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<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">PsyPost – Psychology News</span></td>
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<td><a href="https://www.psypost.org/dolphins-exposed-to-florida-algal-blooms-show-gene-changes-linked-to-alzheimers-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;">Dolphins exposed to Florida algal blooms show gene changes linked to Alzheimer’s disease</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 7th 2025, 08:00</div>
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<p><p>Dolphins living along Florida’s coast appear to be affected by the same types of environmental factors that are being investigated for their potential role in human neurodegenerative diseases. A study published in <a href="https://doi.org/10.1038/s42003-025-08796-0"><em>Communications Biology</em></a> provides evidence that repeated seasonal exposure to algal bloom toxins is associated with molecular and cellular changes in dolphin brains that mirror some features of Alzheimer’s disease. The findings raise concerns about the long-term effects of harmful algal blooms on marine wildlife and possibly on human health in areas where such blooms are common.</p>
<p>Harmful algal blooms, also called HABs, occur when colonies of algae grow out of control, often fueled by warm water temperatures and nutrient pollution. These blooms release toxins that can accumulate through the food chain, affecting both aquatic animals and land mammals. Acute effects of these toxins are well documented, but their long-term impact on brain health is less well understood.</p>
<p>The Indian River Lagoon, a large estuary stretching along Florida’s east coast, has experienced recurring algal blooms over the last two decades. As climate change warms the region, these events are occurring more frequently and lasting longer.</p>
<p>Dolphins that inhabit the lagoon are long-lived, apex predators. Because they share similar exposure risks with humans and display age-related brain changes, they serve as a valuable species for studying the possible neurological consequences of environmental toxin exposure.</p>
<p>Dolphins have been shown to develop some of the same brain abnormalities seen in people with Alzheimer’s disease, including accumulations of amyloid-beta plaques and tau tangles. The co-occurrence of these markers and the dolphins’ repeated exposure to algal bloom toxins offered a unique opportunity to study how environmental changes may affect brain biology over time.</p>
<p>“In this study, we aimed to determine if seasonal change can have an impact on brain health. We focused on harmful algal bloom season, since these blooms can produce a number of neurotoxins. We hypothesized that exposure to neurotoxins would be higher during bloom seasons and neurotoxicity would parallel seasonal change,” explained study author David A. Davis, a research associate professor and associate director of <a href="https://med.miami.edu/programs/brain-endowment-bank" target="_blank" rel="noopener">the Brain Endowment Bank</a> at the University of Miami Miller School of Medicine.</p>
<p>The research team analyzed brain tissue from 20 bottlenose dolphins that had stranded and died in the Indian River Lagoon area between 2010 and 2019. The dolphins were divided into two groups based on when they died: bloom season (June through November) and non-bloom season (December through May). The researchers aimed to determine whether the timing of death, which served as a proxy for toxin exposure, was associated with measurable changes in the brain.</p>
<p>To measure toxin levels, the team used a highly sensitive mass spectrometry method to detect the presence of 2,4-diaminobutyric acid (2,4-DAB), a neurotoxin produced by algae. They found that 2,4-DAB was present in all dolphin brains but was almost 3,000 times more concentrated in those that died during bloom season.</p>
<p>Next, the researchers examined changes in gene expression across the brain. They used RNA sequencing to map which genes were turned on or off in the cerebral cortex. The dolphins that died during bloom season showed altered expression in more than 500 genes, including many involved in nervous system function and immune response. Several of these genes have also been linked to Alzheimer’s disease in humans.</p>
<p>In addition to transcriptomic changes, the team performed immunohistochemical analysis on brain sections from a subset of the dolphins. These tests revealed deposits of amyloid-beta and phosphorylated tau proteins, which are considered hallmarks of Alzheimer’s pathology. These changes were found in dolphins from both seasons, but the data suggest that the factors associated with bloom season, including higher 2,4-DAB concentrations, may interact with and worsen this underlying pathology.</p>
<p>The study provides evidence that seasonal exposure to 2,4-DAB is linked to biological processes that resemble those seen in Alzheimer’s disease. Specifically, dolphins exposed during bloom seasons showed altered signaling in GABA-producing neurons and changes in genes involved in the brain’s basement membrane, both of which play a role in maintaining brain function and structure.</p>
<p>“Our study shows a direct relationship between seasonal change, toxin exposure and brain health,” Davis told PsyPost. “This study is a clue to the Alzheimer’s disease exposome which is believed to consist of multiple types of exposures throughout the lifespan that contribute to the development of the disease.”</p>
<p>One of the most consistent findings was a seasonal increase in the expression of the APOE gene, a well-known genetic risk factor for Alzheimer’s. APOE was upregulated in dolphins from the bloom season, which is characterized by high 2,4-DAB exposure, and this increase tended to rise with each successive bloom season.</p>
<p>“The most surprising observations were the temporal increase in Alzheimer’s disease risk factor genes with each sequential bloom season,” Davis said.</p>
<p>Other Alzheimer’s-related genes, such as APP and MAPT, were also elevated during bloom seasons, and their expression correlated with the concentration of 2,4-DAB in the brain.</p>
<p>In addition, dolphins exposed to more bloom seasons showed increased expression of genes linked to inflammation and cell death. Several of these genes, including TNFRSF25 and CIRBP, are also involved in human neurodegenerative diseases and stress responses.</p>
<p>As with all research, there are limitations. The study relied on opportunistic samples collected from stranded dolphins, which means the causes of death were not controlled by the researchers. While the dolphins selected had similar age, sex, and health profiles, other unknown factors may have contributed to their deaths or the observed brain changes.</p>
<p>The sample size was relatively small, in part due to the challenge of obtaining high-quality brain tissue from wild marine mammals. Despite this, the researchers applied rigorous standards for RNA integrity and used multiple validation techniques to strengthen the reliability of the data.</p>
<p>Importantly, while the study found gene expression changes that match those seen in human Alzheimer’s cases, it did not assess cognitive function in the dolphins. The presence of Alzheimer’s-like markers suggests a similarity in biological response, but it does not confirm that dolphins experience dementia in the same way humans do.</p>
<p>The findings point to the need for more detailed investigations into how 2,4-DAB affects brain cells over time, and whether this toxin interacts with other environmental or genetic risk factors. Future studies could also explore the prevalence of these changes in dolphins that have not stranded, using non-lethal sampling methods, or in controlled laboratory models.</p>
<p>“We plan to investigate the 2,4-DAB toxin that was detected in the dolphin brain in more detail to investigate its role in triggering neurodegeneration,” Davis said.</p>
<p>Because dolphins are considered sentinel species, their health can provide early warning signs of environmental risks that may also affect humans. Given that South Florida has one of the highest rates of Alzheimer’s disease in the United States, the findings suggest a need to explore whether chronic exposure to algal bloom toxins contributes to regional patterns in human neurodegenerative diseases.</p>
<p>“Our study highlights the relationship between environment and brain health,” Davis concluded. “South Florida had the highest prevalence of Alzheimer’s disease in 2024. Our study focused on dolphins found beached in Florida. The data here could provide a link between increased prevalence of the disease in certain geographics.”</p>
<p>The study, “<a href="https://doi.org/10.1038/s42003-025-08796-0">Alzheimer’s disease signatures in the brain transcriptome of estuarine dolphins</a>,” was authored by Wendy Noke Durden, Megan K. Stolen, Susanna P. Garamszegi, Sandra Anne Banack, Daniel J. Brzostowicki, Regina T. Vontell, Larry E. Brand, Paul Alan Cox, and David A. Davis.</p></p>
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<td><a href="https://www.psypost.org/neuroscientists-discover-a-key-brain-signal-that-predicts-reading-fluency-in-children/" 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;">Neuroscientists discover a key brain signal that predicts reading fluency in children</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 7th 2025, 06:00</div>
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<p><p>A new study has discovered a direct link between the number of milliseconds it takes a child’s brain to process the form of a printed word and how well that child understands what they are reading. The finding provides a new way to measure this neural timing in individual children with millisecond precision, a breakthrough that could advance our understanding of how reading skills develop. The research was published in the journal <em><a href="https://doi.org/10.1016/j.dcn.2025.101616" target="_blank">Developmental Cognitive Neuroscience</a></em>.</p>
<p>The investigation was led by a team of researchers at Stanford University who were interested in the brain changes that support the development of fluent reading from late childhood into early adolescence. During this period, reading often transforms from a slow, effortful task into an automatic and engaging activity. The speed of recognizing individual words is known to be a key element in this transition, but the neural mechanisms behind it are not fully understood.</p>
<p>Previous methods for measuring the brain’s processing speed for words, often using a technique called event-related potentials, have been limited by low reliability when applied to individuals. This makes it difficult to connect brain activity directly to a specific child’s reading ability. The researchers aimed to develop and validate a more precise and stable method to measure this neural timing.</p>
<p>“This study emerged from a unique ‘research practice partnership’ between an innovative Bay Area K-8 school, the Synapse School, and the Stanford Educational Neuroscience Initiative (SENSI),” explained senior author Bruce D. McCandliss, the Pigott Family Graduate School of Education Professor in Educational Neuroscience at Stanford University.</p>
<p>“The collaboration began with a series of roundtable discussions involving teachers and researchers to find synergies between my long-term research goals and the topics that educators found most meaningful. This effort was also informed by my multi-year reflections on the challenges that prevent neuroscience from making a meaningful connection with education.”</p>
<p>“Our first collaborative focus was on how reading changes the brain. We knew we could bring brainwave technology to the school, but a significant limitation of current science is its difficulty in delivering what teachers value most: information that is meaningful at the individual student level. Standard approaches are not yet able to provide this, as their conclusions tend to apply to groups rather than individuals.”</p>
<p>“The teachers stressed the importance of protocols brief enough for students to complete within a single class period,” McCandliss continued. “As a science team, we took this as a design challenge, and created innovative approaches that required only a few minutes of data collection for each measure. The science team also contributed back to the teachers the value that can come from measuring reading skills in units of physics… such as capturing the duration of a specific neural computation with millisecond-level precision.”</p>
<p>To achieve this, the researchers and school staff enabled 68 typically developing children between the ages of 8 and 15 to volunteer for the study during their ordinary school day. Each child participated in a session where their brain activity was recorded using electroencephalography, or EEG, a method that measures electrical signals from the brain through sensors on the scalp.</p>
<p>The children also completed a series of standardized tests to assess their reading abilities, including their speed in reading single words and their fluency and comprehension of sentences.<br>
During the EEG recording, participants viewed rapid streams of four-character stimuli presented at a steady rhythm of precisely three items per second. These stimuli included real words, nonwords made of jumbled letters, and strings of unfamiliar symbols called pseudofonts.</p>
<p>This steady, rhythmic presentation is part of a technique known as Steady-State Visual Evoked Potentials. It is designed to elicit a brain response that follows the same rhythm as the flashing images. The brain produces signals not only at the primary frequency of the stimulus, in this case 3 Hz, but also at its multiples, known as harmonics, such as 6 Hz and 9 Hz.</p>
<p>The researchers analyzed the timing, or phase, of the brainwaves produced at these different frequencies. By examining how the phase of the response changed across the harmonics, they were able to calculate a precise processing delay for each child. This delay, called cortical latency, represents the time it takes for information to travel from the eyes to the brain regions that process visual word forms. This approach allowed for the calculation of a stable neural timing marker for each individual participant.</p>
<p>The researchers found that the measurement of cortical latency was consistent for each child. This neural processing speed remained stable regardless of whether the child was viewing actual words, nonwords, or abstract symbols. This high reliability suggests the method is capturing a fundamental aspect of an individual’s visual processing system.</p>
<p>The researchers also found a strong relationship between cortical latency and the participants’ reading skills and age. Children with faster brain processing speeds, indicated by shorter latencies, tended to have higher scores on tests of both single-word reading efficiency and sentence-level reading comprehension. Similarly, older children generally exhibited shorter latencies than younger children, suggesting that this neural process becomes more efficient with age and experience. These relationships held even after accounting for non-verbal intelligence.</p>
<p>A third finding provided insight into how these processes are connected. The study suggests that the link between rapid neural processing and fluent reading comprehension is largely explained by single-word reading speed. In other words, a faster initial neural response to visual text appears to facilitate quicker and more automatic recognition of individual words. This efficiency at the word level may then free up cognitive resources, allowing the reader to focus on understanding the meaning of entire sentences and passages.</p>
<p>“Your brain is operating at multiple time-scales at the same time,” McCandliss told PsyPost. “You might be aware of how your thoughts or feelings are changing from one moment to the next, and how going to school and learning things allows you to recall new facts. But there’s also many faster time-scales, like the time it takes information to get from your eye to computations that route information to the part of your brain that can recognize words.”</p>
<p>“Remarkably, tiny little differences in neural computation speed for visual words is powerfully tied to your fluency in reading comprehension. As reading improves, this neural timing tends to get faster. Education progressively shapes the speed of this rapid neural process.”</p>
<p>The practical significance of these findings lies in both the strength of the relationship and the reliability of the measurement. The connection between cortical latency and reading fluency suggests that a meaningful portion of the differences seen in children’s reading ability, from a struggling third-grader to a proficient eighth-grader, can be accounted for by millisecond-level variations in neural processing speed.</p>
<p>More importantly, the method used to measure this neural timing proved to be exceptionally stable for individuals. This high reliability is a key advance, as it makes it feasible to track subtle changes in a single child’s brain function over time.</p>
<p>“Because we collaborated with a school in designing and carrying out this study, we know that we can now measure this neural speed incredibly precisely and reliably, like a mechanic timing the sparks in your car’s carburetor, in nearly every school child, within schools, without missing anything more than a single class,” McCandliss explained. “This means kids can see the results of their hard work as learning to read progressively refines this core neural function.”</p>
<p>One of the most surprising outcomes for the researchers was the success of the research-practice partnership itself.</p>
<p>“Collaborating with schools to do brain science was not thought to be viable by most, both on the science side and on the education side,” McCandliss said. “When I told them what I was envisioning, I had people in both science and educational practices look at me in ways that made me think ‘this is pretty crazy,’ or at best ‘that’s a pretty whimsical way to invest your research bets after tenure.’ Looking at the number of scientific discoveries we’ve published, I think the surprise is really how promising these sorts of research-practice partnerships can really be, both for science, and for education.”</p>
<p>A second surprise emerged from the data. The research team was initially uncertain whether their technique would yield a meaningful and stable measurement for any single person. There was a genuine concern that an individual’s brainwave data might be too inconsistent to provide anything other than random noise. “We literally had no idea how well this could work at an individual level,” McCandliss said. Fortunately, the results showed a precise and reliable signal at the individual level “in a way that surpassed what we could have hoped for.”</p>
<p>But there are still some limitations to consider. The study’s design is correlational, which means it identifies a relationship between neural processing speed and reading skill but cannot establish causality. For instance, it remains unclear whether faster processing is a cause of proficient reading, or if, conversely, extensive reading practice is what leads to more efficient neural responses. </p>
<p>“Of course, finding a ‘link’ between measures of a child’s cortical latency and academic achievement in reading is really just the beginning of untangling the dynamics of how this relationship develops,” McCandliss said. “It begs for new studies exploring both how increasingly engaging in reading changes neural timing as well as exploring how differences in neural timing might bias the experience of fluent reading, and how each of these causal pathways may play out over the course of reading development.”</p>
<p>Also, because the study observed children across a wide age range at a single point in time, it is difficult to fully separate the effects of natural brain maturation from the effects of accumulating reading experience.</p>
<p>“Given how this science centers around one of our most vulnerable populations — developing children — it is critical to put this in a developmental context as well as an educational context, which means these are values in flux within a person — they are likely changing as they get more experience in reading and more experience in general,” McCandliss told PsyPost. “The true value of these measures will ultimately be in how we can better understand the way they are changing over time within an individual when given highly valuable learning opportunities.”</p>
<p>Future research could build on these findings in several ways, including by testing the same set of children over several years to observe how their neural processing speed changes in relation to their reading instruction and practice. Such longitudinal studies could help clarify the distinct contributions of age and reading experience to the development of neural efficiency.</p>
<p>The researchers are now conducting additional studies to better understand the nature of this neural signal. They plan to test whether the brain’s processing speed changes in response to different types of stimuli, such as high- versus low-frequency words, or other visual forms like faces and cars. A key goal is to determine if this rapid neural response is truly specific to written language or if it also extends to other complex visual categories that the brain specializes in processing, such as faces.</p>
<p>“One of our next scientific goals is to bring education and developmental neuroscience closer together, which means bringing portable EEG tools into schools, collaborating with the schools to devise precise metrics that can track growth over time in neural computation speed, and ultimately relate time series changes within an individual to variations that matter in their educational experiences,” McCandliss said.</p>
<p>“We also plan to expand these findings into research aimed at the specific challenges facing individuals living with clinically significant neurobiological challenges, such as developmental dyslexia, attention challenges, and autistic spectrum disorder.”</p>
<p>“This study is one part of a suite of papers that resulted from the collaboration between my group at Stanford and the Synapse School,” he added. “I encourage readers to look at them as an interlocking set that shows the true potential of research practice partnerships in advancing developmental cognitive neuroscience research related to education.”</p>
<p>“For example, our group is ecstatic that our latest study was just accepted this month for publication in one of the Nature publishing group journals (<em>npj Science of Learning</em>). This new study shows an actual causal impact of two weeks of teacher’s vocabulary activities on neural responses to words that show up in children’s books less than one in a million times, and brings them to levels of cortical responses equivalent to the highest frequency words we’ve ever tested.”</p>
<p>The current study, “<a href="https://doi.org/10.1016/j.dcn.2025.101616" target="_blank" rel="noopener">Cortical latency predicts reading fluency from late childhood to early adolescence</a>,” was authored by Fang Wang, Quynh Trang H. Nguyen, Blair Kaneshiro, Anthony M. Norcia, and Bruce D. McCandliss.</p></p>
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<td><a href="https://www.psypost.org/higher-fluid-intelligence-is-associated-with-more-structured-cognitive-maps/" 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;">Higher fluid intelligence is associated with more structured cognitive maps</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 6th 2025, 22:00</div>
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<p><p>People with higher reasoning skills appear to be better at forming internal maps of how different objects are related in space, according to a study published in <em><a href="https://doi.org/10.1016/j.celrep.2025.116033" target="_blank">Cell Reports</a></em>. The research provides evidence that a key feature of intelligence may stem from the way the brain encodes relationships between experiences, especially through a region called the hippocampus.</p>
<p>The findings point to a link between general cognitive ability and how well people integrate separate pieces of information into a structured whole. Rather than focusing on how smart individuals perform in specific tasks, the researchers examined how their brains encode the structure of experiences. The results suggest that intelligence may involve the ability to form a mental map of the world that helps guide flexible thinking and decision making.</p>
<p>The study was conducted by researchers Rebekka Tenderra and Stephanie Theves at the Max Planck Institute for Empirical Aesthetics and the Max Planck Institute for Human Cognitive and Brain Sciences in Germany. They were interested in exploring how intelligence, especially fluid intelligence, might be related to specific patterns of brain activity during learning.</p>
<p>Fluid intelligence refers to the capacity to solve new problems and recognize patterns, often measured by reasoning tests. It has long been considered one of the core components of general intelligence and is strongly associated with performance across a wide range of tasks. Although past studies have identified brain areas linked to intelligence, such as the frontal and parietal cortices, the specific neural processes that underlie it are less well understood.</p>
<p>The researchers hypothesized that one way people differ in intelligence may be through how well they organize information into relational structures. In other words, smarter individuals might be more likely to represent different pieces of information as part of a broader map, capturing how elements relate to each other in space or conceptually. Previous studies had suggested that the hippocampus, a part of the brain known for memory and spatial navigation, plays a role in creating these kinds of cognitive maps.</p>
<p>To test their hypothesis, the researchers used brain imaging to observe how participants learned the locations of various objects placed within a virtual arena. Participants saw six different objects, each assigned to a specific spot in a circular space. They practiced placing the objects in the correct locations and received feedback after each attempt.</p>
<p>As the learning progressed, participants became more accurate at remembering where each object belonged. After completing the task, they were asked to arrange the objects from a bird’s-eye view, demonstrating how well they had internalized the layout. Their answers closely matched the actual object positions, suggesting that most participants were able to form a fairly accurate mental map of the environment.</p>
<p>Meanwhile, the researchers used functional magnetic resonance imaging (fMRI) to record activity in the hippocampus while participants viewed the objects. They looked for patterns indicating whether the brain represented the spatial relationships between the objects. Specifically, they examined whether neural activity patterns were more similar for objects that were closer together in the learned layout, and more different for objects that were farther apart.</p>
<p>The key finding was that individuals with higher fluid intelligence scores showed stronger signs of this “map-like” encoding in the right hippocampus. That is, their brain activity reflected a clearer sense of the distances between object locations. This connection between relational encoding and intelligence remained even after accounting for how well the participants performed on the memory tasks, suggesting that the brain patterns were not simply a reflection of who remembered more accurately.</p>
<p>Additional analyses showed that this brain-behavior link was consistent across various cognitive tasks, especially those that were more strongly related to fluid intelligence. The correlation was not driven by any single test but rather reflected a broad tendency among smarter individuals to organize their learning experiences in a more structured, map-like way.</p>
<p>When the researchers compared people with higher versus lower fluid intelligence scores, they found differences in how consistently the brain represented object relationships. Those in the lower intelligence group had neural representations that were less consistent with a two-dimensional map. In practical terms, this suggests they may have encoded some object pairs in ways that didn’t align well with an overall spatial layout, pointing to lapses in integrating relationships across the whole scene.</p>
<p>To further investigate this idea, the researchers asked participants to estimate distances between object pairs on a sliding scale. Again, the results showed that people with higher intelligence scores provided more geometrically consistent estimates, reinforcing the idea that they were better at integrating object relations into a cohesive map.</p>
<p>The researchers also tested whether the observed relationship between intelligence and brain activity was specific to relational encoding. They did this by including a separate memory task where participants simply had to recognize whether they had seen an object before. This task measured basic item memory, not how the objects related to each other. </p>
<p>While participants performed well overall, the strength of brain responses in the hippocampus during this task did not correlate with intelligence scores. This suggests that general reasoning ability is specifically tied to the ability to encode relationships, not just memory in general.</p>
<p>These results add to a growing body of work that views the hippocampus not only as a center for memory and spatial navigation but also as a hub for organizing information in ways that support flexible thinking. The ability to represent how different elements of an experience are related may provide a foundation for solving problems in new contexts or drawing inferences from limited data.</p>
<p>The researchers acknowledge that their study focused on a specific type of relational learning involving spatial arrangements. It remains to be seen whether the same principles apply to other kinds of abstract relationships, such as those involving concepts or rules. In addition, the study was conducted with a relatively homogenous group of healthy adults, which may limit how broadly the findings apply.</p>
<p>Since the research was cross-sectional, it cannot speak to causality. It’s unclear whether having a more structured way of encoding relationships contributes to higher intelligence or whether people with higher intelligence naturally develop better strategies for organizing information. Long-term studies could help clarify how these abilities develop over time and interact.</p>
<p>The researchers suggest that future studies could explore whether these relational encoding patterns show up in other brain regions involved in reasoning or generalization, such as the prefrontal cortex. There is some evidence that these areas also represent structured information, although it is not yet clear how their role compares to that of the hippocampus.</p>
<p>The study, “<a href="https://doi.org/10.1016/j.celrep.2025.116033" target="_blank">Human intelligence relates to neural measures of cognitive map formation</a>,” was authored by Rebekka M. Tenderra and Stephanie Theves.</p></p>
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<td><a href="https://www.psypost.org/can-an-algorithm-predict-a-politicians-future-just-by-analyzing-their-tweets/" 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;">Can an algorithm predict a politician’s future just by analyzing their tweets?</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 6th 2025, 20:00</div>
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<p><p>A new statistical model has successfully sorted members of the U.S. Congress into distinct political and legislative groups based solely on their interaction patterns on the social media platform X. Published in the <em><a href="https://doi.org/10.1080/10618600.2025.2540356" target="_blank">Journal of Computational and Graphical Statistics</a></em>, the study also identified a small number of outliers whose online behavior appeared to signal ambitions for higher office.</p>
<p>Politicians use public platforms to communicate their principles and policy stances to voters. Beyond formal statements, many also cultivate a personal brand through their choices in language and style. With a great deal of political messaging now occurring online, researchers have been investigating how elected officials position themselves by strategically associating with others in their coalition.</p>
<p>The new study was conducted by Benjamin Leinwand, an assistant professor of mathematical sciences at Stevens Institute of Technology, and Vince Lyzinski, a mathematics professor at the University of Maryland. They specialize in network science, a field that analyzes the connections within complex systems. They sought to determine if a model could deduce the underlying structure of a political network by observing only the interactions, without being given any information about political affiliations or which chamber of Congress a member belongs to.</p>
<p>To understand the social landscape of Congress, the researchers needed a tool that could map out the complex web of online interactions. At its core, any such statistical model attempts to calculate a simple value for every pair of individuals: the probability that they will connect. This produces a blueprint of the network, showing which connections are likely and which are not.</p>
<p>Some widely used network models approach this task by combining a few key factors. For instance, a model might estimate the probability of a connection by multiplying a person’s individual “sociability” score with a score representing how interactive their group is. This method works well in many scenarios, but it can break down in networks with extreme variations.</p>
<p>The issue arises in densely connected communities where a few individuals are exceptionally active. In such cases, the model might assign very high sociability scores to these active people and a high interaction score to their group. When these high scores are multiplied together, the resulting probability can exceed 1, or 100 percent. This is a mathematical impossibility that signals the model is failing to accurately represent the underlying social dynamics.</p>
<p>The new model developed by Leinwand and Lyzinski is built on a different mathematical foundation specifically designed to avoid this problem. Its internal calculations are constructed in a way that guarantees the final output for any pair of politicians is always a valid probability, a number between 0 and 1. This ensures the model produces a coherent and logical map of the network, even in its most active and complex regions.</p>
<p>Beyond just preventing errors, this new approach offers greater flexibility. It does not assume that the patterns of connection are the same across the entire network. For example, some models might implicitly assume that the most socially active members of one group are most likely to connect with the most active members of another.</p>
<p>The new model, however, can detect more intricate patterns. It could, for instance, find a situation where moderate members of two different political parties interact frequently, while the most partisan members of those same parties interact very little. It can also recognize that an individual’s tendency to form connections might change depending on the community they are interacting with, providing a more detailed and realistic portrait of political communication.</p>
<p>Using this model, Leinwand and Lyzinski analyzed the public activity of 475 members of the 117th U.S. Congress. Their dataset included every member who posted at least 100 tweets during a four-month period, from February 9, 2022, to June 9, 2022. The model defined a connection between any two politicians if one of them tweeted at or retweeted the other during this time frame.</p>
<p>“We call two people ‘connected,’ if either one in the pair tweeted at the other one or retweeted the other one during this period,” Leinwand explained. The model was not provided with any information about a politician’s party, their chamber, or their policy positions. It was tasked with sorting the 475 individuals into groups based only on the web of their digital connections.</p>
<p>The model identified three primary communities. These algorithmically-defined groups fell along familiar political lines. The first group was composed almost entirely of Senators. The second community consisted mainly of Democratic members of the House of Representatives, and the third was made up largely of Republican members of the House.</p>
<p>The analysis showed that politicians within these three groups tended to interact most frequently with members of their own community. “Republican congresspeople talked among themselves a lot, and Democratic congresspeople talked among themselves a lot, though Democratic congresspeople were somewhat more likely to interact with Senators than their Republican counterparts,” said Leinwand.</p>
<p>He offered a potential explanation for this pattern. At the time of the observation, Democrats held the majority in the Senate. As a result, “one could imagine that Democratic congresspeople might be incentivized to amplify senate leadership messaging in addition to their allies in the House,” he continued.</p>
<p>While the model correctly categorized the vast majority of politicians, it also found a few who did not conform to their group’s typical behavior. Of the 475 members, 463 behaved like the others in their respective communities. The remaining 12 individuals were classified as “exceptions” because their patterns of interaction more closely resembled those of a different group.</p>
<p>“It seems as though certain Democratic congresspeople talked to Senators more, and certain Republican congresspeople talked to Senators more,” Leinwand said. “And so based on their patterns of interactions, they behaved like someone in the other group. They were tweeting at Senators also, rather than only tweeting at their own Congresspeople.”</p>
<p>A closer look at these 12 exceptions revealed a suggestive pattern. Two of the congresspeople flagged by the model for behaving like senators went on to win Senate elections. Peter Welch, a Democrat from Vermont, was elected to the Senate in 2022, and Andy Kim, a Democrat from New Jersey, won his Senate race in 2024.</p>
<p>A third exception identified by the model, Chris Pappas of New Hampshire, is currently a candidate for the Senate. A fourth, David Trone of Maryland, mounted an unsuccessful campaign for the Senate in 2024.</p>
<p>“The thing that jumps out to me is that we have 475 members, and 463 of them are grouped correctly,” Leinwand said. “And of those 12 exceptions, two ended up in the group where our model thought they should be assigned.” This observation suggests the model may be detecting subtle behavioral shifts that precede major career moves.</p>
<p>This does not mean that simply tweeting at senators is a path to winning a Senate seat. However, Leinwand suggests that a deliberate communication strategy may be at play. “They have public facing jobs, so I suspect they’re often tweeting strategically, particularly when they’re including other members of Congress,” he says. “I think if you start positioning yourself in a certain way, if you start interacting with senators on X, you may be seen as more senatorial to voters.”</p>
<p>The researchers note that their study used an exploratory approach designed to search for patterns in the data. To establish more definitive conclusions about political strategy and its effects, different analytical methods would be necessary. Still, the findings hint at the rich information embedded in the architecture of our online interactions. As Leinwand adds, “I suppose some behavior betrays some intention.”</p>
<p>The study, “<a href="https://doi.org/10.1080/10618600.2025.2540356" target="_blank">ACRONYM: Augmented Degree Corrected, Community Reticulated Organized Network Yielding Model</a>,” was authored by Benjamin Leinwand and Vince Lyzinski.</p></p>
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<td><a href="https://www.psypost.org/study-finds-parental-criticism-is-linked-to-less-forgiveness-in-children/" 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;">Study finds parental criticism is linked to less forgiveness in children</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 6th 2025, 18:00</div>
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<p><p>A study of preschool children and their parents in Hong Kong found that parents’ perfectionistic tendencies were linked to their children’s development of relationship skills, and that the children’s capacity for forgiveness played a key role. Parents showing higher perfectionistic strivings (setting high but constructive standards) tended to have children who were more forgiving, which in turn was associated with better relationship skills. </p>
<p>In contrast, parents with higher perfectionistic concerns (focusing on criticism and failure) tended to have children who were less forgiving, which was then linked to poorer relationship skills. The paper was published in the <a href="https://doi.org/10.1177/01650254251361344"><em>International Journal of Behavioral Development</em></a>.</p>
<p>Relationship skills are abilities to build and maintain collaborative and supportive relationships with different people. These skills include empathy, communication, sharing, conflict resolution, and understanding others’ feelings.</p>
<p>Developing strong relationship skills helps children build friendships, work well in groups, and navigate social challenges. These skills also lay the foundation for emotional intelligence, which supports success in school and later in life. Good relationship skills can reduce behavioral problems and promote mental well-being. The importance of these skills has grown as modern children may spend more time online and less in face-to-face play, where social learning naturally occurs.</p>
<p>Parents play a crucial role by modeling respectful communication and empathy in their own relationships. When parents actively listen to their children, encourage cooperation, and guide them in solving disputes, children learn by example. Family routines that involve teamwork—like shared chores or games—strengthen these abilities. Open discussions about emotions help children recognize and manage their own feelings and understand others’. Conversely, parental behaviors like harsh criticism can impair the development of these abilities.</p>
<p>Study author Sum Kwing Cheung and his colleagues wanted to explore whether mothers’ and fathers’ perfectionistic strivings and concerns for their children’s performance were associated with their children’s later relationship skills. They proposed that these parental tendencies might affect children’s forgiveness, which would, in turn, contribute to the development of their relationship skills.</p>
<p>These researchers analyzed data from a larger longitudinal study on the effects of family dynamics on early socio-emotional development. Study participants were 226 first-year kindergarten children and their parents. The children’s average age was just under 4 years old (3.89 years), and 43.9% were boys. All participants were ethnically Chinese.</p>
<p>Data were collected at three time points, each six months apart. At the first time point, participating parents completed an assessment of their perfectionistic strivings and concerns about their children’s performance and an initial assessment of their children’s relationship skills. At the second time point, they completed an assessment of their children’s forgiveness. At the final time point, parents completed the assessment of their children’s relationship skills again.</p>
<p>Parents’ perfectionistic strivings refer to setting high performance standards for their children in a constructive way. In contrast, parents’ perfectionistic concerns involve a focus on their children’s inability to meet high standards, often accompanied by criticism and disappointment.</p>
<p>Results showed a clear indirect pathway. Parents who reported more perfectionistic strivings tended to have children who were more forgiving six months later, and this higher level of forgiveness predicted better relationship skills at the final time point. Conversely, parents who reported more perfectionistic concerns tended to have children who were less forgiving, and this lower level of forgiveness predicted poorer relationship skills. The effect of parental perfectionism on relationship skills was fully explained by its effect on the child’s forgiveness.</p>
<p>The study authors tested a statistical model showing that perfectionistic strivings positively influence forgiveness, while perfectionistic concerns negatively influence it. Forgiveness, in turn, directly fosters better relationship skills. The results supported this proposed model.</p>
<p>The study authors concluded that their findings support the critical roles of both mothers and fathers in developing forgiveness and relationship skills. “It demonstrates that different ways of conveying high performance expectations to children can result in different developmental outcomes,” they summarized. “As such, it is of utmost importance to help mothers as well as fathers recognize the effective ways to communicate with their young children to promote early relationship skills.”</p>
<p>The study contributes to the scientific understanding of how parental attitudes can shape children’s social development. However, it should be noted that all the data used in this study came from parental reports, leaving room for reporting bias to have affected the results.</p>
<p>The paper, “<a href="https://doi.org/10.1177/01650254251361344">Parents’ perfectionistic tendencies predicted early relationship skills: Children’s forgiveness as a mediator,</a>” was authored by Sum Kwing Cheung, Bertha H. C. Kum, and Rebecca Y. M. Cheung.</p></p>
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<td><a href="https://www.psypost.org/study-of-3-million-people-finds-non-voters-tend-to-die-earlier/" 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;">Study of 3 million people finds non-voters tend to die earlier</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 6th 2025, 14:00</div>
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<p><p>A new study of more than three million people in Finland has revealed a strong association between not voting and an increased risk of death over a 21-year period. The analysis showed that this mortality gap between voters and non-voters was even larger than the well-documented gap between individuals with the highest and lowest levels of education. The findings were published in the <em><a href="http://dx.doi.org/10.1136/jech-2025-224663" target="_blank">Journal of Epidemiology & Community Health</a></em>.</p>
<p>In recent years, public health experts and medical associations have begun to frame voting as a social determinant of health. This concept suggests that a person’s health is shaped not just by genetics and lifestyle choices, but also by a wide range of social, economic, and environmental factors. The act of voting can be seen as a measure of an individual’s engagement with their community and their ability to influence policies that affect their well-being, from healthcare access to environmental quality.</p>
<p>Previous research has hinted at a connection between civic participation and health, but these studies often relied on surveys, which can be affected by how people remember their actions or their desire to give socially acceptable answers. A team of researchers from the Helsinki Institute for Demography and Population Health at the University of Helsinki sought a more objective way to investigate this link. They wanted to know if the simple, recorded act of voting was connected to the most definitive health outcome of all: mortality.</p>
<p>To conduct their analysis, the researchers obtained a remarkable dataset from Statistics Finland. They started with the official voting lists from Finland’s 1999 parliamentary election, which covered the entire electorate of the country. This information was then confidentially linked to national administrative records, including demographic data and death certificates, through the end of 2020. This method provided a precise, individual-level record of who voted and who did not, and their survival status over the subsequent two decades.</p>
<p>The study included more than 3.1 million Finnish residents aged 30 and older at the time of the 1999 election. The researchers used a statistical approach known as a Cox proportional hazards model to compare the mortality rates of voters and non-voters. </p>
<p>This type of analysis allows researchers to calculate the relative risk of an event, in this case death, while accounting for other factors, such as age, to ensure a fair comparison. The team first calculated the risk of death for non-voters compared to voters, adjusting only for age. They then added education level into the model to see if it could explain the observed differences.</p>
<p>The results showed a clear and substantial difference in mortality risk. After adjusting for age, men who did not vote in the 1999 election had a 73 percent higher mortality rate over the following 21 years compared to men who did vote. For women, the difference was also significant, with non-voters having a 63 percent higher mortality rate than their voting counterparts.</p>
<p>When the researchers introduced education into their statistical models, the association between voting and mortality remained very strong. The elevated mortality risk for non-voters was only slightly reduced, suggesting that education did not account for the majority of the difference. </p>
<p>The mortality disparity between voters and non-voters proved to be wider than the mortality disparity between individuals with a basic education and those who had completed tertiary education, a finding that highlights the powerful connection between this form of civic engagement and health outcomes.</p>
<p>The association was even more pronounced when the researchers looked at specific causes of death. The risk of dying from “external” causes, a category that includes accidents, violence, and alcohol-attributable conditions, was more than double for non-voters compared to voters. This finding points toward potential links between non-voting and certain behaviors or environmental risks.</p>
<p>The analysis also uncovered nuances related to age and gender. The mortality gap between voters and non-voters was widest among younger adults, those under 50 years old. In another notable finding, women aged 75 and older who did not vote had a higher risk of death than men of the same age who did vote. This is an unusual pattern, as women typically have a longer life expectancy than men at all ages.</p>
<p>The study’s authors point out a primary limitation: their research establishes a strong correlation but cannot prove a direct causal link. It is not clear whether the act of not voting contributes to poorer health, or if underlying health problems and social disadvantages make it more difficult for a person to vote in the first place. For instance, poor health could reduce a person’s mobility, resources, or motivation to participate in an election. The study examined participation in a single election, which might not reflect a person’s long-term voting habits.</p>
<p>Future research could explore these dynamics more deeply. Longitudinal studies that track individuals’ voting patterns across multiple elections alongside changes in their health status could help clarify the direction of this relationship. Such work could better distinguish between individuals who consistently abstain from voting and those who miss an occasional election, potentially revealing more about the mechanisms connecting civic life and physical well-being.</p>
<p>Regardless of the precise causal pathways, the powerful association between voting and mortality has important implications. The researchers suggest that information on voting patterns could serve as a useful indicator for monitoring population health and identifying disparities. The findings also raise concerns about democratic equality. If populations with higher mortality rates are less likely to be represented at the ballot box, their needs and health concerns may receive less political attention, potentially creating a cycle of disadvantage.</p>
<p>The study, “<a href="http://dx.doi.org/10.1136/jech-2025-224663" target="_blank">Voting is a stronger determinant of mortality than education: a full-electorate survival analysis with 21-year follow-up</a>,” was authored by Hannu Lahtinen, Isa Yang, Lasse Tarkiainen, and Pekka Martikainen.</p></p>
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<td><a href="https://www.psypost.org/ai-roots-out-three-key-predictors-of-terrorism-support/" 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 roots out three key predictors of terrorism support</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 6th 2025, 12:00</div>
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<p><p>A new study suggests that individuals who justify terrorism tend to share a distinct worldview characterized by the normalization of violence, moral flexibility, and anti-democratic sentiments. Using a machine learning analysis of data from over 90,000 people across 65 countries, the research provides evidence that support for terrorism is embedded in a broader set of attitudes rather than being an isolated belief. The findings were published in the journal <em><a href="https://doi.org/10.1002/ab.70049" target="_blank">Aggressive Behavior</a></em>.</p>
<p>Public discourse often links terrorism to specific religious or political ideologies, yet extremist violence emerges from a wide range of backgrounds, including white supremacist and anti-government movements. This suggests that the psychological and social factors underlying radicalization may be more general than commonly assumed. </p>
<p>Previous research has identified many potential risk and protective factors for aggression, but these studies have often been limited to smaller, nationally specific samples. The current research aimed to apply a comprehensive, data-driven approach on a global scale to identify which attitudes and beliefs are most consistently associated with the justification of terrorism.</p>
<p>“The study was motivated by evidence that extremist ideologies are evolving in many parts of the world. For example, in recent years, pro-violence right-wing movements, white supremacist groups, and other forms of radicalization within established democracies have gained strength and attracted increasing numbers of followers,” said study author <a href="https://mohsenjoshanloo.weebly.com/" target="_blank">Mohsen Joshanloo</a>, an associate professor at Keimyung University and honorary principal fellow at the Centre for Wellbeing Science at the University of Melbourne.</p>
<p>“These developments suggest that some traditional assumptions about who justifies violence, including terrorism, may no longer hold. Public discourse has not fully kept pace with these changes and requires revision. The aim of this study was to identify patterns in a global dataset and provide an updated, evidence-based understanding of the factors associated with justifying terrorism.”</p>
<p>To conduct the analysis, the researcher utilized data from the seventh wave of the World Values Survey, a large-scale project that gathers information on the beliefs and values of people around the globe. The final sample included 91,659 participants from 65 nations. The study’s outcome of interest was a single question that asked respondents to rate the justifiability of “terrorism as a political, ideological or religious means” on a 10-point scale. </p>
<p>A machine learning algorithm known as Random Forest was employed to analyze the predictive power of 360 different variables from the survey. This method is well-suited for identifying complex patterns in large datasets without being constrained by predefined assumptions. The algorithm builds hundreds of decision trees to determine which factors are the most important predictors of an outcome, in this case, the justification of terrorism.</p>
<p>The final model, which included 271 of the most relevant predictors, was able to explain approximately 64% of the variation in people’s attitudes toward terrorism justification. The analysis revealed that a small number of predictors were especially powerful. These top factors fell into three distinct but related domains. </p>
<p>The first domain was a general normalization of violence. Individuals who were more likely to justify terrorism also tended to believe that other forms of aggression are acceptable. This included the justification of political violence, violence against other people, a man beating his wife, and parents beating their children. This pattern suggests that support for terrorism is not an isolated belief but part of a wider cognitive framework where aggression is viewed as a legitimate tool for resolving conflicts or achieving goals.</p>
<p>A second major pattern involved what the study describes as moral flexibility and a tendency to violate rules. People who justified terrorism were also more likely to approve of dishonest behaviors such as accepting a bribe, stealing property, cheating on taxes, and claiming government benefits one is not entitled to. </p>
<p>These individuals may operate with a moral code that permits breaking established social and ethical norms when it appears personally or ideologically useful. This mindset aligns with psychological concepts of moral disengagement, where individuals cognitively separate their actions from their moral principles, allowing them to engage in unethical behavior without self-censure.</p>
<p>The third key domain was a preference for religious and political authoritarianism. Respondents who justified terrorism were more likely to support a system where religious authorities interpret laws and were less likely to see free elections as an essential characteristic of democracy. They also tended to view a system of governance based on religious law, without political parties or elections, more favorably. </p>
<p>This combination of attitudes points to a skepticism toward democratic institutions and a preference for strong, centralized, and non-pluralistic forms of rule. The authoritarian preference appeared to be focused on political structures, as these same individuals showed more permissive attitudes toward certain personal behaviors like casual sex and homosexuality.</p>
<p>“Those who consider terrorism acceptable often share a worldview in which violence is normalized, moral rules are flexible, and democratic principles are devalued,” Joshanloo told PsyPost. “This worldview is not confined to any single group, religion, or region. Anyone can hold it or adopt it, regardless of location or identity. Outdated and simplistic explanations ignore the fact that pro-violence views are not limited to any particular demographic. To effectively reduce support for terrorism (and violence more broadly), we must address the underlying attitudes that legitimize violence everywhere, without assuming that one’s own group or oneself is immune to such beliefs.”</p>
<p>“Strategies to reduce violence should be guided by current evidence, not outdated stereotypes. For example, strengthening democratic institutions, addressing their weaknesses, and building community trust and cooperation are crucial steps, even though these measures are far more challenging than relying on easy but ineffective assumptions and prejudices.”</p>
<p>The findings can also be interpreted through the lens of the “Dark Triad” of personality traits: Machiavellianism, psychopathy, and narcissism. Although these traits were not measured directly, the observed patterns align with them conceptually. </p>
<p>“For example, endorsing bribery, fraud, and other rule- breaking behaviors for personal gain may reflect Machiavellian tendencies, that is, strategic, self-serving disregard for norms,” Joshanloo explained. “The normalization of violence and lack of empathy align with psychopathic traits, which involve callousness and instrumental use of aggression.” </p>
<p>“Narcissism may be reflected in the preference for authoritarian governance and rejection of democratic principles, signaling an inflated sense of ideological entitlement and disdain for pluralism. Taken together, these connections suggest that support for terrorism is not only ideological but may also stem from deeper psychological dispositions that erode empathy and moral constraints.”</p>
<p>While the study offers a robust global perspective, it has some limitations. The analysis was restricted to the variables available in the World Values Survey, meaning other potentially important factors, such as exposure to extremist propaganda or group grievances, were not included. Because the data was cross-sectional, it identifies associations but cannot establish causality. </p>
<p>Future research could build on these findings by incorporating a wider range of variables, using more detailed psychological measures, and employing longitudinal designs to better understand how these attitudes develop over time.</p>
<p>“It is important to note that this study does not examine engagement in terrorism, but rather the extent to which individuals view terrorism as justifiable,” Joshanloo noted. “The results should be understood as general global patterns, offering a broad picture of what tends to predict justification of terrorism globally. They are not meant to describe any single country, region, group, or context in detail. </p>
<p>“A factor that appears unimportant at the global level might be highly significant in a specific local setting. Therefore, these findings should serve as a backdrop for more nuanced local research rather than a substitute for it. The value of global insights is that they reveal common psychological and ideological tendencies that transcend borders, helping us understand what is broadly associated with terrorism justification worldwide. This big-picture perspective provides a reference point for interpreting local findings and designing strategies that combine global insights with context-specific solutions.”</p>
<p>The study, “<a href="https://doi.org/10.1002/ab.70049" target="_blank">Who Considers Terrorism Justifiable? A Machine Learning Analysis Across 65 Countries</a>,” was authored by Mohsen Joshanloo.</p></p>
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<td><a href="https://www.psypost.org/womens-waist-to-hip-ratio-linked-to-brain-function-in-early-menopause/" 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’s waist-to-hip ratio linked to brain function in early menopause</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Nov 6th 2025, 10:00</div>
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<p><p>A new study suggests that for women who have recently gone through menopause, having more fat stored around the midsection is associated with lower performance on certain thinking and memory tests. This research, published in <em><a href="https://doi.org/10.1097/gme.0000000000002666" target="_blank">Menopause</a></em>, also found that this connection was not altered by the use of hormone therapy over a four-year period.</p>
<p>The time around menopause often involves significant biological changes for women, including a natural decline in the hormone estrogen and shifts in body composition. One common change is an increase in central adiposity, which is the accumulation of fat deep within the abdomen around the internal organs. This type of fat distribution is distinct from overall body weight and is known to be metabolically active, contributing to inflammation and reduced insulin sensitivity, which are risk factors for conditions like heart disease and diabetes.</p>
<p>Researchers have also been exploring how these metabolic changes might relate to brain health. The brain contains receptors for estrogen, particularly in regions responsible for higher-order cognitive processes like memory and executive function, which includes skills like planning and problem-solving. </p>
<p>A team of scientists from institutions across the United States, including the University of Wisconsin-Madison and the Mayo Clinic, hypothesized that the combination of declining estrogen and rising central adiposity could affect a woman’s cognitive abilities during this life stage. Their work is a secondary analysis of data from the Kronos Early Estrogen Preventive Study (KEEPS), a major clinical trial examining the effects of hormone therapy.</p>
<p>To investigate this relationship, the researchers analyzed data from more than 700 women between the ages of 42 and 58. All participants had gone through menopause within the previous three years and were specifically selected for being at low risk for cardiovascular disease. The women were part of a randomized trial and were assigned to one of three groups for four years: one group received estrogen in the form of an oral pill, another received estrogen through a skin patch, and a third group received a placebo.</p>
<p>The scientists measured central adiposity using the waist-to-hip ratio, a simple calculation made by dividing the circumference of the waist by that of the hips. A higher ratio indicates a greater concentration of fat in the abdominal area. The participants’ cognitive abilities were assessed at the beginning of the study and then again at 18, 36, and 48 months. </p>
<p>These assessments involved a comprehensive set of tests designed to measure four distinct areas of mental function: verbal learning and memory; auditory attention and working memory; speeded language and mental flexibility; and visual attention and executive function.</p>
<p>At the beginning of the study, the analysis showed a clear pattern. Women with a higher waist-to-hip ratio tended to have lower scores across all four of the cognitive domains measured. This finding established a direct association between greater central adiposity and poorer cognitive performance at a single point in time for this group of recently postmenopausal women.</p>
<p>When the researchers examined how these cognitive scores changed over the four years of the study, they found that a higher initial waist-to-hip ratio was linked to a decline in one specific cognitive area: visual attention and executive function. This suggests that central adiposity may have a sustained negative effect on the brain systems that support skills like focusing on visual information and organizing complex tasks. The other cognitive domains did not show a similar decline linked to waist-to-hip ratio over the study’s duration.</p>
<p>The study also explored whether taking hormone therapy might influence this connection between body composition and brain function. The results indicated that it did not. The relationship between a higher waist-to-hip ratio and cognitive performance was consistent whether the women were taking oral estrogen, transdermal estrogen, or a placebo. Hormone therapy did not appear to protect against or worsen the cognitive associations linked to central adiposity in this population.</p>
<p>The authors note some limitations to their work. The study participants were predominantly non-Hispanic White, well-educated, and in good cardiovascular health, which means the results may not be generalizable to all women. Additionally, the waist-to-hip ratio is an accessible but indirect measure of abdominal fat. The four-year timeframe of the study may also be too short to observe longer-term cognitive changes or potential effects of hormone therapy.</p>
<p>Future research could explore these relationships in more diverse populations and over longer periods. The researchers suggest that continued follow-up of these participants, as is planned in a continuation study, may help clarify the long-term connections between metabolic health and cognition after menopause. These findings add to a growing body of evidence suggesting that metabolic factors, even in otherwise healthy individuals, may play a meaningful role in brain health as women age.</p>
<p>“Addressing modifiable risk factors early and often is critical to maintaining optimal health and independence as women age. The metabolic and cognitive changes that commonly occur during and after the menopause transition often catch women off-guard and are more difficult to address after the diagnosis has been made. Instituting preventive lifestyle strategies before the menopause transition will result in longitudinal health gains and reduced morbidity and mortality,” said Monica Christmas, associate medical director for The Menopause Society.</p>
<p>The study, “<a href="https://doi.org/10.1097/gme.0000000000002666">Association between central adiposity and cognitive domain function in recently postmenopausal women: an analysis from the KEEPS-Cog substudy of the Kronos Early Estrogen Preventive Study</a>,” was authored by Taryn T. James, N. Maritza Dowling, Carola Ferrer Simó, Hector Salazar, Carol A. Van Hulle, Gilda Ennis, Adrienne L. Johnson, Mary F. Wyman, Lauren W. Y. McLester-Davis, Diane C. Gooding, Barbara Fischer, Shenikqua Bouges, Emre Umucu, Firat Kara, Juliana M. Kling, JoAnn E. Manson, Eliot A. Brinton, Marcelle I. Cedars, Rogerio A. Lobo, Genevieve Neal-Perry, Nanette F. Santoro, Frederick Naftolin, Sherman M. Harman, Lubna Pal, Virginia M. Miller, Kejal Kantarci, and Carey E. Gleason.</p></p>
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<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
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