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.

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 15: Emotions, Aggression, and Stress
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 11: Emotions, Aggression, and Stress
Link ID: 30319 - Posted: 07.11.2026

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

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 13: Memory and Learning
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

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 13: Memory and Learning
Link ID: 30287 - Posted: 06.20.2026

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

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 14: Attention and Higher Cognition
Link ID: 30259 - Posted: 05.27.2026

By Christina Caron Dr. Kyle Staller is a gastroenterologist, so it may be surprising that many of his patients come to him complaining not only about stomach trouble but about their brains, too. Irritable bowel syndrome and other digestive dysfunction can be accompanied by a mental haze. People experiencing constipation and bloating, for example, may describe “a sense of heaviness or being weighed down both physically and mentally,” said Dr. Staller, who works at Massachusetts General Hospital in Boston. “So many of my patients talk about problems like fatigue, brain fog and feeling sluggish,” he added. Scientists are making progress in understanding how the pathway between the brain and the digestive system influences our overall health. They call it the gut-brain axis, and it has been shown to play a big role in immune system support, anxiety, depression, metabolism and disease prevention. It can also affect mental clarity. We asked scientists and clinicians what to know about the gut and brain fog. How does the gut-brain axis work? There are thousands of fibers running from the brain to the abdomen that are known as the vagus nerve. It is a primary conduit of the gut-brain axis. And as the main nerve of the parasympathetic nervous system, it helps the body rest, digest and deter inflammation. Signals also travel back and forth between the gut and brain via stress hormones and immune cells. Crucially, gut bacteria produce chemical messengers (called neurotransmitters) like serotonin, dopamine and GABA that affect the nervous system. When they enter the bloodstream or stimulate the vagus nerve, they can help improve mood, drive motivation, and calm the nervous system. © 2026 The New York Times Company

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 13: Homeostasis: Active Regulation of the Internal Environment
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 9: Homeostasis: Active Regulation of the Internal Environment
Link ID: 30243 - Posted: 05.16.2026

By Kristen French What is a cat, and how do we know when we’ve encountered one? This question may be harder to answer than it seems. Neuroscientists Lisa Feldman Barrett and Earl Miller say people typically think about categories such as cat and apple backward—bottom-up instead of top-down. In reality, you don’t hear a meow, and see whiskers and paws and then conclude, “Cat!” Before any of this happens, your brain has sent signals about a “cat hypothesis”—and a plan for how to respond to a cat—to your body, based on past experience, Barrett and Miller say. This cat hypothesis, in turn, actively orchestrates what signals your body processes and how. In other words, the brain constructs classifications on the fly, and we’re not even conscious this is happening until after the fact. Barrett, a renowned Harvard neuroscientist and psychologist who has written for Nautilus and is best known for her theory of constructed emotion, teamed up with Miller to review “converging” evidence from a wide range of disciplines: neuroanatomy, electrophysiology, brain imaging, and cognitive science. The pair published their results recently in Nature Reviews: Neuroscience. Their new theory of categories has a lot in common with Barrett’s theory of how emotions work. She argues that emotions aren’t hardwired universal reactions, but are instead predictions constructed rapidly and in the moment from internal bodily sensations, past experiences, and cultural context. While her work on emotions has been highly influential, it remains an active subject of debate in the field of psychology. I spoke with Barrett and Miller about what they call “folk psychology,” and how their theory of categorization relates to so-called beginner’s mind, human bias, and objectivity and mental illness. We also talked about Nobel Laureate Daniel Kahneman’s modes of thinking fast and slow. © Copyright 2026

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 15: Emotions, Aggression, and Stress
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 11: Emotions, Aggression, and Stress
Link ID: 30226 - Posted: 05.02.2026

By Chand Chandrasekaran Decisions emerge from coordinated activity patterns across many brain areas. The challenge we face as neuroscientists is figuring out how. Technologies such as Neuropixels and optical imaging enable recordings from populations of neurons across many brain areas, leading to enormously impressive datasets with thousands of neurons. But making sense of these data to uncover the computations underlying decision-making has proved elusive. I think it is a great time for the field to design experiments that match the ambition of our tools. By designing decision-making tasks that vary along multiple dimensions and truly challenge our animals, we might finally understand how multiple brain areas coordinate to drive decisions. The starting point of most decision-making experiments is to get animals to perform a task for rewards, such as juice or food. It is often tempting to train the animal to do “something simple” because the training is easy and quick. Later we can get to the “exciting stuff”: Go in with a kitchen sink of experimental tools to collect neurophysiological data and/or perturb the system and use mathematical tools to uncover how activity in the brain leads to the behavior of interest. Though this approach sounds great in principle, analyzing the neural data associated with simple behavioral tasks can be challenging for multiple reasons. First, when the behavior is too simple, the brain does not need to compute much. When many areas could solve a problem, often they do: Relevant signals pop up all over the brain, leaving us with the somewhat puzzling conclusion that the behavior is global. But some tasks may be too trivial to require different computations from different areas, so it’s unsurprising that many areas look similar in such contexts. Second, animals perform simple tasks quickly, generating only a narrow window of neural activity from which to try to make sense of how they reached a decision. You might be left with just 50 milliseconds of potentially very noisy neural data from which to understand decision-related computations. © 2026 Simons Foundation

Related chapters from BN: Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 14: Attention and Higher Cognition
Link ID: 30211 - Posted: 04.22.2026

By Diana Kwon The ability to conjure pictures in the mind’s eye enables us to remember the past and imagine the future. It also allows us to plan, navigate and create works of art. In a study published April 9 in Science, researchers report that imagining an object reactivates some of the same neurons involved in seeing it in the first place, providing new insight into how mental imagery is produced in the brain. Previous research had hinted that the neurons involved in perceiving and imagining images overlapped. These studies used various methods, such as asking participants to view and then imagine pictures while lying in a functional MRI scanner, to show that the same brain regions were involved in these processes. But whether the same individual neurons were involved remained an open question, says Ueli Rutishauser, a neuroscientist at Cedars-Sinai Medical Center in Los Angeles. Because measuring neuronal activity requires electrodes in the brain, Rutishauser and colleagues studied 16 adults with epilepsy who had already had electrodes temporarily implanted into their brains to identify the origin of their seizures. Participants viewed hundreds of images from five categories — faces, text, plants, animals and everyday objects — while researchers recorded activity from over 700 neurons in the ventral temporal cortex, a region involved in representing visual objects. Of those, about 450 selectively responded to individual categories. Machine learning then revealed that 80 percent of those category-responsive neurons were selective to specific visual features within the images. © Society for Science & the Public 2000–2026.

Related chapters from BN: Chapter 10: Vision: From Eye to Brain; Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 7: Vision: From Eye to Brain; Chapter 14: Attention and Higher Cognition
Link ID: 30195 - Posted: 04.11.2026

By Mac Shine The brain is arguably the most complex object in the known universe, and neuroscience—the discipline charged with understanding it—has grown to match that complexity. Today, the field spans everything from the molecular choreography of a single synapse to the large-scale network dynamics that give rise to conscious experience. It is simultaneously one of the most exciting and most disorienting fields to work in. The conceptual map that connects our different subfields hasn’t been written yet. But a new study published in Aperture Neuro in February takes a remarkable step toward drawing that map. Led by Mario Senden, a computational neuroscientist at Maastricht University, the work applies state-of-the-art text embedding and community detection algorithms to nearly half a million neuroscience abstracts published between 1999 and 2023. It carves the literature into 175 distinct research clusters, characterizing each one along dimensions ranging from spatial scale to theoretical orientation. What emerges is a portrait of a discipline that is, in many ways, healthier than it might appear from the inside. Despite its staggering diversity—clusters range from AMPA receptor trafficking to the neural underpinnings of consciousness—the field is remarkably well integrated; the vast majority of research communities actively draw on and feed into one another. The cluster of resting-state functional MRI dynamics and the molecular mechanisms of hippocampal plasticity emerge as some of the field’s great intellectual hubs, providing conceptual and methodological scaffolding for dozens of downstream communities. But the map also has its fault lines. Microscale and macroscale research communities operate in two largely separate epistemic worlds, divided by spatial scale and by the training trajectories that produce different kinds of neuroscientists. Temporal scales are integrated only pairwise, never holistically. And perhaps most provocatively: Not a single cluster in the entire 175-cluster solution is organized around a theoretical framework. The Bayesian brain, the free energy principle and predictive coding are common targets of empirical science, yet none of them anchor their own research community. Theory, it seems, is something neuroscience does around the edges of the phenomena it is really interested in. © 2026 Simons Foundation

Related chapters from BN: Chapter 1: Introduction: Scope and Outlook; Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 1: Cells and Structures: The Anatomy of the Nervous System; Chapter 14: Attention and Higher Cognition
Link ID: 30192 - Posted: 04.08.2026

Carlo Iacono Everyone is panicking about the death of reading. The statistics look damning: the share of Americans who read for pleasure on an average day has fallen by more than 40 per cent over the past 20 years, according to research published in iScience this year. The OECD calls the 2022 decline in educational outcomes ‘unprecedented’ across developed nations. In the OECD’s latest adult-skills survey, Denmark and Finland were the only participating countries where average literacy proficiency improved over the past decade. Your nephew speaks in TikTok references. Democracy itself apparently hangs by the thread of our collective attention span. This narrative has a seductive simplicity. Screens are destroying civilisation. Children can no longer think. We are witnessing the twilight of the literate mind. A recent Substack essay by James Marriott proclaimed the arrival of a ‘post-literate society’ and invited us to accept this as a fait accompli. (Marriott does also write for The Times.) The diagnosis is familiar: technology has fundamentally degraded our capacity for sustained thought, and there’s nothing to be done except write elegiac essays from a comfortable distance. I spend my working life in a university library, watching how people actually engage with information. What I observe doesn’t match this narrative. Not because the problems aren’t real, but because the diagnosis is wrong. The declinist position rests on a category error: treating ‘screen culture’ as a unified phenomenon with inherent cognitive properties. As if the same device that delivers algorithmically curated rage-bait and also the complete works of Shakespeare is itself the problem rather than how we decide to use it. © Aeon Media Group Ltd. 2012-2026.

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 19: Language and Lateralization
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 15: Language and Lateralization
Link ID: 30132 - Posted: 02.21.2026

Elizabeth Quill Think about your breakfast this morning. Can you imagine the pattern on your coffee mug? The sheen of the jam on your half-eaten toast? Most of us can call up such pictures in our minds. We can visualize the past and summon images of the future. But for an estimated 4% of people, this mental imagery is weak or absent. When researchers ask them to imagine something familiar, they might have a concept of what it is, and words and associations might come to mind, but they describe their mind’s eye as dark or even blank. Systems neuroscientist Mac Shine at the University of Sydney, Australia, first realized that his mental experience differed in this way in 2013. He and his colleagues were trying to understand how certain types of hallucination come about1, and were discussing the vividness of mental imagery. “When I close my eyes, there’s absolutely nothing there,” Shine recalls telling his colleagues. They immediately asked him what he was talking about. “Whoa. What’s going on?” Shine thought. Neither he nor his colleagues had realized how much variation there is in the experiences people have when they close their eyes. This moment of revelation is common to many people who don’t form mental images. They report that they might never have thought about this aspect of their inner life if not for a chance conversation, a high-school psychology class or an article they stumbled across (see ‘How do you imagine?’). Although scientists have known for more than a century that mental imagery varies between people, the topic received a surge of attention when, a decade ago, an influential paper coined the term aphantasia to describe the experience of people with no mental imagery2. © 2026 Springer Nature Limited

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 10: Vision: From Eye to Brain
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 7: Vision: From Eye to Brain
Link ID: 30107 - Posted: 02.04.2026

By Amy X. Wang Alice, fumbling through Wonderland, comes across a mushroom. One bite of it shrinks her down in size. Chowing on the other side makes her swell up, huge, taller than the treetops. Urgently, Alice sets to work “nibbling first at one and then at the other, and growing sometimes taller and sometimes shorter,” until finally she succeeds in “bringing herself down to her usual height” — whereupon everything feels “quite strange.” Is this Lewis Carroll’s 1865 fantasy tale or … the average body-conscious, improvement-obsessed 2026 Whole Foods shopper? Mushrooms, long venerated in literature as dark transformative forces, have become Goopified. Nowadays, you can chug “adaptogenic mushroom coffee,” slurp “functional mushroom cocoa,” doze off with “mushroom sleep drops” or ingest/imbibe any number of other tinctures in the billion-dollar fungal supplements market that promise to fine-tune, or even totally recalibrate, the self. The latest and hottest items in this booming new retail category are mushroom gummies, gushed over by wellness influencers, spilling out from supermarket shelves right there next to your standard cough drops and protein bars. Fungi have aided medical advances like antibiotics and statins, it’s true, and certain species have shown promising results in fighting Parkinson’s or cancer — but what these pastel gumdrops proffer is a broader, more elliptical “cellular well-being.” The mystique feels intentional on product-makers’ part: Like Carroll’s baffled heroine, maybe you’re meant to be in a bit of thrall to the mysterious, almighty mushroom — lurching through Wonderland, charmed and confused by design. After all, you wonder, what are these ancient, alien creatures, growing in the secret dark? Hippocrates was supposedly using them to cauterize wounds around the 5th century B.C.E. In the Super Mario video games, mushrooms might give you extra lives; in HBO’s “The Last of Us,” they bring about the ruin of human civilization. © 2026 The New York Times Company

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 4: The Chemistry of Behavior: Neurotransmitters and Neuropharmacology
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 4: Development of the Brain
Link ID: 30102 - Posted: 01.31.2026

By Pria Anand I loved literature before I loved medicine, and as a medical student, I often found that my textbooks left me cold, their medical jargon somehow missing the point of profound diseases able to rewrite a person’s life and identity. I was born, I decided, a century too late: I found the stories I craved, not in contemporary textbooks, but in outdated case reports, 18th- and 19-century descriptions of how the diseases I was studying might shape the life of a single patient. These reports were alive with vivid details: how someone’s vision loss affected their golf game or their smoking habit, their work or their love life. They were all tragedies: Each ended with an autopsy, a patient’s brain dissected to discover where, exactly, the problem lay, to inch closer to an understanding of the geography of the soul. To write these case studies, neurologists awaited the deaths and brains of living patients, robbing their subjects of the ability to choose what would become of their own bodies—the ability to write the endings of their own stories—after they had already been sapped of agency by their illnesses. Among these case reports was one from a forbidding state hospital in the north of Moscow: the story of a 19th-century Russian journalist referred to simply as “a learned man.” The journalist suffered a type of alcoholic dementia because of the brandy he often drank to cure his writer’s block and he developed a profound amnesia. He could not remember where he was or why. He could win a game of checkers but would forget that he had even played the minute the game ended. In the place of these lost memories, the journalist’s imagination spun elaborate narratives; he believed he had written an article when in fact he had barely begun to conceive it before he became sick, would describe the prior day’s visit to a far-off place when in actuality he had been too weak to get out of bed, and maintained that some of his possessions—kept in a hospital safe—had been taken from him as part of an elaborate heist. Sacks’ journals suggest he injected his own experiences into the stories of his patients. © 2026 NautilusNext Inc.,

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 14: Attention and Higher Cognition
Link ID: 30089 - Posted: 01.21.2026

By Claudia López Lloreda A new commentary calls into question a 2024 paper that described a universal pattern of cortical brain oscillations. But that team has provided a more expansive analysis in response and stands by its original conclusions. Both articles were published today in “Matters Arising” in Nature Neuroscience. Ultimately, the back-and-forth suggests that a frequency “motif” may exist, but it may not be as general as the original study proposed, says Aitor Morales-Gregorio, a postdoctoral researcher at Charles University, who was not involved with any of the work. “The [2024] conclusions are way too optimistic about how general and how universal this principle might be.” The 2024 study identified a brain-wave motif in 14 cortical areas in macaques: Alpha and beta rhythms predominated in the deeper layers, whereas gamma bands appeared in the more superficial layers. Because this motif also showed up in marmosets and humans, the researchers speculated that it may be a universal mechanism for cortical computation in primates. “Results typically come with a level of variability, of noise, of uncertainty,” says 2024 study investigator Diego Mendoza-Halliday, assistant professor of neuroscience at the University of Pittsburgh. But this pattern “was just there the whole time, at all times, in many, many of the recordings.” The team leveraged the findings to create an algorithm that detects Layer 4 of the cortex. But the pattern is “by no means universal,” according to the new commentary, which found the motif in about 60 percent of the recordings in an independent monkey dataset. Further, the algorithm trained to identify Layer 4 of the cortex is unreliable, the commentary shows. © 2025 Simons Foundation

Related chapters from BN: Chapter 3: Neurophysiology: The Generation, Transmission, and Integration of Neural Signals; Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 3: The Chemistry of Behavior: Neurotransmitters and Neuropharmacology; Chapter 14: Attention and Higher Cognition
Link ID: 30044 - Posted: 12.13.2025

By Nora Bradford Here are three words: pine, crab, sauce. There’s a fourth word that combines with each of the others to create another common word. What is it? When the answer finally comes to you, it’ll likely feel instantaneous. You might even say “Aha!” This kind of sudden realization is known as insight, and a research team recently uncovered how the brain produces it (opens a new tab), which suggests why insightful ideas tend to stick in our memory. Maxi Becker (opens a new tab), a cognitive neuroscientist at Duke University, first got interested in insight after reading the landmark 1962 book The Structure of Scientific Revolutions (opens a new tab) by the historian and philosopher of science Thomas Kuhn. “He describes how some ideas are so powerful that they can completely shift the way an entire field thinks,” she said. “That got me wondering: How does the brain come up with those kinds of ideas? How can a single thought change how we see the world?” Such moments of insight are written across history. According to the Roman architect and engineer Vitruvius, in the third century BCE the Greek mathematician Archimedes suddenly exclaimed “Eureka!” after he slid into a bathtub and saw the water level rise by an amount equal to his submerged volume (although this tale may be apocryphal (opens a new tab)). In the 17th century, according to lore, Sir Isaac Newton had a breakthrough in understanding gravity after an apple fell on his head. In the early 1900s, Einstein came to a sudden realization that “if a man falls freely, he would not feel his weight,” which led him to his theory of relativity, as he later described in a lecture. Insights are not limited to geniuses: We have these cognitive experiences all the time when solving riddles or dealing with social or intellectual problems. They are distinct from analytical problem-solving, such as the process of doing formulaic algebra, in which you arrive at a solution slowly and gradually as if you’re getting warmer. Instead, insights often follow periods of confusion. You never feel as if you’re getting warmer; rather, you go from cold to hot, seemingly in an instant. Or, as the neuropsychologist Donald Hebb, known for his work building neurobiological models of learning, wrote in the 1940s, sometimes “learning occurs as a single jump, an all-or-none affair.” © 2025 Simons Foundation

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 13: Memory and Learning
Link ID: 30004 - Posted: 11.08.2025

By Claudia López Lloreda The process of making a decision engages neurons across the entire brain, according to a new mouse dataset created by an international collaboration. “Many, many areas are recruited even for what are arguably rather simple decisions,” says Anne Churchland, professor of neurobiology at University of California, Los Angeles and one of the founding members of the collaboration, called the International Brain Laboratory (IBL). The canonical model suggests that the activity underlying vision-dependent decisions goes from the visual thalamus to the primary visual cortex and association areas, and then possibly to the frontal cortex, Churchland says. But the new findings suggest that “maybe there’s more parallel processing and less of a straightforward circuit than we thought.” Churchland and other scientists established the IBL in 2017 out of frustration with small-scale studies of decision-making that analyzed only one or two brain regions at a time. The IBL aimed to study how the brain integrates information and makes a decision at scale. “We came together as a large group with the realization that a large team effort could be transformative in these questions that had been kind of stymieing all of us,” Churchland says. After years of standardizing their methods and instrumentation across the 12 participating labs, the IBL team constructed a brain-wide map of neural activity in mice as they complete a decision-making task. That map, published today in Nature, reveals that the activity associated with choices and motor actions shows up widely across the brain. The same is true for the activity underlying decisions based on prior knowledge, according to a companion paper by the same team, also published today in Nature. © 2025 Simons Foundation

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 2: Functional Neuroanatomy: The Cells and Structure of the Nervous System
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 2: Neurophysiology: The Generation, Transmission, and Integration of Neural Signals
Link ID: 29918 - Posted: 09.06.2025

By Dan Falk I’ve been fascinated by time for as long as I can remember. In my undergraduate physics classes, time always lurked in the background—it was the “t” that the professors sprinkled into their equations—but it was never quite clear what time actually was. Years later, I wrote a book about time, but even with chapters on Newton and Einstein, and a solid dose of philosophy, something was missing. Nautilus Members enjoy an ad-free experience. Log in or Join now . For starters, we know clocks and watches work, but how do we tell time? If you’re watching network TV and a commercial break begins, you know you have time to use the bathroom or perhaps make a sandwich—in fact, you can probably arrange to be back in front of the TV just as the ads are ending. What makes you so good at judging these intervals of time? I figured that Dean Buonomano, being a neuroscientist, might have some of the answers. Buonomano is known for developing the idea that the key mechanism is not a single clock-like structure in the brain but rather networks of neurons working together, known as “neural dynamics.” But as Buonomano sees it, the brain does much more than keep track of time; in fact, it might be said to create it. It’s thanks to our brains that we feel time’s “flow,” even though nothing in physics points to such a flow out there in the world. Perhaps even more crucially, the brain allows us to engage in “mental time travel”—the ability to recall past events and imagine future happenings. This capability, he argues, was essential in shaping humanity’s path from the African savannah to today’s globe-spanning civilization. © 2025 NautilusNext Inc.,

Related chapters from BN: Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 14: Attention and Higher Cognition
Link ID: 29851 - Posted: 07.12.2025

Humberto Basilio Mindia Wichert has taken part in plenty of brain experiments as a cognitive-neuroscience graduate student at the Humboldt University of Berlin, but none was as challenging as one he faced in 2023. Inside a stark white room, he stared at a flickering screen that flashed a different image every 10 seconds. His task was to determine what familiar object appeared in each image. But, at least at first, the images looked like nothing more than a jumble of black and white patches. “I’m very competitive with myself,” says Wichert. “I felt really frustrated.” Cognitive neuroscientist Maxi Becker, now at Duke University in Durham, North Carolina, chose the images in an attempt to spark a fleeting mental phenomenon that people often experience but can’t control or fully explain. Study participants puzzling out what is depicted in the images — known as Mooney images, after a researcher who published a set of them in the 1950s1 — can’t rely on analytical thinking. Instead, the answer must arrive all at once, like a flash of lightning in the dark (take Nature’s Mooney-images quiz below). Becker asked some of the participants to view the images while lying inside a functional magnetic resonance imaging (fMRI) scanner, so she could track tiny shifts in blood flow corresponding to brain activity. She hoped to determine which regions produce ‘aha!’ moments. Over the past two decades, scientists studying such moments of insight — also known as eureka moments — have used the tools of neuroscience to reveal which regions of the brain are active and how they interact when discovery strikes. They’ve refined the puzzles they use to trigger insight and the measurements they take, in an attempt to turn a self-reported, subjective experience into something that can be documented and rigorously studied. This foundational work has led to new questions, including why some people are more insightful than others, what mental states could encourage insight and how insight might boost memory. © 2025 Springer Nature Limited

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 13: Memory and Learning
Link ID: 29844 - Posted: 06.28.2025

Myrian Wares for Quanta Magazine You’ve just gotten home from an exhausting day. All you want to do is put your feet up and zone out to whatever is on television. Though the inactivity may feel like a well-earned rest, your brain is not just chilling. In fact, it is using nearly as much energy as it did during your stressful activity, according to recent research. Sharna Jamadar (opens a new tab), a neuroscientist at Monash University in Australia, and her colleagues reviewed research from her lab and others around the world to estimate the metabolic cost of cognition (opens a new tab) — that is, how much energy it takes to power the human brain. Surprisingly, they concluded that effortful, goal-directed tasks use only 5% more energy than restful brain activity. In other words, we use our brain just a small fraction more when engaging in focused cognition than when the engine is idling. It often feels as though we allocate our mental energy through strenuous attention and focus. But the new research builds on a growing understanding that the majority of the brain’s function goes to maintenance. While many neuroscientists have historically focused on active, outward cognition, such as attention, problem-solving, working memory and decision-making, it’s becoming clear that beneath the surface, our background processing is a hidden hive of activity. Our brains regulate our bodies’ key physiological systems, allocating resources where they’re needed as we consciously and subconsciously react to the demands of our ever-changing environments. “There is this sentiment that the brain is for thinking,” said Jordan Theriault (opens a new tab), a neuroscientist at Northeastern University who was not involved in the new analysis. “Where, metabolically, [the brain’s function is] mostly spent on managing your body, regulating and coordinating between organs, managing this expensive system which it’s attached to, and navigating a complicated external environment.” © 2025 Simons Foundation.

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 13: Homeostasis: Active Regulation of the Internal Environment
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 9: Homeostasis: Active Regulation of the Internal Environment
Link ID: 29825 - Posted: 06.07.2025

Nicola Davis Science correspondent Whether it is doing sums or working out what to text your new date, some tasks produce a furrowed brow. Now scientists say they have come up with a device to monitor such effort: an electronic tattoo, stuck to the forehead. The researchers say the device could prove valuable among pilots, healthcare workers and other professions where managing mental workload is crucial to preventing catastrophes. “For this kind of high-demand and high-stake scenario, eventually we hope to have this real-time mental workload decoder that can give people some warning and alert so that they can self-adjust, or they can ask AI or a co-worker to offload some of their work,” said Dr Nanshu Lu, an author of the research from the University of Texas at Austin, adding the device may not only help workers avoid serious mistakes but also protect their health. Writing in the journal Device, Lu and colleagues describe how using questionnaires to investigate mental workload is problematic, not least as people are poor at objectively judging cognitive effort and they are usually conducted after a task. Meanwhile, existing electroencephalography (EEG) and electrooculography (EOG) devices, that can be used to assess mental workload by measuring brain waves and eye movements respectively, are wired, bulky and prone to erroneous measurements arising from movements. By contrast, the “e-tattoo” is a lightweight, flexible, wireless device. © 2025 Guardian News & Media Limited

Related chapters from BN: Chapter 18: Attention and Higher Cognition; Chapter 15: Emotions, Aggression, and Stress
Related chapters from MM:Chapter 14: Attention and Higher Cognition; Chapter 11: Emotions, Aggression, and Stress
Link ID: 29815 - Posted: 05.31.2025