Links for Keyword: Learning & Memory

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Two independent teams of scientists from the University of Utah and the University of Massachusetts Medical School have discovered that a gene crucial for learning, called Arc, can send its genetic material from one neuron to another by employing a strategy commonly used by viruses. The studies, both published in Cell, unveil a new way that nervous system cells interact. “This work is a great example of the importance of basic neuroscience research,” said Edmund Talley, Ph.D., a program director at the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health. “What began as an effort to examine the behavior of a gene involved in memory and implicated in neurological disorders such as Alzheimer’s disease has unexpectedly led to the discovery of an entirely new process, which neurons may use to send genetic information to one another.” While Arc is known to play a vital role in the brain’s ability to store new information, little is known about precisely how it works. In addition, previous studies had detailed similarities between the Arc protein and proteins found in certain viruses like HIV, but it was unclear how those commonalities influenced the behavior of the Arc protein. The University of Utah researchers began their examination of the Arc gene by introducing it into bacterial cells. To their surprise, when the cells made the Arc protein, it clumped together into a form that resembled a viral capsid, the shell that contains a virus’ genetic information. The Arc “capsids” appeared to mirror viral capsids in their physical structure as well as their behavior and other properties.

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24535 - Posted: 01.17.2018

Helen Shen For someone who’s not a Sherlock superfan, cognitive neuroscientist Janice Chen knows the BBC’s hit detective drama better than most. With the help of a brain scanner, she spies on what happens inside viewers’ heads when they watch the first episode of the series and then describe the plot. Chen, a researcher at Johns Hopkins University in Baltimore, Maryland, has heard all sorts of variations on an early scene, when a woman flirts with the famously aloof detective in a morgue. Some people find Sherlock Holmes rude while others think he is oblivious to the woman’s nervous advances. But Chen and her colleagues found something odd when they scanned viewers’ brains: as different people retold their own versions of the same scene, their brains produced remarkably similar patterns of activity1. Chen is among a growing number of researchers using brain imaging to identify the activity patterns involved in creating and recalling a specific memory. Powerful technological innovations in human and animal neuroscience in the past decade are enabling researchers to uncover fundamental rules about how individual memories form, organize and interact with each other. Using techniques for labelling active neurons, for example, teams have located circuits associated with the memory of a painful stimulus in rodents and successfully reactivated those pathways to trigger the memory. And in humans, studies have identified the signatures of particular recollections, which reveal some of the ways that the brain organizes and links memories to aid recollection. Such findings could one day help to reveal why memories fail in old age or disease, or how false memories creep into eyewitness testimony. These insights might also lead to strategies for improved learning and memory. © 2018 Macmillan Publishers Limited,

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24520 - Posted: 01.11.2018

Eric Nyquist for Quanta Magazine Brains, beyond their signature achievements in thinking and problem solving, are paragons of energy efficiency. The human brain’s power consumption resembles that of a 20-watt incandescent lightbulb. In contrast, one of the world’s largest and fastest supercomputers, the K computer in Kobe, Japan, consumes as much as 9.89 megawatts of energy — an amount roughly equivalent to the power usage of 10,000 households. Yet in 2013, even with that much power, it took the machine 40 minutes to simulate just a single second’s worth of 1 percent of human brain activity. Now engineering researchers at the California NanoSystems Institute at the University of California, Los Angeles, are hoping to match some of the brain’s computational and energy efficiency with systems that mirror the brain’s structure. They are building a device, perhaps the first one, that is “inspired by the brain to generate the properties that enable the brain to do what it does,” according to Adam Stieg, a research scientist and associate director of the institute, who leads the project with Jim Gimzewski, a professor of chemistry at UCLA. The device is a far cry from conventional computers, which are based on minute wires imprinted on silicon chips in highly ordered patterns. The current pilot version is a 2-millimeter-by-2-millimeter mesh of silver nanowires connected by artificial synapses. Unlike silicon circuitry, with its geometric precision, this device is messy, like “a highly interconnected plate of noodles,” Stieg said. And instead of being designed, the fine structure of the UCLA device essentially organized itself out of random chemical and electrical processes. All Rights Reserved © 2018

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 7: Life-Span Development of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory, Learning, and Development; Chapter 13: Memory, Learning, and Development
Link ID: 24500 - Posted: 01.08.2018

By HENRY ALFORD Here in the valley of my mid-50s, I try not to get into a swivet over my occasionally faulty memory: Sometimes the mind has a mind of its own. But when I read this chilling passage — “I am dementing. I am dementing. I am dementing.” — from Gerda Saunders’s recent memoir “Memory’s Last Breath: Field Notes on My Dementia,” I found myself starting to panic. In a world increasingly dominated by the Google/Apple/Facebook/Amazon hegemony, we hear a lot about the threat to privacy. But isn’t memory just as vulnerable? Now that, as the former New Republic editor Franklin Foer writes in “World Without Mind: The Existential Threat of Big Tech,” “our phone is an extension of our memory; we’ve outsourced basic functions to algorithms,” doesn’t the world seem like an ever-larger parking lot that has mysteriously swallowed our Toyota? Don’t we all wish, now more than ever, that acquaintances came equipped with their own “Previously on this series …” trailer? Mr. Foer and Ms. Saunders aren’t the only writers on this beat. Recent books by Robert Sapolsky, Michael Lemonick, Felicia Yap, Emily Barr, Dale Bredesen, Val Emmich, Oliver Sacks and Elizabeth Rosner, among others, have addressed the theme of non-historical memory. Last July alone, more than a dozen books specifically about the topic, most of them self-published, were released. You’d expect the themes of amnesia or powers of recall to be prevalent in thrillers or in memoirs by trauma survivors or over-beveraged rock stars, but even literary fiction is getting in on the act. In Rachel Khong’s sly, diaristic “Goodbye, Vitamin,” a 30-year-old who moves back home learns she has to care for a dementing father who has started leaving his pants in trees. In Alissa Nutting’s outrageous sex comedy “Made for Love,” a woman on the lam from her tech pioneer husband discovers that he has implanted a chip in her brain that allows him to download all her experiences. © 2018 The New York Times Company

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24499 - Posted: 01.08.2018

By Roni Dengler Our brains don’t rest when we sleep. Electrical waves ripple through our noggins as our neurons talk to each other. Now, researchers have shown that when these waves don’t interact properly, we can lose our long-term memory. The work may help explain why older adults are so forgetful, and it could lead to new therapies to treat memory loss. To find out how sleep contributes to memory loss in old age, Randolph Helfrich, a neuroscientist at the University of California (UC), Berkeley, and his team gave healthy 70- and 20-year-olds a memory test. Participants were trained to match 120 common, short words—for example, “bird”—with nonsense words made of combinations of random syllables, like “jubu.” Once they learned the word-nonsense word combos, the volunteers played a version of the game “memory.” They had to match the word pairs twice: once about 10 minutes after they’d mastered the task, and again a few hours after waking from a full night’s rest. While they slept, researchers recorded the electrical activity in their brains. As expected, the older adults’ ability to remember the word pairs in the morning was worse than their young counterparts’. The electrical recordings revealed one reason. Two kinds of brain waves—slow oscillations, large undulations that promote restorative sleep, and sleep spindles, transient bursts of short waves—are tell-tale marks of deep, typically dreamless, non–rapid eye movement sleep. But these waves are out of sync in older people, the researchers report today in Neuron. This out-of-step activity, they say, interrupts communication between the parts of our brains that store short- and long-term memories. In effect, Helfrich says, the prefrontal cortex where long-term memories are stored needs to tell the hippocampus—the part of the brain where all memories go first—that it’s ready to receive information; if brain waves aren’t in sync, this communication gets lost. So do the memories. © 2017 American Association for the Advancement of Science

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 3: Neurophysiology: The Generation, Transmission, and Integration of Neural Signals
Related chapters from MM:Chapter 13: Memory, Learning, and Development; Chapter 3: Neurophysiology: The Generation, Transmission, and Integration of Neural Signals
Link ID: 24428 - Posted: 12.15.2017

By Catherine Offord Mantis shrimps are not the easiest animals to work with, as neuroanatomist Nicholas Strausfeld knows firsthand. Not least, there’s the challenge of capturing the crustaceans in the wild. Also known as stomatopods, mantis shrimps live in burrows in shallow seawater and have earned the descriptive nickname “thumb splitters,” thanks to their tendency to use their sharp, powerful claws to slash at prey and pursuers. “At low tide, you wade around and you try and catch these things,” says Strausfeld, who has plenty of experience chasing after the purple-spotted mantis shrimp (Gonodactylus smithii) with a small handheld net in the tropical waters around Lizard Island, Australia. “They’re incredibly fast—it’s very difficult.” For Strausfeld and other neurobiologists, however, all the trouble is well worth it, as these feisty little marine predators are yielding unique insight into the evolution of the arthropods—the most species-rich animal phylum on the planet, containing around 85 percent of all described animal species. “We knew [these shrimps] were very interesting,” says neuroanatomist Gabriella Wolff, previously a PhD student in Strausfeld’s lab at the University of Arizona and now a research associate at the University of Washington in Seattle. In addition to a complex visual system that receives inputs from independently moving eyes, “mantis shrimps have very advanced behaviors that we haven’t necessarily seen in other crustaceans so far.” Research has also suggested they are sophisticated navigators, regularly finding their way home from distant feeding sites. Plus, they recognize other individual mantis shrimps, and remember whether their interactions were confrontational or not. © 1986-2017 The Scientist

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 6: Evolution of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24414 - Posted: 12.11.2017

Carl Zimmer When you drive toward an intersection, the sight of the light turning red will (or should) make you step on the brake. This action happens thanks to a chain of events inside your head. Your eyes relay signals to the visual centers in the back of your brain. After those signals get processed, they travel along a pathway to another region, the premotor cortex, where the brain plans movements. Now, imagine that you had a device implanted in your brain that could shortcut the pathway and “inject” information straight into your premotor cortex. That may sound like an outtake from “The Matrix.” But now two neuroscientists at the University of Rochester say they have managed to introduce information directly into the premotor cortex of monkeys. The researchers published the results of the experiment on Thursday in the journal Neuron. Although the research is preliminary, carried out in just two monkeys, the researchers speculated that further research might lead to brain implants for people with strokes. “You could potentially bypass the damaged areas and deliver stimulation to the premotor cortex,” said Kevin A. Mazurek, a co-author of the study. “That could be a way to bridge parts of the brain that can no longer communicate.” In order to study the premotor cortex, Dr. Mazurek and his co-author, Dr. Marc H. Schieber, trained two rhesus monkeys to play a game. The monkeys sat in front of a panel equipped with a button, a sphere-shaped knob, a cylindrical knob, and a T-shaped handle. Each object was ringed by LED lights. If the lights around an object switched on, the monkeys had to reach out their hand to it to get a reward — in this case, a refreshing squirt of water. © 2017 The New York Times Company

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 11: Motor Control and Plasticity
Related chapters from MM:Chapter 13: Memory, Learning, and Development; Chapter 5: The Sensorimotor System
Link ID: 24408 - Posted: 12.08.2017

Anne Churchland Decisions span a vast range of complexity. There are really simple ones: Do I want an apple or a piece of cake with my lunch? Then there are much more complicated ones: Which car should I buy, or which career should I choose? Neuroscientists like me have identified some of the individual parts of the brain that contribute to making decisions like these. Different areas process sounds, sights or pertinent prior knowledge. But understanding how these individual players work together as a team is still a challenge, not only in understanding decision-making, but for the whole field of neuroscience. Part of the reason is that until now, neuroscience has operated in a traditional science research model: Individual labs work on their own, usually focusing on one or a few brain areas. That makes it challenging for any researcher to interpret data collected by another lab, because we all have slight differences in how we run experiments. Neuroscientists who study decision-making set up all kinds of different games for animals to play, for example, and we collect data on what goes on in the brain when the animal makes a move. When everyone has a different experimental setup and methodology, we can’t determine whether the results from another lab are a clue about something interesting that’s actually going on in the brain or merely a byproduct of equipment differences. © 2010–2017, The Conversation US, Inc.

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 18: Attention and Higher Cognition
Related chapters from MM:Chapter 13: Memory, Learning, and Development; Chapter 14: Attention and Consciousness
Link ID: 24392 - Posted: 12.05.2017

By JOANNA KLEIN Chances are that’s a shy elk looking back at a bold magpie, in the photograph above. They get along, so to speak, because the elk needs grooming and the magpie is looking for dinner. But they may have never entered into this partnership if it weren’t for their particular personalities, suggests a study published Wednesday in Biology Letters. Let’s start with the elk. In Canada’s western province of Alberta, they’ve been acting strange. Some have quit migrating, opting to hang around towns with humans who protect them from predators like wolves. Others still migrate. As a doctoral student at the University of Alberta, Robert Found, now a wildlife biologist for Parks Canada, discovered over years of observing their personalities that bold elk stayed, while shy elk migrated. But he noticed something else in the process of completing his research: As elk laid down to rest at the end of the day, magpies approached. There appeared to be a pattern: elk of some personality types aggressively rejected magpies. Others didn’t. “Sometimes the magpies will walk around right on the head and the face of the elk,” Dr. Found said. Scientists define animal personality by an individual animal’s behavior. It’s predictable, but also varies from others in a group. Dr. Found created a bold-shy scale for elk, measuring how close they allowed him to get, where elk positioned themselves within the group, which elk fought other elk, which ones won, how long elk spent monitoring for predators and their willingness to approach unfamiliar objects like old tires, skis and a bike. He also noted which elk accepted magpies. To study the magpies, he attracted the birds to 20 experimental sites with peanuts on tree stumps. During more than 20 separate trials with different magpies, he judged each bird’s behavior relative to the other magpies in a trial. Like the elk, he measured flight response, social structure and willingness to approach items they hadn’t previously encountered (a bike decorated with a boa and Christmas ornaments). He also noted who landed on a faux-elk that offered dog food rather than ticks (a previous study showed magpies liked dog food as much as ticks). © 2017 The New York Times Company

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 6: Evolution of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24380 - Posted: 11.30.2017

By Julie Hecht A good friend insists: "You don't study dogs, Julie. You study human culture. Dog behavior is a product of the people who love them." And since I'm not one for quick comebacks, I typically just smile and pet her dog. Because I like dogs. And I study them (see what I just did there? Bam). Or maybe she's onto something. Is dog behavior independent from where they live? From the cultural norms they're exposed to? Maybe German Shepherds can tell us a thing or two. In 2009, researchers from Hungary and the USA published a cross-cultural survey where German Shepherd owners from each country weighed in on their dogs. While a number of similarities emerged, so did differences. For example, USA German Shepherds were more likely to be kept indoors and have more types of training experiences. And when it came to behavior, on some measures there was no difference between German Shepherds in each country—all owners reported low activity-impulsivity and low inattention scores—but there were also a few differences: the USA dogs scored higher on confidence and aggressiveness than those in Hungary. Does this mean a German Shepherd here isn't the same as a German Shepherd there? One possible answer is: yes, the dogs are different. If German Shepherd lovers in the USA prefer dogs with higher confidence ratings, this preference "could lead to selective breeding for higher confidence, resulting in a population of German Shepherds in the USA with this trait." We know it’s possible to select for particular parental behavioral traits, and then observe them in offspring. "Genetic isolation, as well as environmental variation, could contribute to differences in pet behavior across cultures," the researchers offer. © 2017 Scientific American

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 6: Evolution of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24366 - Posted: 11.27.2017

By Jef Akst | After Nelson Dellis’s grandmother passed away from Alzheimer’s disease in the summer of 2009, he became obsessed with memory. “I had seen her whole decline, so brain health was on my mind,” he says. He found out about annual memory competitions that tested people’s ability to remember large volumes of data—for example, the exact order of 104 playing cards in two decks—and began to learn the strategies so-called “memory athletes” used to pull off these incredible feats. “I found the techniques worked, and with a bit of practice, you can do a lot more than you ever thought you could,” Dellis says. He entered the 2010 USA Memory Championship in New York City and came in third. The next two years in a row, he took first. A mistake in the finals cost him the championship in 2013, but he regained the crown in 2014 and won again in 2015, making him the first and only four-time USA Memory Champion. And all it took was “a bit of practice.” Dellis says there are several strategies memory athletes use, but they’re all based on the same principle: “You want to turn information you’re trying to memorize into something that your brain naturally prefers to absorb”—typically, an image. “Once you have that picture, the next step is to store it somewhere—somewhere in your mind you can safely store it and retrieve it later.” This place is known as a “memory palace,” and it can be any place that’s familiar to you, such as your house. You can then place the images you’ve chosen along a particular path through the memory palace, and “the path, which you know very well, preserves the order.”

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24318 - Posted: 11.11.2017

Using an innovative “NeuroGrid” technology, scientists showed that sleep boosts communication between two brain regions whose connection is critical for the formation of memories. The work, published in Science, was partially funded by the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, a project of the National Institutes of Health devoted to accelerating the development of new approaches to probing the workings of the brain. “Using new technologies advanced by the BRAIN Initiative, these researchers made a fundamental discovery about how the brain creates and stores new memories,” said Nick Langhals, Ph.D., program director at NIH’s National Institute of Neurological Disorders and Stroke. A brain structure called the hippocampus is widely thought to turn new information into permanent memories while we sleep. Previous work by the new study’s senior author, New York University School of Medicine professor György Buzsáki, M.D., Ph.D., revealed high-frequency bursts of neural firing called ripples in the hippocampus during sleep and suggested they play a role in memory storage. The current study confirmed the presence of ripples in the hippocampus during sleep and found them in certain parts of association neocortex, an area on the brain’s surface involved in processing complex sensory information. “When we first observed this, we thought it was incorrect because it had never been observed before,” said Dion Khodagholy, Ph.D., the study’s co-first author and assistant professor at Columbia University in New York.

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24274 - Posted: 11.01.2017

Jon Hamilton When it comes to brain training, some workouts seem to work better than others. A comparison of the two most common training methods scientists use to improve memory and attention found that one was twice as effective as the other. The more effective method also changed brain activity in a part of the brain involved in high-level thinking. But neither method made anyone smarter, says Kara Blacker, the study's lead author and a researcher at The Henry M. Jackson Foundation for the Advancement of Military Medicine in Bethesda, Md. "Our hypothesis was that training might improve fluid intelligence or IQ," Blacker says. "But that's not what we found." Blacker did the memory research when she was part of a team at Johns Hopkins University and the Kennedy Krieger Institute in Baltimore. The results were reported in the Journal of Cognitive Enhancement. The team compared two approaches to improving working memory, which acts as a kind of mental workspace where we store information temporarily. "If somebody gives you directions, you have to keep that information in mind long enough to actually execute going to that location," Blacker says. "If someone tells you a phone number, you have to be able to remember it." To test different methods for improving working memory, the team had 136 young adults spend a month training their brains for 30 minutes a day, five days a week. Johns Hopkins University YouTube One group did something called a "complex span" test, which involves remembering the location of an item despite distractions. A second group trained with something called the dual n-back test. Each day they would sit at a computer watching flashing squares appear on a grid and listening to a voice reading letters from the alphabet. © 2017 npr

Related chapters from BN8e: Chapter 18: Attention and Higher Cognition; Chapter 17: Learning and Memory
Related chapters from MM:Chapter 14: Attention and Consciousness; Chapter 13: Memory, Learning, and Development
Link ID: 24231 - Posted: 10.23.2017

by Sari Harrar, AARP Bulletin, At 99 years old Brenda Milner continues to explore the mind and its relationship to people’'s behavior. You'’re a preeminent neuroscientist, and a professor at Canada's prestigious McGill University. At age 99, what motivates you to keep up your research at the Montreal Neurological Institute and Hospital? I am very curious. Human quirks attract my interest. If you’'re a theoretical person, you can sit and dream up beautiful theories, but my approach is, “What would happen if …”or, “Why is this person doing [that] …”and then, “How can I measure it?” I wouldn't still be working if I didn't find it exciting. AARP Membership: Join or Renew for Just $16 a Year Are you curious in real life, too? Yes. I'm a good "noticer—" of behavior as much as the kind of furniture people have! In the 1950s, you made a revolutionary discovery— that memories are formed in a brain area called the hippocampus, which is now getting lots of attention for its role in memory loss and dementia. Has brain research gotten easier? Nowadays, everyone has functional magnetic resonance imaging. Anybody with access to a medical school can get a good look at the patients' brain while they're alive and young, but it wasn't like that [then]. Psychologists were studying patients who were much older and beginning to show memory impairment. Then they had to wait for their patients to die.

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 7: Life-Span Development of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory, Learning, and Development; Chapter 13: Memory, Learning, and Development
Link ID: 24196 - Posted: 10.16.2017

Laura Sanders The brain’s mapmakers don’t get a break, even for sleep. Grid cells, specialized nerve cells that help keep people and other animals oriented, stay on the clock 24/7, two preliminary studies on rats suggest. Results from the studies, both posted October 5 at bioRxiv.org, highlight the stability of the brain’s ‘inner GPS’ system. Nestled in a part of the brain called the medial entorhinal cortex, grid cells fire off regularly spaced signals as a rat moves through the world, marking a rat’s various locations. Individual grid cells work together to create a mental map of the environment. But scientists didn’t know what happens to this map when an animal no longer needs it, such as during sleep. Grid cells, it turns out, maintain their mapmaking relationships even in sleeping rats, report two teams of researchers, one from the University of Texas at Austin and one from the Norwegian University of Science and Technology in Trondheim. (The Norway group includes the researchers who won a Nobel Prize in 2014 for discovering grid cells (SN Online: 10/6/14).) By eavesdropping on pairs of grid cells, researchers found that the cells maintain similar relationships to each other during sleep as they do during active exploration. For instance, two grid cells that fired off signals nearly in tandem while the rat was awake kept that same pattern during sleep, a sign that the map is intact. The results provide insights into how grid cells work together to create durable mental maps. © Society for Science & the Public 2000 - 2017.

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24186 - Posted: 10.13.2017

By Giorgia Guglielmi This mantis shrimp (Gonodactylus smithii) might have a much more elaborate brain than previously thought. That’s the conclusion of the first study to peer into the head of more than 200 crustaceans, including crabs, shrimp, and lobsters. Researchers discovered that the brain of mantis shrimp contains memory and learning centers, called mushroom bodies, which so far have been seen only in insects. The team also found similar structures in close relatives of these sea creatures: cleaner shrimp, pistol shrimp, and hermit crabs. This may not be a coincidence, the researchers say, because mantis shrimp and their brethren are the only crustaceans that hunt over long distances and might have to remember where to get food. But the finding, reported in eLife, is likely to stir debate: Scientists agree that mushroom bodies evolved after the insect lineage split off from the crustacean lineage about 480 million years ago; finding these learning centers in mantis shrimp means that either mushroom bodies are much more ancient than scientists realized and were lost in all crustaceans but mantis shrimp, or that these structures are similar to their counterparts in insects but have evolved independently. © 2017 American Association for the Advancement of Science.

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 6: Evolution of the Brain and Behavior
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24158 - Posted: 10.07.2017

By Claudia Wallis, A funny thing happened in the Dutch city of Maastricht in the fall of 2011. A policy went into effect banning the sale of marijuana at the city’s 13 legal cannabis shops to visitors from most other countries. The goal was to discourage disruptive drug tourism in a city close to several international borders. The policy had its intended effect, but also a remarkable unintended one: foreign students attending Maastricht University starting getting better grades. According to an analysis published earlier this year in Review of Economic Studies, students who had been passing their courses at a rate of 73.9% when they could legally buy weed were now passing at a rate of 77.9% — a sizeable jump. The effect, which was based on data from 336 undergraduates in more than 4,000 courses, was most dramatic for weaker students, women, and in classes that required more math. Some of this falls in line with past research: marijuana use has been linked to inferior academic achievement (and vice versa), so it makes sense that poorer students might benefit most from a ban, and the drug is known to have immediate effects on cognitive performance, including in math. But what’s really unusual about the study, notes one of its authors, economist Ulf Zoelitz of the Briq Institute on Behavior and Inequality, is that rather than merely correlating academic performance with cannabis use, as much past research has done, “we could cleanly identify the causal impact of a drug policy.” Zoelitz co-authored the study with Olivier Marie of Erasmus University Rotterdam. © 2017 KQED Inc.

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 4: The Chemistry of Behavior: Neurotransmitters and Neuropharmacology
Related chapters from MM:Chapter 13: Memory, Learning, and Development; Chapter 4: The Chemistry of Behavior: Neurotransmitters and Neuropharmacology
Link ID: 24139 - Posted: 10.03.2017

By Matthew Hutson Studying the human mind is tough. You can ask people how they think, but they often don’t know. You can scan their brains, but the tools are blunt. You can damage their brains and watch what happens, but they don’t take kindly to that. So even a task as supposedly simple as the first step in reading—recognizing letters on a page—keeps scientists guessing. Now, psychologists are using artificial intelligence (AI) to probe how our minds actually work. Marco Zorzi, a psychologist at the University of Padua in Italy, used artificial neural networks to show how the brain might “hijack” existing connections in the visual cortex to recognize the letters of the alphabet, he and colleagues reported last month in Nature Human Behaviour. Zorzi spoke with Science about the study and about his other work. This interview has been edited for brevity and clarity. Q: What did you learn in your study of letter perception? A: We first trained the model on patches of natural images, of trees and mountains, and then this knowledge becomes a vocabulary of basic visual features the network uses to learn about letter shapes. This idea of “neural recycling” has been around for some time, but as far as I know this is the first demonstration where you actually gained in performance: We saw better letter recognition in a model that trained on natural images than one that didn’t. Recycling makes learning letters much faster compared to the same network without recycling. It gives the network a head start. © 2017 American Association for the Advancement of Science.

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24130 - Posted: 09.30.2017

By Gary Stix Donald Hebb was a famed Canadian scientist who produced key findings that ranged across the field of psychology, providing insights into perception, intelligence and emotion. He is perhaps best known, though, for his theory of learning and memory, which appears as an entry in most basic texts on neuroscience. But now an alternative theory—along with accompanying experimental evidence—fundamentally challenges some central tenets of Hebb’s thinking. It provides a detailed account of how cells and the electrical and molecular signals that activate them are involved in forming memories of a series of related events. Put forward in 1949, Hebb’s theory holds that when electrical activity in one neuron—perhaps triggered by observing one’s surroundings—repeatedly induces a neighboring “target cell” to fire electrical impulses, a process of conditioning occurs and strengthens the connection between the two neurons. This is a bit like doing arm curls with a weight; after repeated lifts the arm muscle grows stronger and the barbell gets easier to hoist. At the cellular level, repeated stimulation of one neuron by another enables the target cell to respond more readily the next time it is activated. In basic textbooks, this boils down to a simple adage to describe the physiology of learning and memory: “Cells that fire together, wire together.” Every theory requires experimental evidence, and scientists have toiled for years to validate Hebb’s idea in the laboratory. Many research findings have showed that when a neuron repeatedly fires off an electrical impulse (called an “action potential”) at virtually the same time as an adjacent neuron, their connection does indeed grow more efficient. The target cell fires more easily, and the signal transmitted is stronger. This process—known as long-term potentiation (LTP)—apparently induces physiological change or “plasticity” in target cells. LTP is routinely cited as a possible explanation for how the brain learns and forms memories at the cellular level. © 2017 Scientific American,

Related chapters from BN8e: Chapter 17: Learning and Memory
Related chapters from MM:Chapter 13: Memory, Learning, and Development
Link ID: 24093 - Posted: 09.21.2017

by Emilie Reas Paranoia. Munchies. Giggles. Sleepiness. Memory loss. Although the effects of cannabinoids–the active components of marijuana–are familiar to many, their neurobiological substrates are poorly characterized. Perhaps the effect of greatest interest to both neuroscientists and to cannabis users hoping to preserve their cognitive function, is short-term memory impairment that often accompanies marijuana use. Our partial understanding of its physiological and behavioral effects is not for want of studies into its neural effects. Ample research has shown a range of changes to neurotransmission, receptors, ion channels and mitochondria following cannabinoid exposure. However, knowledge of its cellular and molecular properties alone cannot offer a complete picture of its system-wide effects leading to cognitive and behavioral changes. A recent study published in PLOS Computational Biology took a novel approach to address this issue, combining computational modeling with electrophysiological brain recordings from rats performing a memory task, to unravel the dynamics of neural circuits under the influence of cannabinoids. To assess memory changes induced by cannabinoids, the scientists injected tetrahydrocannabinol (THC), the main psychoactive compound in marijuana, into rats before they performed a “delayed-nonmatch-to-sample” working memory task. In this task, rats are cued with one of two levers, and after a delay, are required to select the opposite lever. Compared to sober sessions, performance under THC was impaired by 12%, confirming the all-too-familiar memory impairment associated with cannabis use. THC alters hippocampal activity

Related chapters from BN8e: Chapter 17: Learning and Memory; Chapter 4: The Chemistry of Behavior: Neurotransmitters and Neuropharmacology
Related chapters from MM:Chapter 13: Memory, Learning, and Development; Chapter 4: The Chemistry of Behavior: Neurotransmitters and Neuropharmacology
Link ID: 24087 - Posted: 09.21.2017