Stephanie Dorais You slide your hand into your coat pocket and find an old, folded $100 bill. In the other pocket, you find a coin. Now, here’s the gamble: flip the coin. Heads, you win another $300. Tails, you hand over your $100 bill. Do you take the risk? Mathematically, you should. One coin flip gives you two equally likely futures: in one, heads, you gain $300; in the other, tails, you lose $100. Because each future has a 50 per cent chance of happening, you count half of each outcome: half of $300 is $150, and half of $100 is $50. Balance those against each other, and taking the gamble puts you $100 ahead on average. Decision scientists call this positive expected value. Even when someone grasps the mathematics, however, it’s hard to take the risk. Why? About 50 years ago, the psychologists Amos Tversky and Daniel Kahneman showed that this hesitation is not random. People depart from logic in patterned ways. One of the most durable patterns is loss aversion: our tendency to feel the pain of losing more sharply than the pleasure of an equivalent, or even greater, gain. This is where mindfulness becomes interesting. Mindfulness is usually defined as paying attention to the present moment, on purpose, without immediately judging what is happening. In practice, that can mean noticing a thought before believing it, feeling an emotion before acting on it, or returning attention to the body, the breath, or the world around you. At its simplest, mindfulness creates a pause between what arises in the mind and what we do next. That pause helps because many of our choices are made before we have fully examined them. We may think we are deliberating over the coin toss, but often the body has moved first: recoiling from loss or preserving a decision simply because we have already invested in it. These mental shortcuts are called cognitive biases, and the study of this kind of human misjudgment is central to decision science. © Aeon Media Group Ltd. 2012-2026.

Keyword: Attention; Emotions
Link ID: 30319 - Posted: 07.11.2026

By Natalia Mesa To accurately navigate the world, an animal must learn, remember and continually update how its body position relates to what it sees in the world around it. New findings reveal the circuit mechanisms responsible for this process in fruit flies—and upend a widely held assumption that this kind of learning relies on dopamine. The research “solves this long-standing problem of how you learn about landmarks in the world,” says Lisa Giocomo, professor of neurobiology at Stanford University, who was not involved in the study. “Over the last decade, some of the biggest insights into how the brain generates algorithms for navigational systems have come from Drosophila,” she says. “It’s been astonishing to see what’s been possible with that system.” When a neuron in a fly’s internal compass activates at the same time as a cell responding to a visual landmark, a third type of cell called an EL neuron releases the neuromodulator octopamine onto the visual inputs, according to the work, posted as a preprint in December 2025 and presented at the Jane Coffin Childs Symposium in May 2026. Octopamine acts as a signal that modifies the connection between the compass and visual cells, anchoring the fly’s sense of direction to visual cues. To their knowledge, the synaptic and circuit mechanisms the fly uses to update its internal compass work unlike any yet described, the study investigators say. “It’s a completely new learning mechanism, basically,” says Stanley Heinze, senior lecturer of sensory biology at Lund University, who was not involved in the study. Fruit flies, like other animals, have an internal compass made up of head direction cells that selectively activate based on the direction the fly faces. The fly’s internal representation of the world drifts without visual input but quickly reorients when familiar landmarks reappear. © 2026 Simons Foundation

Keyword: Learning & Memory; Evolution
Link ID: 30313 - Posted: 07.08.2026

By Henry Taylor & The Conversation US You know that feeling when you walk into a room and immediately forget why you came in? Maybe you were there to fetch your keys. On your way to the room, you were thinking about grabbing your keys. But once you arrive, your keys have completely disappeared from your mind. This is sometimes known as the doorway effect, since it often strikes when you walk into a new room. Why does it happen? The answer has a lot to do with a faculty called working memory. Information gets stored in working memory when we need it for the tasks that we are engaged in right now (like remembering to grab your keys). What makes working memory so intriguing is its close link to consciousness. The doorway effect suggests that when information is removed from working memory, it immediately seems to leave consciousness. It also suggests that it is easy for information in working memory to be forgotten. The link between working memory and consciousness is getting increasing attention in psychology, philosophy and neuroscience. Could working memory somehow give rise to consciousness? In my new book, I explore the complex relationship between the two. Working memory: both rich and poor To understand the doorway effect, we’ll need to know a bit about working memory. One thing that makes working memory so special is that it’s so rich, both in terms of the information it has access to, and its processing power. According to recent models of working memory, it can draw information from sensory channels (vision, touch, smell etc), as well as from other memory systems such as long-term memory and also the brain’s system for processing language. In other words, working memory is where a lot of the information in your brain comes together. Once working memory has that information, there’s a lot it can do with it. Inside working memory are a host of different smaller systems for specific tasks, including visual and spatial reasoning (like solving a Rubik’s cube) and storing chunks of information (like a phone number). There’s even a “central executive” system (my favorite). The executive is like a merciless boss, assigning tasks to the different systems within working memory and keeping everything under control. © 2026 SCIENTIFIC AMERICAN

Keyword: Consciousness; Learning & Memory
Link ID: 30309 - Posted: 07.04.2026

By Nora Bradford Mirrors are tricky. Even humans aren’t born with an intuitive understanding of them; we have to learn how they work. Now, scientists have discovered that the California two-spot octopus (Octopus bimaculoides) can also learn to use mirrors, researchers report June 3 in Current Biology. When brainstorming octopus experiments, Mary Kieseler, a neuroscientist at the University of Fribourg in Switzerland, had wondered whether the famously smart creatures could pass the mirror test, which evaluates if an animal can identify itself in a mirror. Because of the challenging logistics the mirror self-recognition test would entail underwater, Kieseler and her team decided to first study whether octopuses could use mirrors as a tool to do something they’re already great at. And octopuses are great at hunting prey. The team began by habituating three wild-caught octopuses to a mirror covering half their tank. They let the octopuses hide from the mirror and even explore the other half of the tank behind it. After the octopuses became comfortable with seeing their reflection and eating in front of the mirror, the team gave them a task: Find a hidden jar with a tasty crab inside, placed where the snack could be found using only its reflection in the mirror. Initially, the octopuses approached the mirror, then turned around to find their prey. But after about 10 to 12 trials, each animal learned to crawl directly to the crab without the mirror pit stop. When using real crabs, there was no way to know whether the octopuses might have been relying on smell or another nonvisual sense to hunt, so Kieseler and her team came up with one final test. Rather than using real crabs, the team used virtual ones. © Society for Science & the Public 2000–2026

Keyword: Intelligence; Learning & Memory
Link ID: 30305 - Posted: 07.01.2026

By K. R. Callaway Strutting and fluttering around cities, pigeons have adapted to an ever-shifting environment. But their environment isn’t the only thing that’s constantly changing. New research suggests the birds themselves avoid stability in their decision-making, instead choosing to live “at the edge of chaos.” As model species for learning and behavior, these birds are helping researchers test a century-old law about how humans and other creatures learn. When learning something new, people and animals alike tend to repeat behaviors that are rewarded. First proposed by Edward Thorndike in 1898, this principle is so well established in psychology that it's become known as the law of effect. But the law implies that beyond making a behavior more frequent, rewards also make it more consistent: reducing variability in the specific way behaviors are performed over time. Although scientists have repeatedly tested whether rewards increase the frequency of behaviors, their effect on consistency is less well studied. University of Iowa experimental psychologist Edward A. Wasserman and his colleagues decided to put it to the test in pigeons—a species that has been integral to the study of learning at the university’s Comparative Cognition Laboratory for more than 50 years. And the study’s results, published in the Journal of Experimental Psychology: Animal Learning and Cognition, suggest these birds experience variability as the spice of life. To see how rewarded behaviors vary, the researchers gave pigeons a series of five colorful buttons to peck. They could peck any buttons in any order, but as long as they pecked five times, a treat would appear. Based on previous theories of learning, the scientists expected the pigeons might eventually slip into a routine—perhaps choosing to repeat patterns they know work or simply pecking the button nearest to them five times. Instead they continued pecking in a variety of patterns. © 2026 SCIENTIFIC AMERICAN,

Keyword: Learning & Memory; Evolution
Link ID: 30304 - Posted: 07.01.2026

By Calli McMurray Kanga the marmoset places her hand on the lever and looks at Dodson, a fellow marmoset working with her on a task. As it becomes apparent that Dodson is ready to pull his own lever, neurons in Kanga’s dorsomedial prefrontal cortex ramp up their firing. The activity reaches its peak as Kanga decides to pull the lever, in sync with her partner. As a reward for their coordinated effort, both marmosets earn a sip of liquid marshmallow fluff. This type of neuronal computation underlies the “evidence accumulation model,” a major theory of how perceptual decisions are made: The brain gathers evidence and executes a decision once the evidence reaches a certain threshold. The marmoset study, which was published last month in Neuron, demonstrates that the model also applies to social decisions. This result wasn’t a given; making a social decision relies on the changing behavior of another animal, and the actions of the decider can influence what the other animal does, says study investigator Monika Jadi, associate professor of psychiatry and neuroscience at Yale University. “It’s a very recurrent system,” she says. Support for the evidence accumulation model has come largely from highly controlled experiments; the fact that the same activity pattern appears in a social and less constrained task “implies that this is a generalizable computation,” says Timothy Hanks, associate professor of neurology at the University of California, Davis, who was not involved in the work. Social, perceptual, foraging and other decisions are “categories we’ve created,” but there may not be anything “acutely different” about them, says Cory Miller, professor of psychology at the University of California, San Diego, who was not involved in the study. “I love this line of work; I think it’s super powerful.” © 2026 Simons Foundation

Keyword: Learning & Memory; Emotions
Link ID: 30297 - Posted: 06.27.2026

By Kathryn Hulick Emma Lembke joined Instagram at age 12. Soon, she found herself “scrolling mindlessly for hours, addicted to gaining a certain number of likes, a certain number of comments.” She often wanted to stop — but couldn’t. She’s not alone. Most of us these days know the feeling of mindlessly scrolling through low-quality content. We call this sensation “brain rot.” The term can also refer to the content being consumed. Tung Tung Tung Sahur, a personified wooden drum (illustrated above), is one in a slew of silly AI-generated characters deemed “Italian brain rot” because many of them have Italian-sounding names. Trendy among middle schoolers, these absurdist characters show up in memes, videos, Roblox games and more. Brain rot is kind of a joke, but it also really isn’t. A growing number of young people and their parents claim that spending too much time on social media, the spawning ground for brain rot, can mess with mental health. Thousands of cases accusing social media companies of harming young users with addictive features are now making their way through U.S. courts. In May, the U.S. government released a Surgeon General’s warning about the harms of screen use for young people, calling out social media as well as gaming, chatbots and more. “Policy makers and tech companies need to acknowledge the potential for harm and create frameworks to protect children to allow for healthy and joyful use,” states the warning, which includes a disclaimer that the document was edited using the AI tool ChatGPT. But the term “brain rot” evokes something more pernicious. Could browsing through stupid content actually make us stupid? This fear isn’t new. Back in 2009, the former CEO of Google, Eric Schmidt, voiced concerns about how digital media was impacting young people’s intelligence: “I worry that the level of interrupt, the sort of overwhelming rapidity of information … is in fact affecting cognition,” he said in an interview with talk show host Charlie Rose. © Society for Science & the Public 2000–2026

Keyword: Attention; Learning & Memory
Link ID: 30288 - Posted: 06.20.2026

By Lauren Schenkman Many animals can solve novel problems, often in a single go. For humans, that could be writing the first line of a poem, tackling a complex equation or improvising a jazz solo. For a macaque monkey, it might mean climbing a new tree to snag a delectable fruit. A new study, published in May in Nature, adds support to the long-standing idea that the brain accomplishes these feats by piecing together bits of existing knowledge (words, mathematical functions, riffs or tree-climbing moves, for example)—a process called compositional generalization. Single-neuron recordings in macaques locate the knowledge blocks, according to the study. The brain activity patterns that occur in the ventral premotor cortex when monkeys learn to draw simple symbols recur in concert when the animals are later prompted to draw complex shapes made up of those symbols. “We have quite a lot of behavioral evidence for compositional generalization across a wide array of different tasks,” says Charlie Wilson, a tenured researcher at the Institut National de la Santé et de la Recherche Médicale (INSERM) and the Stem Cell and Brain Research Institute in Lyon, who was not involved in the new research. “The interesting element here is the step towards showing a neural basis for that.” The new work is part of a growing effort in the field to “bring modern techniques and modern understanding back to bear on this kind of question,” says Tim Buschman, professor of neuroscience and psychology at Princeton University. Buschman was not involved in the study but co-authored a 2025 Nature paper showing how macaques use compositional generalization to respond with specific eye movements to different types of images. “I think it’s really wonderful seeing evidence for these types of components.” © 2026 Simons Foundation

Keyword: Attention; Learning & Memory
Link ID: 30287 - Posted: 06.20.2026

Jon Hamilton The most powerful factors affecting a child's brain development involve socioeconomic opportunities, according to a study in the journal Science. The analysis of more than 2,300 9- and 10-year-olds found that environmental factors ranging from household income to education to neighborhood quality are associated with brain differences that can clearly be seen in MRI scans. The researchers also found that preteens who'd grown up in neighborhoods with lower incomes and limited social support had brain differences associated with less sleep and more stress. "Something is going on in these neighborhoods," says Scott Marek, the study's first author and an assistant professor of radiology at WashU School of Medicine. "We need to find out how socioeconomics is becoming biologically embedded." The research "highlights the fact that the environment in which we grow up and live has powerful impacts on our brain," says Russell Poldrack, a psychology professor at Stanford University who was not involved in the study. It also challenges earlier research that focused on links between brain development and factors like IQ and mental health. Those factors do appear to have a small influence on brain development, says Dr. Nico Dosenbach, an author of the new study and a professor at WashU Medicine in St. Louis. "But socioeconomics was, by a wide margin, absolutely the dominant variable," Dosenbach says. © 2026 npr

Keyword: Development of the Brain; Intelligence
Link ID: 30280 - Posted: 06.13.2026

By Vanessa Hadid, Karim Jerbi, John W. Krakauer Late at night, in neighboring apartments, two people sit alone in front of glowing screens. A university student types into an artificial-intelligence (AI) companion he has started confiding in: “I feel like nobody really understands me.” Next door, a young professional opens a chatbot she has begun to rely on most evenings: “I tried following your advice today, but I still couldn’t finish everything I was supposed to do.” The responses appear instantly: reassuring, thoughtful, even caring. Over time, both people begin to feel these conversations are deeply genuine, as though something on the other side truly understands them. Yet nothing in these systems experiences loneliness, empathy, stress or care. They generate responses from statistical patterns learned across vast amounts of language data. As neuroscientists, we find this reaction unsurprising but concerning. It reveals something important not about machines, but about us. Humans are quick to infer the presence of a mind when behavior looks right. When language is fluent and emotionally attuned, we take it as evidence of inner experience. That intuition feels natural, but it is misleading. Today’s AI systems can sound perceptive and empathetic, yet there is no evidence that these systems are actually experiencing anything. As the use of AI companions and therapeutic tools spreads, this confusion carries real risks. The question is not whether AI is becoming conscious, but why it so easily seems that way. Here, we approach the AI consciousness debate through the lens of neuroscience. Research on nonconscious processing in the human brain shows that behavior that is complex, goal directed and even emotionally responsive can unfold without awareness. This reminds us that behavior and experience can come apart, and that we should resist treating AI’s fluent and seemingly empathetic performance as evidence of a mind. © 2026 Simons Foundation

Keyword: Consciousness; Robotics
Link ID: 30275 - Posted: 06.10.2026

By Claire L. Evans It was the dead of winter in Boston. The surface of the Charles River was frozen solid. But Zachary Kelso (opens a new tab) braved the biting cold to finally put to rest a mystery that has haunted neuroscience labs for over half a century. To do that, Kelso, a research assistant in the Harvard lab of the neuroscientist Sam Gershman (opens a new tab), needed some worms. Specifically, planarians: arrow-headed flatworms, which are among the simplest creatures to possess a brain and a nervous system with bilateral symmetry like ours. Normally, labs order these widely used model organisms from biological supply companies. But the mail-order worms weren’t up to snuff. So Gershman had dispatched Kelso to the Charles’ icy banks to catch some wild ones. “I thought, ‘I’m going to look crazy because I’m using a hammer to beat through the ice,’” Kelso recalled. “So I wore the more business end of business casual.” In philosophy, “qualia” refers to the subjective qualities of our experience: what it’s like for Alice to see blue or for Bob to feel delighted. Qualia are “the ways things seem to us,” as the late philosopher Daniel Dennett put it. In these essays, our columnists follow their curiosity, and explore important but not necessarily answerable scientific questions. It wouldn’t be the last time Kelso found himself in this situation. The Charles River planarians, it turned out, didn’t cut it either. Neither did the worms he sourced while stream-hopping around Eugene, Oregon, in March 2025. Nor did the ones he fished from Michigan lakes that June — this time in thigh-high waders — while picnicking families gawked from shore. Kelso diligently turned over rocks, angled with bits of meat tied to a string, and even followed maps from a vintage guidebook called The Fresh-Water Triclads of Michigan (opens a new tab). But his adventure was fruitless. Sure, he caught plenty of planarians. But back in Gershman’s lab, none of them would do what they were supposed to do. (C) Simons Foundation

Keyword: Learning & Memory; Evolution
Link ID: 30272 - Posted: 06.06.2026

By Erin Garcia de Jesús Buff-tailed bumblebees can figure out on their own how to use a ball as a ladder to nab sugar from an out-of-reach fake flower, researchers report in the June 4 Science. The insects worked out the trick without specific training for the solution, suggesting a remarkable capacity for solving problems. Bumblebees are brainy, with studies showing they may have emotions and can teach one another to score goals in a six-legged version of soccer. The new finding adds yet another skill to their repertoire. “Spontaneous problem-solving is something that has never been shown in any invertebrate before,” says Olli Loukola, a behavioral ecologist at the University of Oulu in Finland. Vertebrates including chimpanzees and parrots can problem solve on their own, although researchers typically focus on captive animals with plenty of experience working out puzzles. “Our study is the first one where we can be 100 percent sure that these individuals don’t have any prior experience about any problem-solving tasks,” Loukola says. Loukola and colleagues first taught bees two necessary associations: Balls are moveable objects and a blue ring — representing a flower — means food. The team then let the bees loose in plexiglass arenas too small for them to fly to reach a blue ring printed on the ceiling. © Society for Science & the Public 2000–2026.

Keyword: Learning & Memory; Intelligence
Link ID: 30271 - Posted: 06.06.2026

By Natalia Mesa Dopamine neurons register surprise: Their activity surges when an experience exceeds expectations and falls silent with disappointment. These prediction errors help brains and artificial-intelligence systems learn from experience by updating future expectations, according to a long-standing model. But because dopamine neurons receive input from several sources, the exact circuit mechanisms that compute the difference have remained mysterious, says Naoshige Uchida, professor of molecular and cellular biology at Harvard University. It turns out that a circuit of just two types of neurons is central to this computation. Dopamine neurons in the ventral tegmental area calculate the error based on input originating from D1 medium spiny neurons in the striatum, according to unpublished mouse data Uchida and his team presented at this year’s Computational and Systems Neuroscience (COSYNE) annual meeting and reported in a preprint posted on bioRxiv in October 2025. This result suggests that “reward learning doesn’t necessarily involve higher-order computation,” says Kauê Costa, assistant professor of psychology at the University of Alabama at Birmingham, who was not involved in the work. “The canonical view is that these types of computations would involve higher-order areas.” But it also bolsters the reward prediction error model, which has come under scrutiny in recent years, says Nathaniel Daw, professor of computational and theoretical neuroscience at Princeton University, who was not involved in the study. “It’s amazing” how much explanatory power the model has had in predicting neuronal responses, he adds. “It’s been a long road to get here. It’s a really beautiful study.” © 2026 Simons Foundation

Keyword: Learning & Memory; Drug Abuse
Link ID: 30270 - Posted: 06.06.2026

R. J. Mackenzie At dawn in late January 1998, two men entered the home of Betty Black in Farmers Branch, a suburb of Dallas, Texas. They killed her in an apparent burglary gone wrong. A few hours later, an eyewitness — Black’s neighbour — described what she had seen to police. She said that two white men with long hair had got out of a car and walked towards Black’s house in the early morning light. The neighbour, Jill Barganier, went to the police station the next day and identified Richard Childs, a white man with long hair, as the car’s driver. Childs would later confess to his involvement and serve 16 years in prison. Over the next week, the police homed in on 28-year-old Charles Don Flores as the second suspect. Flores had been seen with Childs on the morning of the murder, but he was a Latino man with short hair. On 4 February, Barganier was called to the police station. There, in an attempt to jog her memory, an officer used ‘forensic hypnosis’, a discredited practice that has since been discontinued in Texas and many other jurisdictions. During the session, he suggested to Barganier that one of the men might have had “neatly trimmed” hair. She once again described the passenger as a white man with long hair and then helped police to produce a composite sketch that looked nothing like Flores. She studied another photo line-up consisting of Flores and five other Latino men with short hair; she didn’t recognize any of them. More than a year later, however, in March 1999, Barganier’s memory had changed. She testified in court that Flores was in the car, saying that she was “over 100 percent” sure that he was the man she had seen. In the absence of DNA evidence connecting Flores to the crime, this testimony became the cornerstone of the prosecution’s case. A jury convicted Flores of capital murder, and he is currently on death row. © 2026 Springer Nature Limited

Keyword: Attention; Learning & Memory
Link ID: 30259 - Posted: 05.27.2026

By Holly Barker Neurons in the locus coeruleus, which provides norepinephrine to the rest of the brain and spinal cord, are more spatially and functionally diverse than previously thought, a new preprint finds. The work reveals how such a small structure located deep in the brainstem can influence a range of functions in multiple brain regions. Locus coeruleus neurons show gene expression variations that track with differences in the cells’ shape and projection targets, the study found. And neurons that occupy opposite ends of the structure respond differently to the rewards mice receive during a learning task, suggesting that the neurons facilitate learning in distinct ways. “This is the bread-and-butter work that the locus coeruleus field needed,” says Nelson Totah, associate professor of neurophysiology and pharmacology at the University of Helsinki, who was not involved in the study. “What they did here was not ask flashy questions [but] answer fundamental questions about this evolutionarily ancient nucleus, so I’m really glad to see this work.” The locus coeruleus—which translates from Latin to “blue spot”—is named for the blue pigmented cells that synthesize norepinephrine. The structure was long thought to consist of homogeneous neurons that secrete norepinephrine in synchrony. But over the past two decades it has become increasingly clear that the region is structurally and functionally heterogeneous: It has two distinct neuronal subtypes that fire asynchronously and drive opposite behaviors in rats, according to papers published in 2018 and 2017, respectively. The new findings suggest that the structure’s neurons are even more diverse and follow a precise organizational pattern: From one end of the region to the other, neurons show a spatial gradient in gene expression differences that map onto variations in the cells’ morphology, electrical activity and target regions, the new study found. © 2026 Simons Foundation

Keyword: Brain imaging; Learning & Memory
Link ID: 30257 - Posted: 05.27.2026

Simon Spichak Acute stress makes it difficult to link memories of past events with fresh information, a study1 suggests. The results help to explain why people struggle to show insight under pressure. The study, published today in Science Advances, combined brain imaging and psychological testing to show how stress disrupts people’s ability to tap into records of previous experiences and make deductions. The combination of behavioural testing and neural imaging “to actually see what’s going awry is really compelling”, says Brice Kuhl, a neuroscientist at the University of Oregon in Eugene, who was not involved in the study. Only connect The brain connects new and old information to make inferences through a cognitive process called integration. For example, if you have a memory of your friend wearing a bright green jacket, and you see a bright green jacket on a park bench, you might integrate your memory and the visual input to infer that your friend is at the park. This ability can be impaired in individuals with some mental-health conditions, such as anxiety disorders and psychosis. The brain area called the hippocampus is essential for integration. Since it is also particularly vulnerable to stress, Lars Schwabe, a cognitive psychologist at the University of Hamburg in Germany, and his colleagues decided to test how acute stress would affect the brain’s ability to integrate information and make inferences. Memory task On the experiment’s first day, 121 participants were asked to memorize a series of paired images, each containing one image of an animal and one image of either a face or a scene. © 2026 Springer Nature Limited

Keyword: Stress; Learning & Memory
Link ID: 30255 - Posted: 05.23.2026

Diana Kwon It is a dogma in neuroscience that certain brain cells respond in the same way to the same thing. Specific neurons always fire, for example, when we see particular shapes and colours; other neurons activate to swing an arm or wiggle a nose. The brain needs this stability, the theory goes, to respond to the outside world in a consistent way. So, when neuroscientist Laura Driscoll began her doctoral research at Harvard University in Cambridge, Massachusetts in 2012, her first task was to establish this baseline by tracking the activity of individual mouse neurons over time. To Driscoll’s surprise, the baseline kept moving. Over the course of several days, many of the cells’ responses had shifted noticeably. Neurons that had fired when a mouse was in a specific location on day one were barely responding in the same spot after a few weeks. “It absolutely defied all of our expectations,” recalls Driscoll, who is now at the Allen Institute in Seattle, Washington. “This was so surprising that my whole project changed.” In 2017, she and her colleagues reported findings from that project that flew in the face of neuroscience dogma. Over a single day, neurons in the parietal cortex, a hub for processing sensory information, fired predictably in response to specific things, such as the position of the mouse in a virtual maze. But over the course of a few weeks, even though the task of navigating the maze remained the same, these activity patterns underwent major reorganization1. Some of the neurons stopped firing in response to stimuli that had previously activated them; others did the reverse. In groups of cells, however, patterns of neuronal activity remained more consistent over time. The results suggested that individual neurons might not have fixed roles, and that the response of single cells might be less important than the activity of whole populations. © 2026 Springer Nature Limited

Keyword: Learning & Memory; Brain imaging
Link ID: 30251 - Posted: 05.20.2026

By Marta Zaraska 05.19.2026 On a blazing hot day in South Africa, female southern pied babblers can’t think straight. The medium-sized black-and-white birds are trying to get at tasty mealworms behind a see-through barrier. On cooler days, the birds can quickly figure out that all they have to do is go around the small wall of plastic. But when the mercury goes up, the birds just keep stubbornly pecking at the barrier. That experiment is part of a growing body of research showing that animals get their minds muddled during heat waves. When it’s hot outside, birds struggle to learn, dogs bite more often, goat-like chamois pick fights. This is bad news not just for those who get on Fido’s toasted nerves. If the animals can’t stay alert enough to find food or avoid predators, their chances of survival go downhill, says Amanda Ridley, a behavioral ecologist at the University of Western Australia who coauthored the pied babbler study. With climate change making heat waves more common, such cognitive impairments across the animal kingdom could ripple through entire ecosystems, putting already fragile species at greater risk. If pollinators forget which flowers to visit, crops and wild plants may fail. If birds can’t find food as easily, their young may not survive. And on a warming planet, a sharp mind is particularly vital. “A changing climate means that your ability to behaviorally adapt is even more important,” Ridley says.

Keyword: Intelligence; Learning & Memory
Link ID: 30250 - Posted: 05.20.2026

By Kate Golembiewski By watching their peers, dolphins learn to capture fish in empty conch shells, then ferry the shells up to the water’s surface in order to eat. Octopuses can master experimental tasks by watching their tankmates in the laboratory. Crows follow the cues of others in their flock to attack specific humans who have harassed fellow crows in the past. Scientists call it “social learning,” and it essentially means monkey see, monkey do, an adage that turns out to apply to many animals beyond just primates. Now, a study of Australia’s sulfur-crested cockatoos shows that the birds employ social learning to understand whether unfamiliar foods are safe to eat. In more forested areas of the cockatoos’ native range in Australia, New Guinea, and Indonesia, these mohawked parrots eat plant roots, seeds, fruits and insect larvae. But the birds have learned to thrive in urban environments. “They’re everywhere in Sydney,” said Julia Penndorf, a behavioral ecologist and lead author of the study in PLOS Biology, who encountered the birds as a postdoctoral researcher at the Australian National University in Canberra. In urban areas, the birds have expanded their diets to include nonnative plants and nuts, including almonds and sunflower seeds people offer to them, and they can be seen prying the lids off garbage bins in order to forage. “The big issue with urban birds is, they kind of eat everything,” Dr. Penndorf, who now works at the University of Exeter, said. This expanded diet is high-risk, high-reward: the birds have more options for food, but there’s always a chance that strange new snacks might be poisonous. © 2026 The New York Times Company

Keyword: Learning & Memory; Evolution
Link ID: 30229 - Posted: 05.02.2026

By Siddhant Pusdekar Transcriptional changes are essential for converting new experiences into memories but may not be required to make memories last, a new study suggests. The findings, published in eNeuro in March, conflict with a model proposing that positive feedback loops of transcription can help maintain long-term memories, says study investigator Irina Calin-Jageman, professor of biological sciences at Dominican University. But they open up a set of hypotheses about how transcription maintains long-term memories and indicate that the handful of genes whose regulation persists for up to two weeks could be “really key,” she adds. The results, obtained in the sea slug Aplysia californica, are “one small step on our way to understanding this very important question of: What is the role of transcription in forming long-term memories?” says Wayne Sossin, distinguished James McGill professor of neurology and neurosurgery at McGill University, who is listed as a reviewer for the paper. Disproving models doesn’t “get the attention it deserves, I think, from the scientific community,” he says, but science is built on overturning theory. Irina Calin-Jageman and her colleagues focused on the transcriptional traces of a partially faded memory in the sea slug. When the animal feels threatened, it retracts a breathing apparatus on its back called a siphon. After traumatic experiences—such as induced shocks—the slug retracts its siphon for longer than usual, previous work showed. Also, sensory neurons in the pleural ganglia change their gene expression patterns and remain more excitable for up to 24 hours, and synaptic changes can last for several days to weeks, depending on the training. © 2026 Simons Foundation

Keyword: Learning & Memory
Link ID: 30223 - Posted: 04.29.2026