By Yasemin Saplakoglu Every experience we have changes our brain, the way a ceramicist reshapes a slab of clay. Every corner we turn, every conversation we have, every shudder we feel causes cascading effects: Chemicals are released, electricity surges, the connections between brain cells tighten, and our mental models update. The brain is “incredibly plastic, and it stays that way throughout the lifespan of a human,” said Christine Grienberger (opens a new tab), a neuroscientist at Brandeis University. This plasticity, the quality of being easily reshaped, makes the brain really good at learning — a quintessential process that allows us to remember the plotline of a novel, navigate a new city, pick up a new language, and avoid touching a hot stove. But neuroscientists are still uncovering fundamental rules that describe how neuroplasticity reshapes brain connections. Recently, neuroscientists described a new form of neuroplasticity that might be helping the brain learn across a timescale of several seconds — long enough to capture the behavioral process of learning from a single experience. In two recent reviews, published in The Journal of Neuroscience (opens a new tab) and Nature Neuroscience (opens a new tab), they describe “behavioral timescale synaptic plasticity,” or BTSP. This type of learning in the hippocampus, the brain’s memory hub, is caused by an electrical change that affects multiple neurons at once and unfolds across several seconds. Researchers suspect that it may help the brain learn in a single attempt. “It’s pretty clear that [BTSP is] a strong, powerful mechanism that can lead to immediate memory formation,” said Daniel Dombeck, a neuroscientist at Northwestern University who was not involved with the theory’s development. “It’s something that has been missing in the field for a long time.” © 2026 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 30219 - Posted: 04.26.2026

By Angie Voyles Askham The idea that some neural representations can “drift,” or change over time, even in the seeming absence of learning, is broadly accepted. But characterizing the phenomenon across the brain has proved challenging. “The interesting part is what exactly seems to be stable and what exactly seems to be drifting. That’s not an easy question,” says Tobias Rose, a group leader at the University of Bonn Medical Center, who presented findings on drift in the mouse primary visual cortex earlier this month at the Computational and Systems Neuroscience (COSYNE) annual meeting. Other new research adds nuance to the discussion: Neurons that code for head direction in the mouse post-subiculum show little drift, retaining their tuning for multiple weeks, according to a study published last month in Nature. And they differ from hippocampal place cells, which are also part of the spatial navigation system but have highly variable responses, as reported in previous research. The new findings raise questions about how stable and flexible representations interact in the brain, given that signals from the post-subiculum ultimately feed into the hippocampus, says Rose, who was not involved in the work. “It’s a rather important study,” he says. The relative stability of head direction cell tuning does not invalidate previous reports of drift elsewhere in the brain, says Adrien Peyrache, associate professor at the Montreal Neurological Institute, who led the head direction study. Instead, it may be that these invariant responses act as a “rigid backbone” onto which more flexible sensory and cognitive responses can be mapped, he says. “I find it reassuring.” Still, the low drift reported in the new work may be partially due to the study’s methods, which eliminated cells that lost their response from one day to the next, says Timothy O’Leary, professor of information engineering and neuroscience at the University of Cambridge, who was not involved in the work. © 2026 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 30181 - Posted: 03.28.2026

David Adam When neuroscientists gather in the Spanish city of Seville in May for the annual Dopamine Society meeting, one discussion could be unusually lively. Session 31 will feature a debate between researchers who fundamentally disagree about the role dopamine has in the brain. Dopamine is one of the most extensively studied neurotransmitters, chemicals that convey signals from cell to cell. It’s the one with the highest profile outside neuroscience: often known as the ‘pleasure chemical’, it’s depicted as the hit of reward that people get from recreational drugs or scrolling through social media. That’s a gross simplification of what dopamine does; on that, researchers agree. But beyond that, where once there was a simple model that explained how dopamine works in the brain, now there are challenges that seek to amend the theory — or even to overturn it. This could have implications not only for basic neuroscience, but also for clinicians trying to explain and treat conditions such as attention deficit hyperactivity disorder (ADHD) and addiction. If the model is wrong or needs modification, then so might some of the assumptions about what drives these disorders and the best way to treat them. The classic idea, known as the reward prediction error (RPE) hypothesis, is that bursts of dopamine in the brain link stimuli to rewards, helping to reinforce associations that fulfil a need for an animal or a person. The model has dominated and guided research in the field for decades, offering a mathematical framework to interpret data from animal experiments, and it does a good job of explaining behaviour. This was a valuable rarity for researchers struggling to overlay simple theories onto the intense complexity of the brain. “Dopamine was the one field of neuroscience where we had a computational model that explained what the signal was and what it was computing,” says Mark Humphries, a neuroscientist at the University of Nottingham, UK. People in the field knew that some of the assumptions involved in the RPE model were simplistic. But as a working understanding of part of the brain, it was seen as a major step forwards. © 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: 30166 - Posted: 03.19.2026

By Catherine Offord Scientists have plenty of ideas about why aging impairs memory. Reductions in blood flow in the brain, shrinking brain volume, and malfunctioning neural repair systems have all been blamed. Now, new research in mice points to another possible culprit: microbes in the gut. In a study published today in Nature, scientists show how a bacterium that is particularly common in older animals can drive memory loss. This microbe makes compounds that impair signaling along neurons connecting the gut with the brain, dampening activity in brain regions associated with learning and memory, the team found. “This is a tour de force,” says Haijiang Cai, a neuroscientist at the University of Arizona who studies gut-brain communication and was not involved in the work. “They define the pathway all the way from aging and bacteria … to cognitive function—it’s really impressive.” However, he and others emphasize it remains to be seen whether a similar mechanism exists in humans—and if so, how important it is compared with other drivers of cognitive decline. Research on the so-called gut-brain axis has exploded in recent decades. Multiple studies have identified differences in microbiome composition between healthy people and those with cognitive disorders such as Alzheimer’s disease. This kind of research can’t establish cause and effect, though, and the literature is rife with conflicting results. Some groups have used animal experiments to probe the microbe-memory link. In the new study, Stanford University researchers Christoph Thaiss and Maayan Levy tinkered with the microbiomes of young mice—either by housing them with older animals or feeding them these animals’ poop—and then gave them memory tests. For example, one such test rates animals higher if they spend more time exploring new objects than those they’ve seen before. © 2026 American Association for the Advancement of Science.

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 13: Homeostasis: Active Regulation of the Internal Environment
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 9: Homeostasis: Active Regulation of the Internal Environment
Link ID: 30162 - Posted: 03.14.2026

By Catherine Offord Scientists have plenty of ideas about why aging impairs memory. Reductions in blood flow in the brain, shrinking brain volume, and malfunctioning neural repair systems have all been blamed. Now, new research in mice points to another possible culprit: microbes in the gut. In a study published today in Nature, scientists show how a bacterium that is particularly common in older animals can drive memory loss. This microbe makes compounds that impair signaling along neurons connecting the gut with the brain, dampening activity in brain regions associated with learning and memory, the team found. “This is a tour de force,” says Haijiang Cai, a neuroscientist at the University of Arizona who studies gut-brain communication and was not involved in the work. “They define the pathway all the way from aging and bacteria … to cognitive function—it’s really impressive.” However, he and others emphasize it remains to be seen whether a similar mechanism exists in humans—and if so, how important it is compared with other drivers of cognitive decline. Research on the so-called gut-brain axis has exploded in recent decades. Multiple studies have identified differences in microbiome composition between healthy people and those with cognitive disorders such as Alzheimer’s disease. This kind of research can’t establish cause and effect, though, and the literature is rife with conflicting results. Some groups have used animal experiments to probe the microbe-memory link. In the new study, Stanford University researchers Christoph Thaiss and Maayan Levy tinkered with the microbiomes of young mice—either by housing them with older animals or feeding them these animals’ poop—and then gave them memory tests. For example, one such test rates animals higher if they spend more time exploring new objects than those they’ve seen before. © 2026 American Association for the Advancement of Science.

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 13: Homeostasis: Active Regulation of the Internal Environment
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 9: Homeostasis: Active Regulation of the Internal Environment
Link ID: 30161 - Posted: 03.14.2026

By Natalia Mesa Experience kindles most of our learning throughout life, without any explicit instruction or reward. Thanks to this process, called statistical learning, people unconsciously recognize patterns in their surroundings, and infants soak up language. The hippocampus, it turns out, may be essential for this capability, according to a new preprint, beginning to resolve a long-standing debate. Numerous functional MRI studies have suggested that the structure is involved in statistical learning, but lesion studies have produced mixed results. “This is a tour-de-force study,” says Anna Schapiro, associate professor of psychology at the University of Pennsylvania, who was not involved in the work. “It makes me feel more confident that, yes, the hippocampus is involved in statistical learning, but it’s also necessary for that learning across species.” In the study, people and mice learned to respond—by pressing a key or licking a waterspout, respectively—to a particular sound. As they performed this “cover” task, they also heard an irrelevant four-note sequence at random times, interspersed with the other sound. After repeating this cover task 100 times, both people and rodents showed strong pupil dilation, a sign of surprise, whenever the sequence of notes changed slightly, with more similar sequences evoking a smaller response—indicating that they had passively learned the original musical motif and abstract rules about its structure. Neuronal populations in the hippocampus encoded not only the original and altered tone sequences but also how frequently each occurred. Pharmacologically or optogenetically shutting down hippocampal neurons in the mice prevented them from passively learning the auditory pattern and making generalizations about how often it played, but it didn’t disrupt their performance on the cover task. © 2026 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 30154 - Posted: 03.11.2026

By Jake Currie Struggling to remember a forgotten memory is an all-too-common frustration—one that unfortunately becomes more common as we age. We realize that there’s something we can’t recall, but we simply can’t raise it from the depths of our brains. So where did it go? New research published in the Journal of Neuroscience suggests these memories are still lurking in our minds, even though we think they’re long gone. Subscribe to skip ads Featured Video Psychologists from the University of Nottingham led by Benjamin Griffiths strapped participants into a magnetoencephalography machine to measure the magnetic fields surrounding the electrical activity in their brains. Participants were asked to vividly associate a short video clip with a word, and when they were later shown that word, they were asked to recall the video clip while psychologists monitored the magnetic activity of their brains. They found that the brain reactivated memories whether they were consciously recalled or not, meaning the memories were there. When memories were successfully recalled, the reactivated memory signal fluctuated rhythmically in the alpha band. Alpha brain waves, research has shown, are associated with the memorization of visual information, but it was the rhythmicity of the waves that proved key to conscious recall. “What we showed is that even when the brain can reactivate the right memory, it doesn’t guarantee you’ll become aware of it,” Griffiths explained. “Instead, what seems to matter is that the memory rhythmically pulses so that it can be detected above and beyond other neural activity.”

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 2: Functional Neuroanatomy: The Cells and Structure of the Nervous System
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 2: Neurophysiology: The Generation, Transmission, and Integration of Neural Signals
Link ID: 30151 - Posted: 03.07.2026

By Justin O’Hare For decades, two complementary but often siloed approaches have guided neuroscience: cellular neuroscience, which seeks to understand how individual neurons work; and systems neuroscience, which aims to uncover how networks of neurons coordinate to produce thoughts, movements and behaviors. One studies the tree; the other studies the forest. Each approach has produced tremendous advances. For instance, cellular neuroscientists have revealed how ion channels shape the electrical language of the brain, how synapses strengthen or weaken with experience and how gene expression governs neuronal function. Meanwhile, systems neuroscientists have mapped entire circuits, recorded the activity of tens of thousands of neurons during behavior and identified patterns of activity that correlate with memory, decision-making and emotion. But for all these advances, a question lingers: Are we actually any closer to understanding how the brain works? The jaw-dropping datasets produced by systems-level studies are seldom reconciled with biology, and the exquisite detail uncovered by cellular-level studies is rarely extrapolated from circuits to behavior. These disconnects don’t reflect failures of either approach. Rather, they reflect the vast intellectual and material resources that each requires. Nevertheless, the brain is a multiscale organ. It is organized across multiple hierarchical levels operating in concert, not in parallel. To unravel the brain’s deepest complexities, we need to bridge cellular and systems neuroscience. Because of recent technological advances in high-density electrical probes, genetically encoded fluorescent sensors, multiphoton imaging and high-performance computing, we are better suited to do this now than ever before. © 2026 Simons Foundation

Related chapters from BN: Chapter 2: Functional Neuroanatomy: The Cells and Structure of the Nervous System; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 2: Neurophysiology: The Generation, Transmission, and Integration of Neural Signals; Chapter 13: Memory and Learning
Link ID: 30140 - Posted: 02.28.2026

Peter Lukacs Popular wisdom holds we can ‘rewire’ our brains: after a stroke, after trauma, after learning a new skill, even with 10 minutes a day on the right app. The phrase is everywhere, offering something most of us want to believe: that when the brain suffers an assault, it can be restored with mechanical precision. But ‘rewiring’ is a risky metaphor. It borrows its confidence from engineering, where a faulty system can be repaired by swapping out the right component; it also smuggles that confidence into biology, where change is slower, messier and often incomplete. The phrase has become a cultural mantra that is easier to comprehend than the scientific term, neuroplasticity – the brain’s ability to change and form new neural connections throughout life. But what does it really mean to ‘rewire’ the brain? Is it a helpful shorthand for describing the remarkable plasticity of our nervous system or has it become a misleading oversimplification that distorts our grasp of science? After all, ‘rewiring your brain’ sounds like more than metaphor. It implies an engineering project: a system whose parts can be removed, replaced and optimised. The promise is both alluring and oddly mechanical. The metaphor actually did come from engineering. To an engineer, rewiring means replacing old and faulty circuits with new ones. As the vocabulary of technology crept into everyday life, it brought with it a new way of thinking about the human mind. Medical roots of the phrase trace back to 1912, when the British surgeon W Deane Butcher compared the body’s neural system to a house’s electrical wiring, describing how nerves connect to muscles much like wires connect appliances to a power source. By the 1920s, the Harvard psychologist Leonard Troland was referring to the visual system as ‘an extremely intricate telegraphic system’, reinforcing the comparison between brain function and electrical networks. © Aeon Media Group Ltd. 2012-2026.

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 7: Life-Span Development of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 13: Memory and Learning
Link ID: 30108 - Posted: 02.04.2026

By Yasemin Saplakoglu On a remote island in the Indian Ocean, six closely watched bats took to the star-draped skies. As they flew across the seven-acre speck of land, devices implanted in their brains pinged data back to a group of sleepy-eyed neuroscientists monitoring them from below. The researchers were working to understand how these flying mammals, who have brains not unlike our own, develop a sense of direction while navigating a new environment. The research, published in Science, reported that the bats used a network of brain cells (opens a new tab) that informed their sense of direction around the island. Their “internal compass” was tuned by neither the Earth’s magnetic field nor the stars in the sky, but rather by landmarks that informed a mental map of the animal’s environment. These first-ever wild experiments in mammalian mapmaking confirm decades of lab results and support one of two competing theories about how an internal neural compass anchors itself to the environment. “Now we’re understanding a basic principle about how the mammalian brain works” under natural, real-world conditions, said the behavioral neuroscientist Paul Dudchenko (opens a new tab), who studies spatial navigation at the University of Stirling in the United Kingdom and was not involved in the study. “It will be a paper people will be talking about for 50 years.” Follow-up experiments that haven’t yet been published show that other cells critical to navigation encode much more information in the wild than they do in the lab, emphasizing the need to test neurobiological theories in the real world. Neuroscientists believe that a similar internal compass, composed of neurons known as “head direction cells,” might also exist in the human brain — though they haven’t yet been located. If they are someday found, the mechanism could shed light on common sensations such as getting “turned around” and quickly reorienting oneself. It might even explain why some of us are so bad at finding our way. © 2026 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 30094 - Posted: 01.24.2026

By Erin Garcia de Jesús A deck brush can be a good tool for the right task. Just ask Veronika, the Brown Swiss cow. Veronika uses both ends of a deck brush to scratch various parts of her body, researchers report January 19 in Current Biology. It’s the first reported tool use in a cow, a species that is often “cognitively underestimated,” the researchers say. Cows usually rub against trees, rocks or wooden planks to scratch, but Veronika’s handy tool allows her to reach parts of her body that she couldn’t otherwise, says Antonio Osuna-Mascaró, a cognitive biologist at the Messerli Research Institute of the University of Veterinary Medicine, Vienna. It’s unclear how the cow figured it out, but “somehow Veronika learned to use tools, and she’s doing something that other cows simply can’t.” Veronika, a pet cow that lives in a pasture on a small Austrian farm, picks up the brush by its handle with her tongue and twists her neck to place the brush where she needs it. Setting the brush in front of her in different orientations showed that she uses the hard, bristled end to target most areas, including the tough, thick skin on her back. She also uses the nonbristled end, slowly moving the handle over softer body parts such as her belly button and udder. Veronika uses different parts of a deck brush to reach various parts of her body. She uses the brush end to scratch large areas such as her thigh (top left) and back (top right). She uses the handle to scratch more delicate areas such as her navel flap (bottom left) and anus (bottom right). © Society for Science & the Public 2000–2026.

Related chapters from BN: Chapter 6: Evolution of the Brain and Behavior; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 30088 - Posted: 01.21.2026

Lynne Peeples Sometimes the hardest part of doing an unpleasant task is simply getting started — typing the first word of a long report, lifting a dirty dish on the top of an overfilled sink or removing clothes from an unused exercise machine. The obstacle isn’t necessarily a lack of interest in completing a task, but the brain’s resistance to taking the first step. Now, scientists might have identified the neural circuit behind this resistance, and a way to ease it. In a study1 published today in Current Biology, researchers describe a pathway in the brain that seems to act as a ‘motivation brake’, dampening the drive to begin a task. When the team selectively suppressed this circuit in macaque monkeys, goal-directed behaviour rebounded. “The change after this modulation was dramatic,” says study co-author Ken-ichi Amemori, a neuroscientist at Kyoto University in Japan. The motivation brake, which can be particularly stubborn for people with certain psychiatric conditions, such as schizophrenia and major depressive disorder, is distinct from the avoidance of tasks driven by risk aversion in anxiety disorders. Pearl Chiu, a computational psychiatrist at Virginia Tech in Roanoke, who was not involved in the study, says that understanding this difference is essential for developing new treatments and refining current ones. “Being able to restore motivation, that’s especially exciting,” she says. Motivated macaques Previous work on task initiation has implicated a neural circuit connecting two parts of the brain known as the ventral striatum and ventral pallidum, both of which are involved in processing motivation and reward2,3,4. But attempts to isolate the circuit’s role have fallen short. Electrical stimulation, for example, inadvertently activates downstream regions, affecting motivation, but also anxiety. © 2026 Springer Nature Limited

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: 30079 - Posted: 01.14.2026

By Holly Barker In early life, astrocytes help to mold neural pathways in response to the environment. In adulthood, however, those cells curb plasticity by secreting a protein that stabilizes circuits, according to a mouse study published last month in Nature. “It’s a new and unique take on the field,” says Ciaran Murphy-Royal, assistant professor of neuroscience at Montreal University, who was not involved in the study. Most research focuses on how glial cells drive plasticity but “not how they apply the brakes,” he says. Astrocytes promote synaptic remodeling during the development of sensory circuits by secreting factors and exerting physical control—in humans, a single astrocyte can clamp onto 2 million synapses, previous studies suggest. But the glial cells are also responsible for shutting down critical periods for vision and motor circuits in mice and fruit flies, respectively. It has been unclear whether this loss of plasticity can be reversed. Some evidence hints that modifying the neuronal environment—through matrix degradation or transplantation of young neurons—can rekindle flexibility in adult brains. The new findings confirm that in adulthood, plasticity is only dormant, rather than lost entirely, says Nicola Allen, professor of molecular neurobiology at the Salk Institute for Biological Studies and an investigator on the new paper. “Neurons don’t lose an intrinsic ability to remodel, but that process is controlled by secreted factors in the environment,” she says. Specifically, astrocytes orchestrate that dormancy by releasing CCN1, a protein that stabilizes circuits by prompting the maturation of inhibitory neurons and glial cells, Allen’s team found. The findings suggest that astrocytes have an active role in stabilizing adult brain circuits. © 2026 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 30069 - Posted: 01.07.2026

David Adam In a town on the shores of Lake Geneva sit clumps of living human brain cells for hire. These blobs, about the size of a grain of sand, can receive electrical signals and respond to them — much as computers do. Research teams from around the world can send the blobs tasks, in the hope that they will process the information and send a signal back. Welcome to the world of wetware, or biocomputers. In a handful of academic laboratories and companies, researchers are growing human neurons and trying to turn them into functional systems equivalent to biological transistors. These networks of neurons, they argue, could one day offer the power of a supercomputer without the outsized power consumption. The results so far are limited. But keen scientists are already buying or borrowing online access to these brain-cell processors — or even investing tens of thousands of dollars to secure their own models. Some want to use these biocomputers as straightforward replacements for ordinary computers, whereas others want to use them to study how brains work. “Trying to understand biological intelligence is a very interesting scientific problem,” says Benjamin Ward-Cherrier, a robotics researcher at the University of Bristol, UK, who rents time on the Swiss brain blobs. “And looking at it from the bottom up — with simple small versions of our brain and building those up — I think is a better way of doing it than top down.” Biocomputing advocates claim that these systems could one day rival the capability of artificial intelligence and the potential of quantum computers. Other researchers who work with human neurons are more sceptical of what’s possible. And they warn that hype — and the science-fictional allure of what are sometimes labelled brain-in-a-jar systems — could even be counterproductive. If the idea that these systems possess sentience and consciousness takes hold, there could be repercussions for the research community. © 2025 Springer Nature Limited

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 7: Life-Span Development of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 13: Memory and Learning
Link ID: 30010 - Posted: 11.12.2025

By Kevin Berger Steve Ramirez was feeling on top of the world in 2015. His father, Pedro Ramirez, had snuck into the United States in the 1980s to escape the civil war in El Salvador. Pedro Ramirez held jobs as a door-to-door salesman for tombstones, a janitor in a diner, and a technician in an animal lab. After years of ’round-the-clock work, Pedro Ramirez became a U.S. citizen. And here was his son, born in America, with a Ph.D. from the Massachusetts Institute of Technology, still in his 20s, being celebrated as one of the most exciting and promising neuroscientists in the country. Steve Ramirez had published research papers with his MIT mentor Xu Liu that reported how they used lasers to erase fear memories, spur positive memories, and even fabricate new memories in the brain. The experiments were only in mice. But they were impressive. Memories are made of networks of brain cells called engrams. The lasers targeted specific cells in engrams. Zap those cells and the whole engram was muted. The pair of neuroscientists gave a popular TED Talk on memory manipulation and were featured in international press stories that invariably mentioned the plotlines in the movies Eternal Sunshine of the Spotless Mind and Inception could be real. Bad memories could be deleted. New memories could be implanted. One night in 2013 Ramirez and Liu were celebrating the publication of one of their papers in a jazz lounge at the top of the Prudential Building in Boston. The music was grooving, and the city below glittered like stars. Ramirez thought, I’ve never been so happy and so fully alive. In early 2015, Liu, age 37, died suddenly. There had been no warning signs. Ramirez had never had a friend like Liu. Liu opened his mind to experiences in science he couldn’t have imagined. Their relationship felt organic from Ramirez’s first day in the lab. Liu joked they would always have chemistry doing science together. Grief is when the future your brain plans for is cut off. Ramirez’s thoughts of doing science without Liu became a trapdoor that landed him in a cellar of pain. © 2025 NautilusNext Inc.,

Related chapters from BN: Chapter 17: Learning and Memory; Chapter 4: The Chemistry of Behavior: Neurotransmitters and Neuropharmacology
Related chapters from MM:Chapter 13: Memory and Learning; Chapter 4: Development of the Brain
Link ID: 30007 - Posted: 11.12.2025

Katie Kavanagh Why are we able to remember emotional events so well? According to a study published today in Nature1, a type of cell in the brain called an astrocyte is a key player in stabilizing memories for long-term recall. Astrocytes were thought to simply support neurons in creating the physical traces of memories in the brain, but the study found that they have a much more active role — and can even be directly triggered by repeated emotional experiences. The researchers behind the finding suggest that the cells could be a fresh target for treating memory conditions such as those associated with post-traumatic stress disorder and Alzheimer’s disease. “We provide an answer to the question of how a specific memory is stored for the long term,” says study co-author Jun Nagai, a neuroscientist at RIKEN Center for Brain Science in Wako, Japan. By studying astrocytes, Nagai said, the study identifies how the brain selectively filters important memories at the cellular level. Stable memories Nagai and his colleagues focused on the question of memory stabilization: how a short-term memory becomes more permanent in the brain. Previous research had found physical traces of memories in neuronal networks in brain regions such as the hippocampus and amygdala2. But it was unclear how these ‘engrams’ were stored in the brain as lasting memories after repeated exposure to the same stimulus. To dig deeper, the researchers developed a method for measuring activation patterns in astrocytes across a whole brain of a mouse as it completes a memory task. They measured the upregulation of a gene called Fos — an early marker of cell activity that is associated with the physical traces of memories in the brain3. © 2025 Springer Nature Limited

Related chapters from BN: Chapter 15: Emotions, Aggression, and Stress; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 11: Emotions, Aggression, and Stress; Chapter 13: Memory and Learning
Link ID: 29975 - Posted: 10.18.2025

By Claire L. Evans In 1983, the octogenarian geneticist Barbara McClintock stood at the lectern of the Karolinska Institute in Stockholm. She was famously publicity averse — nearly a hermit — but it’s customary for people to speak when they’re awarded a Nobel Prize, so she delivered a halting account of the experiments that had led to her discovery, in the early 1950s, of how DNA sequences can relocate across the genome. Near the end of the speech, blinking through wire-framed glasses, she changed the subject, asking: “What does a cell know of itself?” McClintock had a reputation for eccentricity. Still, her question seemed more likely to come from a philosopher than a plant geneticist. She went on to describe lab experiments in which she had seen plant cells respond in a “thoughtful manner.” Faced with unexpected stress, they seemed to adjust in ways that were “beyond our present ability to fathom.” What does a cell know of itself? It would be the work of future biologists, she said, to find out. Forty years later, McClintock’s question hasn’t lost its potency. Some of those future biologists are now hard at work unpacking what “knowing” might mean for a single cell, as they hunt for signs of basic cognitive phenomena — like the ability to remember and learn — in unicellular creatures and nonneural human cells alike. Science has long taken the view that a multicellular nervous system is a prerequisite for such abilities, but new research is revealing that single cells, too, keep a record of their experiences for what appear to be adaptive purposes. In a provocative study published in Nature Communications late last year, the neuroscientist Nikolay Kukushkin and his mentor Thomas J. Carew at New York University showed that human kidney cells growing in a dish can “remember” patterns of chemical signals (opens a new tab) when they’re presented at regularly spaced intervals — a memory phenomenon common to all animals, but unseen outside the nervous system until now. Kukushkin is part of a small but enthusiastic cohort of researchers studying “aneural,” or brainless, forms of memory. What does a cell know of itself? So far, their research suggests that the answer to McClintock’s question might be: much more than you think. © 2025 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 29872 - Posted: 08.02.2025

By Marta Hill Every year, black-capped chickadees perform an impressive game of hide-and-seek. These highly visual birds cache tens of thousands of surplus food morsels and then recover them during leaner times. Place cells in the hippocampus may help the birds keep track of their hidden bounty, according to a study published 11 June in Nature. The cells activate not only when a bird visits a food stash but also when it looks at the stash from far away, the study shows. “What is really profound about the work is it’s trying to unpack how it is that we’re able to combine visual information, which is based on where we currently are in the world, with our understanding of the space around us and how we can navigate it,” says Nick Turk-Browne, professor of psychology and director of the Wu Tsai Institute at Yale University, who was not involved in the study. With each gaze shift, the hippocampus first predicts what the bird is about to see and then reacts to what it actually sees, the study shows. “It really fits beautifully into this picture of this dual role for the system in representing actual and representing possible,” says Loren Frank, professor of physiology and psychiatry at the University of California, San Francisco, who was not involved in the work. The findings help explain how the various functions of the hippocampus—navigation, perception, learning and memory—work together, Turk-Browne adds. “If we can have a smart, abstract representation of place that doesn’t depend on actually physically being there, then you can imagine how this can be used to construct memories.” © 2025 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 29827 - Posted: 06.14.2025

By Sydney Wyatt Donald Hebb famously proposed in 1949 that when neurons fire together, the synaptic connections between them strengthen, forming the basis for long-term memories. That theory—which held up in experiments in rat hippocampal slice cultures—has shaped how researchers understand synaptic plasticity ever since. But a new computational modeling study adds to mounting evidence that Hebbian plasticity does not always explain how changing neuronal connections enable learning. Rather, behavioral timescale synaptic plasticity (BTSP), which can strengthen synapses even when neurons fire out of sync, better captures the changes seen in CA1 hippocampal cells as mice learn to navigate a new environment, the study suggests. Hebbian spike-timing-dependent plasticity occurs when a neuron fires just ahead of one it synapses onto, leading to a stronger connection between the two cells. BTSP, on the other hand, relies on a complex spike, or a burst of action potentials, in the postsynaptic cell, which triggers a calcium signal that travels across the dendritic arbor. The signal strengthens synaptic connections with the presynaptic cell that were active within seconds of that spike, causing larger changes in synaptic strength. BTSP helps hippocampal cells establish their place fields, the positions at which they fire, previous work suggests. But it was unclear whether it also contributes to learning, says Mark Sheffield, associate professor of neurobiology at the University of Chicago, who led the new study. The new findings suggest that it does—challenging how researchers traditionally think about plasticity mechanisms in the hippocampus, says Jason Shepherd, associate professor of neurobiology at the University of Utah, who was not involved in the research. “The classic rules of plasticity that we have been sort of thinking about for decades may not be actually how the brain works, and that’s a big deal.” © 2025 Simons Foundation

Related chapters from BN: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory and Learning
Link ID: 29810 - Posted: 05.28.2025

By Sydney Wyatt The red nucleus—a pale pink brainstem structure that coordinates limb movements in quadruped animals—also projects to brain areas that shape reward-motivated and action-based movements in people, according to a new functional imaging study. The finding suggests the region, like the cerebral cortex, took on a more complex role over the course of evolution. Many researchers had assumed that brainstem structures remained stuck in evolutionarily ancient roles, says Joan Baizer, professor of physiology and biophysics at the University at Buffalo. Activity in the red nucleus, a structure that emerged once animals began to use limbs for walking, coordinates the speed and accuracy of those movements in rats and helps to control posture in monkeys, previous electrophysiological recordings have shown. And in nonhuman primates, neurons in the red nucleus project to the motor cortex and spinal cord, anatomical studies have demonstrated, seemingly confirming the area’s role in motor function. By contrast, the human red nucleus primarily connects to cortical and subcortical regions involved in action control, reward and motivated behavior, the new work reveals. “If this is such a motor structure, why isn’t it projecting to the spinal cord? That doesn’t really fit with our notion of what this structure is supposed to be doing,” says study investigator Samuel Krimmel, a postdoctoral fellow in Nico Dosenbach’s lab. The new imaging suggests that, at least in people, the neural underpinnings of motivated movement—previously considered to be the role of higher-order brain areas—reach “all the way down into the brainstem,” says Dosenbach, professor of neurology at Washington University School of Medicine, who led the work. The findings were published last month in Nature Communications. © 2025 Simons Foundation

Related chapters from BN: Chapter 11: Motor Control and Plasticity; Chapter 6: Evolution of the Brain and Behavior
Related chapters from MM:Chapter 5: The Sensorimotor System
Link ID: 29790 - Posted: 05.17.2025