<table style="border:1px solid #adadad; background-color: #F3F1EC; color: #666666; padding:8px; -webkit-border-radius:4px; border-radius:4px; -moz-border-radius:4px; line-height:16px; margin-bottom:6px;" width="100%">
<tbody>
<tr>
<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">PsyPost – Psychology News</span></td>
</tr>
<tr>
<td> </td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/ai-detects-hidden-movement-clues-linked-to-parkinsons-disease/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">AI detects hidden movement clues linked to Parkinson’s disease</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Sep 13th 2025, 10:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>Scientists have developed an artificial intelligence system capable of identifying subtle signs of brain disorders, including Parkinson’s disease, by analyzing simple video recordings of a person’s hand movements. The technology successfully pinpointed minute motor impairments in individuals whose performance had been judged as perfectly normal by expert neurologists, opening a new avenue for detecting neurodegenerative conditions at their earliest stages. The findings are published in <em>Nature</em>. </p>
<p>Researchers are persistently searching for better ways to identify neurodegenerative diseases like Parkinson’s disease before obvious symptoms appear. Early detection can be essential for managing the condition and developing treatments that might slow its progression. A major challenge is that the initial changes in motor function are often too slight for a doctor to see during a standard clinical examination. This makes it difficult to diagnose the disease or to identify individuals who are at high risk.</p>
<p>One such high-risk group includes people with a condition known as idiopathic REM Sleep Behavior Disorder. This is a sleep disorder where individuals physically act out their dreams, sometimes with vigorous movements. A large majority of people diagnosed with this sleep disorder will eventually develop Parkinson’s disease or a related condition. This makes them an ideal population for studying the earliest, or prodromal, signs of neurodegeneration.</p>
<p>The core motor symptom of Parkinson’s disease is known as bradykinesia, which is a general term for slowness of movement. This can be accompanied by other related issues, such as hypokinesia, which refers to movements that are too small in amplitude. Another key indicator is the “sequence effect,” where repetitive movements become progressively slower or smaller over time. </p>
<p>While these features are hallmarks of established Parkinson’s disease, it has been unclear if they are present in a detectable way in very early stages or in at-risk individuals with REM Sleep Behavior Disorder. Current methods for quantifying these subtle changes often require specialized, expensive equipment like accelerometers or optical trackers, limiting their widespread use. </p>
<p>To overcome these barriers, a team of researchers from the University of Florida sought to determine if an automated analysis of standard video recordings could unmask these hidden motor deficits. They hypothesized that their video-based approach could detect movement problems in people with early Parkinson’s disease even when a clinician could not, and that some of these features, especially the sequence effect, would also be present in individuals with the sleep disorder.</p>
<p>To test their ideas, the researchers recruited a total of 66 participants, who were divided into three groups. The first group consisted of 18 patients who had been diagnosed with early-stage Parkinson’s disease. The second group was made up of 16 individuals who had a confirmed diagnosis of idiopathic REM Sleep Behavior Disorder. The final group included 32 healthy adults with no history of neurological or sleep disorders to serve as a control group. </p>
<p>All participants underwent a standard neurological motor examination, which was recorded on video using a consumer-grade camera. A central part of this exam is the Finger Tapping task, where a person is asked to repeatedly tap their index finger against their thumb as quickly and as widely as possible for about ten seconds.</p>
<p>A fellowship-trained movement disorders neurologist evaluated and scored each participant’s performance on the Finger Tapping task using a standard clinical scale from 0 to 4, where a score of 0 signifies normal movement and a score of 4 indicates severe impairment. For their analysis, the researchers selected only the videos of finger-tapping performances that received a perfect score of 0. This selection ensured that any motor impairments the artificial intelligence might find would be truly subclinical, meaning they were invisible to the trained human eye.</p>
<p>The selected videos were then processed using a specialized software tool that employs a deep learning model. This model automatically identified and tracked the positions of 21 distinct points on the hand in every frame of the video. From this tracking data, the system calculated the distance between the tip of the index finger and the tip of the thumb throughout the task. This measurement created a continuous signal that represented the opening and closing of the fingers over time. </p>
<p>The researchers then extracted four key kinematic features from this signal for each participant: average movement amplitude (how wide the fingers opened), average movement speed, the decrement in amplitude (how much the movement size decreased from the beginning to the end of the task), and the decrement in speed (how much the movement speed declined).</p>
<p>The artificial intelligence system revealed clear differences between the groups that were not apparent from the clinical scores. Individuals with Parkinson’s disease showed significantly smaller movement amplitude and slower movement speed compared to both the healthy controls and the individuals with REM Sleep Behavior Disorder. They also exhibited a pronounced sequence effect, with both their movement size and speed decreasing over the course of the repetitive taps.</p>
<p>The results for the group with REM Sleep Behavior Disorder were particularly revealing. Unlike the Parkinson’s group, their average movement amplitude and speed were not different from the healthy control group. However, they did show a significant decrement in both amplitude and speed, a pattern similar to what was seen in the Parkinson’s patients. This suggests that the sequence effect, the fatigue-like decline in performance during repetitive movements, may be one of the earliest motor signs of the underlying disease process, appearing even before the classic slowness and smallness of movement associated with a Parkinson’s diagnosis.</p>
<p>To further test the power of these hidden measurements, the researchers used a machine learning algorithm known as a random forest to see if it could accurately classify individuals into their respective groups based only on the four video-derived features. The algorithm performed with high accuracy. It could distinguish people with Parkinson’s disease from healthy controls with 81.5% accuracy. </p>
<p>It could also differentiate individuals with REM Sleep Behavior Disorder from healthy controls with 79.8% accuracy. When tasked with separating the two clinical groups, the model could tell apart individuals with the sleep disorder from those with Parkinson’s disease with 81.7% accuracy. These classification results demonstrate that the subtle, computer-detected features contain enough information to reliably separate the groups, even when they appear identical to a human expert.</p>
<p>The researchers acknowledge certain limitations of their study, most notably the relatively small number of participants. Findings from a smaller sample need to be validated in larger, more diverse groups of people to ensure they are generalizable. Additionally, this work focused exclusively on motor symptoms derived from video. Future research could aim to combine this accessible video analysis with other biological markers, such as those from brain imaging or cerebrospinal fluid, to create an even more powerful and comprehensive tool for predicting who is at risk of developing Parkinson’s disease. </p>
<p>Nevertheless, this study provides evidence that automated video analysis can serve as a sensitive, low-cost, and accessible tool for detecting the earliest signs of neurodegeneration. Such a technology could one day be used for large-scale screening to identify at-risk individuals for inclusion in clinical trials for new neuroprotective therapies, well before more pronounced and life-altering symptoms begin to manifest.</p>
<p>The study, “<a href="https://doi.org/10.1038/s41531-025-01082-0" target="_blank">Video analysis reveals early signs of Bradykinesia in REM sleep behavior disorder and Parkinson’s disease</a>,” was authored by Diego L. Guarín, Gabriela Acevedo, Carolina Calonge, Joshua K. Wong, Nikolaus R. McFarland, Adolfo Ramirez-Zamora, and David E. Vaillancourt.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/new-research-complicates-the-story-of-dog-domestication/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">New research complicates the story of dog domestication</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Sep 13th 2025, 08:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A new study published in <a href="https://doi.org/10.1007/s10071-025-01978-7"><em>Animal Cognition</em></a> suggests that while dogs appear more affectionate and submissive than wolves during greetings with humans, these differences may not be solely due to domestication. Human behavior toward the animals also varied, hinting at possible unconscious biases.</p>
<p>Dogs have lived alongside humans for thousands of years, and many traits we associate with them — such as tail wagging, sustained eye contact, and expressive faces — are often assumed to have evolved as a result of domestication. This has led scientists to question what exactly drives this unique social bond.</p>
<p>One commonly proposed idea is that dogs are “hypersocial,” unusually motivated to seek human attention. Another view holds that dogs are more deferential, tending to comply with humans perceived as dominant.</p>
<p>However, previous research shows that wolves raised in close contact with humans can also engage in cooperative tasks and social interactions with people. This has prompted scientists to question whether dogs’ human-oriented behaviors emerged during the domestication process or are instead rooted in traits already present in wolves.</p>
<p>“We know dogs were domesticated roughly 15,000 years ago but there is still a lot of discussion about what happened during this process – what were dogs selected for to become what we know as dogs today? Previous studies showed that dogs exhibit more human-directed behavior than wolves, but it’s unclear whether this is motivated by hypersociality or their acceptance of humans as dominant figures,” explained study author Svenja Capitain of the Domestication Lab at the University of Veterinary Medicine in Vienna.</p>
<p>“We therefore wanted to compare the facial expressions of human-socialized dogs and wolves during a friendly interaction with a human to try and deduce what the motivation might be – and understand differences in their human-directed facial expressions in the first place, which have not yet been compared. Since the interacting humans couldn’t be blinded to whether they were engaging with a dog or wolf, we also coded for potential biases in human facial behavior as a confounding factor.”</p>
<p>The researchers compared the facial expressions and greeting behaviors of human-socialized wolves and dogs in a highly familiar context. They also investigated how humans responded to the two species, with a particular focus on facial expressions, which are known to convey subtle emotional cues. This bidirectional approach allowed them to examine not only how animals act toward humans, but also how humans might influence those behaviors.</p>
<p>The study took place at the Core Facility Wolf Science Center of the Vetmed University in Austria, where both dogs and wolves are hand-raised from a young age and live in conspecific packs with regular human interaction. Eleven dogs and eleven wolves, all familiar with the greeting routine, participated in the study. An additional group of seven pet dogs with upright ears was included to control for the effects of ear shape, which can affect how facial expressions are displayed and interpreted.</p>
<p>Each animal was greeted by two different human partners, one with whom they shared a strong bond (a primary trainer or caretaker) and another with whom they were familiar but less closely connected (a researcher or student who interacted with them occasionally). The greeting occurred through a fence, mimicking daily interactions at the facility. Human participants wore chest-mounted cameras to record their facial expressions, while multiple stationary cameras captured the animals’ behavior from different angles.</p>
<p>Trained coders used a standardized system called the Dog Facial Action Coding System (DogFACS) to identify specific muscle movements in the animals’ faces, such as inner brow raising or ear rotations. A similar system was used to code human facial expressions associated with positive or negative emotions. In addition to facial movements, the researchers recorded other behaviors commonly interpreted as social or emotional signals, including tail wagging, gaze direction, whining, and physical proximity.</p>
<p>Overall, dogs spent more time near the humans, wagged their tails more, and maintained eye contact more frequently than wolves. Both species showed more of these behaviors toward their bonded person compared to the familiar one, suggesting that relationship strength played a role in their responses. Dogs also exhibited more displacement behaviors like whining and rubbing against the fence, especially when interacting with a bonded person. Wolves did not show this pattern.</p>
<p>When it came to facial expressions, dogs were more likely than wolves to raise their inner eyebrows and slightly more likely to raise their upper lips. “Our findings align with prior studies showing that dogs seek proximity to humans, gaze at them more, and raise their inner eyebrows more than wolves,” Capitain said.</p>
<p>However, these differences were modest and their emotional meanings remain unclear. Other facial expressions, including those associated with stress or positive anticipation, did not differ significantly between species. “We expected more pronounced differences in dogs’ and wolves’ facial expressions given dogs’ long domestication history,” Capitain told PsyPost. “It’s possible that dogs rely more on other body signals, like ear or tail movements, to communicate with humans instead.”</p>
<p>Ear movements revealed more pronounced differences. Wolves were more likely to hold their ears forward, while dogs more often rotated or lowered their ears, which are often interpreted as signs of submission, uncertainty, or appeasement. These differences were not explained by ear shape, as the pet dogs with upright ears showed similar patterns to the dogs with floppy ears.</p>
<p>On the human side, facial expressions varied significantly based on the species of the animal they were greeting. Humans displayed more intense, more frequent, and more positively valenced expressions when interacting with dogs than with wolves, regardless of whether the person had a close relationship with the animal. This pattern held even among highly experienced handlers who had worked with both species for many years and were instructed to treat them equally.</p>
<p>“We were also surprised to find such pronounced biases in the human facial expressions, even among those with extensive experience working with both species,” Capitain explained. “This raises questions about whether humans mirrored the animals’ behavior (e.g., responding to dogs’ intense approaches with more expressive faces) or whether the human influenced the animals’ behavior.”</p>
<p>The results suggest that humans may harbor implicit biases toward dogs, responding to them with more warmth and expressiveness than to wolves even in controlled, familiar settings. These subtle differences in human behavior may, in turn, influence how the animals behave, either in the moment or over the course of their development.</p>
<p>“Interestingly, there were no major differences in the species’ human-directed facial expressions (except for the inner eyebrow raising, which had already been known),” Capitain said. “However, dogs’ human proximity-seeking was accompanied by ear postures generally seen in ambiguous and submissive situations, while wolves showed more forward directed ears, which are associated with confidence and attention.”</p>
<p>“Yet, we cannot interpret these outcomes in terms of species differences or domestication, because we also found marked differences in the human faces. This underlines how complex the human-canine relationship and the study of it can be, and suggests we need to understand our own biases better before drawing conclusions about the animals.”</p>
<p>As with all research, there are some limitations to consider. The sample size was relatively small, which is often the case in studies involving hand-raised wolves. While the researchers used rigorous methods and controls, it remains difficult to determine causality in such a dynamic, bidirectional interaction. It is unclear whether the animals were reacting to differences in human behavior or if humans were unconsciously responding to the animals’ species-typical expressions.</p>
<p>“The human component of the study was exploratory, so increasing the sample size here is a feasible next step,” Capitain noted. “So far, the initial question, what really drives dogs’ human-directed behavior, remains unanswered. But perhaps more importantly, the new questions this research raised is why the humans showed these biases, who was really influencing whom, and how we can guard against potential biases in human-animal interaction research in the future.”</p>
<p>Future studies could help disentangle the direction of influence by using time-series analysis or by standardizing human behavior across interactions. The researchers also hope to explore the origins of the observed human biases and to investigate whether such biases can be measured through implicit association tests or physiological responses.</p>
<p>“We plan to conduct more fine-grained, controlled comparisons of dogs’ and wolves’ human-directed behavior to better understand the domestication process,” Capitain said. “On the human side, we aim to investigate how the facial biases relate to internal biases, where they may originate from, and whether and how they influence the animals. These efforts will not only advance our understanding of dogs and wolves but also improve human-animal coexistence and the rigor of comparative research as a whole.”</p>
<p>“Our lab is dedicated to unravelling the complexities of domestication and human-animal relationships. For more information, you can visit our website (<a href="https://domesticationlab.wordpress.com" target="_blank" rel="noopener">https://domesticationlab.wordpress.com</a>), follow our Instagram channel (<a href="https://www.instagram.com/domlab_vienna/?hl=af" target="_blank" rel="noopener">@DomLab_Vienna</a>), or explore Friederike’s and Sarah’s book, <em<a href="https://amzn.to/4mfH2Cy" target="_blank" rel="noopener">>Wolves and Dogs: Between Myth and Science</a>. We hope our work inspires others to think critically about the fascinating bond between humans and animals.”</p>
<p>The study, “<a href="https://doi.org/10.1007/s10071-025-01978-7">Differences in dogs’ and wolves’ human-directed greeting behaviour: facial expressions, body language, and the problem of human biases</a>,” was authored by Svenja Capitain, Gwendolyn Wirobski, Çağla Önsal, Giulia Pedretti, Valeria Bevilacqua, Sarah Marshall-Pescini, and Friederike Range.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/harvard-scientists-pinpoint-how-sleep-stabilizes-memory-in-fascinating-neuroscience-breakthrough/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Harvard scientists pinpoint how sleep stabilizes memory in fascinating neuroscience breakthrough</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Sep 13th 2025, 06:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>Sleep is often said to help the brain “lock in” what we learn while awake, but the underlying biology remains a topic of debate. A new study published in <em><a href="https://doi.org/10.1523/jneurosci.0381-25.2025" target="_blank">The Journal of Neuroscience</a></em> provides evidence that sleep spindles — brief bursts of brain activity that occur during light non-REM sleep — may help reinforce motor memories by targeting the specific brain areas used during learning. </p>
<p>The findings suggest that sleep spindles are not random but instead follow a targeted pattern that supports learning. Rather than occurring uniformly across the brain, spindles appear to concentrate in cortical areas activated during a task, potentially making them a better indicator of memory consolidation than general spindle activity.</p>
<p>The study was led by Martin Sjøgård and Dimitrios Mylonas from Massachusetts General Hospital and Harvard Medical School, alongside an interdisciplinary team of scientists. Their research focused on sleep spindles, which are believed to play a central role in stabilizing and integrating new memories, especially those involving skills and procedures. </p>
<p>Previous studies have shown that these bursts can occur throughout the cortex, but they often appear more prominently in certain regions depending on what was learned while awake. The team wanted to examine whether these bursts of activity are shaped by prior learning, and whether their location in the brain can predict how much a person’s performance improves after sleep. </p>
<p>To do this, they used two complementary brain imaging techniques—electroencephalography and magnetoencephalography—which, when combined with magnetic resonance imaging, allowed them to localize spindle activity across the brain’s surface with much higher spatial precision than conventional methods. This approach provided a more detailed view of how the sleeping brain revisits and potentially strengthens memories of recent experiences.</p>
<p>For their study, the researchers recruited 25 healthy adults and recorded their brain activity during three separate nap visits, spaced at least a week apart. One session was used for adaptation, another served as a baseline, and the final one followed motor learning. During the motor learning visit, participants performed a finger-tapping task known as the motor sequence task. In this task, participants repeatedly typed a five-digit sequence using their left hand. They completed twelve 30-second trials, with rest breaks between each trial. Their performance was measured by the number of correct sequences typed per trial, which captured both speed and accuracy.</p>
<p>Participants then took a 90-minute nap inside the MEG scanner. Brain activity during non-REM Stage 2 sleep was analyzed for spindle events. A few hours later, participants returned to the scanner and were tested again on the same finger-tapping task to measure how much they had improved.</p>
<p>To pinpoint which brain areas were active during learning, the researchers first examined frequency changes in power from rest to task performance. They identified a network of 102 cortical regions that showed significant suppression of activity during task performance, which included primary motor and somatosensory areas, premotor regions, and supplementary motor areas.</p>
<p>The main finding was that sleep spindle density increased in these task-engaged regions after learning compared to baseline sleep. Specifically, about 18 percent of the identified task-related regions showed a learning-induced increase in spindle activity, compared to just under 3 percent of regions outside of this network. These regions included bilateral hand areas of the primary motor cortex, motor planning regions, and supplementary motor areas.</p>
<p>Importantly, these increases were not arbitrary. Spindle density changes predicted how much participants improved on the task after the nap. But this relationship was region-specific. Performance gains following sleep were associated with increased spindle activity in areas involved in motor planning, such as the supplementary motor area and contralateral premotor cortex. </p>
<p>In contrast, improvements during training itself were linked to spindle activity in motor execution areas like the primary motor cortex and somatosensory regions. The two sets of regions did not overlap, suggesting that initial learning and sleep-dependent improvement rely on different neural processes.</p>
<p>This distinction adds weight to the idea that learning during wakefulness and improvement after sleep reflect separate components of memory formation. Learning may encode the experience, while sleep consolidates and refines it. The study authors suggest that spindles in execution-related areas might stabilize the memory trace, while spindles in planning areas may support the refinement and automation of the skill during sleep.</p>
<p>The researchers also analyzed whether participants who naturally had higher spindle density during the nap were simply better learners. They found that spindle density during the learning-related nap predicted better performance, but spindle density during the baseline nap did not. This suggests that it was the learning experience itself that triggered the increase in spindle activity, rather than individual differences in baseline spindle production.</p>
<p>Interestingly, the study also found increases in spindle activity in regions not directly related to hand movement. For example, areas of the motor cortex involved in mouth and face control also showed heightened spindle density after learning. This may relate to participants’ reported use of covert verbal rehearsal during the task, as many silently repeated the number sequence to guide their movements. Previous work has suggested that these regions may contribute to motor planning and verbal rehearsal, and the current results support the idea that their activation may influence memory consolidation as well.</p>
<p>The authors note that these findings provide support for a growing view that spindles are not a generic sleep phenomenon but a targeted one. Their focal expression may allow the brain to selectively strengthen specific neural circuits, depending on what was learned. This might help explain why deficits in spindle production are observed in conditions like schizophrenia and autism, which are marked by difficulties with learning and memory.</p>
<p>The study relied on daytime naps, during which lighter sleep stages such as non-REM Stage 2 predominate. The team chose to focus on this stage because spindles are more frequent there and have been more strongly linked to motor memory improvements. Only a few participants experienced deep slow-wave sleep during the nap, so the role of this stage remains unclear and would need to be explored in future overnight studies.</p>
<p>Another limitation is that the researchers focused exclusively on a motor task, so the generalizability to declarative or emotional memory tasks remains to be tested. Still, the authors suggest that similar principles may apply. If other types of learning also recruit spindles in specific cortical regions, then tracking these changes could provide a sensitive marker of how well the brain is consolidating new information.</p>
<p>Looking ahead, the research team aims to apply this framework to understand how learning and memory processes are affected in neurodevelopmental disorders. Because spindles are measurable and can be enhanced through noninvasive stimulation techniques, this work may eventually inform new treatments to boost learning in clinical populations.</p>
<p>The study, “<a href="https://doi.org/10.1523/jneurosci.0381-25.2025" target="_blank">Increased Sleep Spindles in Regions Engaged during Motor Learning Predict Memory Consolidation</a>,” was authored by Martin Sjøgård, Dimitrios Mylonas, Bryan Baxter, Zhaoyue Shi, Sheraz Khan, Charmaine Demanuele, Lin Zhu, Catherine Tocci, Robert Stickgold, Matti S. Hämäläinen, and Dara S. Manoach.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/surprising-new-findings-force-scientists-to-rethink-decades-of-brain-plasticity-theories/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Surprising new findings force scientists to rethink decades of brain-plasticity theories</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Sep 12th 2025, 18:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>Inside every human brain lies a detailed map of the body, with different regions dedicated to different body parts – the hands, lips, feet and more. But what happens to this map when a body part is removed?</p>
<p>For decades, <a href="https://academic.oup.com/brain/article/144/7/1929/6206526">scientists believed</a> that when a body part is amputated, the brain’s body map dramatically reorganises itself, with neighbouring body parts taking over the area once represented by the missing limb.</p>
<p>This idea of large-scale brain reorganisation became a central pillar of what neuroscientists call adult brain plasticity: the ability of the brain to change its structure and function in response to injuries, new experiences or training.</p>
<p>Our new study, published in <a href="https://www.nature.com/articles/s41593-025-02037-7">Nature Neuroscience</a>, shows the opposite is true: the brain’s body map remains strikingly stable, even years after amputation.<br>
To test what happens in the brain after a person loses a body part, we took a unique approach.</p>
<p>Working with NHS surgeons, we followed three adult patients who were preparing to undergo lifesaving arm amputations for medical reasons, such as cancer or severe problems with blood supply. We scanned their brains with functional magnetic resonance imaging (MRI) before the amputation and repeatedly afterwards – in some cases for as long as five years.</p>
<p>During the MRI scans, we asked patients to move different body parts: tapping their individual fingers, curling their toes or pursing their lips. This allowed us to map brain activity and to construct the brain’s body map.</p>
<p>After the surgery, we repeated the scans, this time asking them to move their missing (phantom) fingers. Phantom movements are not imaginary: most amputees continue to feel vivid sensations of their missing limbs, even though they are physically no longer there. Doing so gave us a rare opportunity to directly compare the brain’s hand map before and after amputation in the same person.</p>
<p>We discovered that, across all three patients, the map of the hand in the brain remained remarkably unchanged and did not get overwritten by other body parts, such as the face. This neural stability helps explain why so many amputees continue to feel their missing limbs so vividly.</p>
<p>For most amputees, however, phantom sensations are not neutral sensations; they are painful and described as burning, stabbing or itching. For years, the dominant explanation for these painful sensations came from the idea that the brain’s body map has reorganised itself. In turn, this theory inspired therapies such as <a href="https://www.youtube.com/watch?v=OnPxKr1dMU0">mirror box therapy</a>, virtual reality training, or <a href="https://www.youtube.com/watch?v=QplcT2MjuEc">sensory-discrimination exercises</a>, all aimed at fixing supposedly broken maps.</p>
<p>Our findings show the brain’s body map is <em>not</em> broken. This helps explain why these therapies consistently fail to outperform placebo treatments in clinical trials. If the map remains intact, trying to fix it is a dead end.</p>
<h2>The real culprit</h2>
<p>Instead, our results suggest we should look elsewhere, for example, in the nerves that are cut during surgery. Severed nerves can form tangled clusters that misfire signals back to the brain. New amputation surgical techniques are being developed to preserve nerve signalling and maintain stable connections to the brain.</p>
<p>Our findings have important implications for developing prosthetic limbs and brain-computer interfaces. Invasive next-generation brain-computer interfaces can tap directly into the preserved map of the amputated body part to decode what movements are being attempted or even deliver electrical stimulation to the map to enable amputees to feel their missing limb.</p>
<p>These technologies are in development and could, one day, restore natural and intuitive control and sensations of a prosthetic limb, by using the preserved body map.</p>
<p>Our results show that our brains have a resilient model of the body that maintains the representations, even when the sensory input is lost. For amputees, this means that the missing limb lives on in the brain, sometimes as a source of discomfort, but also as a resource for future technologies to use.<!-- Below is The Conversation's page counter tag. Please DO NOT REMOVE. --><img decoding="async" src="https://counter.theconversation.com/content/263547/count.gif?distributor=republish-lightbox-basic" alt="The Conversation" width="1" height="1"><!-- End of code. If you don't see any code above, please get new code from the Advanced tab after you click the republish button. The page counter does not collect any personal data. More info: https://theconversation.com/republishing-guidelines --></p>
<p> </p>
<p><em>This article is republished from <a href="https://theconversation.com">The Conversation</a> under a Creative Commons license. Read the <a href="https://theconversation.com/scientists-have-been-wrong-about-phantom-limbs-for-decades-new-study-263547">original article</a>.</em></p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/breath-based-meditation-technique-shifts-brain-into-deeply-relaxed-state-study-finds/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Breath-based meditation technique shifts brain into deeply relaxed state, study finds</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Sep 12th 2025, 16:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A new study published in <em><a href="https://doi.org/10.1038/s44184-025-00156-4" target="_blank">npj Mental Health Research</a></em> provides evidence that breath-based meditation, specifically Sudarshan Kriya Yoga, alters brain rhythms in a way that may support relaxation and mental well-being. Using electroencephalography (EEG), the researchers tracked how different components of the technique influenced brain activity and found that rhythmic breathing gradually shifted brain dynamics into a relaxed meditative state characterized by theta and delta rhythms, reduced alpha power, and a decrease in non-repeating brain signals known as aperiodic activity.</p>
<p>The research was motivated by a growing need for accessible mental health interventions. Across the globe, people are facing rising rates of depression, anxiety, and stress-related disorders. At the same time, access to trained mental health professionals remains limited. These challenges have prompted researchers to investigate low-cost, scalable practices like yoga, meditation, and controlled breathing. Techniques such as Sudarshan Kriya Yoga have already demonstrated benefits for people with conditions ranging from PTSD to hypertension. However, the underlying brain mechanisms during the practice remain poorly understood.</p>
<p>Sudarshan Kriya Yoga combines specific postures, multiple forms of breath control, and guided meditation in a sequence designed to promote physical and emotional well-being. Previous studies have noted changes in EEG patterns following yoga practice, but few have examined how brain activity shifts during the technique’s distinct stages. The new study aimed to fill this gap by recording and analyzing EEG signals before, during, and after each component of the yoga sequence.</p>
<p>“I have been practicing meditation for about 16 years now. I have been curious as to what happens to the brain when one meditates which has led me to explore the neuroscience of meditation using tools like EEG/fMRI etc. Breathwork allows for an easier transition to a deeper meditative state. I was interested to know how that would happen, so along with the team at the Sri Sri Institute of Advanced Research we analyzed the brain dynamics during a guided breath based meditation paradigm,” said study author Vaibhav Tripathi.</p>
<p>The research involved 43 regular practitioners of Sudarshan Kriya Yoga, most of whom had years of experience with the technique. The participants were recruited from a yoga and meditation center in India and asked to follow the standard Sudarshan Kriya Yoga routine while seated, with EEG recordings taken throughout the session. A separate control group of ten participants listened to calming music for the same duration, allowing the researchers to compare the effects of the breathing practice with those of passive relaxation.</p>
<p>The yoga protocol included several phases: initial breathing exercises (pranayama), bhastrika (a more vigorous breath technique), om chanting, cyclical breathing (kriya), and a meditative resting phase called yoga-nidra. To ensure signal consistency, participants remained seated throughout and were guided by a prerecorded audio track. The researchers focused their analysis on five main time periods: resting before the practice, pranayama, kriya, yoga-nidra, and a post-session resting period.</p>
<p>EEG data were collected from 24 channels across the scalp. Using advanced signal processing tools, the researchers extracted specific features from the EEG data, including the amplitude, frequency, and width of delta, theta, and alpha brain waves. They also measured the slope of aperiodic activity, which reflects more spontaneous, non-rhythmic electrical patterns. These measures were statistically compared across the five phases of the meditation session.</p>
<p>The study revealed distinct patterns of brain activity linked to different phases of the Sudarshan Kriya Yoga technique. During the kriya phase, there was a noticeable increase in theta wave activity, particularly in brain areas associated with attention and emotional regulation. This pattern remained elevated through the subsequent yoga-nidra phase. Theta rhythms have been associated with relaxed alertness and internal focus in prior research, which may help explain the meditative effects observed during Sudarshan Kriya Yoga.</p>
<p>At the same time, alpha wave activity—a marker typically linked to sensory processing and alertness—declined sharply during the yoga-nidra period. This drop was especially prominent in parietal and occipital regions of the brain, which process visual and sensory information. The reduction in alpha amplitude and bandwidth may reflect a shift toward a less externally focused and more internally absorbed mental state.</p>
<p>The researchers also documented a rise in delta wave activity during the yoga-nidra stage. Delta waves are typically associated with deep sleep and unconscious processes, but can also appear during states of deep meditation. The increase in delta power suggests that the final stages of the yoga technique guide the brain into a profoundly relaxed state that resembles the early phases of sleep but with preserved awareness.</p>
<p>In addition to these changes, the study found a decrease in aperiodic activity, particularly during the yoga-nidra and post-resting phases. This flattening of the EEG spectrum suggests reduced random or non-repeating brain activity, possibly indicating a quieter and more stable mental state. These shifts were not observed in the control group, suggesting that the EEG changes were specific to the breath-based practice.</p>
<p>Interestingly, although the participants varied in how long they had been practicing yoga, the researchers did not find significant differences in brain activity based on experience level. This suggests that even among experienced practitioners, the practice induces consistent brain changes across individuals. Notably, the deepest meditative states, marked by delta-theta dominance and reduced alpha and aperiodic activity, occurred during the yoga-nidra phase, suggesting that the full sequence of Sudarshan Kriya Yoga builds toward a specific neurological outcome.</p>
<p>“We found that rhythmic breathing practice like Sudarshan Kriya Yoga allows an easier access to a deep state of meditation,” Tripathi told PsyPost. “EEG from participants were recorded before, during and after they were practicing the technique. EEG records brain activity which can be quantified into different rhythms like alpha, beta, theta, delta and gamma. What we found was that the breathing activated the theta rhythms in the brain which allowed a practitioner to easily transition to a relaxed state with heightened theta-delta activity. This activity is somewhere between fully awake (alpha/beta dominant) to fully asleep (slow waves and delta dominant), suggesting that the practitioner is in a relaxed yet aware state which traditional texts of meditation have referred to as Turiya (fourth state of consciousness, the others being sleeping, awake and dreaming).” </p>
<p>While the study provides new insights into the neurophysiological effects of Sudarshan Kriya Yoga meditation, it is not without limitations. The researchers relied on qualitative self-reports to assess relaxation rather than formal mood or state questionnaires. More precise behavioral and physiological measures—such as heart rate variability or cortisol levels—could strengthen future studies.</p>
<p>Additionally, the current research focused on experienced practitioners. It remains unclear whether the same EEG patterns would emerge in beginners or how long it might take for such changes to develop. Including novices in future research could help clarify how yoga influences brain rhythms over time and whether these changes correlate with psychological improvements.</p>
<p>“We’d like to extend this line of research to understand how different meditative practices affect the brain rhythms and if there are variations across individuals,” Tripathi said. “We would also like to categorize how the experience of meditation differs across days within the same individual and if we can find brain signals that respond to these variations. The long term goal is to have a clear biomarker of different stages of meditation which can be observed using accessible devices.”</p>
<p>The study, “<a href="https://doi.org/10.1038/s44184-025-00156-4" target="_blank">Unlocking deep relaxation: the power of rhythmic breathing on brain rhythms</a>,” was authored by Vaibhav Tripathi, Lakshmi Bhaskar, Chhaya Kharya, Manvir Bhatia, and Vinod Kochupillai.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/emotional-abuse-emerges-as-top-predictor-of-suicidal-thoughts-in-largest-ever-student-study/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Emotional abuse emerges as top predictor of suicidal thoughts in largest-ever student study</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Sep 12th 2025, 14:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A massive international study has found that almost half of all first-year university students have experienced suicidal thoughts at some point in their lives, a rate significantly higher than that of the general population. The research, which is the largest of its kind ever conducted, also identified key risk factors, including childhood adversity and specific mental health conditions, that are associated with these thoughts and behaviors. The findings were published in the journal <em><a href="http://dx.doi.org/10.1016/j.psychres.2025.116555">Psychiatry Research</a>.</em></p>
<p>The transition to university represents a period of profound change and heightened stress for young people. Many students are leaving home for the first time, facing new academic pressures, and navigating complex social environments. Previous research has indicated that this age group has seen a concerning rise in suicidal ideation in recent years.</p>
<p>Scientists have long understood that factors like difficult childhood experiences and mental health disorders are linked to suicide risk. However, there was a need for a large-scale, comprehensive study to quantify the prevalence of these issues among a global student population and to better understand the specific pathways that lead from suicidal thoughts to plans and attempts. This investigation aimed to fill that gap by examining these connections in an exceptionally large and diverse group of students.</p>
<p>The research was conducted as part of the World Mental Health International College Student Initiative, a project led by Harvard University. Between 2017 and 2023, the researchers gathered data from nearly 73,000 students, most of whom were in their first year of university. The participants were spread across 71 universities in 18 different countries, including Australia, Canada, Spain, Kenya, Mexico, South Africa, and Sweden.</p>
<p>Students at participating institutions were invited via email to complete a confidential online survey. This questionnaire was designed to gather information on several fronts. It asked students if they had ever experienced suicidal thoughts, made a suicide plan, or attempted suicide. It also included questions to assess their history of mental health disorders and whether they had faced adverse life events, particularly during childhood.</p>
<p>The survey responses painted a stark picture of the mental health challenges facing this population. The data revealed that 47 percent of the students who participated had experienced suicidal thoughts at some point in their lifetime. Beyond thinking about suicide, 26 percent reported having made a specific plan, and 10 percent had made a suicide attempt.</p>
<p>The numbers were also high for the 12 months immediately preceding the survey. Within that one-year period, 30 percent of students had experienced suicidal thoughts, 14 percent had made a plan, and 2.3 percent had attempted suicide.</p>
<p>The researchers noted that these rates are substantially higher than those found in the general population. They did offer a word of caution, suggesting that the results might be slightly overestimated. This is because students who have struggled with suicidal ideation may have been more inclined to participate in a survey on mental health, a phenomenon known as self-selection bias.</p>
<p>A central finding of the study was the connection between childhood experiences and later suicide risk. Philippe Mortier, a researcher at the Hospital del Mar Research Institute who was involved in the study, explained that experiences of emotional abuse, sexual abuse, and neglect are strongly associated not only with the initial development of suicidal thoughts but also with the progression to making plans and attempting suicide.</p>
<p>“Exposure to emotional abuse, sexual abuse, and neglect—especially during childhood—is directly linked to suicidal ideation and the progression to planning and attempting suicide,” explains Mortier. “All these factors carry risk — every traumatic event, every mental disorder, without exception — increases the risk of suicidal thoughts and suicide attempts.”</p>
<p>The results also pointed to the impact of having parents with mental health disorders, which was identified as a risk factor that can contribute to a child’s exposure to adversity.</p>
<p>The analysis also shed light on how risk is distributed unevenly across different student groups. Gender identity emerged as a significant factor. Students who identified as transgender were found to be at a substantially higher risk for suicidal behaviors. Compared to their peers, they were 2.4 times more likely to experience suicidal thoughts and 3.6 times more likely to attempt suicide. The researchers suggest that this is because transgender individuals are often exposed to a greater number of risk factors, including social stigma and discrimination.</p>
<p>The study also found that sexual orientation was a key predictor. Students identifying as non-heterosexual faced a greater likelihood of suicidal thoughts and behaviors. These risks remained even after accounting for other factors like childhood adversity and mental health disorders.</p>
<p>When all factors were considered together, the three strongest predictors of suicidal behavior were a history of emotional abuse, a diagnosis of major depressive disorder, and a diagnosis of bipolar disorder.</p>
<p>The study also provided a more nuanced look at how different factors influence different stages of suicidal behavior. For example, mood disorders like major depression were most strongly associated with the initial emergence of suicidal thoughts. In contrast, other conditions, such as panic disorder and bipolar disorder, were more strongly linked to the transition from having thoughts to making an attempt.</p>
<p>This distinction helps to show the complex processes involved in escalating suicide risk. Similarly, emotional abuse was a very strong predictor for the onset of suicidal thoughts, while physical abuse was uniquely associated with the repetition of suicide attempts over time. These patterns suggest that different types of interventions may be needed for students at different points on the risk spectrum.</p>
<p>Mortier stated that preventing these outcomes will require a greater investment in mental health support at the university level. He argued that institutions need more resources to help reduce the prevalence of mental health disorders and lower the risk of suicide among their students.</p>
<p>Jordi Alonso, the Spanish coordinator of the initiative, added that effective prevention must be comprehensive. He explained that any successful strategy has to take into account the combination of risk factors that a student may face. This includes their sex, gender identity, sexual orientation, and any accumulation of adverse childhood experiences. These factors can interact in ways that create a negative feedback loop, progressively increasing an individual’s vulnerability to suicide.</p>
<p>The researchers acknowledged several limitations to their work. The study was cross-sectional, meaning it captured a single moment in time. A longitudinal study that follows the same group of students over several years would provide a deeper understanding of how these risk factors develop and interact over time.</p>
<p>The information on mental health disorders and childhood adversity was also based on students’ self-reports rather than on formal clinical interviews. Finally, because the study included a specific set of 18 countries, the results may not be generalizable to all university students globally. Future research is needed to replicate these findings in other populations and to design and test prevention programs based on the risk factors identified in this extensive investigation.</p>
<p>The study, “<a href="https://doi.org/10.1016/j.psychres.2025.116555" target="_blank" rel="noopener">The associations of childhood adversities and mental disorders with suicidal thoughts and behaviors – Results from the World Mental Health International College Student Initiative</a>,” was authored by Philippe Mortier, Xue Yang, Yasmin A. Altwaijri, Jacob A. Holdcraft, Sue Lee, Nancy A Sampson, Yesica Albor, Ahmad N. Alhadi, Jordi Alonso, Nouf K. Al-Saud, Claes Andersson, Lukoye Atwoli, Randy P. Auerbach, Caroline Ayuya Muaka, Patricia M. Báez-Mansur, Laura Ballester, Jason Bantjes, Harald Baumeister, Marcus Bendtsen, Corina Benjet, Anne H. Berman, Ronny Bruffaerts, Paula Carrasco, Silver C.N. Chan, Irina Cohut, María Anabell Covarrubias Díaz Couder, Marcelo A. Crockett, Pim Cuijpers, Oana A. David, Dong Dong, David D. Ebert, Jorge Gaete, Mireia Felez-Nobrega, Carlos García Forero, Margalida Gili, Raúl A. Gutiérrez-García, Josep Maria Haro, Penelope Hasking, Xanthe Hunt, Mathilde M. Husky, Florence Jaguga, Leontien Jansen, Álvaro I. Langer, Yan Liu, Scarlett Mac-Ginty, Vania Martínez, Andre Mason, Muthoni Mathai, Margaret McLafferty, Andrea Miranda-Mendizabal, Elaine K. Murray, Catherine M. Musyoka, Siobhan M. O’Neill, Claudiu C. Papasteri, José A. Piqueras, Codruta A. Popescu, Charlene Rapsey, Kealagh Robinson, Tiscar Rodriguez-Jimenez, Damian Scarf, Oi-ling Siu, Dan J. Stein, Sascha Y. Struijs, Cristina T. Tomoiaga, Karla Patricia Valdés-García, Shelby Vereecke, Daniel V. Vigo, Angel Y. Wang, Samuel Y.S. Wong, Ronald C. Kessler, and the World Mental Health International College Student collaborators.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/women-prone-to-self-objectification-tend-to-have-lower-empathy/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Women prone to self-objectification tend to have lower empathy</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Sep 12th 2025, 12:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A series of three studies found that women who are more prone to self-objectification tend to have reduced empathy, both affective and cognitive. These women were also more likely to experience self-dehumanization. In turn, self-dehumanization was associated with diminished theory-of-mind abilities—the capacity to understand that other people have their own thoughts, perceptions, and goals. The paper was published in <a href="https://doi.org/10.1177/03616843251340962"><em>Psychology of Women Quarterly</em></a>.</p>
<p>Self-objectification is a psychological process in which individuals, especially women, view and evaluate themselves mainly in terms of how their bodies appear to others, rather than their abilities or internal qualities. Women who adopt this perspective often monitor their physical appearance, a behavior known as “self-surveillance.”</p>
<p>This habit leads them to compare themselves with cultural beauty standards, which are often unrealistic or unattainable. As a result, self-objectification is linked to body shame, as people judge themselves harshly for failing to meet these ideals. It can also heighten anxiety about how one’s body is perceived in social situations.</p>
<p>Over time, these pressures may contribute to disordered eating and depression. Sexual experiences can also be affected, as self-objectifying individuals often focus on how their body looks rather than on their sensations or satisfaction. Women high in self-objectification may feel pressure to conform to external evaluations, which can lower self-esteem and increase vulnerability to depression. The process is not only psychological but also social, reinforced by media, advertising, and interpersonal feedback.</p>
<p>Study author Gian Antonio Di Bernardo and his colleagues set out to examine whether self-objectification interferes with the ability to understand other people’s emotions and mental states. They hypothesized that women prone to self-objectification would show lower empathy, weaker theory-of-mind abilities, and a greater tendency toward self-dehumanization—the process by which individuals come to see themselves as less than fully human, denying their own dignity, agency, or worth.</p>
<p>The researchers conducted three studies. The first examined whether self-objectification was linked to decreased empathy. Participants were 226 heterosexual Italian women with an average age of 28. They completed an online survey that measured self-objectification (using the 14-item Self-Objectification Beliefs and Behaviors Scale), self-dehumanization, and empathy (via the Interpersonal Reactivity Index).</p>
<p>The second study repeated this procedure with a new sample of 336 heterosexual Italian women, who were slightly older, with an average age of 34. The third study also surveyed Italian heterosexual women but added an assessment of theory-of-mind abilities (the Reading the Mind in the Eyes test).</p>
<p>Results from the first two studies indicated that women more prone to self-objectification tended to report lower levels of empathy, including both cognitive empathy (perspective taking) and affective empathy (empathic concern). They also showed higher levels of self-dehumanization. A statistical model suggested that self-objectification may lead to self-dehumanization, which in turn predicts lower empathy.</p>
<p>The third study confirmed these findings and also showed that women who scored higher in self-dehumanization tended to have somewhat weaker theory-of-mind abilities. Although theory-of-mind performance was not directly associated with self-objectification, the researchers suggested that both may be indirectly linked through self-dehumanization.</p>
<p>“Taken together, our findings suggest that a dysfunctional body image may have detrimental effects not only internally (i.e., the denial of full humanity to oneself) but also externally (i.e., greater difficulty in understanding others’ emotional and mental states). These results underscore the urgent need to challenge self-objectification and promote a healthier, more authentic perception of self,” the study authors concluded.</p>
<p>The study sheds light on the links between self-objectification and empathy. However, it should be noted that all three studies were conducted on Italian women, mostly young. Results on other cultural and demographic groups might not be identical.</p>
<p>The paper “<a href="https://doi.org/10.1177/03616843251340962">No Hard Feelings: The Role of Self-Objectification and Self-Dehumanization in Understanding Emotions and Mental States in Cisgender Heterosexual Women</a>” was authored by Gian Antonio Di Bernardo, Chiara Pecini, Bianca Tallone, Giuseppe Raguso, and Luca Andrighetto.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
<p><strong>This information is taken from free public RSS feeds published by each organization for the purpose of public distribution. Readers are linked back to the article content on each organization's website. This email is an unaffiliated unofficial redistribution of this freely provided content from the publishers. </strong></p>
<p> </p>
<p><s><small><a href="#" style="color:#ffffff;"><a href='https://blogtrottr.com/unsubscribe/565/DY9DKf'>unsubscribe from this feed</a></a></small></s></p>