful new strategy for combating neurodegenerative diseases.

Alzheimer’s disease is a progressive brain disorder that gradually erodes memory and thinking skills. At its core, the disease is associated with the abnormal buildup of a protein called amyloid-beta. In a healthy brain, amyloid-beta is regularly cleared away, but in Alzheimer’s patients, it clumps together to form sticky plaques that disrupt communication between brain cells and trigger inflammation. For decades, researchers have searched for ways to remove these plaques or prevent their formation.

A key player in this process is the blood-brain barrier, a dense network of cells that acts as a highly selective gatekeeper for the brain. It allows essential nutrients to enter while blocking out harmful substances. This barrier also plays an active role in pushing waste products, including amyloid-beta, out of the brain and into the bloodstream for disposal. In Alzheimer’s disease, this barrier becomes dysfunctional, trapping amyloid-beta inside the brain and contributing to its accumulation. The scientists behind this new study focused on repairing this fundamental breakdown in the brain’s maintenance system.

The researchers engineered tiny, hollow spheres made of polymers, known as polymersomes. These are not simply vehicles to carry a drug; they are designed to be the therapeutic agent itself. The surface of each nanoparticle was decorated with a specific number of molecules that act like keys, designed to interact with a particular protein on the blood-brain barrier called LRP1. This protein, LRP1, is a primary transporter responsible for moving amyloid-beta out of the brain.

The team’s design was based on a sophisticated understanding of how LRP1 works. When LRP1 binds to large, sticky clumps of amyloid-beta, the binding is very strong. This strong interaction signals the cell to destroy the LRP1 protein, reducing the brain’s ability to clear amyloid. The researchers engineered their nanoparticles to have a “medium-strength” attraction to LRP1. This moderate binding doesn’t trigger the protein’s destruction. Instead, it encourages the LRP1 protein to efficiently shuttle its cargo out of the brain and then return to the barrier to repeat the process.

To test their design, the team used a well-established mouse model of Alzheimer’s disease. These mice are genetically programmed to develop amyloid plaques and cognitive decline similar to that seen in humans. The researchers administered just three intravenous injections of the nanoparticles to 12-month-old mice, an age when significant pathology is already present. The results were immediate and striking.

Within just two hours of a single injection, the amount of amyloid-beta in the brains of the treated mice dropped by nearly 45 percent. Concurrently, levels of amyloid-beta in their bloodstream increased by eight times. This provided clear evidence that the nanoparticles were successfully helping the blood-brain barrier transport the toxic protein out of the brain and into general circulation, where it could be disposed of by the body.

To visualize these effects in living animals, the team used positron emission tomography, a type of brain imaging that can detect amyloid plaques. Scans taken before the treatment showed significant amyloid buildup in the Alzheimer’s model mice. Just 12 hours after receiving the nanoparticles, new scans revealed a sharp decrease in the amyloid signal. Further analysis using advanced 3D imaging of the entire brain confirmed an overall reduction in amyloid volume of approximately 41 percent.

The treatment did more than just remove amyloid; it appeared to restore the health of the blood-brain barrier itself. The researchers found that after treatment, the levels of the LRP1 transport protein on the barrier cells returned to normal. They also observed changes in other cellular proteins, indicating that the nanoparticles had successfully shifted the barrier’s transport mechanism from a destructive pathway to a protective and efficient one.

The most significant finding was the effect on cognition and behavior. To measure this, the scientists used the Morris water maze, a standard test of spatial learning and memory in rodents. In this test, mice must learn the location of a hidden platform in a small pool of water. Before treatment, the Alzheimer’s mice struggled with this task. After receiving the nanoparticles, their performance improved dramatically, becoming nearly indistinguishable from that of healthy, non-diseased mice.

Remarkably, this cognitive recovery was long-lasting. The researchers tested the same mice again six months after the initial three-dose treatment. Even after this extended period, the treated mice retained their improved cognitive abilities, performing just as well as healthy mice of the same age. Additional behavioral tests, such as those measuring nest-building ability and preference for sweet tastes, further supported the conclusion that the treatment had restored not only memory but also the animals’ overall quality of life.

While these results offer a promising new avenue for Alzheimer’s research, the study has limitations. The experiments were conducted in mice, and animal models, though valuable, do not perfectly replicate the complexity of human Alzheimer’s disease. The path from a successful mouse study to a safe and effective human therapy is a long one that will require extensive further investigation.

Future research will likely focus on confirming these mechanisms in more complex models and eventually testing the safety and efficacy of such a strategy in humans. The study also opens the door to applying this concept of “barrier repair” to other neurological disorders where blood-brain barrier dysfunction is a known factor, such as Parkinson’s disease or amyotrophic lateral sclerosis. By shifting the focus from simply targeting a disease’s symptoms to repairing the underlying biological systems, this work establishes a new and potentially powerful approach in the fight against neurodegeneration.

The study, “Rapid amyloid-β clearance and cognitive recovery through multivalent modulation of blood–brain barrier transport,” was authored by Junyang Chen, Pan Xiang, Aroa Duro-Castano, Huawei Cai, Bin Guo, Xiqin Liu, Yifan Yu, Su Lui, Kui Luo, Bowen Ke, Lorena Ruiz-Pérez, Qiyong Gong, Xiaohe Tian & Giuseppe Battaglia.

A team of researchers in Brazil has engineered an inexpensive, disposable sensor that can detect a key protein linked to mental health conditions using a drop of saliva. Published in the journal ACS Polymers Au, the device could one day offer a rapid, non-invasive tool to help in the diagnosis and monitoring of disorders like depression and schizophrenia. The results are available in under an hour, offering a significant departure from current lab-based methods.

Diagnosing and managing psychiatric disorders currently relies heavily on clinical interviews and patient-reported symptoms, which can be subjective. Scientists have been searching for objective biological markers, and a protein called brain-derived neurotrophic factor, or BDNF, has emerged as a promising candidate. Lower-than-normal levels of BDNF, which supports the health and growth of neurons, have been consistently associated with conditions like major depression, bipolar disorder, and schizophrenia.

Existing methods for measuring BDNF typically involve blood draws and rely on complex, time-consuming laboratory procedures like the enzyme-linked immunosorbent assay. These techniques are often expensive and require specialized equipment and personnel, making them impractical for routine clinical use or for monitoring patient progress outside of a dedicated lab. The researchers sought to develop a fast, affordable, and non-invasive alternative that could be used at the point of care, motivated by the global increase in mental health conditions.

The foundation of the device is a small, flexible strip of polyester, similar to a piece of plastic film. Using a screen-printing technique, the scientists printed three electrodes onto this strip using carbon- and silver-based inks. This fabrication method is common in electronics and allows for inexpensive, mass production of the sensor strips.

To make the sensor specific to BDNF, the team modified the surface of the main working electrode in a multi-step process. First, they coated it with a layer of microscopic carbon spheres, which are synthesized from a simple glucose solution. This creates a large, textured surface area that is ideal for anchoring other molecules and enhances the sensor’s electrical sensitivity.

Next, they added a sequence of chemical layers that act as a sticky foundation for the biological components. Onto this foundation, they attached specialized proteins called antibodies. These anti-BDNF antibodies are engineered to recognize and bind exclusively to the BDNF protein, much like a key fits into a specific lock. A final chemical layer was added to block any remaining empty spots on the surface, which prevents other molecules in saliva from interfering with the measurement.

When a drop of saliva is applied to the sensor, any BDNF protein present is captured by the antibodies on the electrode. This binding event physically alters the electrode’s surface, creating a minute barrier that impedes the flow of electrons. The device then measures this change by sending a small electrical signal through the electrode and recording its resistance to that signal.

A greater amount of captured BDNF creates a larger barrier, resulting in a higher resistance, which can be precisely quantified. The entire process, from sample application to result, can be completed in about 35 minutes. The data is captured by a portable analyzer that can communicate wirelessly with a device like a smartphone, allowing for real-time analysis.

The research team demonstrated that their biosensor was remarkably sensitive. It could reliably detect BDNF across a vast concentration range, from incredibly minute amounts (as low as 10⁻²⁰ grams per milliliter) up to levels typically seen in healthy individuals.

This wide detection range is significant because it means the device could potentially identify the very low BDNF levels that may signal a disorder. It could also track the increase in BDNF levels as a patient responds positively to treatment, such as antidepressants, offering an objective measure of therapeutic success.

The sensor also proved to be highly selective. When tested against a variety of other substances commonly found in saliva, including glucose, uric acid, paracetamol, and even the spike protein from the SARS-CoV-2 virus, the device did not produce a false signal. It responded specifically to BDNF, confirming the effectiveness of its design.

Furthermore, tests using human saliva samples that were supplemented with known quantities of the protein showed that the sensor could accurately measure BDNF levels even within this complex biological fluid. The researchers estimated the cost of the materials for a single disposable strip to be around $2.19, positioning it as a potentially accessible diagnostic tool.

The current study was a proof-of-concept and has certain limitations. The experiments were conducted with a limited number of saliva samples from a single volunteer, which were then modified in the lab to contain varying concentrations of the target protein.

The next essential step will be to test the biosensor with a large and diverse group of patients diagnosed with various psychiatric conditions to validate its accuracy and reliability in a real-world clinical setting. Such studies would be needed to establish clear thresholds for what constitutes healthy versus potentially pathological BDNF levels in saliva. The researchers also plan to secure a patent for their technology and refine the device for potential commercial production. Future work could also explore integrating sensors for other biomarkers onto the same strip, allowing for a more comprehensive health assessment from a single saliva sample.

The study, “Low-Cost, Disposable Biosensor for Detection of the Brain-Derived Neurotrophic Factor Biomarker in Noninvasively Collected Saliva toward Diagnosis of Mental Disorders,” was authored by Nathalia O. Gomes, Marcelo L. Calegaro, Luiz Henrique C. Mattoso, Sergio A. S. Machado, Osvaldo N. Oliveira Jr., and Paulo A. Raymundo-Pereira.

Researchers have developed a new method for training artificial intelligence that dramatically improves its speed and energy efficiency by mimicking the structured wiring of the human brain. The approach, detailed in the journal Neurocomputing, creates AI models that can match or even exceed the accuracy of conventional networks while using a small fraction of the computational resources.

The study was motivated by a growing challenge in the field of artificial intelligence: sustainability. Modern AI systems, such as the large language models that power generative AI, have become enormous. They are built with billions of connections, and training them can require vast amounts of electricity and cost tens of millions of dollars. As these models continue to expand, their financial and environmental costs are becoming a significant concern.

“Training many of today’s popular large AI models can consume over a million kilowatt-hours of electricity, which is equivalent to the annual use of more than a hundred US homes, and cost tens of millions of dollars,” said Roman Bauer, a senior lecturer at the University of Surrey and a supervisor on the project. “That simply isn’t sustainable at the rate AI continues to grow. Our work shows that intelligent systems can be built far more efficiently, cutting energy demands without sacrificing performance.”

To find a more efficient design, the research team looked to the human brain. While many artificial neural networks are “dense,” meaning every neuron in one layer is connected to every neuron in the next, the brain operates differently. Its connectivity is highly sparse and structured. For instance, in the visual system, neurons in the retina form localized and orderly connections to process information, creating what are known as topographical maps. This design is exceptionally efficient, avoiding the need for redundant wiring. The brain also refines its connections during development, pruning away unnecessary pathways to optimize its structure.

Inspired by these biological principles, the researchers developed a new framework called Topographical Sparse Mapping, or TSM. Instead of building a dense network, TSM configures the input layer of an artificial neural network with a sparse, structured pattern from the very beginning. Each input feature, such as a pixel in an image, is connected to only one neuron in the following layer in an organized, sequential manner. This method immediately reduces the number of connections, known as parameters, which the model must manage.

The team then developed an enhanced version of the framework, named Enhanced Topographical Sparse Mapping, or ETSM. This version introduces a second brain-inspired process. After the network trains for a short period, it undergoes a dynamic pruning stage. During this phase, the model identifies and removes the least important connections throughout its layers, based on their magnitude. This process is analogous to the synaptic pruning that occurs in the brain as it learns and matures, resulting in an even leaner and more refined network.

To evaluate their approach, the scientists built and trained a type of network known as a multilayer perceptron. They tested its ability to perform image classification tasks using several standard benchmark datasets, including MNIST, Fashion-MNIST, CIFAR-10, and CIFAR-100. This setup allowed for a direct comparison of the TSM and ETSM models against both conventional dense networks and other leading techniques designed to create sparse, efficient AI.

The results showed a remarkable balance of efficiency and performance. The ETSM model was able to achieve extreme levels of sparsity, in some cases removing up to 99 percent of the connections found in a standard network. Despite this massive reduction in complexity, the sparse models performed just as well as, and sometimes better than, their dense counterparts. For the more difficult CIFAR-100 dataset, the ETSM model achieved a 14 percent improvement in accuracy over the next best sparse method while using far fewer connections.

“The brain achieves remarkable efficiency through its structure, with each neuron forming connections that are spatially well-organised,” said Mohsen Kamelian Rad, a PhD student at the University of Surrey and the study’s lead author. “When we mirror this topographical design, we can train AI systems that learn faster, use less energy and perform just as accurately. It’s a new way of thinking about neural networks, built on the same biological principles that make natural intelligence so effective.”

The efficiency gains were substantial. Because the network starts with a sparse structure and does not require complex phases of adding back connections, it trains much more quickly. The researchers’ analysis of computational costs revealed that their method consumed less than one percent of the energy and used significantly less memory than a conventional dense model. This combination of speed, low energy use, and high accuracy sets it apart from many existing methods that often trade performance for efficiency.

A key part of the investigation was to confirm the importance of the orderly, topographical wiring. The team compared their models to networks that had a similar number of sparse connections but were arranged randomly. The results demonstrated that the brain-inspired topographical structure consistently produced more stable training and higher accuracy, indicating that the specific pattern of connectivity is a vital component of its success.

The researchers acknowledge that their current framework applies the topographical mapping only to the model’s input layer. A potential direction for future work is to extend this structured design to deeper layers within the network, which could lead to even greater gains in efficiency. The team is also exploring how the approach could be applied to other AI architectures, such as the large models used for natural language processing, where the efficiency improvements could have a profound impact.

The study, “Topographical sparse mapping: A neuro-inspired sparse training framework for deep learning models,” was authored by Mohsen Kamelian Rad, Ferrante Neri, Sotiris Moschoyiannis, and Roman Bauer.

A new study reveals the human brain’s remarkable ability to maintain communication between its two hemispheres even when the primary connection is almost entirely severed. Researchers discovered that a tiny fraction of remaining nerve fibers is sufficient to sustain near-normal levels of integrated brain function, a finding published in the Proceedings of the National Academy of Sciences. This observation challenges long-held ideas about how the brain is wired and suggests an immense potential for reorganization after injury.

The brain’s left and right hemispheres are linked by the corpus callosum, a massive bundle of about 200 million nerve fibers that acts as a superhighway for information. For decades, scientists have operated under the assumption that this structure has a map-like organization, where specific fibers connect corresponding regions in each hemisphere to perform specialized tasks. Based on this model, damage to a part of the corpus callosum should result in specific, predictable communication breakdowns between the brain halves.

To test this idea, researchers turned to a unique group of individuals known as split-brain patients. These patients have undergone a rare surgical procedure called a callosotomy, where the corpus callosum is intentionally cut to treat severe, otherwise untreatable epilepsy. This procedure provides a distinct opportunity to observe how the brain functions when its main inter-hemispheric pathway is disrupted. Because the surgery is no longer common, data from adult patients using modern neuroimaging techniques has been scarce, leaving a gap in understanding how this profound structural change affects the brain’s functional networks.

The international research team studied six adult patients who had undergone the callosotomy procedure. Four of the patients had a complete transection, meaning the entire corpus callosum was severed. Two other patients had partial transections. One had about 62 percent of the structure intact, while another, patient BT, had approximately 90 percent of his corpus callosum removed, leaving only a small segment of fibers, about one centimeter wide, at the very back of the structure.

To assess the functional consequences, the researchers first performed simple bedside behavioral tests. The four patients with complete cuts exhibited classic “disconnection syndromes,” where one hemisphere appeared unable to share information with the other. For example, they could not verbally name an object placed in their left hand without looking at it, because the sensation from the left hand is processed by the right hemisphere, while language is typically managed by the left. The two hemispheres were acting independently.

In contrast, both patients with partial cuts showed no signs of disconnection. Patient BT, despite having only a tiny bridge of fibers remaining, could perform these tasks successfully, indicating robust communication was occurring between his hemispheres.

To look directly at brain activity, the team used resting-state functional magnetic resonance imaging, or fMRI. This technique measures changes in blood flow throughout the brain, allowing scientists to identify which regions are active and working together. When two regions show synchronized activity over time, they are considered to be functionally connected. The researchers compared the brain activity of the six patients to a benchmark dataset from 100 healthy adults.

In the four patients with a completely severed corpus callosum, the researchers saw a dramatic reduction in functional connectivity between the two hemispheres. The brain’s large-scale networks, which normally span both sides of the brain, appeared highly “lateralized,” meaning their activity was largely confined to either the left or the right hemisphere. It was as if each side of the brain was operating in its own bubble, with very little coordination between them.

The findings from the two partially separated patients were strikingly different. Their patterns of interhemispheric functional connectivity looked nearly identical to those of the healthy control group. Even in patient BT, the small remnant of posterior fibers was enough to support widespread, brain-wide functional integration. His brain networks for attention, sensory processing, and higher-order thought all showed normal levels of bilateral coordination. This result directly contradicts the classical model, which would have predicted that only the brain regions directly connected by those few remaining fibers, likely related to vision, would show preserved communication.

The researchers also analyzed the brain’s dynamic activity, looking at how moment-to-moment fluctuations are synchronized across the brain. In healthy individuals, the overall rhythm of activity in the left hemisphere is tightly coupled with the rhythm in the right hemisphere. In the patients with complete cuts, these rhythms were desynchronized, as if each hemisphere was marching to the beat of its own drum.

Yet again, the two patients with partial cuts showed a strong, healthy synchronization between their hemispheres, suggesting the small bundle of fibers was sufficient to coordinate the brain’s global dynamics. Patient BT’s brain had apparently reorganized its functional networks over the six years since his surgery to make optimal use of this minimal structural connection.

The study is limited by its small number of participants, a common challenge in research involving rare medical conditions. Because the callosotomy procedure is seldom performed today, finding adult patients for study is difficult. While the differences observed between the groups were pronounced, larger studies would be needed to fully characterize the range of outcomes and the ways in which brains reorganize over different timescales following surgery.

Future research could focus on tracking patients over many years to map the process of neural reorganization in greater detail. Such work may help uncover the principles that govern the brain’s plasticity and its ability to adapt to profound structural changes. The findings open new avenues for rehabilitation research, suggesting that therapies could aim to leverage even minimal remaining pathways to help restore function after brain injury. The results indicate that the relationship between the brain’s physical structure and its functional capacity is far more flexible and complex than previously understood.

The study, “Full interhemispheric integration sustained by a fraction of posterior callosal fibers,” was authored by Tyler Santander, Selin Bekir, Theresa Paul, Jessica M. Simonson, Valerie M. Wiemer, Henri Etel Skinner, Johanna L. Hopf, Anna Rada, Friedrich G. Woermann, Thilo Kalbhenn, Barry Giesbrecht, Christian G. Bien, Olaf Sporns, Michael S. Gazzaniga, Lukas J. Volz, and Michael B. Miller.

A new study suggests that revealing the political affiliations of a newsroom’s journalists can influence public trust and engagement. The research, published in Communication Research, found that people report higher trust in news outlets they perceive as politically balanced or those that provide no political information about their staff, compared to outlets dominated by one party.

The motivation for this research stems from the steady decline of public trust in the news media within the United States. Scholars and journalists alike have been exploring ways to rebuild this confidence, with a particular focus on the concept of journalistic transparency. The idea is that by being more open about how news is gathered and produced, outlets can signal their honesty and integrity to the public. This openness can serve as a mental shortcut, or heuristic, that helps people decide whether a source is credible.

The researchers wanted to test a specific and rarely examined form of transparency: disclosing the collective political leanings of the journalists working at a news outlet. They sought to understand if this information would help or hinder trust and whether people’s own political identities would shape their reactions.

To investigate this question, the researchers conducted a series of three online experiments. In each experiment, participants were shown a brief description of a news outlet. They were then randomly assigned to see different versions of a graphic that displayed the political composition of that outlet’s newsroom. After viewing the description and graphic, participants answered questions designed to measure their trust in the outlet, their intention to use it for news in the future, and their intention to actively avoid it.

The first experiment focused on political ideology. Participants were shown information about a real news program, The National Desk, and were assigned to one of four conditions. One group received no information about the journalists’ politics, serving as a control. A second group was told the newsroom was perfectly balanced with an equal number of liberal and conservative journalists. The third and fourth groups were told the newsroom had a large majority of either liberal journalists or conservative journalists.

The results showed that participants had significantly higher trust in the outlet when it was presented as balanced or when no political information was provided. Correspondingly, they reported a greater willingness to use these outlets and a lower intention to avoid them. There was no meaningful difference in trust between the balanced outlet and the one with no political information disclosed.

This initial experiment also revealed a powerful pattern related to partisanship. Democrats and Republicans both expressed much lower trust in the outlet that was dominated by the opposing ideology. For example, Democrats rated the conservative-majority newsroom as far less trustworthy, while Republicans felt the same way about the liberal-majority newsroom. This points to a strong “out-group bias,” where people are quick to distrust a source associated with a political group they oppose.

However, the study did not find evidence of an “in-group favoritism.” Democrats did not trust the liberal-majority outlet any more than the balanced or unaffiliated one, and Republicans showed a similar lack of preference for the conservative-majority outlet.

The second experiment extended these ideas by focusing on party affiliation rather than general ideology. The design was similar, but this time the breakdown included Democrats, Republicans, and Independents. A fifth condition was added to test perceptions of a newsroom with a majority of Independent journalists.

The findings from this experiment closely mirrored the first. People reported the most trust in the outlets that were politically balanced, had a majority of Independents, or provided no partisan information at all. The outlets with a clear Democratic or Republican majority were trusted significantly less. Again, the pattern of out-group dislike was strong among both Democrats and Republicans, with no accompanying favoritism for their own party’s newsroom.

The third and final experiment was designed to confirm that these effects were not tied to the specific name of the news program used in the first two studies. The researchers replicated the second experiment’s design but used a fictional news organization called the Independent News Network, a name pre-tested to be seen as neutral.

The results were consistent for a third time. This replication strengthens the conclusion that it is the information about the political composition of the newsroom, not a pre-existing perception of an outlet’s brand, that drives these judgments about trust. The studies also consistently showed that trust acted as the key mechanism. When people perceived an outlet as less trustworthy because of its partisan slant, that decrease in trust directly led to their intentions to avoid the outlet and not use it in the future.

The researchers note some limitations to their work. The studies presented a hypothetical situation, as news organizations do not typically publicize the partisan breakdown of their staff, which means the experiments may not perfectly reflect real-world behavior. The study also measured general perceptions of an outlet without providing participants with any specific news articles, and people’s reactions might change depending on the topic of the news.

Future research could explore whether these findings hold when applied to well-known media brands, which people already have strong opinions about. It could also examine how people react to specific news stories when they are aware of the political leanings of the newsroom that produced them.

The study, “In Diversity We Trust? Examining the Effect of Political Newsroom Diversity on Media Trust, Use, and Avoidance,” was authored by Eliana DuBosar, Jay D. Hmielowski, and Muhammad Ehab Rasul.

A new study published in the journal Psychology of Aesthetics, Creativity, and the Arts suggests that individuals with a combination of high narcissism and psychological insecurity are more likely to be “cultural omnivores,” consuming both highbrow and lowbrow art forms. This behavior appears to be a strategy to satisfy two distinct psychological needs: signaling social status and projecting a sense of personal integrity.

Narcissism is often understood as a personality trait characterized by a grandiose sense of self, a persistent need for admiration, and a focus on one’s own importance. While this may project an image of supreme confidence, psychological research has shown that narcissism can exist alongside deep-seated feelings of insecurity, such as low self-esteem or a sense that one is not living as their “true self.” It is this particular combination of traits that interested the researchers.

Traditionally, cultural taste was seen through the lens of social class. Sociologists argued that elites used their preference for “highbrow” culture, like classical music and fine art, to distinguish themselves from other social classes. In recent decades, however, this pattern has shifted. Observers have noted the rise of the “cultural omnivore,” an individual who appreciates both high-status cultural products and more popular, “lowbrow” forms like pop music or street art.

The study’s authors proposed that this modern trend might be explained not just by social class, but by specific personality dynamics. They hypothesized that people high in narcissism but low in self-security might use cultural consumption as a tool. Liking highbrow culture could serve their need to signal superior status, while an appreciation for lowbrow culture, often seen as more authentic, could help soothe their inner feelings of inauthenticity.

To investigate this idea, the researchers conducted two separate studies. In the first experiment, they surveyed 178 university students. Participants completed questionnaires designed to measure their levels of narcissism and self-esteem. They were then asked to rate how likely they would be to participate in a variety of cultural activities.

Some of these activities were classified as highbrow, including attending a classical symphony or visiting art galleries. Others were categorized as lowbrow, such as going to pop concerts or viewing graffiti and street art. The researchers analyzed the data to see if there was a connection between the participants’ personality scores and their cultural intentions.

The findings revealed a distinct pattern. For individuals who scored high on the narcissism scale, having lower self-esteem was associated with a stronger intention to participate in highbrow cultural activities. A similar relationship appeared for lowbrow culture. The participants with high narcissism and low self-esteem also expressed a greater interest in lowbrow activities.

This confirmed that the insecure narcissist profile was linked to being a cultural omnivore, showing an appetite for both ends of the cultural spectrum. The analysis also suggested that this behavior was connected to a general motivation for “distinction seeking,” or a desire to establish a unique and notable identity through their choices. This relationship held even when the researchers accounted for other factors, like a person’s openness to new experiences or their own perception of their social status.

The second study was designed to explore the specific motivations behind these dual preferences. The researchers wanted to confirm if status seeking was driving the interest in highbrow culture, while a need for integrity was behind the preference for lowbrow culture. This experiment involved 144 university students and used a slightly different approach.

Instead of measuring general self-esteem, the researchers measured a more specific form of insecurity known as self-alienation, which is the feeling of being out of touch with one’s true self. They also focused on a particular aspect of narcissism related to superiority and arrogance. Participants were then randomly assigned to read a biography of a fictional artist.

One version of the biography presented the artist as highbrow, noting that her paintings were exhibited in major museums around the world. The other version framed her as lowbrow, explaining that her work was given to family and friends before being discovered by an art dealer in her hometown. After reading one of the biographies, participants rated their interest in seeing the artist’s work. They also answered questions about their current motivations, including their desire to signal status and their need to project self-integrity.

The results of this experiment provided clearer support for the researchers’ hypothesis. Among participants who read about the highbrow artist, those with the insecure narcissist profile showed greater interest in her work. This increased interest was statistically linked to a heightened desire for status at that moment. Consuming high-status art appeared to satisfy their need to be seen as having high status.

For the participants who read about the lowbrow artist, a different motivation was at play. In this case, the insecure narcissist group’s interest in the art was connected to their desire to signal self-integrity. The perceived authenticity of the lowbrow artist seemed to offer a way for these individuals to bolster their own shaky sense of self. The two studies together paint a nuanced picture of how personality can shape cultural tastes.

This research provides a new psychological perspective on a phenomenon that has largely been studied through a sociological framework. It suggests that for some people, the choice of what art to consume is not merely a matter of taste but a complex strategy for managing their identity and internal insecurities.

The authors note that their findings are based on statistical associations, and future research could explore these mechanisms further. For instance, an experiment could temporarily change a person’s feelings of security to see if it directly affects their cultural preferences. Researchers could also examine whether this pattern of behavior extends to other domains, such as luxury consumption, social media use, or even charitable giving.

The study, “How Insecure Narcissists Become Cultural Omnivores: Consuming Highbrow Culture for Status Seeking and Lowbrow Culture for Integrity Signaling,” was authored by Hanna Shin and Nara Youn.

A single dose of testosterone can alter the fundamental learning processes men use to avoid harm, making them more sensitive to negative outcomes when their own well-being is on the line. The study, published in the journal Biological Psychology, reveals a nuanced role for the hormone, suggesting it fine-tunes self-preservation mechanisms, which in turn affects prosocial behavior.

Testosterone is associated with the pursuit of social status, but most studies have focused on behaviors related to acquiring rewards. Less understood is the hormone’s role in avoiding harm, a behavior that is equally significant for one’s standing in a group. Successfully avoiding harm to oneself signals strength and competence, while avoiding harm to others demonstrates moral character and builds a trustworthy reputation. Scientists hypothesized that testosterone might support both self-protective and prosocial harm avoidance, but that it might achieve this through distinct computational mechanisms in the brain.

To investigate this, the study team recruited 120 healthy male university students. In a double-blind procedure, participants were randomly assigned to receive either a single dose of testosterone gel or an identical-looking placebo gel applied to their shoulders. Three hours later, after the hormone had reached peak levels in the body, the participants began a learning task designed to measure how they learn to prevent harm to themselves and to a stranger.

In the task, participants repeatedly chose between two abstract symbols on a screen. One symbol had a high probability (75%) of avoiding a mild electric shock, while the other had a low probability (25%). In some blocks of trials, the potential shock was for the participant himself (the “Self” condition). In other blocks, the shock was for another participant, a confederate who they believed was in an adjacent room (the “Other” condition). Over 64 trials for each condition, participants had to learn through trial and error which symbol was the safer choice.

The researchers analyzed the results in two ways. First, they looked at the participants’ overall performance. They found that men in both the testosterone and placebo groups learned the task successfully. Participants generally made more correct choices for themselves than for others, but their learning curve was steeper when making decisions for another person, meaning they caught up more quickly. The testosterone group showed a small but distinct difference: the performance gap between making choices for themselves and for others persisted for more trials than it did in the placebo group.

To understand the learning processes behind these choices, the researchers used computational modeling. This approach, based on reinforcement learning theory, allows scientists to estimate the hidden mental variables that guide decisions. A key concept is the “prediction error,” which is the difference between an expected outcome and the actual outcome. Learning occurs when we use this error to update our expectations. The model estimated “learning rates,” which quantify how much weight a person gives to these prediction errors.

The researchers were particularly interested in whether learning rates differed for positive prediction errors (good news, like avoiding a shock) and negative prediction errors (bad news, like receiving a shock).

The modeling revealed that the most accurate description of participants’ behavior involved separate learning rates for good and bad news, and that these rates changed depending on who was at risk. In the placebo group, men showed a higher learning rate from negative outcomes when another person could be shocked, compared to when they themselves were at risk. This suggests a heightened sensitivity to causing harm to others.

The testosterone group, however, displayed a different pattern of learning. Specifically, when making decisions for themselves, men who received testosterone learned significantly more from negative outcomes and less from positive outcomes compared to the placebo group. Essentially, the hormone appeared to increase their sensitivity to the possibility of personal harm. When making choices for the other person, their learning rates were not significantly different from the placebo group.

The researchers also calculated a “prosocial learning index” by comparing the learning rate for others to the learning rate for self. This analysis showed that the testosterone group had a lower prosocial learning rate from negative outcomes compared to the placebo group. This change was not because they cared less about the other person; it was a consequence of their self-related learning from harm becoming so much stronger.

An additional finding involved trait anxiety. In the placebo group, men with higher anxiety learned more quickly from negative outcomes when another’s well-being was at stake, which aligns with the idea that anxiety increases sensitivity to threats. In the testosterone group, this relationship was reversed. Higher anxiety was associated with reduced learning from negative outcomes for others relative to oneself. This finding provides computational support for the idea that testosterone can have anxiety-reducing effects, altering how personality traits influence social decision-making.

The study does have some limitations that open paths for future inquiry. The research included only male participants, so the findings cannot be generalized to others. Replicating the results with a larger, preregistered study would increase confidence in the conclusions. Future experiments could also include a condition where participants believe their choices are being observed by others, which would provide a more direct test of the social status hypothesis in a harm-avoidance context.

The study, “Testosterone modulates harm-avoidance learning for the self and others through distinct computational mechanisms,” was authored by Shaoxiong Liu, Haohui Wang, Cheng-Ta Yang, and Honghong Tang.