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How to find the age of a memory stored in the brain?

How to find the age of a memory stored in the brain?


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Is there any way to find how old one's memory is?

One can find the age of stones, plants, animals, etc. So why not find the age of a memory stored inside one's brain?


We are only barely beginning to understand how the brain works, including memory. We do know that it is a very complex thing. There are many different kinds of memory; many different processes are involved in creating and recalling memories. One factor that plays into a naïve concept of "how old a memory is" is that "remembering" does not seem to be a passive activity; instead, every time we remember a memory we re-create it.

Having said that I don't see a theoretical reason why there wouldn't be a way to determine the age of a memory… but we currently don't know it.

Consider that we don't magically know the ages of stones, plants, or animals. We learned to figure it out from studying those things, seeing how they change over time, and deducing ways to use that knowledge to guess their age. For example, people discovered that in many climates trees alternate a growing season and a dormant season, and this results in the trunk having "tree rings" for each year they've lived. They've also seen that animals have specific life cycles and look different (if only in size) depending on their ages, and they can use that to roughly estimate an animal's age. Obviously this depends completely on the animal in question; different animals grow in different ways and we can tell their ages in correspondingly different ways, and not always to great precision.

For most of human history we were completely unable to tell the age of stones. Only the discovery of radioactivity, and that the atoms inside stones transmute into other elements over the millennia and that this allows us to tell how long it has been since the stone crystallized (i.e. the atoms got stuck where they are), enabled radiometric dating.

Similarly with memory, it is completely plausible that once we understand very well what a memory is, what its exact correlates in the brain are, and how those correlates change over time, it will be possible to tell how old a memory is. But we aren't there yet (see some articles at the end for where we are).

And while it's plausible that we'll be able to know the age of a memory once we understand it well enough, it is by no means inevitable. To give a counter-example, there is absolutely no way to tell the age of, say, a water molecule. We understand water molecules extremely well. They form and can be destroyed, so for every water molecule there is a certain amount of time since it formed, i.e. it has an age. But a water molecule is just an oxygen atom linked to two hydrogen atoms; its properties are dictated by chemistry and don't depend on how long it has existed. There is no way to tell the age of a given water molecule just from looking at it. Similarly, computers give a timestamp to a file when they create it, but if they didn't do that I don't think we could tell how long a file had been on the disk just from examining the disk itself. So it is certainly theoretically possible that once we understand how memory works, we'll find that we can't, in fact, know the age of a memory.

Here are some papers on memory to give an idea of what neurobiologists are looking at these days:

The Regulation of Transcription in Memory Consolidation
http://cshperspectives.cshlp.org/content/7/1/a021741.short
This paper looks at the role of DNA transcription in the consolidation of long-term memory (as such consolidation apparently requires new proteins being created)

Structural Components of Synaptic Plasticity and Memory Consolidation
http://cshperspectives.cshlp.org/content/7/7/a021758.short
This paper (more or less the same authors) looks at the structural factors involved in consolidating memories by strenghtening synapses and creating new ones.

The many faces of working memory and short-term storage
https://link.springer.com/article/10.3758/s13423-016-1191-6
This recent (2017) paper discusses "Working memory" and how the field doesn't have a single, coherent definition of that concept yet.

Functional neuroimaging studies of encoding, priming, and explicit memory retrieval
http://www.pnas.org/content/95/3/891.short
This 1998 imaging study looks at what regions of the brain light up in various memory-related tasks, and suggests such imaging studies can be useful to investigate brain function. They were right, but notice how general the areas they see are, and how they only can guess at what might be going on there.

The Molecular Biology of Memory Storage: A Dialog Between Genes and Synapses
http://teachline.ls.huji.ac.il/72336/sphira/Kandelnobellecture.pdf
This is a very long lecture from 2000 from one of the authors of the above papers, summarizing their life's research on the molecular and synapse-level mechanisms of memory. These paragraphs give a historical overview of how scientists have thought memory works:

In his Croonian Lecture to the Royal Society of 1894, Santiago Ramo'n y Cajal proposed a theory of memory storage: memory is stored in the growth of new connections[16]. This prescient idea was neglected in good part for half a century as students of learning fought over newer competing ideas. First, Karl Lashley, Ross Adey, Wolfgang Köhler, and a number of Gestalt psychologists proposed that learning leads to changes in electric fields or chemical gradients, which they postulated surround neuronal populations and are produced by the aggregate activity of cells recruited by the learning process. Second, Alexander Forbes and Lorente de No proposed that memory is stored dynamically by a self-reexciting chain of neurons. This idea was later championed by Donald Hebb as a mechanism for short-term memory. Finally, Holger Hyden proposed that learning led to changes in the base composition of DNA or RNA. Even though there was much discussion about the merits of each of these ideas, there was no direct evidence to support any of them [reviewed in 17].

We were now in a position to address these alternative ideas by confronting directly the question of how learning can occur in a circuit with fixed neuronal elements. Kupfermann, Castellucci, Carew, Hawkins, and I examined the neural circuit of the gill-withdrawal reflex while the animal underwent sensitization or habituation, a form of learning in which the animal learns to ignore an innocuous stimulus to siphon when given with monotonous repetition. (We later also extended these studies to an examination of classical conditioning [20].) Our studies provided clear evidence for Cajal's idea: learning results from changes in the strength of the synaptic connections between precisely interconnected cells [6, 7]. Thus, while the organism's developmental program assures that the connections between cells are invariant, it does not specify their precise strength. Rather, experience alters the strength and effectiveness of these pre-existing chemical connections. Seen in the perspective of these three forms of learning, synaptic plasticity emerged as a fundamental mechanism for information storage by the nervous system, a mechanism that is built into the very molecular architecture of chemical synapses [95]

Notice how twenty years ago, this person was saying we can finally begin to answer century-old questions of what form memory storage takes in the brain to begin with.

A Putative Biochemical Engram of Long-Term Memory https://www.sciencedirect.com/science/article/pii/S0960982216311393
Exciting 2016 article: they've maybe found one place where one memory might be stored! First line of the abstract:

How a transient experience creates an enduring yet dynamic memory remains an unresolved issue in studies of memory.

Same idea in the first line of the abstract of this 2016 article on associative memory:

Neural ensemble dynamics underlying a long-term associative memory https://www.nature.com/articles/nature21682

The brain's ability to associate different stimuli is vital for long-term memory, but how neural ensembles encode associative memories is unknown.


Researchers find where musical memories are stored in the brain

A group of Dartmouth researchers has learned that the brain's auditory cortex, the part that handles information from your ears, holds on to musical memories.
In a study titled "Sound of silence activates auditory cortex" published in the March 10 issue of Nature, the Dartmouth team found that if people are listening to music that is familiar, they mentally call upon auditory imagery, or memories, to fill in the gaps if the music cuts out. Using functional magnetic resonance imaging (fMRI) to measure brain activity, the researchers found that study participants could mentally fill in the blanks if a familiar song was missing short snippets.

"We played music in the scanner [fMRI], and then we hit a virtual 'mute' button," says first author David Kraemer, a graduate student in Dartmouth's Psychological and Brain Sciences Department. "We found that people couldn't help continuing the song in their heads, and when they did this, the auditory cortex remained active even though the music had stopped."

The researchers say that this finding extends previous work on auditory imagery and parallels work on visual imagery, which both show that sensory-specific memories are stored in the brain regions that created those events. Their study, however, is the first to investigate a kind of auditory imagery typical of everyday experience.

"It's fascinating that although the ear isn't actually hearing the song, the brain is perceptually hearing it," says coauthor William Kelley, Assistant Professor of Psychological and Brain Sciences at Dartmouth.

The researchers also found that lyrics impact the different auditory brain regions that are recruited when musical memories are reconstructed. If the music went quiet during an instrumental song, like during the theme from the Pink Panther, individuals activated many different parts of the auditory cortex, going farther back in the processing stream, to fill in the blanks. When remembering songs with words, however, people simply relied on the more advanced parts of the auditory processing stream.

"It makes us think that lyrics might be the focus of the memory," says Kraemer.

The other researchers on this study are Professor C. Neil Macrae and graduate student Adam Green, both with the Psychological and Brain Sciences Department at Dartmouth.


Introduction

The human brain is made of millions of neurons placed in an organized manner to ensure the working of the organ. These neurons communicated with each other using specialized chemicals called neuron transmitters. These chemicals are of several types, and the release varies and depends on several different factors. We know a lot about the brain, and there is a lot that we do not. But, with its complexities and unique coordination system, we have barely scratched the surface.

The human brain is the least understood part of the whole body. This control unit made of organic matter is remarkably complex and is a conundrum of its own. Although the primary function and coordination are pretty defined, the enigma of deeper understanding remains. There are pathways and complex neural connections that are still unknown to humans. The basic communication patterns are known, but how the information is coded in the same chemical is beyond understanding. Behavioral patterns, decisions, preferences, and belief systems originate in the brain, but all processes are unclear. The paradox of memory and emotion is a question of its own.

In this article, we will try to understand human memory and its types, the ways it can be stored in the brain, factors that can trigger memory storage, reasons why a person forgets certain events, and many more. So, keep reading!


Where Are Old Memories Stored in the Brain?

In the 1920s the behavioral psychologist Karl Lashley conducted a now famous series of experiments in an attempt to identify the part of the brain in which memories are stored. He trained rats to find their way through a maze, then made lesions in different parts of the cerebral cortex in an attempt to erase what he called the "engram," or the original memory trace. Lashley failed to find the engram&mdashhis experimental animals were still able to find their way through the maze, no matter where he put lesions on their brains. He therefore concluded that memories are not stored in any single area of the brain, but are instead distributed throughout it.

Subsequent work on amnesics&mdashmost notably the studies of the recently deceased patient known only as H.M. carried out by Brenda Milner&mdashimplicated a part of the brain called the hippocampus as being crucial for memory formation. More recently, it was established that the frontal cortex is also involved current thinking holds that new memories are encoded in the hippocampus and then eventually transferred to the frontal lobes for long-term storage. A new study, led by Christine Smith and Larry Squire at the University of California at San Diego, now provides evidence that the age of a memory determines the extent to which we are dependent on the frontal cortex and hippocampus for recalling it. In other words, the location of a recollection in the brain varies based on how old that recollection is.

Smith and Squire assessed the brain activity associated with the recollection of old and new memories. They recruited 15 healthy male participants, and used functional magnetic resonance imaging (fMRI) to scan their brains while they answered 160 questions about news events that took place at different periods of time during the past 30 years. The study sounds simple, but the design of the experiments was actually somewhat complex, because the researchers had to overcome a number of confounding variables.

First, when one is asked to recall any given memory, the brain encodes not only the questions that were asked to cue the retrieval, but also the resulting recollection, so the associated activity could therefore interfere with that which is being assessed. Second, more recent memories are likely to be richer and more vivid than older ones, so the strength of the fMRI signal could be related not just to the time at which a recalled event occurred but also to the richness of the participants' recollection of it. Finally, recalled memories could be strongly associated with personal events in the participants' lives, which could make them easier to remember.

Testing Old Memories

Smith and Squire therefore designed their experiments so that they could assess the effects of the age of a memory independently of both the encoding of the test questions and richness of the recollection of the memory. At the beginning of the task, the researchers presented in random order blocks of questions about events in each time period, and they asked participants to indicate whether or not they knew the answer. About 10 minutes later, while still in the scanner, the participants were asked three questions about each news event. First, they were asked to recall the original question they had been asked about the event (to assess how well they had encoded the information). Then, they were asked the answer to that question (to assess the accuracy of recall) and, finally, how much they knew about each of the events (to assess the richness of each memory).

In general, the participants' ability to recall any given news event decreased in relation to the amount of time that had passed since the event had occurred. As expected, they were better able to recollect more recent events than older ones. The researchers also found that the participants' memory of the questions they had been asked, and of the content of each news event, was independent of how long ago the events had occurred. The richness of the participants' memories was also unrelated to when a particular event occurred the memories of events that occurred in the distant past were often as rich as those of more recent events.
In their analyses, the researchers used only those fMRI data from the questions that had been answered correctly. This data set showed that medial temporal lobe structures (the hippocampus and amygdala) exhibited gradually decreasing activity as the participants recalled progressively older memories. This drop in activity was true for memories of news events that occurred up to 12 years before, but the recollection of events that took place longer than 12 years was associated with a constant level of activity in those areas. The opposite activation pattern was observed in areas of the frontal, parietal and lateral temporal lobes: activity in these areas increased with the age of the news event being recalled, but remained constant during the recollection of more recent events.

File Cabinets in the Brain

This study therefore provides anatomical and functional evidence supporting the findings obtained from brain-damaged patients with memory impairments. Patients such as H.M., who have lesions in the hippocampus on both sides of the brain, not only lose the ability to form new memories, but also lose memories for events that occurred in the years preceding the onset of their amnesia. The memories of events that took place in the distant past remain intact, whereas those that occurred at intermediate times are lost in a graded manner. This finding suggests that, with time, the hippocampus becomes less important for a given memory, and the frontal cortex more so.

Lashley's theory of memory was not right, but neither was it completely wrong. Why, then, might old memories be transferred from the hippocampus to the frontal cortex? It may be because retrieving older memories requires stronger associations and increased effort&mdashmemory encoding in the frontal cortex is more complex than in the hippocampus, and involves a widely distributed network with a greater number of connections. The frontal cortex may therefore be better suited to the task of retrieving memories that were encoded in the distant past.

Are you a scientist? Have you recently read a peer-reviewed paper that you want to write about? Then contact Mind Matters editor Jonah Lehrer, the science writer behind the blog The Frontal Cortex and the book Proust Was a Neuroscientist. His latest book is How We Decide.


Research in Brain Function and Learning

The brain begins to mature even before birth. Although it continues to mature throughout most of life, the brain does not mature at the same rate in each individual.

This should not be surprising. After all, our bodies grow at different rates — we reach puberty at different ages and our emotional maturity at different times as well. Why should our brains be any different?

Just because you have a classroom full of students who are about the same age doesn't mean they are equally ready to learn a particular topic, concept, skill, or idea. It is important for teachers and parents to understand that maturation of the brain influences learning readiness. For teachers, this is especially important when designing lessons and selecting which strategies to use.

As a teacher, all children need to be challenged and nurtured in order to profit from your instruction. Instruction that is above or below the maturity level of a child's brain is not only inappropriate it can also lead to behavior problems in your classroom. Inappropriate behaviors — such as avoidance, challenging authority and aggression towards other students — can be explained by a failure to match instruction to the brain maturity of your students.

You should also know that all brain functions do not mature at the same rate. A young child with highly advanced verbal skills may develop gross and fine motor control more slowly and have trouble learning to write clearly. Another child may be advanced physically but not know how to manage his/her social skills. Others may be cognitively advanced but show emotional immaturity.

For all of these reasons, it is important to understand how our brains mature as well as the differences that may be present at each stage of "normal" development.

The recommendations below are supported by evidence.

  • Be aware of developmental differences among your students. These differences have implications for behaviors that students display in your classroom.
  • Understand that normal development varies widely within the same age and the same grade. Our educational system is set up for the convenience of teaching large numbers of children in a grade-level classroom. The age for entrance into a particular grade is not necessarily linked to brain maturity for all children. Although you do not determine which children are in your class, you should be sensitive to the variety of developmental levels presented in your classroom.
  • Be aware that children who are born prematurely may not be at the same developmental level as others of their chronological age. Children who are born more than 8 weeks early may not catch up to their peers until they are 3 or 4 years old. Although premature children over the age of 4 are often indistinguishable from children who were not premature, there may be prematurely born children who continue to show delays. Be aware of this possibility when discussing a child's progress with his/her parents.

- Sitting at the front of the class.
- Adjusting his/her pace of school work.
- Receiving a more overt display of understanding and encouragement by his/her teacher.

In addition, it is often helpful to provide children who have chronic illnesses and/or physical limitations alternate activities and to help their peers to understand the reason for offering these different activities.

Activities that pair motor and auditory skills can encourage the development of both pathways.

A child who has difficulty with writing and other fine motor skills benefits from lacing cards, mazes and tracing. These activities actually help students develop the visual-motor areas or their brains.

When a child talks through a difficult visual problem, it can help him/her learn. In other cases, a child whose language skills are delayed may benefit from tasks that don't require language.

  • Don't assume that a child has a disability just because his/her learning is delayed. Be aware that the development of cognitive and other skills is often uneven.
  • Don't assume that delays a child is showing today will get better over time. If a child does not improve his/her progress, it is important to gather more information and then refer the child for further evaluation if indicated.
  • Don't adopt a one-size-fits-all approach. Experienced teachers vary skills and activities for different students within a grade. Some of this variability works because of the different life experiences of children and some works because of differences in brain maturity. But, for either reason, variety is a good thing.
  • Don't place children in groups based solely on age. For some children, learning to read is a struggle. Many are not ready to learn to read until they are seven years old, while others are ready at age four. (This may be particularly true for boys.) Social maturity does not correlate with other learning skills. Both social and learning characteristics need to be addressed separately to determine appropriate placement.
  • Don't judge ability based on physical appearance. It's very important not to judge children based on their physical appearance. Children who are taller and/or more physically mature may not be cognitively advanced. And children with cerebral palsy often have average to above average ability despite significant problems with motor and speech production.

Children learn in different ways. And although the maturity of the brain is an important factor when it comes to learning differences, the real story is more complicated than that. The way children learn depends on age, level of development and brain maturity. Learning differences are also related to genetics, temperament and environment, but in this module we will focus on how and when the brain matures.

Different brain structures mature at different rates and follow different paths, but maturation begins long before birth. As a fetus grows, nerve cells (neurons) travel to their eventual locations within the brain. The survival of any one neuron is not guaranteed. There is competition among neurons for limited space and those that do not find a home — a place where they can live and thrive — are pruned back and destroyed. It is not yet known why some neurons find a home and others do not, but after a neuron settles down it continues to grow and develop within its region of the brain.

When pruning does not happen or is incomplete, disorders in learning and/or behavior can be the result.

Development of the brain from 25 days to 9 months:

At birth, both motor and sensory systems of the brain are already up and running. A newborn infant has enough motor control to feed and to move away from painful or other unpleasant stimuli. Although visual and auditory systems are present at birth, they continue to develop in the first few months of life as the brain reacts to the environment (Carlson, 2014).

In healthy children, motor and sensory systems continue to develop during toddlerhood and the preschool years. Auditory and visual skills improve during this time too. Since brain development after birth is influenced by inputs from the environment, and because those inputs are unique to each child, every human brain is unique.

Note: Inputs from the environment are not always a good thing. Children born prematurely are thought to associate the initial noise and clatter around them as painful. Research indicates that a quiet environment allows these children to catch up as their neurons make connections (Rothbart et al., 2003).

Although the age at which a child is ready to learn a specific skill becomes hard-wired as the brain develops, learning itself is also environmentally determined. For example, a child is ready to learn to read when his or her auditory system is developmentally ready to distinguish one sound from another. But if reading instruction is not provided, or if the child's parents do not enrich the environment by reading to him or her, learning to read will be delayed.

Conversely, a child whose auditory system is not ready when reading instruction is provided will also be delayed in learning to read.

The ability to read is also enhanced by the development of the auditory cortex and the development of skills involved in remembering what is taught and applying that knowledge to real problems.

Note: A key predictor of reading readiness is a child's ability to understand rhyming (Semrud-Clikeman, 2006). This ability translates into skills in understanding how sounds differ and in turn predicts a child's success with phonics instruction.

At every stage of development, it is important to give children age-appropriate tasks. But, be careful when you combine tasks. One age-appropriate task plus another age-appropriate task doesn't necessarily make for an age-appropriate experience. For example:

In the early grades, children learn how to coordinate fine motor skills and visual skills. They are able to copy letters and figures they see. Although this simple task is automatic for you, it takes a lot of concentration for them. Therefore, a child should not be asked to copy items from the blackboard and solve problems at the same time unless the act of copying has become automatic.

During the early elementary years, fibers continue to grow between neurons and the white matter of the brain (also called myelin). The growing neural networks of connected neurons and fibers are essential to the transmission of information throughout the brain. As the brain matures, more and more fibers grow and the brain becomes increasingly interconnected. These interconnected networks of neurons are very important to the formation of memories and the connection of new learning to previous learning.

As neural networks form, the child learns both academically and socially. At first, this learning is mostly rote in nature. As skills become more automatic, the child does not have to think as hard about what he or she is learning or doing, and brain resources are freed up to be used for complex tasks that require more and more attention and processing. Skills in reading, mathematics and writing become more specialized and developed.

The late elementary and middle school years

From late elementary school into middle school, inferential thinking becomes more emphasized in schools, while rote learning is de-emphasized. This shift in focus is supported by the increased connectivity in the brain and by chemical changes in the neuronal pathways that support both short and long term memory. These chemical changes can continue for hours, days and even weeks after the initial learning takes place (Gazzaniga, & Magnun, 2014). Learning becomes more consolidated, as it is stored in long-term memory.

During the early elementary years, the child develops motor skills, visual-motor coordination, reasoning, language, social understanding and memory. As learning is consolidated into neural networks, concepts combine into meaningful units that are available for later use. An ability to generalize and abstract begins at this stage and continues into adulthood. Also during this time, the child learns about perspective-taking and social interaction. The ability to understand one's social place is crucial for the development of appropriate relationships with other people. These skills are closely tied to development of the tracts of the right hemisphere as well as in the areas of the brain that are tied to emotional processing (also called the limbic system) (Semrud-Clikeman, 2007). (A tract is a pathway that connects one part of the brain with another, usually consisting of myelin-insulated axons. Tracts are known collectively as white matter.)

During the later elementary years and early middle school years, the child's brain activity is mostly in the posterior regions where the areas for auditory, visual and tactile functioning intersect. This intersection is called the association area of the brain and generally contains information that has been learned and is now stored. This is the information that is commonly measured on achievement tests and verbally based ability tests.

The frontal lobes begin to mature more fully in middle school. The maturation continues through high school and adulthood (Semrud-Clikeman & Ellison, 2009). The frontal lobes are a more recent evolutionary development in brains and allow humans to evaluate and adapt their behavior based on past experience. The frontal lobes are also thought to be where social understanding and empathy reside (Damasio, 2008).

The refined development of the frontal white matter tracts begins around age 12 and continues into the twenties. This region of the brain is crucial for higher cognitive functions, appropriate social behaviors and the development of formal operations. These tracts develop in an orderly fashion and experience appears to contribute to further development.

If you are teaching adolescents, you should emphasize inferential thinking as well as metacognition. For some adolescents, brain development matches our educational expectations. For others, the two do not coincide and there is a mismatch between biology and education. In this case, the adolescent is unable to obtain the maximum benefit from instruction and is often unable to understand more advanced ideas. Although learning problems may be due to immaturity, they may indicate more serious learning or attentional problems.

As connecting tracts in the frontal lobes become more refined, adolescents are expected to "think" about their behaviors and to change these behaviors. Unfortunately, this is the time when adolescents are more risk-prone and impulsive than adults. Some of this tendency is linked to changes in hormonal development as well as in brain changes.

The figure below shows the white matter tracts in a mature brain. Notice the colored areas that reveal the tracts from front to back of the brain, allowing for good communication both from front to back as well as from right to left.

Brain changes in the frontal lobe continue at a fast pace during adolescence and the healthy individual becomes better able to control more primitive methods of reacting (such as fighting or being verbally aggressive) in favor of behaviors that are adaptive. Adolescents and young adults start to see the world through the eyes of others and they become better at relating to other people.

Their progress toward more independence can be an exciting but also daunting task. When the transition to more adult behavior is problematic, the difficulty may be due to brain maturation. That's where a teacher can help.

Some adolescents need more structure others need more freedom. A teacher is in a unique place to help parents and adolescents to understand these boundaries and to tailor their guidance to each situation. Schools are also beginning to recognize that smaller groupings and more contact with adults helps, too. These changes are very appropriate and in tune with the social and emotional needs of adolescents — as well as brain maturation — that are occurring at this crucial time.

In each stage of development, it is important for teachers to understand the relationship between neurological development and learning. This understanding is particularly important when there is a mismatch between development and educational expectations. The mismatch may be due to brain maturational differences or it can be due to a developmental disability. Research has found differences in brain structure, activation and development in children with learning disabilities (Aylward, E. H., et al., 2003 Maisog et al., 2008 Shaywitz, 2004), attention deficit hyperactivity disorder (Siedman et al., 2006 Swanson, et al., 2007) and in mood disorders (Konarski, et al., 2008 Pliszka, 2005). Further research is needed in all of these areas.

Myth: You can train certain parts of the brain to improve their functioning.

Fact: This has been an attractive and sometimes lucrative idea for many entrepreneurs. However, it is not possible to target a specific brain region and teach just to that part of the brain. The brain is highly connected. Neurons in the brain learn remember and forget, but they do not do so in isolation. Skills need to be broken down into their component parts and these parts can be taught. However, we do not totally understand how this learning takes place nor do we know exactly "where" in the brain that learning is stored. Evidence from victims of stroke and head injury show that injury to the brain of one individual may not result in the same loss in the brain of another person (Goeggel, 2012). Brains are like fingerprints — although there are commonalities, there are differences that make each brain unique.

Myth: You are born with certain abilities and these do not change over time.

Fact: At one time, people believed that the brain developed into its full form by the age of three, and that what developed afterwards was just a matter of refinement. In fact, we now know that the brain is plastic — it changes with experience and development. Evidence shows that rather than ending development at the age of 5, or even 12, brain development continues into one's twenties. For some adolescents, the maturation of the frontal lobes may not end until age 25. For others, frontal-lobe maturity may be reached by the age of 18 or 19. For this reason, some adolescents may require additional time before they are ready for college, while others are ready at an earlier age.

A child with a learning disability will always have the disability.

While a child with a learning disability, or with attention deficit hyperactivity disorder (ADHD), may show continuing problems in these areas, there are treatments that may help the child compensate for the problems. (These interventions are discussed in other parts of this module.) The brain changes with experience and the direct teaching of appropriate skills is the most important aspect of learning for children with special needs. Shaywitz (2004) reports success in teaching compensation skills to children with severe dyslexia beginning at an early age and continuing throughout school. Gross-Glenn (1989) found that adults with an early history of dyslexia, who had learned to read, had developed different pathways compared to those without such a history. The evidence from this research indicates that new pathways can be formed with intervention. Although these pathways are not as efficient as those generally utilized for these tasks, they can function adequately. Response To Intervention is a method that can help tailor an intervention to a child's needs (Fiorello, Hale, & Snyder, 2006).

The environment can improve a child's ability.

The environment can increase ability or it can lower it. A child with average ability in an enriched environment may well accomplish more than a bright child in an impoverished environment. Although it is heartening to believe that enrichment can be effective at any point, recent research indicates that early enrichment is more beneficial than later enrichment. The brain grows in spurts, particularly in the 24th to 26th week of gestation, and between the ages of one and two, two and four, middle childhood (roughly ages 8 to 9) and adolescence (Semrud-Clikeman & Ellison, 2009). These brain growth spurts are roughly commensurate with Piaget's stages of development. They coincide with periods of fast learning of language and motor skills in the one to four year old child concrete operations in middle childhood and formal operations in adolescents. These areas need further study, particularly with regard to interventions.

Skills such as working memory, planning, organization and attention develop over time with brain maturation and with practice.

Working memory is the ability to keep information in mind while solving a problem. For young children, teachers need to give directions one at a time. For late elementary school children, directions can be given in a limited series of steps. For children with difficulty in this area, it is helpful to have them repeat the directions to make sure they recall what is asked of them. Listing steps on the blackboard can also be helpful. Problems in working memory can be linked to difficulties with distractibility and/or attention.

Executive functions are those skills that allow a person to evaluate what has happened, to review what was done, and to change course to an alternative or different response (Diamond, 2006). Executive function skills allow children to understand what has happened previously and to change their behavior to fit new situations. Teachers can help with executive function development by including exercises that ask "what do you think may happen next in the story?" or they can provide story maps.

Planning and organization is the ability to plan and organize is a skill that develops along with the brain's ability to consolidate information. These skills develop slowly and with experience and development. Teachers can assist in developing these abilities by initially asking the child to think about the steps needed to complete a project. Teaching the child how to analyze a problem is also helpful — what do you need to do first? What do you need to do next? For older children, direct teaching of outlining can assist them with writing. The use of day planners and calendars can also help students plan for the completion of longer assignments.

Working memory

Do you ever go to a telephone book to look up a number and remember it just long enough to dial it? That's an example of working memory. If you get distracted between looking up the number and dialing the number, you will forget it. In order for something in working memory to be stored, it must be rehearsed and practiced. For a young child, this is particularly difficult because attention and distractibility significantly impact working memory. In addition, working memory is generally a frontal lobe function and for younger children the frontal lobe is not as well developed as in older children. Therefore, asking a young child to do more than one, or at the most two things at a time will not be successful — their brains are simply not ready. For elementary school children, working memory improves as the brain matures. Most children in elementary school are able to follow up to four directions at one time. For those who are younger, it is possible to practice one direction at a time or to have the child repeat the directions — practicing these skills improves performance. For adolescents, working memory may fail due to distractions. To improve the functioning of working memory it is helpful to make sure the person is listening to you. In addition, even for a fully developed working memory, the memory buffer is sensitive to overload. If a student is asked to do (or remember) too many things at once, he/she will not be able to process this information. Similarly, in a lecture format, information needs to be provided both visually and orally in order for sufficient material to make it into the working memory buffer. The use of lists, rehearsals and day planners have all been found to be helpful in remembering information that would otherwise overload working memory (Diamond, & Lee, 2011).

Executive functions

Evidence suggests that these skills primarily reside in the frontal lobes and develop over time. Although young children have some ability to improve their executive functioning skills based on feedback from teachers and parents, executive functions improve with age. Older children become more adept with these skills and use them more flexibly. It is interesting to note that executive functions are negatively affected by lack of focus, and children with ADHD frequently have difficulty with executive functions.

Recent research also indicates that when material is emotionally charged in a negative way (such as the pressure to learn something for a test, or the pressure of being called on by the teacher and made to answer a question), executive functioning decreases. This happens to some degree in every child, but it is particularly true for children with ADHD (Castellanos, Songua-Barke, & Milham, 2006).

When you are asking any child to perform a task that requires concentration and planning, it is important to provide as much scaffolding as possible for the child in order for him/her to profit from instruction. With maturity, executive functioning is related to appropriate behavior in a variety of situations.

Posner's model

In Posner's model of attention, both posterior and anterior regions of the brain form a complex network that includes subcortical structures such as the caudate nucleus for processing attention-related activities (Posner, & Rothbart, 2007). In this model, there are three networks believed to be involved: alerting, orienting and executive.

The alerting network lets a person know that something different is occurring. The orienting network orients the person to an event — where the event is, what the event is, etc. The executive network coordinates input of information and determines appropriate actions and reactions. Right frontal lobe dysfunctions are related to deficits in the alerting network, bilateral posterior dysfunctions are consistent with deficits in the orienting network, and left caudate nucleus dysfunctions correspond to deficits in the executive network.

Similar to Posner's theory, Corbetta and Shulman (2002) suggest that networks in various parts of the brain are involved in attentional functions. They say that the anterior of the brain is involved in selecting or detecting items to be attended to and preparing goal-driven behavior. The second system is in the temporal-parietal region and the lower frontal regions of the right hemisphere. It is this system that is specialized for the selection of relevant stimuli particularly when an event is unexpected. This second network pays attention to environmental events that are important because they are either rare or surprising. As such, this system would be a protective system to channel attention to particularly threatening or rewarding stimuli.

For further recommendations for skills also see Lynn Meltzer's "Executive Function in Education: From Theory to Practice" (Meltzer, 2011).

  1. Reward good behaviors quickly and as frequently as possible. Please refer to the module on giving praise.
  2. Follow through with consequences. When a child breaks the established rules, warn once. If the behavior continues, follow through with the promised consequence immediately.
  3. For excessive activity:
    1. Use activity as a reward. Alternate a seat-based activity with a more physical activity. For example, send the child to the office with a note for the secretary or give an activity that removes the child from the situation.
    2. Solicit active responses. Examples include talking, moving or organizing responses.
    3. Do not try to reduce physical activity.
    4. Encourage non-disruptive movement.
    5. Allow students to stand while doing seatwork.

    There are few direct studies of differences in brain development between girls and boys, and few to none on ethnicity. However, there are a number of studies looking at differences in brain structure and functioning in children with learning disabilities (LDs), autistic spectrum disorder or ADHD. Findings shed light on the difficulties that can arise when brain development does not go according to plan.

    The next paragraphs briefly review the literature on gender differences, learning disabilities and ADHD. The review is not exhaustive, as research in this area is ongoing. It continues to contribute to our understanding of how the brain matures and give us ideas about interventions that can be used to alleviate problems.

    Although there are few studies looking at gender differences in young girls and boys, it has been found that adult women have a larger corpus callosum (a bundle of myelinated fibers connecting the two hemispheres) than men (Semrud-Clikeman, Fine, & Bledsoe, 2009). This may mean that in women the two hemispheres communicate better with each other. In addition, there are indications that women have their skills spread throughout the brain, while males tend to have their skills in specific regions of the brain. It is not clear whether these differences are universally present. As a result, much more research is needed.

    More and more we are learning that children with learning disabilities have brains that are different. Using magnetic resonance imaging (MRI), many studies have found that the brain area involved in matching sounds and letters is compromised in children with dyslexia (Maisog, Einbinder, Flowers, Turkeltaub, & Eden, 2008). These smaller brain areas correlate with poorer performance on tests of reading achievement, word attack and rapid naming ability of letters, numbers and objects (Gabrieli, 2009). The corpus callosum has also been found to differ in children with dyslexia. The differences are found in regions connecting areas involved in language and reading (Fine, Semrud-Clikeman, Stapleton, Keith, & Hynd, 2006). These differences appear to be due to decreased rates of pruning during the fifth and seventh month of gestation (Paul, 2011).

    Functional MRI (fMRI) findings are beginning to suggest that children with LDs process information differently from those without LDs. Frontal brain regions are more efficient in fluent adult readers compared to children who are beginning to read (Schlaggar, 2003). As a child develops, the left frontal region becomes more active. But, fluent reading appears to be related to this region too. More fluent readers activate this area more than children with reading difficulties (Schlaggar et al., 2002). Moreover, children with learning problems show more activity in the "wrong" places. For example, their parietal and occipital areas are more active, and they show more activity in the right hemisphere than the left. In contrast, children without learning problems activate the frontal regions and the left hemisphere with less activation in the right hemisphere.

    Activation of the brain is more diffuse when children are beginning to learn to read. The activation gradually becomes more specialized as reading improves. Similarly, when asked to read single words, normal readers show left hemispheric activation, whereas those with dyslexia show more right hemispheric activation (Breier, et al., 2002 Papincolaou, 2003).

    Brain regions in the left hemisphere and temporal region have been found to be more active in good readers compared to those who had compensated for their dyslexia and were able to read adequately (Raizada, Tsao, Liu, Holloway, Ansari, & Kuhl, 2010). In addition, Gabrieli (2003) found that improvements were found in activation following remediation of auditory processing ability. It is not yet clear whether these changes continue over time further study is needed to understand possible brain response to remediation. This finding is important because activation of the left hemisphere, a region specialized for language functions, plays an important role in reading while the right hemisphere has generally been implicated for processing of novel stimuli. Since children with learning disabilities activate the right hemisphere when they read, this seems to indicate that they find reading to be a more novel task than a learned task.

    Early reading uses visual-perceptual processes generally located in the posterior portion of the brain. As the reading process becomes more automatized, the frontal systems become more active. Thus, the progression from simple letter and word calling to actual reading comprehension requires a maturation of neural pathways linking the back of the brain to the front (Shaywitz, 2004). Changes from right hemispheric processing to left hemispheric processing have also been found to occur with improvement in reading skills and improvement in language functioning. Such changes are not found for children with dyslexia, and their reading skill does not become automatic and effortless. Additional research is progressing in learning disabilities in older students.

    There have been several studies of the possible structural differences between children with and without attention deficit hyperactivity disorder (ADHD) (Bledsoe, Semrud-Clikeman, Pliszka, 2009 Castellanos, Sonuga-Barke, Milham, & Tannock, 2006 Cherkasova, & Hechtman, 2009 Shaw, Eckstrand, Sharp, Blumenthal, Lerch, Greenstein, . & Rapoport, 2007). A study of total brain volume found a five percent smaller volume in the brains of the group with ADHD compared to a control group. This difference in volume was not related to age, height, weight, or IQ. Another structure of interest has been the caudate nucleus. The caudate nucleus is located in the center of the brain and is associated with the neurotransmitter dopamine. The caudate has been found to be smaller in children with ADHD, possibly indicating less availability of dopamine — the neurotransmitter that assists with focusing of attention and impulse control (Semrud-Clikeman et al., 2006). Volumetric studies have also found smaller frontal lobe volumes in children with ADHD particularly the white matter volume of the frontal lobe. Differences have also been noted in the white matter in the posterior regions of the brain particularly for those children who did not respond to stimulant medication such as Ritalin (Hale, Reddy, Semrud-Clikeman, Hain, Whitaker, Morley, . & Jones, 2011).

    3-D illustration of the Caudate

    Coronal slice showing white matter

    The finding of reduced white matter volume in the right frontal and posterior regions of the brain, as well as caudate asymmetry differences, suggests that systems commonly associated with sustained attention are different for children with ADHD. This finding may help to explain the difficulty children with ADHD have in more advanced attentional functions, such as self-regulation and executive function. Reduced white-matter volume leads to less communication between the frontal and posterior areas. The posterior region of the brain is responsible for accessing information from previous situations while the frontal region of the brain applies this knowledge to the current situation at hand. When there is not enough communication between these two centers, the child will have difficulty either accessing previously learned information or applying it correctly to the new situation. This corresponds to the finding that a child with ADHD has difficulty applying knowledge (or rules) even though he/she may be able to tell you the rule.

    A fairly new avenue of investigation is the gene X environment interaction to help understand the etiology and course of ADHD. Nigg et al. (2010) reviewed the literature and found that psychosocial factors contribute to attentional difficulty. For example, a child may do adequately if family stresses are lower. However, if family disruptions (divorce, contentious parenting) occur, significant impairment may ensue. ADHD has a relatively high heritability meaning that it tends to run in families. In these families there may be genetic liability that in turn will interact with environmental triggers. Thus, when working with families with a history of ADHD, it is important for educators to provide information as appropriate and to be aware of these vulnerabilities.

    The development of fewer connections between brain areas may well impact the efficiency of these connections — resulting in a poorer level of functioning but not a total loss of function (Fair, Nagel, Bathula, Dias, Mills, . & Nigg, 2010 Makris, Buka, Biederman, Papadimitriou, Hodge, Valera, . & Seidman, 2008 Nigg, 2006). Functional neuroimaging, which allows one to view what the brain is doing when the person is completing a task, showed lowered activation in the regions of the frontal lobe and caudate nucleus when the child is asked to inhibit a response. (Not respond when he/she would like to respond) (Pliszka et al., 2006). Less activation may well indicate fewer connections being made between neural networks and poorer attention to detail. Additional study is needed in this area to more fully understand differences that may be present in children with ADHD and those without.

    Children with autism have been found to have larger heads than the general population (Verhoeven, De Cock, Lagae, & Sunaert, 2010). It has been found that the brains of toddlers with autism are 10 percent larger than same-aged peers, with the largeness of the head decreasing with age. They continue, however, to be larger than matched aged peers throughout life (Anagnostou, & Taylor, 2011). Interestingly, there is no difference in head size at birth (Keller, Kana, & Just, 2007) and the brain growth that later occurs may be due to early overgrowth of neurons, glial cells and a lack of synaptic pruning. Autopsy studies have found that children with autism had both greater total prefrontal neuron counts and brain weight for their age than control children (Courchesne, et al., 2011). Findings have suggested that the extra tissue that causes the increase in size is not well utilized or organized — thus resulting in poorer skill development (Aylward et al., 2002). Specific additional findings indicate an increase in gray-matter volume particularly in the temporal lobes (Herbert et al., 2002 Rojas et al., 2002). Using structural MRI analyses, Courchesne et al. (2003) found smaller amounts of white matter compared to gray matter in toddlers and adolescents. Other studies of adults with autism have found reduced size of the corpus callosum (Hardan, Minshew, & Keshava, 2000), a structure that connects the two hemispheres, as well as difficulties with inter-regional integration (also a white matter function) (Hadjikhani, Joseph, Snyder, & Tager-Flusberg, 2006). Some studies have suggested that the larger brain, higher white matter volume and disrupted gray matter cellular columns may contribute difficulty that a person with autism has in integrating information and generalizing this information to new situations (Schultz et al., 2000). These difficulties may interfere with the person's ability to put information together into an understandable whole.

    fMRI autism vs. healthy control activation pattern

    MRI autism vs. healthy control volume comparision

    The amygdala, anterior cingulate and hippocampus are part of the limbic system — the emotional part of the brain. The amygdala is important in emotional arousal, as well as processing social information. The hippocampus allows for the short-term and eventual long-term storage of information while the anterior cingulate works as a type of central executive, directing attention where it is most required.

    Autopsies of autistic individuals have revealed abnormalities of both the hippocampus and the amygdala including fewer connections and smaller hippocampi. This finding could lead to difficulties in forming new memories or associating emotions with past memories (Carlson, 2014), and may contribute to difficulties seen in people with autism with respect to social reciprocity and social awareness. Structural neuroimaging studies of children with autism show the volume of the amygdala and hippocampus to be enlarged (Groen, Teluij, Buitelaar, & Tendolkar, 2010), although further research is needed in these areas. Some have suggested that the amygdala may be important for mediating physiological arousal and if it is not as active, the person may well not be as motivated for participating in social activities (Murphy, Deeley, Daly, Ecker, O'Brien, Hallahan, & Murphy, 2012).

    More recent studies have begun evaluating discrete areas of the brain that may be disrupted in people with autism. An area of the temporal lobe that has been found to be important for recognizing faces has been studied in children with autism. This area has been found to be underactive in people with autism and the degree of under-activation is highly correlated with the degree of social impairment (Schultz et al., 2001). Of additional interest is that this area of the temporal lobe has also been implicated in successful solution of Theory of Mind tasks, skills that are also impaired in people with autism (Castelli et al., 2000 Martin & Weisberg, 2003).

    Both the frontal lobes and the upper area of the temporal lobes are important for understanding and perception of social interactions as well as interpretation of facial expressions. The frontal lobes have also been implicated in the ability to take another's perspective — or in social cognition. These areas are intimately connected to the limbic system as well as the temporal lobe areas discussed earlier in this section. Studies of brain metabolism have found reduced activity in these regions of the brain in patients with autism particularly when asked to perform tasks that tap social cognition and perception (Harms, Martin, & Wallace, 2010).

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    Abstract: Higher-level reasoning or understanding.

    Amygdala: An almond-shaped cluster of neurons in the limbic system thought to be involved in processing emotions and memory.

    Anterior cingulate: Anterior section of the cingulate cortex. Asymmetry: favoring one side or the other. Also called laterality.

    Attention deficit hyperactivity disorder: Mental disorder that consists of behaviors such as impulsivity, hyperactivity and difficulties with inhibition and self-regulation

    Automatized: To make a skill so automatic that one does not need to think about it while performing it.

    Caudate nucleus: Part of the Basal-Ganglia, the Caudate nucleus is thought to be involved in regulation of movement, learning and memory.

    Corpus Callosum: A white matter structure that connects the right and left hemispheres of the cerebral cortex. Thought to contain approximately 250 million axons that allow right and left hemisphere communication.

    Dopamine (DA): Part of the catecholamine family of neurotransmitters (epinephrine and norepinephrine), Dopamine is naturally produced in the brain and is thought to be involved in reward-based cognitive functions.

    Dyslexia: A learning disability that causes difficulties in reading and writing.

    Empathy: The ability to recognize and vicariously experience another person's emotional state.

    Executive function: Higher-order cognitive processes that allow one to control organization of thought, and apply context specific rules in order to execute a task successfully.

    Formal operations: The skill to think systematically about all of the parts of a problem and to arrive at a reasonable solution.

    Frontal lobes: Area of the brain made up by the front portions of right and left hemispheres of the cerebral cortex. These areas are involved in memory, planning, organization, language and impulse control. These areas also have been linked to personality.

    Functional magnetic resonance imaging (fMRI): A technique in which neural activity is measured by changes in blood flow. Brighter areas on an fMRI images indicate higher amounts of blood flow and greater activity.

    Generalize: To apply a conclusion beyond a specific example.

    Glial cells: Cells of the nervous system that provide physical support and nutrition for neurons. Higher cognitive functions: See executive functions.

    Hippocampus: Part of the limbic system involved in storing new knowledge.

    Impulsive: Behaviors that are not thought out.

    Inferential thinking: Reading between the lines, often involves meaning that is implied rather than explicit.

    Inhibition: The ability to regulate behavior or impulses.

    Inter-regional integration: Neural connections that are similar in location. Language: A system/group of symbols used in verbal and visual communication.

    Learning disability: Difficulties in the development of language, reading, mathematical reasoning or other academic undertakings compared to expectations of one's ability. Believed to be neurological in nature.

    Left hemisphere: The left side of the cerebral cortex, thought to mediate language and verbal communication.

    Limbic system: A multistructural system involved in emotions, memory and physical regulation. Structures such as the amygdala, cingulate gyrus, hippocampus, hypothalamus, ammillary body, nucleus accumbens, orbitofrontal cortex, and thalamus are all structures of the limbic system.

    Memory: Ability to store and recall conceptual, social, emotional and physical information.

    Metacognition : Thinking about one's own learning, thinking or perception.

    Myelinate: The white matter in the brain. It is made up of lipids (fat) that help impulses move more quickly along the nerve.

    Myelination: Process during development by which Myelin is formed over the neurons.

    Neuronal pathways: These are pathways through which nerve messages travel as they move among the various parts of the brain.

    Neurons: Cells that make up the nervous system, they process and transmit signals electrically.

    Neurotransmitter: Nervous system chemicals that relay, amplify and modulate electrical signals from one neuron to another neuron.

    Perspective-taking: The ability to understand another person's point of view or beliefs. Processing of novel stimuli: Analyzing new information that the brain has not seen before.

    Pruning: Process by which brain cells die off in order to make room for more efficient connections between neurons.

    Reasoning: Mental process that deals with one's ability to perceive and respond to feelings, thoughts and emotions.

    Right hemisphere: The right side of the cerebral cortex, thought to mediate spatial, social and emotional understanding.

    Risk-prone: Susceptible to taking chances and making mistakes.

    Rote: Learning by memorization.

    Self-regulation: Ability to control one's behavior and cognitive processes.

    Social understanding: Ability to manage and function in social settings such as peer relationships.

    Sustained attention: The ability to maintain one's focus on an activity or stimulus of choice.

    Synaptic pruning: When weaker neural connections are thinned and replaced by stronger connections.

    Temporal region: The side region of the cerebrum thought to be involved in auditory processing.

    Theory of Mind tasks: Tasks that evaluate whether one has the ability to consider another's personal beliefs, needs, desires and intentions.

    Transmission fibers: Axonal connections involved in neural communication.

    Visual-motor: Coordination of visual and motor processes, like tracing letters.

    Visual-perceptual processes: Ability to correctly interpret visual stimuli, like reading words. White matter fibers: Myelinated axons.

    White matter volume: Quantified amount of myelinated axons.


    Learning and Memory in the Brain: How Science Cracked Your Mind's Code

    Dr. Eric Kandel is University Professor and Fred Kavli Professor and Director of the Kavli Institute for Brain Science at the Columbia University College of Physicians and Surgeons. His most recent book is The Age of Insight: The Quest to Understand the Unconscious in Art, Mind, and Brain, from Vienna 1900 to the Present.

    Kandel's research has shown that learning produces changes in behavior by modifying the strength of connections between nerve cells, rather than by altering the brain's basic circuitry. He went on to determine the biochemical changes that accompany memory formation, showing that short-term memory involves a functional modulation of the synapses while long-term memory requires the activation of genes and the synthesis of proteins to grow new synaptic connections. For this work, the Austrian-born Kandel was awarded the 2000 Nobel Prize in Physiology or Medicine.

    Eric Kandel: What reductionism allows you to do is to take a complex problem and focus on one component of it and try to understand it in some detail. And sometimes you can just do it by focusing on one component, other times it requires selecting a particular biological system if you're working in biology, in which that component is prominent or easy to study. And that allows you to study in depth the problem. It will be hard to do if you looked at it in all its complexities.

    For me the reductionist approach was really very profitable and not something that I really thought a lot about before. I originally went to medical school with the idea of becoming a psychoanalyst. I didn't have a strong biological background at all. And then in my senior year at medical school there was a five-month elective period in which you could do whatever you wanted to and I thought that even a psychoanalyst should know something about the brain. And so I took an elective in brain science. There were very few people doing brain science in those days, but Columbia had an outstanding person, Harry Grenfist. And I worked in his lab and I worked with one of his associates Don Perpera and had an absolutely spectacular experience.

    I mean actually doing science is so different than reading about it. There's a sensual pleasure of doing the experiments there's the fun of thinking about it coming up with a new finding. I just thought it was marvelous. And Denise and I had just decided to get married and we had dinner one night and I remember saying to her, "You know, I could see doing this for the rest of my life but it's completely unrealistic. You don't have any money and I don't have any money, you know, we want to have kids I should have a really gone into practice." And she banged on the table and she said, "Money is of no significance." I should tell you sotto voce that in the subsequent 60 years she's not repeated those words very often, but she did say them that night and it made a big impact on me. So I decided to go ahead with science. And when I got out of medical school, which she was in 1956, physicians were being drafted in the service for two years, but if you qualified for the National Institute of Health that served as an alternative to draft duty. So he nominated me, Grenfist, to the NIH, National Institute of Health, and I was selected. So in fact I spent three years there, I spent next three years doing brain biology. And I asked myself what's the central problem in psychoanalysis and I thought memory storage. We all who we are because we remember and psychoanalysis is designed to allow you to relive earlier experiences, earlier memories in a protected environment.

    Brenda Miller has shown that the hippocampus in the mammalian brain is central for memory storage. And I had mastered it in Grenfist's lab how to put electrodes into single cells. This is something many people can do now, but when he taught it to me relatively few people could do it, the fact the whole population doing brain science was very small. So my colleague Olen Spence, whom I've recruited to join me on this and I were the first people in the world to record from single cells in the hippocampus. We were euphoric. The people around us thought it was fantastic. Two incompetent people coming to the NIH and the intellectual environment is so extraordinary it brings them up to this higher level. So we studied these single cells to characterize their properties and we saw after a while they were not dramatically different from the other two or three groups of cells that have been described. So clearly learning doesn't reside just in the properties of cells, it should have been obvious in the beginning, it resides in how behavior is modified by learning, how something changes in the neural network.

    And we had no idea what the sensor information coming into the hippocampus was. We tried various things and nothing worked. It turns out that space is very important, it's a complex modality. So I realized one needed to take a very different approach, a reductionist approach rather than going to the most complex example human memory, take it very simple. Pablo Thorndike just studied simple reflex behaviors and how they were modified by learning. So I began to look for an animal that had simple reflex behaviors and it was adventitious from a nervous system point of view and that's what led me to Aplysia. It's an animal that has only 20,000 nerve cells compared to the hundred millions of nervous cells in your brain, it only has 20,000. And each of them is gigantic. Aplysia have the largest nerve cells in the animal kingdom. And you can easily put an electrode into any of these cells and be there for 24 hours if you wanted to.

    And the cells are not only large they're uniquely identifiable so you can return to the same cell in every animal of the species. Not only that but it turns out that one of the most interesting laboratories, there are only two laboratories working on it, was in Paris. My wife is a Parisian chauvinist so we went to Paris. The alternative was Marseilles, another person was working Angelique worked in Marseilles. Denise said, "Going to Marseilles is likely going to Albany, we should go to Paris," so we went to Paris. We had a great year. And I started to work out a very simple behavior in the animal, a withdrawal reflex like the withdrawal of a hand from a hot object and I showed it could be modified by different forms of learning. And in each case the learning involved a change in the strength of synaptic connections. So nerve cells connect with each other that junctions called synapses and I found that those synapses, they're not fixed but they're plastic they're modified by learning. Certain kinds of learning causes an increase in strength, learned fear, classic conditioning. Some like habituation learning to forget about something leads to a decrease in synaptic strength.

    Later I found there's a short-term memory node. Long-term memory and - short-term memory is a change in functional connections that last for minutes to hours and long-term memory is actually an anatomical change, a growth of new synaptic connections. So I really learned a great deal about this. And then about 1980 I started a second front I returned to the hippocampus. By that time one had a much better understanding. And it turned out that the rules there were pretty much the same here except one is looking at more complex behavior.

    The human brain has become the premier object of study for fields ranging from psychology to machine learning and artificial intelligence. What we know about the brain has expanded greatly in the last quarter century, thanks primarily to a specific method of scientific inquiry: reductionism. As Nobel Prize-winning scientist Eric Kandel explains, this process of breaking apparently whole parts into smaller units gives a real sense of the brain's underlying mechanisms.

    Kandel's personal story of how he made new discoveries about the brain parallel his own reductionist method: by breaking down the steps he went through, we can better understand how scientific discoveries are made. In this case, they were surprisingly haphazard. Indeed Kandel was not schooled in neuroscience at all. He was primarily interested in psychoanalysis, and in his senior year of school, was given the chance to study the biology of the brain at the National Insitutes of Health.

    Once there, he pursued specific methods of breaking down individual brain regions into component parts, observing how individual neurons reacted to stimulus, and how they worked to store memories in the brain. This method — reductionism — revealed to Kandel the difference between long-term and short-term memory, and the plastic nature of the brain itself. His life's work is an example of the surprising ways scientific discovery can happen, and the creativity involved in reaching new understandings of the world — and ourselves.


    Transcript

    How does the human memory work? Twenty years ago you might have found your answer in a book, or by asking a friend. But today, you’ll Google it. There were 3.5 million searches in 1998, now, there are 4.7 trillion search queries everyday. 1 When something changes our lifestyle so monumentally, you can bet it’s changing us as well.

    Google has become our external hard drive. In a recent experiment, college students remembered less information when they thought they could easily access it later. We used to rely on friends and family members for this method of memory outsourcing, remembering who knew what rather than the information itself. 2 But now, Google is the friend with all of the expertise. If the sum of all knowledge is constantly available in our pockets, is it any wonder that we’ve stopped bothering to keep it in our heads?

    Neurons that fire together, wire together.” And the same goes for those that fire apart. Neuroimaging of frequent Internet users shows twice as much activity in the prefrontal cortex as sporadic users. 3 This part of the brain is reserved for short-term memory and quick decision-making. Essentially, our brains recognize that most of the flood of online information is trivial, and doesn’t deserve our full attention. The problem is, the brain does what we train it to do. And every time we open a browser, we prepare for skimming instead of learning. So even if we really want to remember something from Google, our brains are predisposed to forget. Everything we ever wanted to know is available to us, and we have conditioned ourselves to ignore it.

    What do we actually know? If the goal is to forge a creative mind through critical thinking, our Google amnesia may be problematic. The information and experience that gets encoded into our long-term memory is the basis of our unique intelligence. 4 Still, we may be able to mitigate the impact to our long-term memory by adapting our response to this new reality. After all, we can’t stop the sea change of the information age. In recent years, American schools have focused less on fact memorization and more on teaching students how to make innovative connections between the curriculum and real life. 5 This way, it’s less about the knowledge you have, and more about how you use the information at hand.


    What happens to the brain as we age?

    Brain aging is inevitable to some extent, but it is not uniform it affects everyone, or every brain, differently.

    Share on Pinterest The effects of aging on the brain can vary from person to person.

    Slowing down brain aging or stopping it altogether would be the ultimate elixir to achieve eternal youth. Is brain aging a slippery slope that we need to accept? Or are there steps that we can take to reduce the rate of decline?

    At around 3 pounds in weight, the human brain is a staggering feat of engineering, with around 100 billion neurons interconnected via trillions of synapses.

    Throughout a lifetime, the brain changes more than any other part of the body. From the moment the brain begins to develop in the third week of gestation to old age, its complex structures and functions are changing, networks and pathways connecting and severing.

    During the first few years of life, the brain forms more than 1 million new neural connections every second. The size of the brain increases fourfold in the preschool period, and by age 6, it reaches around 90% of its adult volume.

    The frontal lobes are the area of the brain responsible for executive functions, such as planning, working memory, and impulse control. These are among the last areas of the brain to mature, and they may not develop fully until around 35 years of age .

    As people age, their bodily systems — including the brain — gradually decline. “Slips of the mind” are associated with getting older. That said, people often experience those same slight memory lapses in their 20s but do not give it a second thought.

    Older adults often become anxious about memory slips due to the link between impaired memory and Alzheimer’s disease. However, Alzheimer’s and other dementias are not a part of the normal aging process.

    Common memory changes that are associated with normal aging include:

    • Difficulty learning something new: Committing new information to memory can take longer.
    • Multitasking: Slowed processing can make planning parallel tasks more difficult.
    • Recalling names and numbers: Strategic memory, which helps with remembering names and numbers, begins to decline at age 20.
    • Remembering appointments: Without cues to recall the information, the brain may put appointments into “storage” and not access them unless something jogs the person’s memory.

    Although some studies show that one-third of older adults struggle with declarative memory — that is, memories of facts or events that the brain has stored and can retrieve — other studies indicate that one-fifth of 70-year-olds perform cognitive tests just as well as people aged 20.

    Scientists are currently piecing together sections of the giant puzzle of brain research to determine how the brain subtly alters over time to cause these changes.

    General changes that researchers think occur during brain aging include:

    • Brain mass: Shrinkage in the frontal lobe and hippocampus, which are areas involved in higher cognitive function and encoding new memories, starts at around the age of 60 or 70 years.
    • Cortical density: This refers to the thinning of the outer-ridged surface of the brain due to declining synaptic connections. Fewer connections may contribute to slower cognitive processing.
    • White matter: White matter consists of myelinated nerve fibers that are bundled into tracts and carry nerve signals between brain cells. Researchers think that myelin shrinks with age, and, as a result, processing is slower and cognitive function is reduced.
    • Neurotransmitter systems: Researchers suggest that the brain generates fewer chemical messengers with age, and it is this decrease in dopamine, acetylcholine, serotonin, and norepinephrine activity that may play a role in declining cognition and memory and increasing depression.

    In understanding the neural basis of cognitive decline, researchers can uncover which therapies or strategies may help slow or prevent brain deterioration.

    Several brain studies are ongoing to solve the brain aging conundrum, and scientists are frequently making discoveries.

    The sections below will outline some of these in more detail.

    Stem cells

    In 2017, researchers from Albert Einstein College of Medicine in New York City, NY, revealed in a mouse study that stem cells in the brain’s hypothalamus likely control how fast aging occurs in the body.

    “Our research shows that the number of hypothalamic neural stem cells naturally declines over the life of the animal, and this decline accelerates aging,” says Dr. Dongsheng Cai, a professor of molecular pharmacology.

    “But,” he adds, “we also found that the effects of this loss are not irreversible. By replenishing these stem cells or the molecules they produce, it’s possible to slow and even reverse various aspects of aging throughout the body.”

    Injecting hypothalamic stem cells into the brains of normal old and middle-aged mice, whose stem cells had been destroyed, slowed or reversed measures of aging. The researchers say that this is a first step toward slowing the aging process and potentially treated age-related conditions.

    SuperAgers

    “SuperAgers” are a rare group of individuals over the age of 80 years who have memories as sharp as those of healthy people decades younger.

    Research by scientists at Northwestern University Feinberg School of Medicine in Chicago, IL, compared SuperAgers with a control group of same-age individuals.

    They found that the brains of the SuperAgers shrink at a slower rate than those of their age-matched peers, which results in a greater resistance to the typical memory loss that occurs age. This suggests that age-related cognitive decline is not inevitable.

    “We found that SuperAgers are resistant to the normal rate of decline that we see in average [older adults], and they’re managing to strike a balance between life span and health span, really living well and enjoying their later years of life,” says Emily Rogalski, an associate professor.

    By studying how SuperAgers are unique, the researchers hope to unearth biological factors that might contribute to maintaining memory ability in advanced age.

    Researchers have discovered several factors that speed up brain aging.

    For example, obesity in midlife may accelerate brain aging by around 10 years, and both sugar and diet varieties of soda are associated with poorer brain health.

    A growing body of evidence suggests that people who experience the least declines in cognition and memory all share certain habits:

    • engaging in regular physical activity
    • pursuing intellectually stimulating activities
    • staying socially active
    • managing stress
    • eating a healthful diet
    • sleeping well

    Recent research highlights a plethora of ways that people can actively take charge of their health and perhaps decrease the rate at which their brains age.

    The following sections will look at some of these tips in more detail.

    Exercising

    One intervention that crops up time and time again to stave off age-related mental decline is physical exercise.

    Performing a combination of aerobic and resistance exercise of moderate intensity for at least 45 minutes each session on as many days of the week as possible can significantly boost brain power in people aged 50 and over.

    Likewise, other research by the University of Miami in Florida found that individuals over the age of 50 who engaged in little to no exercise experienced a decline in memory and thinking skills comparable to 10 years of aging in 5 years, compared with those who took part in moderate or high intensity exercise.

    Essentially, physical activity slowed brain aging by 10 years.

    Dancing may also have an anti-aging effect on the brains of older adults. A study by the German Center for Neurodegenerative Diseases in Magdeburg found that although regular exercise can reverse the signs of brain aging, the most profound effect was among people who danced.

    Playing an instrument

    Researchers at Baycrest Health Sciences in Toronto, Canada, revealed why playing a musical instrument may help older adults ward off age-related cognitive decline and retain their listening skills.

    Researchers found that learning to play a sound on a musical instrument changes brain waves in such a way that improves an individual’s listening and hearing skills. The alteration in brain activity indicates that the brain rewires itself to compensate for disease or injuries that might prevent a person’s ability to perform tasks.

    “It has been hypothesized,” says Dr. Bernhard Ross, a senior scientist at Baycrest’s Rotman Research Institute, “that the act of playing music requires many brain systems to work together, such as the hearing, motor, and perception systems.”

    “This study was the first time we saw direct changes in the brain after one session, demonstrating that the action of creating music leads to a strong change in brain activity,” he adds.

    Eating a healthful diet

    A key component of brain health is diet. In 2018, researchers linked omega-3 and omega-6 fatty acids in the blood with healthy brain aging.

    Another study has also determined that consuming foods included in the Mediterranean or MIND diet is associated with a lower risk of memory difficulties in older adults.

    Research by the University of Illinois at Urbana-Champaign discovered that middle-aged people with higher levels of lutein — which is a nutrient present in green leafy vegetables, such as kale and spinach, as well as eggs and avocados — had similar neural responses to younger individuals than those of people of the same age.

    “As people get older, they experience typical decline. However, research has shown that this process can start earlier than expected. You can even start to see some differences in the 30s,” says first study author Anne Walk, a postdoctoral scholar.

    “We want to understand how diet impacts cognition throughout the life span,” she adds. “If lutein can protect against decline, we should encourage people to consume lutein-rich foods at a point in their lives when it has maximum benefit.”

    The number of adults in the United States over the age of 65 is set to more than double in the next 40 years, rising from 40.2 million in 2010 to 88.5 million by 2050.

    Due to this aging population, it will become increasingly important to understand the cognitive changes that go hand in hand with aging.

    Although many questions remain regarding the aging brain, research is making progress in illuminating what happens to our cognitive functions and memory throughout our lifetime.

    It is also emphasizing the ways in which we can preserve our mental abilities to improve our quality of life as we advance into older adulthood.


    THE HIPPOCAMPUS

    Another group of researchers also experimented with rats to learn how the hippocampus functions in memory processing ([link]). They created lesions in the hippocampi of the rats, and found that the rats demonstrated memory impairment on various tasks, such as object recognition and maze running. They concluded that the hippocampus is involved in memory, specifically normal recognition memory as well as spatial memory (when the memory tasks are like recall tests) (Clark, Zola, & Squire, 2000). Another job of the hippocampus is to project information to cortical regions that give memories meaning and connect them with other connected memories. It also plays a part in memory consolidation: the process of transferring new learning into long-term memory.

    Injury to this area leaves us unable to process new declarative memories. One famous patient, known for years only as H. M., had both his left and right temporal lobes (hippocampi) removed in an attempt to help control the seizures he had been suffering from for years (Corkin, Amaral, González, Johnson, & Hyman, 1997). As a result, his declarative memory was significantly affected, and he could not form new semantic knowledge. He lost the ability to form new memories, yet he could still remember information and events that had occurred prior to the surgery.


    For a closer look at how memory works, view this video on quirks of memory, and read more in this article about patient HM.


    Working memory

    Prefrontal cortex

    The prefrontal cortex (PFC) is the part of the neocortex that sits at the very front of the brain. It is the most recent addition to the mammalian brain, and is involved in many complex cognitive functions. Human neuroimaging studies using magnetic resonance imaging (MRI) machines show that when people perform tasks requiring them to hold information in their short-term memory, such as the location of a flash of light, the PFC becomes active. There also seems to be a functional separation between left and right sides of the PFC: the left is more involved in verbal working memory while the right is more active in spatial working memory, such as remembering where the flash of light occurred.