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Research into the nature of memory reveals how cells that store information are stabilized over time

by University at Buffalo

Research into the nature of memory reveals how cells that store information are stabilized over time

Think of a time when you had two different but similar experiences in a short period. Maybe you attended two holiday parties in the same week or gave two presentations at work. Shortly afterward, you may find yourself confusing the two, but as time goes on that confusion recedes and you are better able to differentiate between these different experiences.

New research published in Nature Neuroscience reveals that this process occurs on a cellular level , findings that are critical to the understanding and treatment of memory disorders, such as Alzheimer's disease.

Dynamic engrams store memories

The research focuses on engrams, which are neuronal cells in the brain that store memory information. "Engrams are the neurons that are reactivated to support memory recall ," says Dheeraj S. Roy, Ph.D., one of the paper's senior authors and an assistant professor in the Department of Physiology and Biophysics in the Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo. "When engrams are disrupted, you get amnesia."

In the minutes and hours that immediately follow an experience, he explains, the brain needs to consolidate the engram to store it. "We wanted to know: What is happening during this consolidation process? What happens between the time that an engram is formed and when you need to recall that memory later?"

The researchers developed a computational model for learning and memory formation that starts with sensory information, which is the stimulus. Once that information gets to the hippocampus, the part of the brain where memories form, different neurons are activated, some of which are excitatory and others that are inhibitory.

When neurons are activated in the hippocampus, not all are going to be firing at once. As memories form, neurons that happen to be activated closely in time become a part of the engram and strengthen their connectivity to support future recall.

"Activation of engram cells during memory recall is not an all or none process but rather typically needs to reach a threshold (i.e., a percentage of the original engram) for efficient recall," Roy explains. "Our model is the first to demonstrate that the engram population is not stable: The number of engram cells that are activated during recall decreases with time, meaning they are dynamic in nature, and so the next critical question was whether this had a behavioral consequence."

Dynamic engrams are needed for memory discrimination

"Over the consolidation period after learning, the brain is actively working to separate the two experiences and that's possibly one reason why the numbers of activated engram cells decrease over time for a single memory," he says. "If true, this would explain why memory discrimination gets better as time goes on. It's like your memory of the experience was one big highway initially but over time, over the course of the consolidation period on the order of minutes to hours, your brain divides them into two lanes so you can discriminate between the two."

Roy and the experimentalists on the team now had a testable hypothesis, which they carried out using a well-established behavioral experiment with mice. Mice were briefly exposed to two different boxes that had unique odors and lighting conditions; one was a neutral environment but in the second box, they received a mild foot shock.

A few hours after that experience, the mice, who typically are constantly moving, exhibited fear memory recall by freezing when exposed to either box. "That demonstrated that they couldn't discriminate between the two," Roy says. "But by hour twelve, all of a sudden, they exhibited fear only when they were exposed to the box where they were uncomfortable during their very first experience. They were able to discriminate between the two. The animal is telling us that they know this box is the scary one but five hours earlier they couldn't do that."

Using a light-sensitive technique, the team was able to detect active neurons in the mouse hippocampus as the animal was exploring the boxes. The researchers used this technique to tag active neurons and later measure how many were reactivated by the brain for recall. They also conducted experiments that allowed a single engram cell to be tracked across experiences and time. "So I can tell you literally how one engram cell or a subset of them responded to each environment across time and correlate this to their memory discrimination," explains Roy.

The team's initial computational studies had predicted that the number of engram cells involved in a single memory would decrease over time, and the animal experiments bore that out.

"When the brain learns something for the first time, it doesn't know how many neurons are needed and so on purpose a larger subset of neurons is recruited," he explains. "As the brain stabilizes neurons, consolidating the memory, it cuts away the unnecessary neurons, so fewer are required and in doing so helps separate engrams for different memories."

What is happening with memory disorders?

The findings have direct relevance to understanding what is going wrong in memory disorders, such as Alzheimer's disease. Roy explains that to develop treatments for such disorders, it is critical to know what is happening during the initial memory formation, consolidation and activation of engrams for recall.

"This research tells us that a very likely candidate for why memory dysfunction occurs is that there is something wrong with the early window after memory formation where engrams must be changing," says Roy.

He is currently studying mouse models of early Alzheimer's disease to find out if engrams are forming but not being correctly stabilized. Now that more is known about how engrams work to form and stabilize memories, researchers can examine which genes are changing in the animal model when the engram population decreases.

"We can look at mouse models and ask, are there specific genes that are altered? And if so, then we finally have something to test, we can modulate the gene for these 'refinement' or 'consolidation' processes of engrams to see if that has a role in improving memory performance," he says.

Now at the Jacobs School, Roy conducted the research while a McGovern Fellow at the Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University. Roy is one of three neuroscientists recruited to the Jacobs School this year to launch a new focus on systems neuroscience in the school's Department of Physiology and Biophysics.

Co-authors on the paper are from Imperial College in London; the Institute of Science and Technology in Austria; the McGovern Institute for Brain Research at MIT; and the Center for Life Sciences & IDG/McGovern Institute for Brain Research at Tsinghua University in China.

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Research into the nature of memory reveals how cells that store information are stabilized over time

Dheeraj Roy, PhD, assistant professor, Dept. of Physiology and Biophysics, Jacobs School of Medicine and Biomedical Sciences.

Dheeraj Roy, PhD, assistant professor in the Department of Physiology and Biophysics in the Jacobs School of Medicine and Biomedical Sciences at UB, is a senior author on a new paper that explains aspects of how memory works at the cellular level.  ( Photo: Sandra Kicman)

Neuroscientists demonstrate how the brain improves its ability to distinguish between similar experiences, findings that could lead to treatments for Alzheimer’s disease and other memory disorders

By Ellen Goldbaum

Release Date: January 19, 2024

BUFFALO, N.Y. – Think of a time when you had two different but similar experiences in a short period. Maybe you attended two holiday parties in the same week or gave two presentations at work. Shortly afterward, you may find yourself confusing the two, but as time goes on that confusion recedes and you are better able to differentiate between these different experiences.

New research published in Nature Neuroscience today reveals how this process occurs on a cellular level, findings that are critical to the understanding and treatment of memory disorders, such as Alzheimer’s disease.

Dynamic engrams store memories

The research focuses on engrams, which are neuronal cells in the brain that store memory information. “Engrams are the neurons that are reactivated to support memory recall,” says Dheeraj S. Roy, PhD, one of the paper’s senior authors and an assistant professor in the Department of Physiology and Biophysics in the Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo. “When engrams are disrupted, you get amnesia.”

In the minutes and hours that immediately follow an experience, he explains, the brain needs to consolidate the engram to store it. “We wanted to know: What is happening during this consolidation process? What happens between the time that an engram is formed and when you need to recall that memory later?”

The researchers developed a computational model for learning and memory formation that starts with sensory information, which is the stimulus. Once that information gets to the hippocampus, the part of the brain where memories form, different neurons are activated, some of which are excitatory and others that are inhibitory.

When neurons are activated in the hippocampus, not all are going to be firing at once. As memories form, neurons that happen to be activated closely in time become a part of the engram and strengthen their connectivity to support future recall.

“Activation of engram cells during memory recall is not an all or none process but rather typically needs to reach a threshold (i.e., a percentage of the original engram) for efficient recall,” Roy explains. “Our model is the first to demonstrate that the engram population is not stable: The number of engram cells that are activated during recall decreases with time, meaning they are dynamic in nature, and so the next critical question was whether this had a behavioral consequence.”

Dynamic engrams are needed for memory discrimination

“Over the consolidation period after learning, the brain is actively working to separate the two experiences and that’s possibly one reason why the numbers of activated engram cells decrease over time for a single memory,” he says. “If true, this would explain why memory discrimination gets better as time goes on. It’s like your memory of the experience was one big highway initially but over time, over the course of the consolidation period on the order of minutes to hours, your brain divides them into two lanes so you can discriminate between the two.”

Roy and the experimentalists on the team now had a testable hypothesis, which they carried out using a well-established behavioral experiment with mice. Mice were briefly exposed to two different boxes that had unique odors and lighting conditions; one was a neutral environment but in the second box, they received a mild foot shock.

A few hours after that experience, the mice, who typically are constantly moving, exhibited fear memory recall by freezing when exposed to either box. “That demonstrated that they couldn’t discriminate between the two,” Roy says. “But by hour twelve, all of a sudden, they exhibited fear only when they were exposed to the box where they were uncomfortable during their very first experience. They were able to discriminate between the two. The animal is telling us that they know this box is the scary one but five hours earlier they couldn’t do that.”

Using a light-sensitive technique, the team was able to detect active neurons in the mouse hippocampus as the animal was exploring the boxes. The researchers used this technique to tag active neurons and later measure how many were reactivated by the brain for recall. They also conducted experiments that allowed a single engram cell to be tracked across experiences and time. “So I can tell you literally how one engram cell or a subset of them responded to each environment across time and correlate this to their memory discrimination,” explains Roy.”

The team’s initial computational studies had predicted that the number of engram cells involved in a single memory would decrease over time, and the animal experiments bore that out.

“When the brain learns something for the first time, it doesn’t know how many neurons are needed and so on purpose a larger subset of neurons is recruited,” he explains. “As the brain stabilizes neurons, consolidating the memory, it cuts away the unnecessary neurons, so fewer are required and in doing so helps separate engrams for different memories.”

What is happening with memory disorders?

The findings have direct relevance to understanding what is going wrong in memory disorders, such as Alzheimer’s disease. Roy explains that to develop treatments for such disorders, it is critical to know what is happening during the initial memory formation, consolidation and activation of engrams for recall.

“This research tells us that a very likely candidate for why memory dysfunction occurs is that there is something wrong with the early window after memory formation where engrams must be changing,” says Roy.

He is currently studying mouse models of early Alzheimer’s disease to find out if engrams are forming but not being correctly stabilized. Now that more is known about how engrams work to form and stabilize memories, researchers can examine which genes are changing in the animal model when the engram population decreases.

“We can look at mouse models and ask, are there specific genes that are altered? And if so, then we finally have something to test, we can modulate the gene for these ‘ refinement’ or ‘consolidation’ processes of engrams to see if that has a role in improving memory performance,” he says.

Now at the Jacobs School, Roy conducted the research while a McGovern Fellow at the Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University. Roy is one of three neuroscientists recruited to the Jacobs School this year to launch a new focus on systems neuroscience in the school’s Department of Physiology and Biophysics.

Co-authors on the paper are from Imperial College in London; the Institute of Science and Technology in Austria; the McGovern Institute for Brain Research at MIT; and the Center for Life Sciences & IDG/McGovern Institute for Brain Research at Tsinghua University in China.

The work was funded by the President’s PhD Scholarship from Imperial College London; Wellcome Trust; the Biotechnology and Biological Sciences Research Council; the Simons Foundation; the Engineering and Physical Sciences Research Council; the School of Life Sciences and the IDG/McGovern Institute for Brain Research. Roy was supported by the Warren Alpert Distinguished Scholar Award and the National Institutes of Health.

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Scientists find first in human evidence of how memories form

In a discovery that could one day benefit people suffering from traumatic brain injury, Alzheimer's disease, and schizophrenia, UT Southwestern researchers have identified the characteristics of more than 100 memory-sensitive neurons that play a central role in how memories are recalled in the brain.

Bradley Lega, M.D., Associate Professor of Neurological Surgery, Neurology, and Psychiatry, said his findings, published in the journal NeuroImage , may point to new deep brain-stimulation therapies for other brain diseases and injuries.

"It sheds important light on the question, 'How do you know you are remembering something from the past versus experiencing something new that you are trying to remember?'" said Dr. Lega, a member of the Peter O'Donnell Jr. Brain Institute.

The most significant finding was that firing occurs with different timing relative to other brain activity when memories are being retrieved. This slight difference in timing, called "phase offset," has not been reported in humans before. Together, these results explain how the brain can "re-experience" an event, but also keep track of whether the memory is something new or something previously encoded.

"This is some of the clearest evidence to date showing us how the human brain works in terms remembering old memories versus forming new memories," Dr. Lega said.

His study identified 103 memory-sensitive neurons in the brain's hippocampus and entorhinal cortex that increase their rate of activity when memory encoding is successful. The same pattern of activity returned when patients attempted to recall these same memories, especially highly detailed memories.

This activity in the hippocampus may have relevance to schizophrenia because hippocampal dysfunction underlies schizophrenics' inability to decipher between memories and hallucinations or delusions. The neurons identified by Dr. Lega are an important piece of the puzzle for why this happens, said Carol Tamminga, M.D., Professor and Chair of Psychiatry and a national expert on schizophrenia.

"Hallucinations and delusions in people with a psychotic illness are actual memories, processed through neural memory systems like 'normal' memories, even though they are corrupted. It would be important to understand how to use this 'phase offset' mechanism to modify these corrupted memories," Dr. Tamminga said.

An opportunity to learn more about human memory arose from surgeries where electrodes that were implanted in epilepsy's patients' brains to map the patients' seizures could also be used to identify neurons involved in memory. In this study, 27 epilepsy patients who had the electrodes implanted at UT Southwestern and a Pennsylvania hospital participated in memory tasks to generate data for brain research.

The data analysis does not conclusively prove, but adds new credibility to important memory model called Separate Phases at Encoding And Retrieval (SPEAR) that scientists developed from rodent studies.

"It's never been nailed down. It's one thing to have a model; it is another thing to show evidence that this is what's happening in humans," Dr. Lega said.

The SPEAR model, which predicts the "phase offset" reported in the study, was developed to explain how the brain can keep track of new-versus-old experiences when engaged in memory retrieval. Previously, the only evidence in support of SPEAR came from rodent models.

This study was supported by National Institutes of Health grants R01NS125250 and R01NS106611.

Dr. Tamminga holds the Stanton Sharp Distinguished Chair in Psychiatry.

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  • Hye Bin Yoo, Gray Umbach, Bradley Lega. Neurons in the human medial temporal lobe track multiple temporal contexts during episodic memory processing . NeuroImage , 2021; 245: 118689 DOI: 10.1016/j.neuroimage.2021.118689

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What Is Memory?

Reviewed by Psychology Today Staff

Memory is the faculty by which the brain encodes, stores, and retrieves information. It is a record of experience that guides future action.

Memory encompasses the facts and experiential details that people consciously call to mind as well as ingrained knowledge that surface without effort or even awareness. It is both a short-term cache of information and the more permanent record of what one has learned. The types of memory described by scientists include episodic memory, semantic memory , procedural memory , working memory , sensory memory , and prospective memory .

Each kind of memory has distinct uses—from the vivid recollections of episodic memory to the functional know-how of procedural memory. Yet there are commonalities in how memory works overall, and key brain structures, such as the hippocampus, that are integral to different kinds of memory.

In addition to memory’s role in allowing people to understand, navigate, and make predictions about the world, personal memories provide the foundation for a rich sense of one’s self and one’s life—and give rise to experiences such as nostalgia .

To learn more, see Types of Memory , How Memory Works , and Personal Memories and Nostalgia .

research on memory reveals that

Memory loss is the unavoidable flipside of the human capacity to remember. Forgetting, of course, is normal and happens every day: The brain simply cannot retain a permanent record of everything a person experiences and learns. And with advancing age, some decline in memory ability is typical. There are strategies for coping with such loss—adopting memory aids such as calendars and reminder notes, for example, or routinizing the placement of objects at risk of getting lost.

In more severe cases, however, memory can be permanently damaged by dementia and other disorders of memory . Dementia is a loss of cognitive function that can have various underlying causes, the most prominent being Alzheimer’s disease. People with dementia experience a progressive loss of function, such that memory loss may begin with minor forgetfulness (about having recently shared a story, for example) and gradually progress to difficulty with retaining new information, recognizing familiar individuals, and other important memory functions. Professional assessment can help determine whether an individual’s mild memory loss is a function of normal aging or a sign of a serious condition.

Memory disorders also include multiple types of amnesia that result not from diseases such as Alzheimer’s, but from brain injury or other causes. People with amnesia lose the ability to recall past information, to retain new information, or both. In some cases the memory loss is permanent, but there are also temporary forms of amnesia that resolve on their own.

To learn more, see Memory Loss and Disorders of Memory .

research on memory reveals that

Though memory naturally declines with age, many people are able to stay mentally sharp. How do they do it? Genes play a role, but preventative measures including regular exercise, eating a healthy diet , and getting plenty of sleep—as well as keeping the brain active and challenged—can help stave off memory loss.

The science of memory also highlights ways anyone can improve their memory , whether the goal is sharpening memory ability for the long term or just passing exams this semester. Short-term memory tricks include mnemonic devices (such as acronyms and categorization), spacing apart study time, and self-testing for the sake of recalling information. Sleep and exercise are other memory boosters .

Through committed practice with memory-enhancing techniques, some people train themselves to remember amazing quantities of information, such as lengthy sequences of words or digits. For a small number of people, however, extraordinary memory abilities come naturally. These gifted rememberers include savants, for whom powerful memory coincides with some cognitive disability or neurodevelopmental difference, as well as people with typical intellects who remember exceptional quantities of details about their lives.

To learn more, see How to Improve Memory and Extraordinary Memory Abilities .

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Memory is a key element in certain mental health conditions : Abnormal memory function can contribute to distress, or it can coincide with an underlying disorder. Forgetfulness is associated with depression ; connections in memory, such as those involving feared situations or drug-related cues, are an integral part of anxiety and substance use disorders; and post- traumatic symptoms are entwined with the memory of traumatic experiences.

In fact, experiences such as distressing memories and flashbacks are among the core symptoms of post-traumatic stress disorder. For someone with PTSD , a range of cues—including situations, people, or other stimuli related to a traumatic experience in some way—can trigger highly distressing memories, and the person may seek to avoid such reminders.

As a feature of various mental disorders, aberrant or biased memory function can also be a target for treatment. Treatments that involve exposure therapy , for example, are used to help patients reduce the power of trauma-related memories through safe and guided encounters with those memories and stimuli associated with the trauma.

To learn more, see Memory and Mental Health .

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Technology has made our brains more machine-like. What are we losing when they act as human routers rather than for reading, contemplating, critiquing, synthesizing, and retaining?

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New study reveals how brain waves control working memory

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MIT neuroscientists have found evidence that the brain’s ability to control what it’s thinking about relies on low-frequency brain waves known as beta rhythms.

In a memory task requiring information to be held in working memory for short periods of time, the MIT team found that the brain uses beta waves to consciously switch between different pieces of information. The findings support the researchers’ hypothesis that beta rhythms act as a gate that determines when information held in working memory is either read out or cleared out so we can think about something else.  

“The beta rhythm acts like a brake, controlling when to express information held in working memory and allow it to influence behavior,” says Mikael Lundqvist, a postdoc at MIT’s Picower Institute for Learning and Memory and the lead author of the study.

Earl Miller, the Picower Professor of Neuroscience at the Picower Institute and in the Department of Brain and Cognitive Sciences, is the senior author of the study, which appears in the Jan. 26 issue of Nature Communications .

Working in rhythm

There are millions of neurons in the brain, and each neuron produces its own electrical signals. These combined signals generate oscillations known as brain waves, which vary in frequency. In a 2016 study , Miller and Lundqvist found that gamma rhythms are associated with encoding and retrieving sensory information.

They also found that when gamma rhythms went up, beta rhythms went down, and vice versa. Previous work in their lab had shown that beta rhythms are associated with “top-down” information such as what the current goal is, how to achieve it, and what the rules of the task are.

All of this evidence led them to theorize that beta rhythms act as a control mechanism that determines what pieces of information are allowed to be read out from working memory — the brain function that allows control over conscious thought, Miller says.

“Working memory is the sketchpad of consciousness, and it is under our control. We choose what to think about,” he says. “You choose when to clear out working memory and choose when to forget about things. You can hold things in mind and wait to make a decision until you have more information.”

To test this hypothesis, the researchers recorded brain activity from the prefrontal cortex, which is the seat of working memory, in animals trained to perform a working memory task. The animals first saw one pair of objects, for example, A followed by B. Then they were shown a different pair and had to determine if it matched the first pair. A followed by B would be a match, but not B followed by A, or A followed by C. After this entire sequence, the animals released a bar if they determined that the two sequences matched.

The researchers found that brain activity varied depending on whether the two pairs matched or not. As an animal anticipated the beginning of the second sequence, it held the memory of object A, represented by gamma waves. If the next object seen was indeed A, beta waves then went up, which the researchers believe clears object A from working memory. Gamma waves then went up again, but this time the brain switched to holding information about object B, as this was now the relevant information to determine if the sequence matched.

However, if the first object shown was not a match for A, beta waves went way up, completely clearing out working memory, because the animal already knew that the sequence as a whole could not be a match.

“The interplay between beta and gamma acts exactly as you would expect a volitional control mechanism to act,” Miller says. “Beta is acting like a signal that gates access to working memory. It clears out working memory, and can act as a switch from one thought or item to another.”

A new model

Previous models of working memory proposed that information is held in mind by steady neuronal firing. The new study, in combination with their earlier work, supports the researchers’ new hypothesis that working memory is supported by brief episodes of spiking, which are controlled by beta rhythms.

“When we hold things in working memory (i.e. hold something ‘in mind’), we have the feeling that they are stable, like a light bulb that we’ve turned on to represent some thought. For a long time, neuroscientists have thought that this must mean that the way the brain represents these thoughts is through constant activity. This study shows that this isn’t the case — rather, our memories are blinking in and out of existence. Furthermore, each time a memory blinks on, it is riding on top of a wave of activity in the brain,” says Tim Buschman, an assistant professor of psychology at Princeton University who was not involved in the study.

Two other recent papers from Miller’s lab offer additional evidence for beta as a cognitive control mechanism.

In a study that recently appeared in the journal Neuron , they found similar patterns of interaction between beta and gamma rhythms in a different task involving assigning patterns of dots into categories. In cases where two patterns were easy to distinguish, gamma rhythms, carrying visual information, predominated during the identification. If the distinction task was more difficult, beta rhythms, carrying information about past experience with the categories, predominated.

In a recent paper published in the Proceedings of the National Academy of Sciences , Miller’s lab found that beta waves are produced by deep layers of the prefrontal cortex, and gamma rhythms are produced by superficial layers, which process sensory information. They also found that the beta waves were controlling the interaction of the two types of rhythms.

“When you find that kind of anatomical segregation and it’s in the infrastructure where you expect it to be, that adds a lot of weight to our hypothesis,” Miller says.

The researchers are now studying whether these types of rhythms control other brain functions such as attention. They also hope to study whether the interaction of beta and gamma rhythms explains why it is so difficult to hold more than a few pieces of information in mind at once.

“Eventually we’d like to see how these rhythms explain the limited capacity of working memory, why we can only hold a few thoughts in mind simultaneously, and what happens when you exceed capacity,” Miller says. “You have to have a mechanism that compensates for the fact that you overload your working memory and make decisions on which things are more important than others.”

The research was funded by the National Institute of Mental Health, the Office of Naval Research, and the Picower JFDP Fellowship.

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Scientists Pinpoint the Uncertainty of Our Working Memory

The human brain regions responsible for working memory content are also used to gauge the quality, or uncertainty, of memories, a team of scientists has found, uncovering how these neural responses allow us to act and make decisions based on how sure we are about our memories.

New Study Shows the Extent We Trust Our Memory in Decision-Making

The human brain regions responsible for working memory content are also used to gauge the quality, or uncertainty, of memories, a team of scientists has found. Its study uncovers how these neural responses allow us to act and make decisions based on how sure we are about our memories.

“Access to the uncertainty in our working memory enables us to determine how much to ‘trust’ our memory in making decisions,” explains Hsin-Hung Li, a postdoctoral fellow in New York University’s Department of Psychology and Center for Neural Science and the lead author of the paper , which appears in the journal Neuron . “Our research is the first to reveal that the neural populations that encode the content of working memory also represent the uncertainty of memory.”

Working memory, which enables us to maintain information in our minds, is an essential cognitive system that is involved in almost every aspect of human behavior—notably decision-making and learning. 

For example, when reading, working memory allows us to store the content we just read a few seconds ago while our eyes keep scanning through the new sentences. Similarly, when shopping online, we may compare, “in our mind,” the item in front of us on the screen with previous items already viewed and still remembered. 

“It is not only crucial for the brain to remember things, but also to weigh how good the memory is: How certain are we that a specific memory is accurate?” explains Li. “If we feel that our memory for the previously viewed online item is poor, or uncertain, we would scroll back and check that item again in order to ensure an accurate comparison.”

While studies on human behaviors have shown that people are able to evaluate the quality of their memory, less clear is how the brain achieves this. 

More specifically, it had previously been unknown whether the brain regions that hold the memorized item also register the quality of that memory.

In uncovering this, the researchers conducted a pair of experiments to better understand how the brain stores working memory information and how, simultaneously, the brain represents the uncertainty—or, how good the memory is—of remembered items. 

In the first experiment, human participants performed a spatial visual working memory task while a functional magnetic resonance imaging (fMRI) scanner recorded their brain activity. For each task, or trial, the participant had to remember the location of a target—a white dot shown briefly on a computer screen—presented at a random location on the screen and later report the remembered location through eye movement by looking in the direction of the remembered target location.

Here, fMRI signals allowed the researchers to decode the location of the memory target—what the subjects were asked to remember—in each trial. By analyzing brain signals corresponding to the time during which participants held their memory, they could determine the location of the target the subjects were asked to memorize. In addition, through this method, the scientists could accurately predict memory errors made by the participants; by decoding their brain signals, the team could determine what the subjects were remembering and therefore spot errors in their recollections.  

In the second experiment, the participants reported not only the remembered location, but also how uncertain they felt about their memory in each trial. The resulting fMRI signals recorded from the same brain regions allowed the scientists to decode the uncertainty reported by the participants about their memory. 

Taken together, the results yielded the first evidence that the human brain registers both the content and the uncertainty of working memory in the same cortical regions.

“The knowledge of uncertainty of memory also guides people to seek more information when we are unsure of our own memory,” Li says in noting the utility of the findings.

The study’s other researchers included Wei Ji Ma and Clayton Curtis, professors in NYU’s Department of Psychology; Thomas Sprague, an NYU postdoctoral researcher at the time of the study and now an assistant professor at the University of California, Santa Barbara; and Aspen Yoo, an NYU doctoral student at the time of the study and now a postdoctoral fellow at the University of California, Berkeley.

The research was supported by grants from the National Eye Institute (NEI) (R01 EY-016407, R01 EY-027925, F32 EY-028438) and the NEI Visual Neuroscience Training Program (T32-EY007136).

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  • NEWS FEATURE
  • 20 February 2024

Mind-reading devices are revealing the brain’s secrets

  • Miryam Naddaf

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Scientists have studied how brain–computer interfaces, such as this non-invasive cap, change brain activity. Credit: Silvia Marchesotti

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Moving a prosthetic arm. Controlling a speaking avatar. Typing at speed. These are all things that people with paralysis have learnt to do using brain–computer interfaces (BCIs) — implanted devices that are powered by thought alone.

These devices capture neural activity using dozens to hundreds of electrodes embedded in the brain. A decoder system analyses the signals and translates them into commands.

Although the main impetus behind the work is to help restore functions to people with paralysis , the technology also gives researchers a unique way to explore how the human brain is organized, and with greater resolution than most other methods.

Scientists have used these opportunities to learn some basic lessons about the brain. Results are overturning assumptions about brain anatomy, for example, revealing that regions often have much fuzzier boundaries and job descriptions than was thought. Such studies are also helping researchers to work out how BCIs themselves affect the brain and, crucially, how to improve the devices.

“BCIs in humans have given us a chance to record single-neuron activity for a lot of brain areas that nobody’s ever really been able to do in this way,” says Frank Willett, a neuroscientist at Stanford University in California who is working on a BCI for speech.

The devices also allow measurements over much longer time spans than classical tools do, says Edward Chang, a neurosurgeon at the University of California, San Francisco. “BCIs are really pushing the limits, being able to record over not just days, weeks, but months, years at a time,” he says. “So you can study things like learning, you can study things like plasticity, you can learn tasks that require much, much more time to understand.”

Recorded history

The idea that the electrical activity of the human brain could be recorded first gained support 100 years ago. German psychiatrist Hans Berger attached electrodes to the scalp of a 17-year-old boy whose surgery for a brain tumour had left a hole in his skull. When Berger recorded above this opening, he made the first observation of brain oscillations and gave the measurement a name: the EEG (electroencephalogram).

Researchers immediately saw that recording from inside the brain could be even more valuable; Berger and others used surgery to place electrodes on the surface of the cortex to study the brain and diagnose epilepsy. Recording from implanted electrodes is still a standard method for pinpointing where epileptic seizures begin, so that the condition can be treated using surgery.

research on memory reveals that

The brain-reading devices helping paralysed people to move, talk and touch

Then, in the 1970s, researchers began to use signals recorded from further inside animal brains to control external machines, giving rise to the first implanted brain–machine interfaces.

In 2004, Matt Nagle, who was paralysed after a spinal injury, became the first person to receive a long-term invasive BCI system that used multiple electrodes to record activity from individual neurons in his primary motor cortex 1 . Nagle was able to use his system to open and close a prosthetic hand, and to perform basic tasks with a robotic arm.

Researchers have also used EEG readings — collected using non-invasive electrodes placed on a person’s scalp — to provide signals for BCIs. These have allowed paralysed people to control wheelchairs, robotic arms and gaming devices, but the signals are weaker and the data less reliable than with invasive devices.

So far, about 50 people have had a BCI implanted, and advances in artificial intelligence, decoding tools and hardware have propelled the field forwards.

Electrode arrays, for instance, are becoming more sophisticated. A technology called Neuropixels has not yet been incorporated into a BCI, but is in use for fundamental research. The array of silicon electrodes, each thinner than a human hair, has nearly 1,000 sensors and is capable of detecting electrical signals from a single neuron. Researchers began using Neuropixels arrays in animals seven years ago, and two papers published in the past three months demonstrate their use for questions that can be answered only in humans : how the brain produces and perceives vowel sounds in speech 2 , 3 .

Commercial activity is also ramping up. In January, the California-based neurotechnology company Neuralink, founded by entrepreneur Elon Musk, i mplanted a BCI into a person for the first time . As with other BCIs, the implant can record from individual neurons, but unlike other devices, it has a wireless connection to a computer

And although the main driver is clinical benefit, these windows into the brain have revealed some surprising lessons about its function along the way.

Fuzzy boundaries

Textbooks often describe brain regions as having discrete boundaries or compartments. But BCI recordings suggest that this is not always the case.

Last year, Willett and his team were using a BCI implant for speech generation in a person with motor neuron disease (amyotrophic lateral sclerosis). They expected to find that neurons in a motor control area called the precentral gyrus would be grouped depending on which facial muscles they were tuned to — jaw, larynx, lips or tongue. Instead, neurons with different targets were jumbled up 4 . “The anatomy was very intermixed,” says Willett.

They also found that Broca’s area, a brain region thought to have a role in speech production and articulation, contained little to no information about words, facial movements or units of sound called phonemes. “It seems surprising that it’s not really involved in speech production per se,” says Willett. Previous findings using other methods had hinted at this more nuanced picture (see, for example, ref. 5).

Frank Willett working at a computer with a participant who has a brain implant that interprets her attempts at speech into words on the computer screen

Researcher Frank Willett operates software that translates Pat Bennett’s attempts at speech into words on a screen, through a BCI. Credit: Steve Fisch/Stanford Medicine

In a 2020 paper about motion 6 , Willett and his colleagues recorded signals in two people with different levels of movement limitation, focusing on an area in the premotor cortex that is responsible for moving the hands. They discovered while using a BCI that the area contains neural codes for all four limbs together, not just for the hands, as previously presumed. This challenges the classical idea that body parts are represented in the brain’s cortex in a topographical map, a theory that has been embedded in medical education for nearly 90 years.

“That’s something that you would only see if you’re able to record single-neuron activity from humans, which is so rare,” says Willett.

Nick Ramsey, a cognitive neuroscientist at University Medical Center Utrecht in the Netherlands, made similar observations when his team implanted a BCI in a part of the motor cortex that corresponds to hand movement 7 . The motor cortex in one hemisphere of the brain typically controls movements on the opposite side of the body. But when the person attempted to move her right hand, electrodes implanted in the left hemisphere picked up signals for both the right hand and the left hand, a finding that was unexpected, says Ramsey. “We’re trying to find out whether that’s important” for making movements, he says.

research on memory reveals that

The rise of brain-reading technology: what you need to know

Movement relies on a lot of coordination, and brain activity has to synchronize it all, explains Ramsey. Holding out an arm affects balance, for instance, and the brain has to manage those shifts across the body, which could explain the dispersed activity. “There’s a lot of potential in that kind of research that we haven’t thought of before,” he says.

To some scientists, these fuzzy anatomical boundaries are not surprising. Our understanding of the brain is based on average measurements that paint a generalized image of how this complex organ is arranged, says Luca Tonin, an information engineer at the University of Padua in Italy. Individuals are bound to diverge from the average.

“Our brains look different in the details,” says Juan Álvaro Gallego, a neuroscientist at Imperial College London.

To others, findings from such a small number of people should be interpreted with caution. “We need to take everything that we’re learning with a grain of salt and put it in context,” says Chang. “Just because we can record from single neurons doesn’t mean that’s the most important data, or the whole truth.”

Flexible thinking

BCI technology has also helped researchers to reveal neural patterns of how the brain thinks and imagines.

Christian Herff, a computational neuroscientist at Maastricht University, the Netherlands, studies how the brain encodes imagined speech. His team developed a BCI implant capable of generating speech in real time when participants either whisper or imagine speaking without moving their lips or making a sound 8 . The brain signals picked up by the BCI device in both whispered and imagined speech were similar to those for spoken speech. They share areas and patterns of activity, but are not the same, explains Herff.

That means, he says, that even if someone can’t speak, they could still imagine speech and work a BCI. “This drastically increases the people who could use such a speech BCI on a clinical basis,” says Herff.

The fact that people with paralysis retain the programmes for speech or movement, even when their bodies can no longer respond, helps researchers to draw conclusions about how plastic the brain is — that is, to what extent it can reshape and remodel its neural pathways.

It is known that injury, trauma and disease in the brain can alter the strength of connections between neurons and cause neural circuits to reconfigure or make new connections. For instance, work in rats with spinal cord injuries has shown that brain regions that once controlled now-paralysed limbs can begin to control parts of the body that are still functional 9 .

But BCI studies have muddied this picture. Jennifer Collinger, a neural engineer at the University of Pittsburgh in Pennsylvania, and her colleagues used an intracortical BCI in a man in his 30s who has a spinal cord injury. He can still move his wrist and elbow, but his fingers are paralysed.

Collinger’s team noticed that the original maps of the hand were preserved in his brain 10 . When the man attempted to move his fingers, the team saw activity in the motor area, even though his hand did not actually move.

Close up on the head of a patient with a brain implant about to be connected to a computer

Brain–computer interface technology is helping people with paralysis to speak — and providing lessons about brain anatomy. Credit: Mike Kai Chen/The New York Times/Redux/eyevine

“We see the typical organization,” she says. “Whether they have changed at all before or after injury, slightly, we can’t really say.” That doesn’t mean the brain isn’t plastic, Collinger notes. But some brain areas might be more flexible in this regard than others. “For example, plasticity seems to be more limited in sensory cortex compared to motor cortex,” she adds.

In conditions in which the brain is damaged, such as stroke, BCIs can be used alongside other therapeutic interventions to help train a new brain area to take over from a damaged region. In such situations, “people are performing tasks by modulating areas of the brain that originally were not evolved to do so”, says José del R. Millán, a neural engineer at the University of Texas at Austin, who studies how to deploy BCI-induced plasticity in rehabilitation.

In a clinical trial, Millán and his colleagues trained 14 participants with chronic stroke — a long-term condition that begins 6 months or more after a stroke, marked by a slowdown in the recovery process — to use non-invasive BCIs for 6 weeks 11 .

research on memory reveals that

Abandoned: the human cost of neurotechnology failure

In one group, the BCI was connected to a device that applied electric currents to activate nerves in paralysed muscles, a therapeutic technique known as functional electrical stimulation (FES). Whenever the BCI decoded the participants’ attempts to extend their hands, it stimulated the muscles that control wrist and finger extension. Participants in the control group had the same set-up, but received random electrical stimulation.

Using EEG imaging, Millán’s team found that the participants using BCI-guided FES had increased connectivity between motor areas in the affected brain hemisphere compared with the control group. Over time, the BCI–FES participants became able to extend their hands, and their motor recovery lasted for 6–12 months after the end of the BCI-based rehabilitation therapy.

What BCIs do to the brain

In Millán’s study, the BCI helped to drive learning in the brain. This feedback loop between human and machine is a key element of BCIs, which can allow direct control of brain activity. Participants can learn to adjust their mental focus to improve the decoder’s output in real time.

Whereas most research focuses on optimizing BCI devices and improving their coding performance, “little attention has been paid to what actually happens in the brain when you use the thing”, says Silvia Marchesotti, a neuroengineer at the University of Geneva, Switzerland.

Marchesotti studies how the brain changes when people use a BCI for language generation — looking not just in the regions where the BCI sits, but more widely. Her team found that, when 15 healthy participants were trained to control a non-invasive BCI over 5 days, activity across the brain increased in frequency bands known to be important for language and became more focused over time 12 .

One possible explanation could be that the brain becomes more efficient at controlling the device and requires fewer neural resources to do the tasks, says Marchesotti.

Studying how the brain behaves during BCI use is an emerging field, and researchers hope it will both benefit the user and improve BCI systems. For example, recording activity across the brain allows scientists to detect whether extra electrodes are needed in other decoding sites to improve accuracy.

Understanding more about brain organization could help to build better decoders and prevent them making errors. In a preprint posted last month 13 , Ramsey and his colleagues showed that a speech decoder can become confused between a user speaking a sentence and listening to it. They implanted BCIs in the ventral sensorimotor cortex — an area commonly targeted for speech decoding — in five people undergoing epilepsy surgery. They found that patterns of brain activity seen when participants spoke a set of sentences closely resembled those observed when they listened to a recording of the same sentences. This implies that a speech decoder might not be able to differentiate between heard and spoken words when trying to generate speech.

The scope of current BCI research is still limited, with trials recruiting a very small number of participants and focusing mainly on brain regions involved in motor function.

“You have at least tenfold as many researchers working on BCIs as you have patients using BCIs,” says Herff.

Researchers value the rare chances to record directly from human neurons, but they are driven by the need to restore function and meet medical needs. “This is neurosurgery,” says Collinger. “It’s not to be taken lightly.”

To Chang, the field naturally operates as a blend of discovery and clinical application. “It’s hard for me to even imagine what our research would be like if we were just doing basic discovery or only doing the BCI work alone,” he says. “It seems that both really are critical for moving the field forwards.”

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Scientists Uncover Brain Signals for Good Memory Performance

By University of Basel September 27, 2023

Brain Memory Concept

Researchers at the University of Basel found a direct link between activity in certain brain regions like the hippocampus and memory performance, using the world’s largest functional imaging study on memory, involving nearly 1,500 participants. The findings, which revealed stronger brain activation in individuals with better memory, could impact future research linking biological characteristics to brain signals.

Individuals exhibit substantial variations in their memory capabilities. A study by the University of Basel has now identified a connection between specific brain signals and these differences in memory performance.

Although it is established that particular areas of the brain are essential for memory functions, it has remained unclear whether these regions demonstrate varying activity levels related to the storage of information in individuals with differing memory performance levels.

Having investigated this matter, a research team led by Professor Dominique de Quervain and Professor Andreas Papassotiropoulos has now published its results in the journal  Nature Communications .

In the world’s largest functional imaging study on memory, they asked nearly 1,500 participants between the ages of 18 and 35 to look at and memorize a total of 72 images. During this process, the researchers recorded the subjects’ brain activity using MRI. The participants were then asked to recall as many of the images as possible – and as in the general population, there were considerable differences in memory performance among them.

Signals in brain regions and networks

In certain brain regions including the hippocampus, the researchers found a direct association between brain activity during the memorization process and subsequent memory performance. Individuals with a better memory showed a stronger activation of these brain areas. No such association was found for other memory-relevant brain areas in the occipital cortex – they were equally active in individuals with all levels of memory performance.

Functional Networks Associated With Individual Differences in Memory Performance

Functional networks associated with individual differences in memory performance. Credit: MCN, University of Basel

The researchers were also able to identify functional networks in the brain that were linked to memory performance. These networks comprise different brain regions that communicate with each other to enable complex processes such as the storage of information.

“The findings help us to better understand how differences in memory performance occur between one individual and another,” said Dr. Léonie Geissmann, the study’s first author, adding that the brain signals of a single individual do not allow for any conclusions to be drawn about their memory performance, however.

According to the researchers, the results are of great importance for future research aimed at linking biological characteristics such as genetic markers to brain signals.

Basel-based research on memory

The current study forms part of a large-scale research project conducted by the Research Cluster Molecular and Cognitive Neurosciences (MCN) at the University of Basel’s Department of Biomedicine and the University Psychiatric Clinics (UPK) Basel. The aim of this project is to gain a better understanding of memory processes and to transfer the findings from basic research into clinical applications.

Reference: “Neurofunctional underpinnings of individual differences in visual episodic memory performance” by Léonie Geissmann, David Coynel, Andreas Papassotiropoulos and Dominique J. F. de Quervain, 14 September 2023, Nature Communications . DOI: 10.1038/s41467-023-41380-w

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New study reveals how brain waves control working memory

MIT neuroscientists have found evidence that the brain’s ability to control what it’s thinking about relies on low-frequency brain waves known as beta rhythms.

In a memory task requiring information to be held in working memory for short periods of time, the MIT team found that the brain uses beta waves to consciously switch between different pieces of information. The findings support the researchers’ hypothesis that beta rhythms act as a gate that determines when information held in working memory is either read out or cleared out so we can think about something else.  

“The beta rhythm acts like a brake, controlling when to express information held in working memory and allow it to influence behavior,” says Mikael Lundqvist, a postdoc at MIT’s Picower Institute for Learning and Memory and the lead author of the study.

Earl Miller, the Picower Professor of Neuroscience at the Picower Institute and in the Department of Brain and Cognitive Sciences, is the senior author of the study, which appears in the Jan. 26 issue of Nature Communications .

Working in rhythm

There are millions of neurons in the brain, and each neuron produces its own electrical signals. These combined signals generate oscillations known as brain waves, which vary in frequency. In a 2016 study , Miller and Lundqvist found that gamma rhythms are associated with encoding and retrieving sensory information.

They also found that when gamma rhythms went up, beta rhythms went down, and vice versa. Previous work in their lab had shown that beta rhythms are associated with “top-down” information such as what the current goal is, how to achieve it, and what the rules of the task are.

All of this evidence led them to theorize that beta rhythms act as a control mechanism that determines what pieces of information are allowed to be read out from working memory — the brain function that allows control over conscious thought, Miller says.

“ Working memory is the sketchpad of consciousness, and it is under our control. We choose what to think about,” he says. “You choose when to clear out working memory and choose when to forget about things. You can hold things in mind and wait to make a decision until you have more information.”

To test this hypothesis, the researchers recorded brain activity from the prefrontal cortex, which is the seat of working memory, in animals trained to perform a working memory task. The animals first saw one pair of objects, for example, A followed by B. Then they were shown a different pair and had to determine if it matched the first pair. A followed by B would be a match, but not B followed by A, or A followed by C. After this entire sequence, the animals released a bar if they determined that the two sequences matched.

The researchers found that brain activity varied depending on whether the two pairs matched or not. As an animal anticipated the beginning of the second sequence, it held the memory of object A, represented by gamma waves. If the next object seen was indeed A, beta waves then went up, which the researchers believe clears object A from working memory. Gamma waves then went up again, but this time the brain switched to holding information about object B, as this was now the relevant information to determine if the sequence matched.

However, if the first object shown was not a match for A, beta waves went way up, completely clearing out working memory, because the animal already knew that the sequence as a whole could not be a match.

“T he interplay between beta and gamma acts exactly as you would expect a volitional control mechanism to act,” Miller says. “Beta is acting like a signal that gates access to working memory. It clears out working memory, and can act as a switch from one thought or item to another.”

A new model

Previous models of working memory proposed that information is held in mind by steady neuronal firing. The new study, in combination with their earlier work, supports the researchers’ new hypothesis that working memory is supported by brief episodes of spiking, which are controlled by beta rhythms. Two other recent papers from Miller’s lab offer additional evidence for beta as a cognitive control mechanism.

In a study that recently appeared in the journal Neuron , they found similar patterns of interaction between beta and gamma rhythms in a different task involving assigning patterns of dots into categories. In cases where two patterns were easy to distinguish, gamma rhythms, carrying visual information, predominated during the identification. If the distinction task was more difficult, beta rhythms, carrying information about past experience with the categories, predominated.

In a recent paper published in the Proceedings of the National Academy of Sciences , Miller’s lab found that beta waves are produced by deep layers of the prefrontal cortex, and gamma rhythms are produced by superficial layers, which process sensory information. They also found that the beta waves were controlling the interaction of the two types of rhythms.

“When you find that kind of anatomical segregation and it’s in the infrastructure where you expect it to be, that adds a lot of weight to our hypothesis,” Miller says.

The researchers are now studying whether these types of rhythms control other brain functions such as attention. They also hope to study whether the interaction of beta and gamma rhythms explains why it is so difficult to hold more than a few pieces of information in mind at once.

“Eventually we’d like to see how these rhythms explain the limited capacity of working memory, why we can only hold a few thoughts in mind simultaneously, and what happens when you exceed capacity,” Miller says. “You have to have a mechanism that compensates for the fact that you overload your working memory and make decisions on which things are more important than others.”

The research was funded by the National Institute of Mental Health, the Office of Naval Research, and the Picower JFDP Fellowship.

MIT News story

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How to improve your memory for the things that matter, a new book explains how our brains selectively remember and forget, and how to use that knowledge to our advantage. 
.

Have you ever forgotten a lunch date and stood up a good friend? This can be embarrassing and disconcerting, a potential sign that your memory just isn’t what it used to be.

But, according to a new book by researcher Charan Ranganath, Why We Remember , this kind of gaffe is less about a faulty memory and more an artifact of how memory works.

“Although we tend to believe that we can and should remember anything we want, the reality is we are designed to forget,” he says.

research on memory reveals that

As Ranganath explains, our memory isn’t just a repository for everything that’s ever happened to us; it’s much more fluid than that, affected by the context of our past experiences as well as what’s happening in the present moment. Because our lives are full of incoming sensory information and our reactions to it, the laying down of a memory needs to be a competitive process, with priority given to more important, novel, or salient experiences at the expense of others. That’s why we might forget about our lunch date in the midst of a pressing work deadline.

Ranganath argues that if we understand how and why we remember things, we’ll be better prepared to use our memories wisely. And, he writes, this is important, as memory plays a pretty all-encompassing role in nearly every aspect of our lives.

“[Memories] are the driving force behind life-changing decisions, from what career to pursue and where to live to what causes you believe in, even how you raise your children and what sort of people you want around you,” he says.

How memory works

Because memory is so important, many parts of our brains are involved in creating memories—most notably, the hippocampus and prefrontal cortex—working together to help keep track of our lives and make future predictions.

The hippocampus is the primary center of memory, laying down “episodic memories,” based on specific experiences within particular contexts (such as when and where something occurred). Because it uses context to index a memory, the hippocampus plays a role in orienting us in time and space. This means people with damage to the hippocampus, such as those with Alzheimer’s, have trouble with getting lost and are often disoriented. However, even with an intact hippocampus, you might wake up in a strange hotel room and feel disoriented for a moment. The difference is that you can quickly draw on episodic memory to recall why you’re there.

Recalling episodic memories allows you to “time travel,” in a way, re-experiencing feelings and thoughts you had at different times in your life. Because they are context-driven, these memories can be triggered by putting yourself in a similar context to where an event occurred. For example, you might walk into your childhood home and smell your mother’s cooking and be transported to a powerful memory of eating dinner with your parents when you were a child (and the good or bad of that experience). Music is also a powerful way to stir up episodic memories , with songs from our teen to early adult years being particularly potent.

Current emotions affect memory, too, says Ranganath, so that feeling sad may lead to recalling sad memories. And you can affect your feelings in the present by recalling the past, such as when you think back nostalgically about a trip you took abroad and relive the happy memories. Research suggests that reminiscing can be good for your mood and sense of self, if you focus on positive memories (which, fortunately, are easier to recall). And, if we recall past experiences of being generous, for example, it can make us more generous in the present.

The prefrontal cortex is also important for memory, especially “semantic memory”—the consolidation of memories from the past that can be used to understand our present self and our circumstances and to make predictions. It’s implicated in learning and in directing our behavior, helping us to navigate our lives. So, while the hippocampus might contain memories of the many places we’ve left our house keys in the past, the prefrontal cortex might recognize a pattern in those memories and help us know where to look for a lost pair. It may also notice a pattern of memory lapses, signaling us to be more careful in the future.

In that way, the prefrontal cortex assists in weeding what we can let go of from what we most need to know, helping us make good choices.

“The human brain is not a memorization machine; it’s a thinking machine,” says Ranganath. “We organize our experiences in ways that allow us to make sense of the world we live in.”

How to improve memory for things we want to remember

The important thing isn’t to remember everything, writes Ranganath, but to remember what we most value. Luckily, there are many ways we can improve our memory for things that matter to us.

Taking good care of our physical bodies (getting enough food, exercise, and rest, for example) will improve our brain health generally, and so improve memory, says Ranganath. But we can also use the nature of memory to make certain memories stand out.

Events are more memorable when they are novel or surprising. So, if we want to draw on a memory later, we can focus more on unexpected things in an experience. For example, going to a new restaurant with your romantic partner will make the experience more memorable than going to a favorite hangout, where you often dine. And, since we tend to remember events imbued with stronger emotions—higher highs and lower lows—that can also play a role in creating a lasting memory.

When it comes to learning, we can use mnemonic devices to remember things that may otherwise be difficult to recall, such as using the phrase “King Philip came over for good spaghetti” to remember taxonomy categories (kingdom, phylum, class, order, family, genus, species). Chunking large bits of information into more manageable pieces—a trick often used by memory savants—can also be useful, says Ranganath. It’s the reason our phone numbers and social security numbers are broken up into three sections, to make them easier to remember.

However, memory isn’t just about recall; it’s about thinking through things and seeing connections between disparate elements. So, our brains are designed to organize memories into fuller narratives or schemas that help us make sense of the present and know what to do. This is why a seasoned basketball player can “read” their opponents’ positions on the court and instantly initiate the right play. Schemas formed through past experiences of thousands of plays on the court help them predict what will happen in the future if they make a particular move.

Memory also isn’t as objective and unchanging as we think, in part because our brains reconstruct a memory each time it’s recollected. While memories may be based on bits and pieces of what actually occurred in the past, they can also be embellished by our minds, based on what we think probably happened or what we imagine could have happened. This is why two people can remember something they experienced together so differently—something that can be both entertaining and exasperating.

“Each time we revisit the past in our minds, we bring with us information from the present that can subtly, and even profoundly, . . . alter the content of our memories,” says Ranganath. “Consequently, every time we recall an experience, what we remember is suffused with the residue of the last time we remembered it.”

Factors like how recently something happened, how much something is repeated, and how we are feeling at the time will change how well we recall a memory. Also, the people around us can affect our memory for an event, by either sharing their own memory (which may contradict ours) or by their expectations of how an event should be remembered. That’s why two people witnessing a street fight may see different things occurring, but eventually come to have similar memories about what happened. Their memories influence each other, more so if they talk it through after the fact.

Being able to update our memories when we get new information is not a bug but a feature of memory. Unfortunately, that means memory can be easily corrupted, too, says Ranganath. For example, eyewitness accounts of crimes can be influenced by the kinds of leading questions witnesses are asked by law enforcement and by their feelings of fear or stress in the moment. That can lead someone to mistake an innocent person for a criminal, with terrible consequences. Similarly, there are many cases of people who’ve confessed to a crime simply because they became convinced through coercion that they shouldn’t trust their own memory of what happened.

While we can (and do) use our memory to remember important lessons from life and make good decisions, we must also be humble when it comes to our memory. By understanding the way memory works, we can learn to strengthen it for the things we need to know and to avoid some of the pitfalls.

“When we get to know the remembering self, we can seize the opportunity to play an active role in our remembering, freeing ourselves from the shackles of the past, and instead using the past to guide us toward a better future,” says Ranganath.

About the Author

Jill suttie.

Jill Suttie, Psy.D. , is Greater Good ’s former book review editor and now serves as a staff writer and contributing editor for the magazine. She received her doctorate of psychology from the University of San Francisco in 1998 and was a psychologist in private practice before coming to Greater Good .

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Why you’re always forgetting things, according to a memory scientist

Neuroscientist charan ranganath offers a scientifically robust rationale to accept that we can’t remember everything.

research on memory reveals that

“Why drag about this corpse of your memory,” Emerson offered in “Self-Reliance.” It was an invitation to let go of past beliefs and things once said aloud — indeed, former versions of ourselves — for the sake of reinvention. The transcendentalist preacher’s son even once told his daughter Ellen that it was “a vice to remember,” hoping to get her to stop fixating on mistakes she’d made in her homework.

These days, most of us are instead trying to remember, whether it’s where we left our car keys or reading glasses or who the president of Mexico is. Semantic memory, the ability to recall facts and figures, differs from episodic memory, the ability to travel back to the past in our minds and re-create — however hazily — a scene. The latter relies on imagination, writes neuroscientist and clinical psychologist Charan Ranganath in his new book, “ Why We Remember: Unlocking Memory’s Power to Hold on to What Matters .” Each time we recall past episodes, we reconstruct them anew, “like hitting ‘play’ and ‘record’ at the same time,” he writes. This explains some of the ways memory fails us, whether witnesses erroneously led to think a person in a lineup snatched a purse, or unintentional plagiarism. (Ranganath, who is also a musician, believes it’s plausible that George Harrison truly didn’t realize he ripped off the melody of “He’s So Fine” while writing “My Sweet Lord.”)

“To forget is to be human,” Ranganath asserts. His book largely seeks to reassure the reader, with lucid and rigorous explanations of the relevant neuroscience, that much of our everyday forgetting is just fine. The problems we have with memory — and we have many — arise, instead, from our expectation that it will be accurate and photographic instead of creative and impressionistic. Our minds render the past in surrealist montages, not as cinéma verité; we are more Willem de Kooning than Dorothea Lange.

Evolution made us this way, Ranganath tells us — though he does so without examining what might distinguish the memory-making of humans from that of, say, elephants or crows. Experiences that are the most distinctive, the most emotionally arousing and the most linked to our survival — threats, nourishment, the possibility to reproduce — stay with people more readily. We lose track of things like our house keys because we use them so routinely that the many instances of key placement interfere with one another, such that yesterday’s instance of an everyday event has little staying power in the mind. Traumatic memories that linger, by contrast, function as warnings to avoid those same dangers in the future — something early humans needed.

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Many of the book’s verdicts about how memory manifests are intuitive, if not obvious: A smell or a song can cue up lost episodes from the past, something Proust knew a century ago when he placed the madeleines in Marcel’s tea. When we put down the camera and soak in all the sensory details, we’re more likely to hold an event in our minds than if we see it through the lens. But Ranganath’s book shines when it’s illuminating how this all works in the brain. His descriptions of complex studies are entertaining and clarifying, and he vividly paints the intellectual history of the science of memory, including how prevailing notions have been unseated over time by experimental research. He’s a generous, humble narrator, telling us about the bets he lost with other scientists whose hypotheses he had dismissed. He describes scientific progress — accurately — not as a product of singular geniuses but as arising “from the collective work of a diverse community.” His self-deprecation adds to his credibility and notably contrasts with the self-aggrandizing tone in many trade books written by scientists.

This is not a book about becoming a memory champion (for that, see “Moonwalking With Einstein,” by Joshua Foer), nor is it a book about avoiding dementia and other memory disorders. But, with a few exceptions — most notably, when he’s discussing the veterans he has counseled who suffer from post-traumatic stress disorder — Ranganath implies that more remembering would be better . But what about the usefulness of forgetting? When should we remember, and when should we try to forget? And do we have a choice? We know that nostalgia can be a way to linger in the past instead of embracing the realities of the present or the possibilities of the future. Past grievances can keep entire societies from escaping cycles of violence. And on a personal level, don’t we have good reasons to leave behind past notions of self, to constantly reimagine who we are for the sake of living fuller and more creative lives?

When the author Lewis Hyde contemplated such questions through the prism of literature, history and art in his book “A Primer for Forgetting” (2019), he noted that Jorge Luis Borges, who believed that imagination required a blend of memory and oblivion, longed for the liberty to forget himself to be someone new. The composer John Cage used the I Ching’s chance operations to forget known melodies and invent new sequences of notes he hoped people could listen to with more aliveness instead of anticipation. (This also hedged against the risk of even subconscious plagiarism.) Hyde posited that creativity might require forgetting. Ranganath briefly touches on this when he describes a study showing that people with higher performance on creative thinking tests were more susceptible to being implanted with false memories. But his readers won’t get an understanding of how neuroscience substantiates or challenges the intuitions of Borges and Cage, nor of how memory might hinder or aid their own creativity.

Ranganath does make a brief case that human artists will always outshine AI artists because they draw on varied influences — a notion that becomes more tenuous as AI advances continue to stun. But he leaves aside the question of whether we should be reevaluating the purposes of memory amid technological change. Emerson treated his notebooks as an external memory bank, not knowing that one day people would size up their computers by their working memory. Should we keep ceding more memory tasks to smartphone cameras and artificial intelligence, or do we need to keep training our minds to enhance our semantic and episodic memory?

What’s most compelling about “Why We Remember” is that it offers a scientifically robust rationale to accept with grace that, no matter what happens in this new world, we will not remember everything we want. Memory research makes clear that there is no use in fighting the tide of forgetting that leaves some memories ashore even as it sweeps away — mercifully, at times — the rest.

Bina Venkataraman is The Washington Post’s columnist covering the future. She was previously editorial page editor of the Boston Globe and since 2011 has taught at MIT. She is the author of “The Optimist’s Telescope: Thinking Ahead in a Reckless Age.”

Why We Remember

Unlocking Memory’s Power to Hold on to What Matters

By Charan Ranganath

Doubleday. 291 pp. $30

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A new study finds the memory systems that give trivia champions an edge.

Don

Memory is complicated. A new study co-authored by Jeopardy! contestant Monica Thieu looks at how two different memory systems might give some people an edge with recalling facts.

DON GONYEA, HOST:

I'll take episodic semantic linkage for $1,000, please, Ken. What makes some people "Jeopardy!" champions and others unable to remember, for example, when the first U.S. dollar was printed? What is the subject of our next interview? Monica Thieu is a multi-time "Jeopardy!" contestant and co-author, along with Lauren Wilkins and Mariam Aly, of a new study looking at how links between two memory systems may give trivia experts an edge. Monica Thieu joins me now. Hi there.

MONICA THIEU: Hi.

GONYEA: OK, let's start with a quiz - a quick one. When was the first U.S. dollar printed?

THIEU: Oh, gosh. Great choice of a question that I don't actually know the answer to.

GONYEA: 1862.

THIEU: Ah, yeah.

GONYEA: (Laughter).

THIEU: That's one of those questions where you think the reason you're asking this is because the answer is not what you think it is. And so you got to say something.

GONYEA: So what got you interested in studying trivia and memory?

THIEU: What it really started was I really wanted to have a research study where I could convince Ken Jennings to come and get his brain scanned. And that's still hasn't happened yet. So the opportunity is still out there. But as I started learning more about how memory works from the sort of technical, cognitive psychology perspective, I started wondering, hey, we define memory often as these two mostly separate systems - episodic memory, which is like our memory for things that happen to us in the world that often comes with when you close your eyes, in your mind's eye, and you think about, you know, getting lunch with a friend last week. You can imagine who you were with, the taste of the food, maybe the weather, if you were sitting outside on the patio. And then there's semantic memory, which is our memory for facts and knowledge about the world - for example, who was printed on the first dollar bill.

And so we became curious, because when I was talking to other trivia folks that I met through "Jeopardy!" and other trivia activities of, like, there's got to be something special about their memories, and I suppose my memory as well. Could it be possible that the way that we remember this kind of information is by sort of binding these two memory systems together, that maybe remembering those details about how and when we learned some facts actually helps that information stick for later.

GONYEA: One of the studies that you have done, you had participants look at museum exhibits.

THIEU: Yes, absolutely. So we tried to pick exhibits on topics that people would not hopefully know the fact already. So, for example, you might be sitting and on your computer screen, you'll see a picture of, let's say like a little round, like, circular armpit guard that goes on a piece of armor, and you'll hear an audio narrator describing to you the history of this particular round armpit guard, which happens to be called a besagew, I believe. And we also show them, you know, a particular - like, this museum is in this background, and it's all amber-colored, or this museum has this other background with this other font design, and it's all cobalt-colored, so that we could study not only do you remember the fact that you learned in this museum exhibit, but did you see it in the amber museum or the cobalt museum, so that we can get those details about not only what did you learn, but what else did you see and experience while you were learning it?

GONYEA: And then what do you see happening as you play that out?

THIEU: What we found is that trivia experts, when they picked, for example, the correct armpit guard, or they picked the correct museum that they saw the armpit guard in, they were also then more likely to remember the name of the armpit guard itself. Whereas for trivia non-experts, their memory was basically equally as good for which exhibit picture they saw, but it didn't seem to help them remember the facts.

GONYEA: Say I want to get better at remembering or recalling something like the name of the Wright Brothers' airplane. How would you go about helping me recall that?

THIEU: Yeah. One thing I do want to say is that while we found this relationship between people who are sort of already naturally good at trivia, we still don't know if training people to do this will help them. I personally believe that it will, but we'd have to do another study to see. But what we think is that learning new facts in really rich and interesting contexts is going to give you more of those hooks for other parts of your episodic memory that will help that semantic information stick better.

GONYEA: It sounds like you're telling us to live in the world and experience things.

THIEU: Absolutely. If you can go, you know, on a trip to D.C., go to the Smithsonian Air and Space Museum, eat something really interesting after you haven't eaten before, really trying to make that memory for the facts as rich as possible. I personally think those are going to stick better, but that's also me, the human, not necessarily me, the scientist.

GONYEA: Monica Thieu is co-author, along with Mariam Aly and Lauren Wilkins, of a new study in the journal Psychonomic Bulletin and Review. Thank you very much for talking to us.

THIEU: Thank you.

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Empirical Evidence Supporting Neural Contributions to Episodic Memory Development in Early Childhood: Implications for Childhood Amnesia

Memories for events that happen early in life are fragile—they are forgotten more quickly than expected based on typical adult rates of forgetting. Although numerous factors contribute to this phenomenon, data show one major source of change is the protracted development of neural structures related to memory. Recent empirical studies in early childhood reveal that the development of specific subdivisions of the hippocampus (i.e., the dentate gyrus) are related directly to variations in memory. Yet the hippocampus is only one region within a larger network supporting memory. Data from young children have also shown that activation of cortical regions during memory tasks and the functional connectivity between the hippocampus and cortex relate to memory during this period. Taken together, these results suggest that protracted neural development of the hippocampus, cortex, and connections between these regions contribute to the fragility of memories early in life and may ultimately contribute to childhood amnesia.

You have to begin to lose your memory, if only in bits and pieces, to realize that memory is what makes our lives. Life without memory is no life at all… Our memory is our coherence, our reason, our feeling, even our action. Without it we are nothing. ( Buñuel (1984 , p.17).

How Does the Ability to Remember Change Across Development?

The ability to remember details from events in life is critical for functioning and a personal sense of self. Why is it then that, as adults, we recall so little from our childhood? This inability to remember, termed infantile amnesia or childhood amnesia , is one of the most robust and replicable phenomena in developmental psychology ( Freud, 1910 ; Newcombe, Lloyd, & Ratliff, 2007 ; Pillemer & White, 1989 ). Although it was originally thought that early experiences were simply not encoded into memory ( Piaget & Inhelder, 1969 ), research with young children has repeatedly documented that this is not the case. In fact, even very young children can form memories for events (see Bauer, 2006, for a review). However, the same research suggests that early memories are extremely fragile and prone to being forgotten, especially when they include the details of events (e.g., Bauer, 2015 ; Bauer & Larkina, 2014 , 2016 ).

In one of the earliest studies on autobiographical memories, although children as young as 3 years could recall a family vacation to Disneyworld after six to 12 months, the older the children were during the trip, the more details they remembered ( Hamond & Fivush, 1991 ). Building on this landmark study, a sizable empirical literature now documents accelerated rates of forgetting for autobiographical memories across childhood (e.g., Bauer & Larkina, 2014 , 2016 ; Peterson, Warren, & Short, 2011 ). For example, when researchers track young children’s memories over time, results suggest they grow into their amnesia; this means that although 3- and 4-year-olds initially recall details of events, these details are later forgotten. When rates of forgetting are assessed empirically, 4- to 8-year-olds forget more rapidly than adults ( Bauer & Larkina, 2016 ). Moreover, among children, 4- to 6-year-olds forget more rapidly than 8-year-olds, particularly during open-ended recall of autobiographical memories. Thus, although childhood amnesia may extend through childhood, after about the sixth year, the stability and consistency of memories increase dramatically (e.g., Bauer & Larkina 2014 , 2016 ; Peterson et al., 2011 ).

Studies examining children’s memories for real-life events have high ecological validity. However, the events and details recalled vary considerably among children. Because of this variability, it is often challenging to manipulate these events parametrically to probe mechanisms underlying changes in children’s ability to recall them. As a result, some researchers have turned to controlled, laboratory-based episodic memory paradigms. Similar to real-world events, in these laboratory paradigms, children are presented with events that are rich in contextual details (i.e., specific items encountered at particular times and places) and then asked to recall these details after a delay. The advantage of this approach is that lab-based events can be designed to be manipulated experimentally. Thus, although autobiographical and lab-based memories differ, they share critical overlapping core features since both require memories for the details of previous experiences.

Lab-based studies identify a developmental timeline of memory that is similar to that identified by naturalistic studies. These studies suggest that the ability to remember details of events improves dramatically across early childhood and becomes robust around the sixth year. In one study, 4-year-olds, 6-year-olds, and adults were tested on their ability to recall isolated parts of pictures as well as combinations of these parts ( Sluzenski, Newcombe, & Kovacs, 2006 ). For example, participants were shown a tiger at a playground and then asked to determine whether they had previously seen the animal (the tiger), the location (the playground), or the animal in the location (the tiger at the playground). Participants’ memory for the animal and the location in isolation were similar across all three age groups. However, their memory for the combinations (i.e., animals in locations) increased between 4-year-olds and 6-year-olds but not between 6-year-olds and adults. Moreover, the ability to remember combinations was related to children’s memory for details from a more naturalistic memory task (recalling a story after a delay). On the basis of these results, the authors argued that memory for details (i.e., memory for items bound to contexts) “may be near or at adult levels by about the age of 6 years” ( Sluzenski et al., 2006 , p. 98).

Research has documented similar age-related improvements in memory for details across early childhood using a variety of other paradigms, including memory for pairs of items or words (e.g., Yim, Dennis, & Sloutsky, 2013 ), the source of novel facts (e.g., Drummey & Newcombe, 2002 ; Riggins, 2014 ), and the spatial location in which an item was originally encountered (e.g., Bauer et al., 2012 ). Closely related research suggests that early childhood is a time when children’s ability to form very detailed memories and discriminate between them also improves ( Canada, Ngo, Newcombe, Geng, & Riggins, 2018 ; Ngo, Newcombe, & Olson, 2017b ). Taken together, findings from lab-based paradigms support the suggestion that an important transition in children’s ability to form and recall detailed memories occurs during early childhood.

Why Does Memory Change Across Development?

Researchers have proposed many reasons why memories for details become more robust toward the end of early childhood than during other developmental periods. First, developmental psychologists have long noted changes in the nature of cognition between 5 and 7 years. This shift marks the transition from Piaget’s preoperational stage to the concrete operational stage, and signifies increased sophistication of children’s thinking across numerous domains of cognition (e.g., categorical reasoning, perspective taking, metamemory, strategy use; Piaget & Inhelder, 1969 ). Second, developments in language, theory of mind, executive function and self-concept (e.g., increases in self-knowledge and the capacity for self-source monitoring) also occur and relate to improvements in autobiographical memory (e.g., Ross, Hutchison, & Cunningham, 2019 ). Third, studies suggest that the purpose of memory (i.e., what children need to remember) may change during this period. Specifically, infants and young children initially benefit from extracting generalities across items and situations. Only after this initial foundational knowledge is laid down does retaining specific details become important ( Newcombe et al., 2007 ). Fourth, in many societies, formal schooling is introduced at this age, and schooling affects both cognitive ability and brain development ( Brod, Bunge, & Shing, 2017 ).

Finally, theories of memory and data from animal models suggest that brain development may underlie this shift in memory (e.g., Bauer, 2006, 2014 , 2015 ; Lavenex & Banta Lavenex, 2013 ; Nadel & Zola-Morgan, 1984 ; Pillemer & White, 1989 ). Specifically, researchers have hypothesized that postnatal changes in the hippocampus, a neural structure critical for memory in adults, underlie age-related improvements in children’s ability to recall past events ( Madsen & Kim, 2016 ; Nadel & Zola-Morgan, 1984 ). The term hippocampus is of Greek origin and roughly translates to seahorse because of its shape. The hippocampus has specific subdivisions (termed subregions or subfields ) that can be examined independently or in relation to each other. Subregions include the head, body, and tail of the hippocampus, which show differential connectivity to surrounding cortical regions via white matter tracts. Subfields refer to the functional subunits of the hippocampus (dentate gyrus, cornu ammonis [CA]1-4, subiculum; Yushkevich et al., 2015 ; see Figure 1 ). Although the subfields are anatomically distinct, MRI scans’ low spatial resolution makes it difficult to delineate them individually. To circumvent this issue, researchers often combine smaller subfields (e.g., CA2-4) with larger regions (e.g., the dentate gyrus).

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(age 4.54 years), including subregions (head, body, tail) and subfields (CA1-4, subiculum, dentate gyrus or DG). Note the disproportionate distribution of subfields along the longitudinal axis. Dotted lines indicate exact location of coronal slices. Yellow lines indicate approximate boundaries between subregions.

Neuroanatomical data from nonhuman primates show that age-related changes in specific subfields and the connections between them persist until 5 to 7 years ( Lavenex & Banta Lavenex, 2013 ; Serres, 2001 ). One of these subfields, the dentate gyrus, is critical for adultlike memory formation. Thus, researchers have proposed that the prolonged developmental trajectory may underlie the immature profile of memory during this period (i.e., poor ability to recall details and accelerated forgetting, Bauer, 2006, 2014 ; Lavenex & Banta Lavenex, 2013 ; Nadel & Zola-Morgan, 1984 ; Pillemer & White, 1989 ).

In addition, in recent studies with animals, changes in rates of generating new neurons (neurogenesis) contributed to an observed shift in young rodents’ ability to remember ( Josselyn & Frankland, 2012 ). In these studies, the decline of postnatal neurogenesis corresponded with the ability to form long-term memories. The authors suggest that high levels of neurogenesis prohibit the formation of stable memories, likely by replacing synaptic connections in preexisting hippocampal memory circuits ( Josselyn & Frankland, 2012 ). Thus, animal models clearly support the notion that neural development, particularly development of the hippocampus, influences memory early in life.

Yet the hippocampus is only one piece within the memory network. In research with adults and school-aged children, cortical areas (e.g., the prefrontal and posterior parietal cortices) are recruited during the formation and retrieval of detailed memories ( Ghetti & Bunge, 2012 ; Ofen, 2012 ). In fact, these cortical regions are often credited for age-related changes in memory later in childhood and adolescence (e.g., Tang, Shafer, & Ofen, 2018 ). In particular, the prefrontal cortex is thought to be necessary for the strategic part of memory, which includes cognitive control mechanisms that aid and regulate memory ( Shing, Werkle-Bergner, Li, & Lindenberger, 2008 ). These findings are consistent with research with both animals (e.g., Huttenlocher & Dabholkar, 1997 ) and humans (e.g., Giedd et al., 1999 ) that shows protracted development of cortical regions, particularly the prefrontal cortex. However, how these cortical regions contribute to memory early in life has been studied less.

Evidence for Relations Between Neural Development and Memory in Early Childhood

As a result of the challenges of obtaining neuroimaging data from children younger than age 8, empirical evidence exploring the hypothesis that brain development is related to the ability to form long-term, detailed memories has emerged only recently. 1 These studies have examined age-related differences in both brain structure and function, and how these differences relate to memory ability. Specifically, development of brain structure, function, and the functional connections between brain regions are all linked with developmental improvements in memory. Thus, neural development during this period is multifaceted, which may be why dramatic changes in memory are observed near the end of early childhood.

Brain Structure

Building on behavioral research in early childhood and neuroimaging studies in school-aged children, the first study to examine links between memory and the hippocampus early in life explored relations between detailed memories and the hippocampus. The study compared 4- and 6-year-olds’ capacity to recall details of a past lab-based event (i.e., where an object was previously encountered) and the size (i.e., volume) of subregions of the hippocampus ( Riggins, Blankenship, Mulligan, Rice, & Redcay, 2015 ). Better memory was related to larger hippocampal head volume for 6-year-olds, but not for 4-year-olds. These results suggest that relations between brain and behavior fluctuate across early development (consistent with reports in school-aged children; DeMaster, Pathman, Lee, & Ghetti, 2013 ), and may emerge during early childhood.

Another study, of 4- to 8-year-olds, provided further evidence of differential relations between brain and behavior using more precise measurements of the hippocampus ( Riggins et al., 2018 ). The study used a similar memory paradigm and performance was related to subfields of the hippocampus. Again, relations between brain and behavior varied across development. Specifically, within the head of the hippocampus, relations between children’s aptitude for recalling fine-grained details was related to volume of the dentate gyrus/CA2-4 subfields. However, this association was moderated by age: In younger individuals, smaller volumes were associated with less detailed memories; in older individuals, smaller volumes were associated with more detailed memories, as reflected by the type and number of errors made on the task (see Figure 2A ). This finding is not only consistent with previous research, but also extends prior studies to implicate the dentate gyrus/CA2-4 subfields as the subdivisions related to developmental improvements in precision of memory.

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and A) memory for details (as measured by the number of intra-experimental errors on a source memory task) in the head of the hippocampus ( Riggins et al., 2018 ) and B) precision of memories (as measured by mnemonic discrimination) in the head and body of the hippocampus ( Canada et al., 2018 ). In both studies, age moderated the association so that in younger children, larger volumes were associated with better performance, whereas in older children, smaller volumes were associated with better performance.

A third studyprobed the association between memory for details and the dentate gyrus more specifically. Researchers examined hippocampal subfields in relation to young children’s ability to discriminate between two similar events from memory ( Canada et al., 2018 ). Developmental differences in relations between the precision of memories and the volume of the dentate gyrus/CA2-4 subfields appeared; in younger individuals, smaller volumes were associated with less precise memories, but in older children, smaller volumes correlated with more precise memories (see Figure 2B ). These results further support the hypothesis that age-related differences in the hippocampus (specifically, the dentate gyrus/CA2-4 subfields) are related to developmental improvements in children’s ability to form and retain detailed memories during this transitional period (see Keresztes et al., 2017 , for similar findings in 6- to 14-year-olds and adults).

Finally, structural connections between brain regions via axonal pathways (i.e., white matter tracts) implicated in memory in school-aged individuals and adults also vary by age (e.g., Lebel & Beaulieu, 2011 ). White matter pathways have been related to differences in memory performance across early childhood. Specifically, the integrity of the white matter fiber bundles between the hippocampus and the inferior parietal lobule (a region important for memory in adults) was associated with 4- and 6-year-olds’ performance on two lab-based memory tasks. These findings suggest that not only is development of hippocampal structure important, but also the connections between the hippocampus and cortical regions ( Ngo et al., 2017a ).

Brain Function

Task-based functional magnetic resonance imaging (fmri). 2.

Task-based fMRI is challenging to do with young children because of the constraints of the MRI environment (lying still in a scanner while performing a cognitively challenging task for an extended period). One study of young children examined patterns of activation during the formation of memories for associations between an item (e.g., a banana) and a character (e.g., Mickey Mouse; Geng, Redcay, & Riggins, 2019 ). During successful memory formation, the hippocampus and several cortical regions showed increased activity (see Figure 3A ). Increased activity in some of these cortical regions (e.g., the inferior/superior parietal lobule) was expected since studies of older individuals have reported similar results ( Ghetti & Bunge, 2012 ). However, the increases in other cortical regions (e.g., the orbital frontal gyrus) were unexpected since they have been reported infrequently in studies of older individuals; this suggests that younger children may rely on a wider or more distributed network of brain regions to encode detailed memories successfully. In addition, connectivity between the hippocampal subregions (the head versus the body/tail) and the cortex (i.e., the inferior frontal gyrus) varied as a function of age, implying increased specialization of connectivity of the hippocampus along the anterior-to-posterior axis to cortical regions across development (see Figures 3B and ​ and3C). 3C ). Finally, activation of the hippocampus and several cortical regions varied as a function of both age and performance. These findings suggest it is neither maturation nor task demands alone that contribute to activation differences during development, but that both are important.

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A) Brain regions showing greater activation during memory formation when details are subsequently recalled.

IPL/SPL: inferior/superior parietal lobule; IOG: inferior occipital gyrus; ITG: inferior temporal gyrus; IFG: inferior frontal gyrus; hipp: hippocampus; OFG: orbital frontal gyrus.

B) Functional connectivity differences between anterior and posterior (body and tail) hippocampus to left IFG were associated with age during memory formation.

C) Scatterplot showing relation between functional connectivity differences between anterior and posterior hippocampus and left IFG and age during memory formation.

Task-free fMRI.

Given the challenges of obtaining task-based fMRI data from young children, many researchers have begun to explore functional connectivity between regions in the absence of an overt task (e.g., Vanderwal, Kelly, Eilbott, Mayes, & Castellanos, 2015 ). These measures of functional connectivity are thought to arise from co-activation of brain regions that builds up over time ( Fox & Raichle, 2007 ). Thus, although not measured during an overt task, the strength of functional connectivity between regions can be used as an estimate of the integrity or maturity of the memory system.

Two studies have explored relations between task-free hippocampal functional connectivity and memory ability assessed outside the MRI scanner in young children ( Geng et al., 2019 ; Riggins, Geng, Blankenship, & Redcay, 2016 ). Findings from both studies were similar to those from task-based fMRI studies. Specifically, they revealed that functional connectivity between the hippocampus and cortical regions was influenced by age and performance. These studies also suggested that functional connectivity between the hippocampus and regions not typically thought to relate to memory formation in adults decreased developmentally (i.e., the orbital frontal gyrus and left and right middle temporal gyrus in Geng et al., 2019 ; the right inferior frontal gyrus in Riggins et al., 2016 ).

Overall, findings from both task-based and task-free fMRI studies are in line with the interactive specialization framework, which suggests that, with age, the hippocampus becomes functionally integrated with cortical regions that are part of the hippocampal memory network in adults, and also becomes functionally segregated from regions not related to memory in adults ( Johnson, 2011 ). Thus, both integration and segregation are critical for developmental improvements in memory (see Figure 4 ).

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The hippocampus is depicted in red and cortical regions are depicted in circles. Double-sided arrows represent functional connections. Solid black arrows represent connections that are present and gray arrows represent connections that are weak or absent. Interactive specialization suggests that changes occur both in the integration and the segregation of brain regions over development. In this depiction, there are functional connections between the hippocampus and memory regions that are present in children and in adults (e.g., inferior parietal lobule, IPL). There are also functional connections with other memory regions that are weak or absent in children, but present in adults (e.g., dorsolateral prefrontal cortex, DLPFC) as the hippocampus becomes more functionally integrated with memory regions. Finally, there are functional connections with nonmemory regions in children (e.g., orbital frontal gyrus, OFG) that are weakened or absent in adults, as the hippocampus becomes more segregated from nonmemory regions. Not pictured are relations between cortical regions, which also likely change across development. For illustrative purposes, lines are indicated as present or absent; however, the strength of these functional connections likely varies with age.

Summary and Conclusion

Taken together, these studies suggest development in multiple neural measures that vary during the early years of life and contribute to age-related differences in young children’s ability to remember details of events. First, relations between hippocampal structure (i.e., the volume of subregions and subfields) and memory vary across development. Second, functional activation of the hippocampus and multiple cortical regions contribute to memory in early childhood, yet vary as a function of age and performance. Finally, structural and functional connectivity between the hippocampus and multiple cortical regions is related to memory but also varies with age and performance. Together, these findings highlight the multifaceted ways in which the brain relates to memory development during this period and may account for why changes in memory at this time are quite dramatic.

These findings provide some of the first empirical support from young children regarding brain-behavior associations in the domain of memory early in life. These data are critical because they provide evidence that supports neural explanations for childhood amnesia. Although the findings we have reviewed focused on lab-based memories, they are consistent with research with 8- to 11-year-olds that used fMRI to investigate recall of autobiographical memories ( Bauer, Pathman, Inman, Campanella, & Hamann, 2016 ). Research on neural bases of memory in early childhood is beginning to provide a bridge and fill a gap in the literature connecting what we know about memory processes early in life versus what we know about these processes later. Making such connections is critical for a comprehensive understanding of memory. Ultimately, this knowledge will help develop interventions targeting memory when they can have the largest impact—early in development, when plasticity is abundant.

Findings regarding the role of brain development in children’s ability to recall events may contribute to the offset of childhood amnesia. Yet changes in the neural correlates of memory must be considered with other factors, including improvements in other areas of cognition and their underlying neural systems (e.g., language, theory of mind, self-concept), changes in the goal of memory during this time, and the context in which children form and retrieve these memories. Researchers should explore to what extent these factors are competitive versus complementary in nature. Although the idea is speculative, development in other cognitive domains, which appear dissimilar on the surface, may converge at the neural level because they may rely on overlapping neural circuitry. For example, the hippocampus plays a role in the development of memory as well as of language ( Lee et al., 2015 ), emotion ( Stern, Botdorf, Cassidy, & Riggins, 2019 ), and spatial navigation ( Lavenex & Banta Lavenex, 2013 ). Moreover, improvements across domains may have additive or interactive effects. For example, simultaneous improvements in memory and self-concept or theory of mind may combine to produce gains in autobiographical memory that exceed what would be expected by either in isolation. Such possibilities provide opportunities for research on the numerous measures that contribute simultaneously to childhood amnesia.

Knowledge regarding why childhood amnesia exists is important to scientists, students, policymakers, and the public for several reasons. First, memory development and brain development are both active areas of scientific inquiry and are of interest to those studying these constructs. Second, autobiographical memory is important for developing self-identity, mental health, and functioning within social contexts, which makes childhood amnesia intriguing to those who are interested primarily in social development. Third, policymakers are particularly interested in information regarding brain development in early childhood since changes occur rapidly during this time; previous research has informed an array of policies, such as those related to early childhood education. Finally, childhood amnesia is a ubiquitous phenomenon—it affects everyone. Understanding why we forget events from our earliest years gives everyone more insight into their minds and the records of their personal pasts.

Acknowledgments

The work described in this article was supported by the National Institute of Health under grant HD079518 (to Tracy Riggins), by the National Science Foundation via a Graduate Research Fellowship Program grant (to Morgan Botdorf), and by the University of Maryland. We also thank two anonymous reviewers for their insightful feedback.

1 A fair amount of neuroimaging research has been conducted in older children and adolescents, but the youngest children in these studies tend to be 8 years old, which is beyond the period of childhood amnesia, the focus of this article (see Ghetti & Bunge, 2012 , for a review).

2 Although event-related potentials have been used to examine brain function in young children during memory tasks, they lack spatial resolution to test the hypotheses generated from animal models. Therefore, we focus our review on fMRI.

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Stanford Medicine study identifies distinct brain organization patterns in women and men

Stanford Medicine researchers have developed a powerful new artificial intelligence model that can distinguish between male and female brains.

February 20, 2024

sex differences in brain

'A key motivation for this study is that sex plays a crucial role in human brain development, in aging, and in the manifestation of psychiatric and neurological disorders,' said Vinod Menon. clelia-clelia

A new study by Stanford Medicine investigators unveils a new artificial intelligence model that was more than 90% successful at determining whether scans of brain activity came from a woman or a man.

The findings, published Feb. 20 in the Proceedings of the National Academy of Sciences, help resolve a long-term controversy about whether reliable sex differences exist in the human brain and suggest that understanding these differences may be critical to addressing neuropsychiatric conditions that affect women and men differently.

“A key motivation for this study is that sex plays a crucial role in human brain development, in aging, and in the manifestation of psychiatric and neurological disorders,” said Vinod Menon , PhD, professor of psychiatry and behavioral sciences and director of the Stanford Cognitive and Systems Neuroscience Laboratory . “Identifying consistent and replicable sex differences in the healthy adult brain is a critical step toward a deeper understanding of sex-specific vulnerabilities in psychiatric and neurological disorders.”

Menon is the study’s senior author. The lead authors are senior research scientist Srikanth Ryali , PhD, and academic staff researcher Yuan Zhang , PhD.

“Hotspots” that most helped the model distinguish male brains from female ones include the default mode network, a brain system that helps us process self-referential information, and the striatum and limbic network, which are involved in learning and how we respond to rewards.

The investigators noted that this work does not weigh in on whether sex-related differences arise early in life or may be driven by hormonal differences or the different societal circumstances that men and women may be more likely to encounter.

Uncovering brain differences

The extent to which a person’s sex affects how their brain is organized and operates has long been a point of dispute among scientists. While we know the sex chromosomes we are born with help determine the cocktail of hormones our brains are exposed to — particularly during early development, puberty and aging — researchers have long struggled to connect sex to concrete differences in the human brain. Brain structures tend to look much the same in men and women, and previous research examining how brain regions work together has also largely failed to turn up consistent brain indicators of sex.

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Vinod Menon

In their current study, Menon and his team took advantage of recent advances in artificial intelligence, as well as access to multiple large datasets, to pursue a more powerful analysis than has previously been employed. First, they created a deep neural network model, which learns to classify brain imaging data: As the researchers showed brain scans to the model and told it that it was looking at a male or female brain, the model started to “notice” what subtle patterns could help it tell the difference.

This model demonstrated superior performance compared with those in previous studies, in part because it used a deep neural network that analyzes dynamic MRI scans. This approach captures the intricate interplay among different brain regions. When the researchers tested the model on around 1,500 brain scans, it could almost always tell if the scan came from a woman or a man.

The model’s success suggests that detectable sex differences do exist in the brain but just haven’t been picked up reliably before. The fact that it worked so well in different datasets, including brain scans from multiple sites in the U.S. and Europe, make the findings especially convincing as it controls for many confounds that can plague studies of this kind.

“This is a very strong piece of evidence that sex is a robust determinant of human brain organization,” Menon said.

Making predictions

Until recently, a model like the one Menon’s team employed would help researchers sort brains into different groups but wouldn’t provide information about how the sorting happened. Today, however, researchers have access to a tool called “explainable AI,” which can sift through vast amounts of data to explain how a model’s decisions are made.

Using explainable AI, Menon and his team identified the brain networks that were most important to the model’s judgment of whether a brain scan came from a man or a woman. They found the model was most often looking to the default mode network, striatum, and the limbic network to make the call.

The team then wondered if they could create another model that could predict how well participants would do on certain cognitive tasks based on functional brain features that differ between women and men. They developed sex-specific models of cognitive abilities: One model effectively predicted cognitive performance in men but not women, and another in women but not men. The findings indicate that functional brain characteristics varying between sexes have significant behavioral implications.

“These models worked really well because we successfully separated brain patterns between sexes,” Menon said. “That tells me that overlooking sex differences in brain organization could lead us to miss key factors underlying neuropsychiatric disorders.”

While the team applied their deep neural network model to questions about sex differences, Menon says the model can be applied to answer questions regarding how just about any aspect of brain connectivity might relate to any kind of cognitive ability or behavior. He and his team plan to make their model publicly available for any researcher to use.

“Our AI models have very broad applicability,” Menon said. “A researcher could use our models to look for brain differences linked to learning impairments or social functioning differences, for instance — aspects we are keen to understand better to aid individuals in adapting to and surmounting these challenges.”

The research was sponsored by the National Institutes of Health (grants MH084164, EB022907, MH121069, K25HD074652 and AG072114), the Transdisciplinary Initiative, the Uytengsu-Hamilton 22q11 Programs, the Stanford Maternal and Child Health Research Institute, and the NARSAD Young Investigator Award.

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu .

Artificial intelligence

Exploring ways AI is applied to health care

Stanford Medicine Magazine: AI

Artistic image showing a laser beam hitting an atom, causing it to emit pulses of light and smaller sub-atomic particles.

Innovative technique reveals that leaping atoms remember where they have been

University of Oxford researchers have used a new technique to measure the movement of charged particles (ions) on the fastest ever timescale, revealing new insights into fundamental transport processes. These include the first demonstration that the flow of atoms or ions possesses a ‘memory.’ The results have been published in the journal Nature .

Two smartly dressed men sit at a table. They look at something in the distance; one has raised his arm to point at something out of shot. On the table, there is an open notebook, a laptop and a molecular model of a lattice structure.

In the new study, a team of researchers based at Oxford’s Department of Materials and the SLAC National Accelerator Laboratory, California made the surprising discovery that the movement of individual ions can be influenced by its recent past; in other words, there is ‘a memory effect.’ This means that, on the microscopic scale, history can matter: what a particle did a moment ago can affect what it does next.

Up to now, this has been extremely challenging to observe because such an effect is unnoticeable by simple observation. To test whether ion movement has a memory, something unusual must be introduced: disturb the system, and then watch how the disturbance dies down.

Senior author Professor Saiful Islam (Department of Materials, University of Oxford) said: ‘To use a visual analogy, such an experiment is like throwing a rock into a pond to watch how far the waves spread. But for watching atoms flow, the rock in our study must be a pulse of light. Using light, we have captured the movement of ions on the fastest-ever timescale, revealing the link between the individual movement of atoms and macroscopic flow.’

The components of a laser are arranged on a metal grid-like structure. There are many lenses, some illuminated by a purple light.

In order to capture this, the team used a technique called pump-probe spectroscopy, using rapid, intense pulses of light to both trigger and measure the ions’ movement. Such nonlinear optical methods are commonly used to study electronic phenomena in applications from solar cells to superconductivity, but this was the first time it has been used to measure ionic motions without involving electrons.

Lead author Dr Andrey Poletayev (Department of Materials, University of Oxford, and formerly SLAC National Accelerator Laboratory) said: ‘We found something interesting, which happened a short time after the ion motions we triggered directly. The ions recoil: if we push them to the left, they then preferentially reverse to the right afterwards. This resembles a viscous substance being jerked rapidly then relaxing more slowly - like honey. This means that for a time after we pushed the ions with light, we knew something about what they would do next.’

Besides the implications for materials discovery, this work disabuses the notion that what we see on the macroscopic level – transport that appears memory-free – is directly replicated at the atomic level. Dr Andrey Poletayev, Department of Materials, University of Oxford.

The researchers were only able to observe such an effect for a very short time, a few trillionths of a second, but expect this will increase as the sensitivity of the measurement technique improves. Follow-up research aims to exploit this newfound understanding to make faster and more accurate predictions of how well materials can transport charge for batteries, and engineering new kinds of computing devices that would operate more rapidly.

According to the researchers, quantifying this memory effect will help to predict the transport properties of potential new materials for the better batteries we need for the growth in electric vehicles. However, the findings have implications for all technologies in which atoms flow or move, whether in solids or in fluids, including neuromorphic computing, desalination, and others.

Dr Poletayev added: ‘Besides the implications for materials discovery, this work disabuses the notion that what we see on the macroscopic level – transport that appears memory-free – is directly replicated at the atomic level. The difference between these scales, caused by the memory effect, makes our life very complicated, but we have now shown that it is possible to measure and quantify this.’

The study ‘The persistence of memory in ionic conduction probed by nonlinear optics’ has been published in Nature .

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