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This section will go over and explain how the brain works and how it is responsible for different areas of the brain that control language, processing, and movement. Understanding how the brain works helps teachers plan lessons for a class of diverse learners and it helps with reaching different parts of the brain when they are planning.

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1. It is important to incorporate visuals and movement activities when teaching and planning. This will stimulate multiple areas of the brain.

2. Model and practice storytelling. This will stimulate the language region of the brain.

3. Allow students the opportunity to participate in Think Aloud's. This allows them to explain their thinking and stimulate the area of the brain for language.

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Also known as Neuroplasticity

By Eagle Gamma, published March 23, 2021

Take-home Messages

Brain plasticity, also known as neuroplasticity, is the biological, chemical, and physical capacity for the brain to reorganize its structure and function.

Neuroplasticity occurs as a result of learning, experience and memory formation, or as a result of damage to the brain.

Learning and new experiences cause new neural pathways to strengthen whereas neural pathways which are used infrequently become weak and eventually die. This process is called synaptic pruning.

Although traditionally associated with changes in childhood, recent research indicates that mature brains continue to show plasticity as a result of learning.

During human development, neuroplasticity provides protective effects in terms of managing traumas (Cioni et al., 2011). Also, learning music or second languages can increase neuroplasticity (Herholtz & Zatorre, 2012).

Plasticity allows the brain to cope better with the indirect effects of brain damage resulting from inadequate blood supply following a stroke.

Fundamentally, the nervous system needs to rearrange itself in order to adapt to the unfolding situation that it faces. The genes program the body to have neuroplasticity so that animals can survive in unpredictable environments.

Neuroplasticity, also called brain plasticity, refers to the capacity of the brain to change and adapt in structure and function in response to learning and experience.

Behance Discovery - Alexey Kashpersky
The brain possesses a remarkable ability to rewire itself. These changes range from individual neuron pathways making new connections, to systematic adjustments like cortical remapping.

This occurs in all healthy people, especially children, as well as after various problems like brain injuries.
Early Theories
Early experimental work on neuroplasticity was conducted by an eighteenth-century Italian scientist, Michele Malacarne, who discovered that animals made to learn tasks would develop larger brain structures (Rosenzweig, 1996).

The first theoretical notions of neural plasticity were developed in the nineteenth century by William James, a pioneer of psychology. James wrote about this topic in his 1890 book The Principles of Psychology (James, 1890).

In the twentieth century, influential neuroscientist Santiago Ramón y Cajal proposed that neurons in adults break down and rebuild (Fuchs & Flügge, 2014).
Modern Theories
Progress of the idea - modern theories: Modern experimental instruments like imaging tools have yielded enough information to develop improved theories.

Scientists now think that neuroplasticity occurs throughout all life stages, having extensive capacities from childhood development through healing diseases (Doidge, 2007).

The brain can rearrange itself in terms of the functions it carries out, as well as in terms of the basic underlying structure (Zilles, 1992).

Functional Plasticity

Functional Recovery After Brain Trauma

Functional plasticity is the brain's ability to move functions from a damaged area of the brain after trauma, to other undamaged areas. Existing neural pathways that are inactive or used for other purposes take over and carry out functions lost because of the injury.

After brain injury such as accidents or stroke, the unaffected brain areas can adapt and take over the functions of the affected parts. This process vary in speed but it can be fast in the first few weeks (phase of spontaneous recovery) then it becomes slower.

It can be helped by rehabilitation, and the nature of rehabilitation programmes varies with the type of injury from retraining some types of movement to speech therapy.

There are ways through which brain plasticity can enable brain-damaged people to regain some of their past capacities. Each of the approaches through which the nervous system adapts its functionality has differences in terms of how it occurs, as well as in which patients it occurs.
Homologous Area Adaptation
Evidence for Functional Plasticity
Homologous Area Adaptation:
Case studies of stroke victims who have experienced brain damage and thus lost some brain functions have shown that the brain has an ability to re-wire itself with undamaged brain sites taking over the functions of damaged brain sites.

Thus, neurons next to damaged brain sites can take over at least some of the functions that have been lost.

A youth with a right parietal lobe injury wound up with the left parietal lobe taking over some functions normally occurring on the right side. The youth then had difficulty with tasks normally occurring on the left side, because some right-side equivalents had taken over left-side brain resources (Grafman, 2000).
Neuronal Unmasking:
Wall (1977) noticed the brain contained 'dormant synapses' - neural connections which have no function.

However, when brain damage occurs these synapses can become activated and open up connections to regions of the brain that are not normally active and take over the neural function that has been lost as a result of damage.

Structural Plasticity

How Experience Changes Brain Plasticity

Structural neuroplasticity is the brain's ability to change its physical structure as a result of learning, involving reshaping individual neurons (nerve cells).

During infancy, the brain experiences rapid growth in the number of synaptic connections. As each neuron matures, it sends out multiple branches, this increases the number of synaptic contacts from neuron to neuron. At birth, each neuron in the cerebral cortex has approximately 2,500 synapses.

By the time a child is three years old, the number of synapses is approximately 15,000 synapses per neuron (Gopnick, et al. 1999).

As we mature the connections we do not use are deleted and the ones we use frequently are strengthened, and this is called neural pruning (Purcell & Zukerman, 2011). This process continues throughout our life.

While plasticity occurs throughout life, it is especially relevant during the early "critical years," when brain plasticity enables the senses, language, and other skills to develop.
Developmental plasticity
Part of the development of the vision system is genetically hardwired. However, another part of this development depends on neuroplasticity. As a child grows, the incoming information from light sources, such as light reflected off the faces of caregivers, provides necessary cues for the brain to adjust its growth patterns. The equivalent plasticity-based growth also occurs with the other senses, calibrating the young person to local conditions.

The development of language reveals even more about neuroplasticity. Again, part of this functionality is genetically hardwired, but part depends on feedback from the environment. An individual has certain nerve cells programmed to become grammar modules. For these to function correctly, they require the input of specific grammatical rules from a culture, such as the rules of English or Spanish. Thus, neuroplasticity enables the brain to process language.
New neural connections, different densities of nerve cells, varying strengths of neural connections
How does neuroplasticity work? At the most basic level, it starts with the production of a new nerve cell ( neurogenesis). Then, individual neurons develop new connections to each other.

A neuron works by sending or receiving electrochemical signals with other neurons in the brain.

The way that individual neurons connect to each other controls how the signals get sent, like the routing of messages over the internet or of instructions codes in a computer processor.

As each neuron develops connections to others, this results in growing clusters of cells. The neurons can adjust the level or strength of signal with connecting neurons.

This ongoing process provides fine-tuning of the neural architecture. Neuroplasticity uses cascades of electrochemical signals that unfold as a result of the expression of genetic codes through cell signal molecules (Flavell & Greenberg, 2008).
Rewiring larger regions, reorganizing the nervous system at multiple levels
Neurons work together at several different levels. Not only individual cells, but even clumps within brain regions can grow in greater or lower density.

As cells grow or die in different regions, the relative densities vary. Such variations can provide an even broader adjustment or neuroplasticity in the brain than individual nerve cell connections.

When nerve bundles become broken, through injury or surgery, the brain can regrow these elements (Doidge, 2007). Surprisingly, the brain can reconnect itself in an efficient manner even to deal with sizable upsets. It operates like a plant, able to regrow around lost parts.

The brain can regrow after injury, starting instantly at the molecular level in the injured area (Wall & Wang, 2002). Gradually, the repairs extend through subcortical layers, reaching larger-scale cortical levels of the brain.

This growth occurs throughout the nervous system, including the spine and distributed branches, not only in the brain.
Recurring synaptic connections grow more efficient (cell assembly theory)
Nerve cells work by producing electrochemical activity in the "synapses," which are gaps connecting the cells together. As a synaptic connection fires more often, it grows more efficient, in what is known as "cell assembly theory." A phrase describing this phenomenon is "cells that fire together wire together" (Lowel, 1992).

The nerve connections grow stronger when one cell fires before the other, rather than when they both fire simultaneously. Sequential firing produces a causal relationship, enabling the nervous system to learn.

As a comparison, internet search engines track which sites link directly to which other sites. The combined directional links of billions of sites produce an efficient map of the internet, as the combined directional links of billions of neurons produce an efficient map of the body and its environment.

Evidence for Structural Plasticity

The famous study by Maguire et al., 2000 demonstrates brain plasticity. She studied 16 London taxi drivers and found an increase of the volume of grey matter in the posterior hippocampus compared to a control group. This area of the brain is involved in short-term memory and spatial navigation.

Further support comes from Mechelli et al (2004) who found that learning a second language increases the density of grey matter in the left inferior parietal cortex and that the degree of structural reorganization in this area is influenced by the fluency attained and the age at which the second language was learnt.

With age, neuroplasticity decreases however Mahncke et al. (2006) used a computer training program with older adults with memory impairment and found a significant improvement compared to the control group.

This has potential benefits for society as a brain-plasticity-based intervention targeting normal age-related cognitive decline may delay the time when these people need support in their everyday life.

Learning and new experiences cause new neural pathways to strengthen whereas neural pathways which are used infrequently become weak and eventually die. Thus brains adapt to changing environments and experiences. Boyke ('08) found that even at 60+, learning of a new skill (juggling) resulted in increased neural growth in the visual cortex.

Kuhn (2014) found that playing video games for 30+ minutes per day resulted in increased brain matter in the cortex, hippocampus and cerebellum. Thus, the complex cognitive demands involved in mastering video games caused the formation of new synaptic connections in brain sites controlling spatial navigation, planning, decision-making, etc.

Davidson (2004) matched 8 experienced practitioners of Tibetan Buddhist meditation against 10 participants with no meditation experience. Levels of gamma brain waves were far higher in the experienced meditation group both before and during meditation. Gamma waves are associated with the coordination of neural activity in the brain. This implies that meditation can increase brain plasticity and cause permanent and positive changes to the brain.

Kempermann (1998) found that rats housed in more complex environments showed an increase in neurons compared to a control group living in simple cages. Changes were particularly clear in the hippocampus - associated with memory and spatial navigation.

A similar phenomenon was shown in a study of London taxi drivers. MRI scans revealed that the posterior portion of the hippocampus was significantly larger than a control group, and the size of difference was positively correlated with the amount of time spent as a taxi driver (i.e. greater demands on memory = more neurons in this portion of the hippocampus).

Critical Evaluation

Neuroplasticity can explain a broad range of facts about the structure and function of the brain. This notion does, however, have some constraints.

These involve the gradual decline of neuroplasticity with age, as well as certain restrictions in terms of how much neural plasticity is possible even in young, healthy people. Also, scientists have yet to learn many critical aspects about neuroplasticity.
The limits of brain plasticity (decline with age, biological constraints)
Neuroplasticity can only go so far. Non-human animals show many areas of brain plasticity. However, their brains cannot reshape themselves enough to learn a human language or perform advanced mathematics.

Neuroplasticity works on biologically available material, which imposes limitations like only adjusting the specific neural substrate of a cognitive function, or adapting a brain function somewhat for a season.

In people whose brains reuse large regions for different operations, such as blind people whose vision centers become useful for touch or sound, this capacity can only work for specific types of processing.

Even people blind from birth would not become able to reuse their color-detection brain cells for touch, because unlike geometry-detection brain cells, these have hard-coding for visual input (Grafman, 2000).

Even in healthy individuals, neuroplasticity declines with age (Lu et al., 2004). Over the years, as the body becomes less flexible, so does the brain.

Much of neuroplasticity is geared towards enabling younger people to develop an understanding and capacity to act within their surroundings. This stabilizes to some extent in adulthood, even declining in the elderly.

One can see the decline of neuroplasticity in how older people become more fixed in their ways, while younger people learn rapidly.
What don't we know about brain plasticity?
Neuroplasticity has grown over recent centuries into a topic of considerable interest to scientists, but remains poorly understood. The brain imaging tools for conducting studies on this topic are still young. As such, much knowledge has yet to be found.

Scientists remain unsure about many of the mechanisms underlying brain plasticity (Grafman, 2000). While a few of the processes have been studied in molecular detail, others have not, and the conceptual understanding of how they take place is a source of ignorance.

The technical underpinnings of neuroplasticity therefore represent an area of active interest, in which further investigations are being carried out./p>

Neuroplasticity, the freedom of the brain to readjust its routing to enable more effective calculation in response to injury or normal challenges, has shown itself to occur across a range of animals.

However, we still only know some of the brain regions in which it occurs, some of the mechanisms through which it happens, and some of the costs and advantages that it offers.
Animal adaptations
Animals other than humans exhibit neuroplasticity as much as humans do, or in some cases even more.

Animals evolved to survive over periods of years, through recurring cycles of weather and other environmental conditions. As such, some species exhibit neuroplasticity in cyclical patterns (Nottebohm, 1981).

Brain regions involved in navigating the environment, like the hippocampus, often grow during mating season (Nottebohm, 1981). Also, in some birds, the brain centers for singing mating songs grow during this period.

Other animals have their brains develop differently depending on season, such as to adjust when to lay more eggs or become pregnant (Wayne et al., 1998).
Behavioral or environmental modification
Several alterations to one's behaviors or environmental conditions can affect how the brain structures itself. These include sports or other physical activities, meditation, using drugs, or pollution.

When a person becomes physically active, this affects the brain along with the rest of the body. Aerobic activities like running or bicycling increase the rate at which the brain produces neurons (Gomez-Pinilla & Hillman, 2013). This results in better awareness of one's surroundings, decision-making, as well as affect and other mental functions.

Meditation practices, which involve focusing one's attention, can also invoke neuroplasticity (Lutz et al., 2004). In this case, the brain increases its capacities for controlling emotions or awareness.

Drugs, including alcohol as well as illicit drugs and certain medications, can affect the brain (Ganguly & Poo, 2013). These substances often produce some chemical adjustments in the brain, which can last well beyond the duration of drug use, even for decades. In some cases, like heavy drinking, entire brain regions can restructure themselves to recover lost functionality.

The brain responds to the environment as a main part of its normal function. As such, the brain can also undergo harm from environmental problems. Air pollution, heavy metals, and other pollutants can inhibit brain development. For example, air pollution can destroy brain cells, reducing cognitive function (Calderón-Garcidueñas, 2002).

About the Author

Eagle Gamma writes about psychology as well as other topics in science and culture. He also produces 3D animations, games, and wearable products.

APA Style References

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Brain Plasticity (Neuroplasticity) - Simply Psychology

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Also known as Neuroplasticity By Eagle Gamma, published March 23, 2021 Take-home Messages Brain plasticity, also known as neuroplasticity, is the biological, chemical, and physical capacity for the brain to reorganize its structure and function. Neuroplasticity occurs as a result of learning, experience and memory formation, or as a result of damage to the brain.

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Neuroscience of Learning is the science of the relation of the nervous system to learning and behavior (Ludvik, 2016). It focuses on how learning strengthens the brain and the central nervous system that is composed of the brain and the spinal cord. The central nervous system is responsible for controlling voluntary behavior such as thinking and acting.

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1. Use repetition and review to build memory.

2. Let students explore through hands on activities.

3. Pause lessons to reflect and think deeply.

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Neuroscience-Based Learning Strategies for Teachers and Students

by Betsy Hill, originally published in STEM Magazine, on the value of brain-based learning strategies

"We covered all of the material but they just can't remember it when it comes time for the test."

"They all passed the test, but now it's like they've never seen the material."

Learning - which we often think of as the ability to recall and apply information on a test and as the basis for future learning - is supposed to be happening at school, but often it just doesn't seem to be happening the way anyone wants, students or teachers.

There's a lot we can learn from neuroscience about the learning process and how to get learning to stick. Teachers need to understand some basics of neuroscience so that they can help students learn better. Students also need to learn about their brains so that they will be able to utilize strategies to be more successful, whether it is school-related or not.

First of all, what is learning? Students are supposed to be learning in school, but it is likely that few of them can tell you what learning is. And their teachers may not do much better. When I ask teachers what learning is, I get a variety of answers, often to do with acquiring knowledge and skills, or applying new knowledge, or recalling information. None of those is wrong really, but it skips over what they really need to know.

Learning is a biological activity.

Learning is the process of creating and strengthening connections among neurons in our brains. Neurons are the cells that communicate with electrical and chemical signals at junctions called synapses. And it is the connections among these cells, formed into maps or networks, that give rise to all human behavior. When we have an experience, groups of neurons (networks) are activated (talk to each other). The more often those networks are activated together, the more likely they are to activate together the next time - a phenomenon the neuroscientists call "neurons that fire together, wire together."

Remembering or recalling involves reactivating the networks of neurons that were activated in the earlier learning process. It is not like pulling information out of a vault or a file cabinet. There is no single storage place for memory in the brain. Memory is all over the brain in the places that experienced the learning previously.

Given that learning is about connecting neurons, and strengthening the connections among them, then what both students and teachers need to understand is what helps that process work most effectively.

We can think about learning as three stages:

What we will do in this article is discuss, at a fairly basic level, what is happening at each of the stages of learning and what neuroscience and educational research tell us about how to enhance each of those stages.
Encoding
When we take information in through our senses, it is represented by a pattern of activation of a network of neurons. That pattern of activation is like the code by which that information can later be retrieved. The information is then stored, by connecting it with other networks that represent prior knowledge and abilities, and through consolidation and strengthening of those networks. When it comes time to retrieve the information, a cue triggers the reactivation of the networks so that we can experience it again and remember it.

In order for information to be encoded in memory, it needs first to get through the processes our brains use to decide what to pay attention to, Most of the information we are exposed to does not actually get to the stage that we are conscious of seeing, hearing or feeling it. Our brains filter out most of the information and let through the specific information our brains decide is important enough. If something seems important, particularly if it is threatening, our neurons will send strong signals to each other. If not, the information will simply be discarded or the signals will be weaker. We ramp up and down the power of the signals based on how relevant and important the information seems. So, whatever increases the signal will help with encoding. Three important factors that can amplify the signal are attention, meaning and multiple modalities.

Attention: When teachers say, "Pay attention," students may or may focus on what the teacher wants. The fact of the matter is that our brains are always paying attention to something, but it is not always what the teacher would like for them to be attending to. And even when students are paying attention to the teacher, they may not be focused on the specific information the teacher deems important. So, for example, students may be focused on the rhyming scheme of a poem when the teacher means for them to focus on meaning or vice versa. Being mindful of which signal we are trying to ramp up is important because what we think the signal is may not necessarily be what the students think it is. We can ramp up the signal by saying, "This is important and rhyming patterns will be on the test," or we can do it by making it intrinsically interesting (like turning the poem into a rap).

Meaning: When it comes to meaning, we need to make sure our students have prior knowledge to connect the new knowledge to and see its relevance. I too frequently encounter teachers who can't explain to students why they need to learn some aspect of the curriculum. If the teacher doesn't know, in most cases the students will be equally clueless. Teachers are told to make subject matter relevant so that students will be motivated to learn it. But on the biological level, if that newly formed network of neurons has no other networks to attach to, it is like being on an island with no one to talk to. It can't stick if it doesn't have something to stick to.

Multiple Modalities: The notion of learning styles and the concept that some learners are visual and some are verbal is erroneous. The evidence strongly supports the use of multiple modalities. If the only signal is auditory, the brain will activate parts of the auditory system. If it is only visual, the activation will be in the visual system. If the learning process engages multiple modalities, the experience is represented in different parts of the brain. When the brain is called upon to retrieve that information later, it will have multiple pathways by which to activate that network.
Storage
When our brain store information, signals from different parts of the brain converge on the hippocampus, so named from the Greek because it resembles a seahorse. The hippocampus orchestrates the processing of those signals and their reactivation, at least until the memory becomes so strong that it is independent of the hippocampus's mediation. Thus, when it comes to storage of information, whatever supports the hippocampus is likely to result in more stable storage,

Here, teachers and students want to keep in mind the following:

There is an old Russian proverb that says, "Repetition is the mother of learning." (повторение мать учения - it rhymes in Russian.) The analogous dictum in English is "Practice makes perfect." To be precise, from the brain's point of view, practice doesn't make perfect, but it does make permanent. When we practice something over and over again, it reactivates the neural networks involved in the original learning and strengthens those neural connections.

It is also important that repetition vary the conditions of the rehearsal of information within a range. As a simple example, kids who practice basketball free throws from a distance of 6 feet and 8 feet perform better than kids who practice only at 7 feet (the actual free-throw distance for the age group).

Remember too that repetition does not always mean rote repetition. The kind of "repetition" or practice that will help store the information most securely in memory depends on the type of memory involved. We now know that there is a difference between procedural memory (which includes tasks like typing, playing the piano, tying your shoes and riding a bike) and declarative memory (which includes tasks like remembering the events of the Civil War, or explaining the steps of the Scientific Method). Building procedural memory requires more rote practice; building declarative requires more elaborative practice (journaling, simulations and role plays, experiments, etc.).

Sleep, exercise and time are also critical for information to be stored in the brain. Our brains actually consolidate memory while we sleep (and you thought it was just taking a vacation). When your students fully understand this principle, they will never again pull an "all-nighter" preparing for a test.

Don't teach too many things at one time. There is a phenomenon called "interference" which simply means that when our brains are first learning something and haven't yet had a chance to store it securely, new incoming information can actually interfere with that storage process.

Retrieval
If you can't remember (retrieve) the information, you can't truly be said to have learned it. There are so many things we learn for "a moment" - the test, the performance, the science fair. Have you ever heard a student run into class the day of the test and say, "Don't talk to me. I just want to take the test while it is fresh in my mind." Fresh in one's mind and deeply learned are two entirely different things, as far as our brain are concerned.

Things that will make retrieval easier:

1. Make learning and retrieval harder. Yes, that is an oxymoron. But what we know is that effortful retrieval of information reinforces those precious neural connections and later makes it easier to retrieve the information. This has very practical implications for teachers and students. Reading over your notes leverages short-term memory. Quizzing yourself with flash cards or something similar is FAR more effective. It is also important to test yourself on what you don't know rather than what you know well. And embrace those weekly low-stakes quizzes (rename them "retrieval practice!") as opportunities to strengthen those neural connections through effortful retrieval.

2. Make it harder. Again! Start your presentation with "when we finish the presentation I'm going to ask what are the three most important things that you've learned - that are the most important for you." Don't forget to ask them at the end!

3. Spread the practice out over time. Once is not enough. Exposure to information and retrieval practice needs to be repeated over time. The most effective is if you wait for some forgetting to occur. Then the learner can see what gaps there are in the knowledge that has survived and focus on that.

4. Practice interleaving. Imagine that you have just picked up (maybe hefted is a better word) a big book of maps. Between the pages of the book are sheets of tracing paper so that you can trace a map and take it with you. Those sheets between the pages are interleaved. Now imagine how that would apply to learning. If we mix up related but different topics, it will help encourage more flexible thinking with a variety of ways to activate the information and stronger interconnected networks.

As Dr. Melina Uncapher from the University of California San Francisco recently told a group of educators and other brain enthusiasts, "Make learning harder to make retrieval easier!"

Whether you are a teacher or a student, understanding what ramps up the signal that gets new information encoded in our brains, knowing how to ensure that the information is stored and consolidated over time (and with sleep), and using the strategies will make it easier to retrieve that information when and how you want it, can dramatically change how well learning happens in school.

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Neuroscience of Learning Brain-Based Learning Strategies

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by Betsy Hill, originally published in STEM Magazine, on the value of brain-based learning strategies "We covered all of the material but they just can't remember it when it comes time for the test." "They all passed the test, but now it's like they've never seen the material."

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Brain Development focuses on how our brains are different based on genetics, environmental stimulation, nutrition, steroids and teratogens. Brain development starts at fetal development and continues as we reach adulthood. Student learn best when the teacher understands the differences of students and what level of development they may be in. This is why many classrooms are considered diverse because student are all at different level of development and there are many factors to consider when teaching and planning.

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Ready-to-Learn: Brain development in children

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1. Regular repetition and practice helps solidify learning and build stronger neural pathways and promotes better focus in students.

2. Give students real life tasks they can succeed at.

3. Encourage group learning and interaction.

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Cite this

Semrud-Clikeman, M. (2015, March 9). Research in brain function and learning. American Psychological Association. https://www.apa.org/education-career/k12/brain-function

The importance of matching instruction to a child's maturity level

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.

Do:

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.

Be aware that childhood illnesses - such as ear infections, asthma, severe allergies, frequent hospitalizations, etc. - or family disruption caused by death or divorce may impact a child's development. A child with a history of these difficulties may benefit from specific accommodations, including:

- 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.

Be aware that a healthy brain likes to learn, and children learn best when they are exposed to a variety of ideas, experiences, skills and materials. In the early years, children like to explore and learn using several senses or multiple skills at the same time.

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 of 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.

Be aware that brain systems do not all develop at the same time or at the same rate. A child may show advanced development in one area and be delayed in another. For example, a child may read early but be physically clumsy.

Brain development also does not occur in a straight line. Some skills may develop earlier than other skills. Also, precocious ability does not necessarily last. It is possible for a child to be accelerated in reading or verbal skills in kindergarten but show average ability by third or fourth grade.

Don't:

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.

What do we know about brain maturation?

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.

Late elementary to middle school years

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.

Where does learning occur?

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.

Myths about brain development and learning

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.

Facts about brain development and learning

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.

4. Positively reinforce effort as well as success. For example, tell the child how well he/she is working.

5. Give clear, concise instructions.

6. Have a child repeat directions to you aloud.

7. Reinforce directions with a visual reminder when appropriate. For example, provide a list on the blackboard of what is expected and the approximate amount of time that each step should take.

8. Allow limited choice of tasks, topics and activities.

9. Use a child's interest whenever possible in designing activities or introducing material.

10. Match a child's learning ability and preferred method of response.

11. Allow alternate response modes (computer, taped assignments) with every assignment.

12. Provide a predictable routine in your class.

13. Encourage the use of color coded folders or other forms of personal organizers.

14. Make tasks as interesting as possible.

15. Allow children to work with partners.

16. Alternate high and low interest tasks.

17. Give targeted children priority seating close to the teacher.

18. Increase or provide novelty at later stages of the task to keep the child motivated.

19. Decrease the length of the tasks you assign.

20. Break up tasks into smaller parts.

21. Have tasks arranged so that children complete smaller parts after longer parts.

22. For every task students tend not to prefer, engage in two preferred tasks. Let students know that this will happen.

23. Give fewer math or spelling problems. For example, have the child do only the odd or even problems. Or put fewer problems (words on one page).

24. Use distributed (rather than mass) practice for problems beginning a task.

25. Increase structure and/or add emphasis to relevant parts of a task or assignment.

26. Ask a child to repeat directions.

27. Use written directions.

28. Set realistic standards for acceptable work.

29. Point out topic sentences, headings, etc. to improve task completion.

30. Use lists and assignment organizers.

31. Substitute verbal or motor responses for written responses.

32. Have a child work on easier parts of a task before tackling the more difficult ones.

33. Underline key words in directions.

34. Allow quiet play.

35. Encourage note taking for older children in high school.

36. Reward short intervals of patient waiting.

37. Don't assume that impulsive behaviors are aggressive.

38. Cue the child to upcoming difficult times when extra control is needed.

39. Bring distracters or toys that are quiet and absorbing.

40. Encourage after school activities.

41. Develop the child's sense of confidence and responsibility.

42. Encourage targeted children to play with children who can serve as positive role models.

43. Model good behavior.

44. Reward good behavior.

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.

Attention deficit hyperactivity disorder

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).

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.

Autistic spectrum disorders

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.

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.

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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.

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Motivation and Emotions is another area to focus on how a student learns and how it affects their learning. Positive feelings can help learning while fear and stress can have a major affect on learning making it harder for students.

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1. Celebrate effort and growth, not just right answers.

2. Let students set learning goals.

3. Do morning check ins or use mood meters.

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Emotions and learning are inseparable. Emotions can both enhance and interfere with learning depending on which ones are driving or colouring the experience. Emotions can also be contagious, with strong positive or negative emotional states infecting others in the learning environment. Whether in a face-to-face or online environment, the emotional states of learners - and teachers - can influence one another. When educators understand the role that emotions play in learning and teaching, and how individual and shared emotional states can influence the dynamic of the learning environment and experience, they can design more effective learning experiences.

In this third article in our series covering the seven principles in the Higher Education Learning Framework, we look at emotions and learning in detail.

Emotions play a role in how and why students learn

Educators and students need to acknowledge the integral role that emotions have in learning. Emotions are an embodied response to a stimulus (whether real or perceived, external or internal) and are experienced along a continuum from positive to negative. In the learning environment, emotions can play a powerful role in supporting or undermining learning and teaching. Emotions are inherently linked to and influence cognitive skills such as attention, memory, executive function, decision-making, critical thinking, problem-solving and regulation, all of which play a key role in learning.

Positive learning emotions include interest, curiosity, wonder, passion, creativity, engagement and joy. These activate the reward system of the brain, make the experience desirable, and aid in focus and attention. Positive emotional states can enable students to broaden their perspective, see alternatives, persist through challenges and respond effectively to criticism and failure.

Positive emotions and the learning states they promote reciprocally influence the learner's motivation. Motivation can be considered the drive and energy behind learning. Students can be motivated by both their internal goals for learning (mastery goals) or external factors such as grade recognition (performance goals). Mastery goals are often driven by personal interest, curiosity, relevance and effective learning regulation processes. Students who demonstrate mastery of goal orientation have been shown to have a more productive disposition towards learning, which results in more sustained experiences of learning success.

On the other end of the spectrum, negative emotional states such as anxiety, stress, sadness, disinterest, disengagement, worry and fear can impede learning processes and the motivation to learn, and stifle the development of effective learning dispositions. If a learner perceives a threat, their attention will be drawn to this, interfering with their ability to learn. In a learning environment, threats might be in the form of failure, being unprepared or feeling disconnected from other learners or the teacher. Unproductive negative emotions can lead to low motivation or disengagement, which can negatively impact a student's learning experience and present challenging environments and dynamics for educators to navigate during class.

However, negative emotions such as confusion can also be a powerful learning tool.

How can we implement emotions and learning in higher education?

1. Be aware of individual and group emotional states. These can be indicated by tone, non-verbal cues and language used to describe learning. Use this information to shape instructional practices, incorporating multiple and varied activities that engage emotional states and provide opportunities for dialogue. Pose open-ended questions that present alternative perspectives or possibilities to foster curiosity, interest and engagement, and encourage dialogue and debate. Interactive tasks allow students to be more actively engaged in the learning experience. These could include structured small group or breakout room discussions, short quizzes or practical tasks that apply ideas in context.

2. Encourage self-reflection and metacognition through structured activities and assessments that connect new knowledge and skills, pose questions and prompt introspection.

3. Promote an enjoyable and supportive learning culture in the course. Learn with and from your students, demonstrate value for their contributions and encourage their voice in and about the course.

4. Provide opportunities for students to develop and practise strategies that foster emotional and learning regulation. Discuss with students the importance of confusion, curiosity, creative thinking, taking risks and exploring new possibilities and ideas in their learning, and learning from errors and failure. Increase the use of formative feedback to foster dialogue about learning and to provide opportunities for students to clarify misunderstandings.

5. Give students a sense of agency and control over their learning. Support them to build effective self-regulated learning skillsand provide multiple ways through which they can demonstrate their understanding, for example through submitting assessment tasks in different formats.

6. Promote and foster a sense of belonging within the course. Model and provide opportunities for students to establish positive relationships and connection. Ways to create familiarity and trust include structured cooperative learning activities, online or face-to-face drop-in sessions immediately before or after class, online introductory discussion boards, and opportunities for incidental conversation.

No longer should higher education focus on learning as a purely cognitive process; emotions are an integral and valuable part of learning, and can be leveraged to promote engagement, motivation and student success. Recognising the role of emotions in learning can result in learning and teaching experiences that are enhanced and engaging.
Annemaree Carroll is head of the Science of Learning Research Centre Learning Lab; Stephanie MacMahon is programme director of the Learning Lab; Jason M. Lodge and Alexandra Osika lead the Learning Lab's work in higher education. The Science of Learning Research Centre Learning Lab at the School of Education at the University of Queensland brings together multidisciplinary researchers and interprofessional partners with the aim of transforming learning across the lifespan. If you found this interesting and want advice and insight from academics and university staff delivered directly to your inbox each week, sign up for the Campus newsletter.

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Emotions and learning: what role do emotions play in how and why students learn?

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If educators understand the factors that interplay with emotional states to affect learning, they can work with this to enhance the learning experience. Here are six strategies to manage the role of emotions in learning

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Instruction Application shows how brain science connects to teaching. Lessons should use what we know about how the brain learns best.

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Teaching Strategies: Cognitive Load Theory

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1. Teach in short chunks with visuals and breaks.

2. Let students work together on projects.

3. Give feedback often and let students reflect.

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- Dr. Bobbi Hansen

To non-educators, the term "brain-based learning" may sound redundant. Doesn't all learning involve our brains? Yes - but brain-based learning delves a little deeper into the science of how we learn in order to deliver more effective instruction.

This introduction to brain-based learning serves as an accompaniment to Dr. Bobbi Hansen's presentation, "Teaching with Superpowers: Instructing Through Brain-Informed Practices," delivered during a University of San Diego Master of Education town hall.
View the recorded presentation here. >>
What Is Brain-Based Learning? Key Principles Benefits of Brain-Based Learning 8 Brain-Based Teaching Strategies How to Build a Brain-Based Curriculum: 7 Ideas
What Is Brain-Based Learning?

Brain-based learning involves teachers creating conditions that increase student motivation, engagement and long-term retention by tapping into the natural ways the brain receives, processes and stores information. This approach can be applied to classroom teaching methods, lesson planning, curriculum design and any other educational engagement. As long as the planning and delivery is rooted in the latest research on the science of learning, it's considered brain-based instruction.

The research in question centers primarily around the brain's ability to change and reorganize itself to receive and retain new information in a process called neuroplasticity. New information and experiences can physically reshape the brain's neural pathways; the more we practice new skills or review new information, the stronger those pathways become and the better we retain the information or ability.

Our brain's neuroplasticity is influenced, both positively and negatively, by motivation, stress and challenge, as well as our emotional state as we're learning. Understanding how neuroplasticity works (especially in young, developing brains) can help curriculum designers and educators build lessons that are more likely to "stick." When students master new concepts or gain new skills in the classroom, teachers see this neuroplasticity in action. Perhaps Dr. David Sousa, an educational neuroscience consultant, puts it best: "Successful teachers are brain-changers!"

History

The theory of the left and right brain has been synonymous with learning styles since it was introduced in the 1960s. Neuropsychologist Roger W. Sperry posited that all humans are either right-brain or left-brain dominant, depending on how they think and receive information. More informed neurological research, however, has since disproven this theory; we now know that humans use each hemisphere of their brain for different tasks, and that neither is dominant over the other.

As neurological research and discovery gained traction in the 1990s, some researchers began to apply their findings to the classroom. In " Understanding a Brain-Based Approach to Learning and Teaching," Geoffrey Caine and Renate Nummela Caine proposed that educators leverage neuroscience to improve students' knowledge retention and performance. The Caines found that students had better comprehension and retention in a collaborative, hands-on, brain-based learning environment than those in a traditional lecture-based classroom. Scientifically speaking, active learning leads to the growth of dendrites - nerve cell extensions in the brain that influence how neurons collect and process information. This is good news for knowledge retention.

Brain-based learning has since gained significant traction in schools. As evidenced by texts like Neuroteach: Brain Science and the Future of Education (Rowman & Littlefield, 2016), there remains a continued insistence that all educators have a working knowledge of how the brain receives and retains information in order to be better teachers.

Key Principles of Brain-Based Learning

The overall goal of brain-based learning is not complicated, nor is it unattainable:
To create a learning environment and classroom strategy where all students can thrive.
To achieve this goal, educators need to break down their instruction (and their students' learning) into smaller components. In her town hall presentation to USD MEd students, Dr. Bobbi Hansen identifies four key principles of brain-based learning:

1. Experience: New experiences only reshape the brain when we are actively participating in those experiences.

2. Flow: Stress affects memory, so instructors need to facilitate a "flow state" in which students are comfortable, safe and focused.

3. "Sticky" learning: Utilize teaching methods that result in higher knowledge retention, such as learning by doing or student-led instruction.

4. Brain-informed teaching practices: Identify and implement the teaching strategies that will best support the current group of students.

The following are some specific classroom examples that incorporate these four key principles:
Health and wellness
Physical activity isn't only for the gym. When students are able to take stretch breaks, go for short walks or otherwise move their bodies during lessons, the more engaged they will be when they come back. Movement-based learning is more common in younger grades, but teachers should not count older students out - bringing some light physical engagement to classroom lessons can:

Energize and revitalize students (and teachers)

Improve students' attention spans

Help students receive and retain more information

Positivity
When students are in a positive emotional state, they are more willing to engage in lessons and classroom activities. Social validation from their peers and affirmations from their teacher can contribute to students' feelings of belonging.
Group work
When learning new material, it can be highly valuable to hear other students' reactions or experience how they take in new information. Group activities help students learn from one another and may even help them understand information better than they would have from their teachers' presentations.
Peer teaching
Educators may occasionally feel unprepared to teach certain course material but find that their comprehension grows as they begin to deliver their lessons. Teaching others is the most effective way to learn, and this applies to students as well. If a handful of students grasp a concept right away, they can then turn around and teach their peers, thereby strengthening their own understanding and delivering this new information in a way that resonates with their classmates.
Practice
Repetition, experimentation and productive failure are all more effective than simple memorization of facts or vocabulary. Students should have an opportunity to practice new skills and retrieve new knowledge before any major assessment.
Limiting lectures
Traditional lecture-based teaching has been proven not as effective as active learning. Making lessons more active rather than passive promotes students' knowledge retention.
Meaningful information
Academic concepts can often feel disconnected from students' actual lives. How many teachers have fielded the question, "But when am I ever going to need this?" Finding ways to connect course materials to the real world boosts student engagement and gives relevant meaning to abstract concepts.
Written and verbal information
Lessons and assignments that incorporate varied modes of delivery give students a better chance of logging information in their long term memory. This involves the instructor delivering both spoken and written lessons, and the students demonstrating their understanding through both written and verbal assignments.
Stimulation
Not all students learn the same way, but there are ways to capture their attention that generally garner a positive reaction. Incorporating movement, humor, games or current events that are of interest to their age group can increase students' participation, processing abilities and the likelihood that they will remember the course content.
Stress mitigation
In general, stress negatively impacts our brains' neuroplasticity, preventing us from retaining information. By and large, students learn and perform better in a classroom environment that is calm, safe, supportive and positive (and with a teacher who exhibits the same qualities).

Benefits of Brain-Based Learning

When information is presented in a way that accounts for the brain's ability to process it, it can vastly improve the learning experience. Brain-based learning supports:

Skills retention

Higher academic performance

Academic progression

Resiliency

Long-term memory

Brain health and function

Mood

Classroom cooperation

Motivation

A positive attitude

8 Brain-Based Teaching Strategies

As long as a lesson is built around the way students receive and retain information, brain-based learning can look like almost anything. Educators can utilize multiple instructional methods while following the principles of experience, flow, "sticky" learning and brain-based teaching strategies. These principles remain the same no matter the age of the student; it is up to the teacher and their creativity to build age-appropriate lessons rooted in a brain-based foundation.

Here are some high-level strategies teachers can use when building their brain-based lesson plans:

Combine written and verbal information to boost learning retention

Prioritize engagements that are hands-on, creative, useful and have an emotional impact

Favor lessons and activities that help students develop critical thinking skills over simple memorization

Model lessons and assignments on real-world challenges that students can relate to

Create lessons that teach students social and team-building skills in addition to course content

Build opportunities to practice course content into every lesson, or before moving on to the next unit

Incorporate movement or brain breaks into lessons, regardless of grade level

Ensure that neither lessons nor the classroom environment contribute to unnecessary stress or anxiety

How to Build a Brain-Based Curriculum: 7 Ideas

As mentioned above, a brain-based curriculum can look like anything, so long as lessons are built to encourage students' neuroplasticity and optimal knowledge retention. It's important to note that not all strategies work for all students, so rely on trial and error to see what works and what doesn't for your classroom.

Break learning into chunks.

This may seem obvious to many educators, but it bears repeating. Students learn best when they can digest new concepts bit by bit; break lessons down into bite-sized pieces that fall into introductory, practice and review segments before moving on to a new concept or topic.

Include "turn and talk" time in your lessons.

Take breaks during each lesson or unit for students to talk amongst themselves and solidify their understanding of the topic. This can fall into the "review" stage mentioned above. You can also task students with explaining a new concept to a parent or someone unfamiliar with it. After all, teaching is the best way to grasp a new skill or subject.

Not all "chunks" need to involve learning! Leave space in each lesson for movement or stretch breaks. You can even create lessons that get students moving while they learn - e.g. role playing a historical event or reading out loud "popcorn"-style with a tossed ball.

Include multisensory elements in each lesson.

For some topics, using visual elements may be a no-brainer; but challenge yourself to activate other senses during your lessons. Can you help students "physicalize" parts of speech? How can you bring a history lesson to life through sound?

Encourage students to try to remember what they've learned from a lesson, even if the topic is fairly new to them. The process of remembering strengthens memory and identifies gaps that call for a refresher. For example, rather than providing a study guide with bullet points covering key points of a lesson, build your study guides around questions that students will need to answer, thereby creating their own study guide through retrieval.

Concept mapping is the act of connecting separate elements of a topic or unit into a web of comprehension. For example, in a unit on cell structure, students can list out what they've learned about each component of a cell, then visually connect the components to each other by explaining their relationships.

Whenever possible, get your students out of the classroom to apply their learning in the real world. Field trips are a classic example of experiential learning, but even taking your students for a walk around campus to talk about the weather or photosynthesis can help make abstract concepts easier to understand.

This is just a sampling of the ways in which creative educators can leverage neuroscience to help their students succeed in the classroom.

The best teachers never stop pursuing new ways to make learning accessible for all students. The specializations offered by USD's Master of Education program enable educators to drill down into specific areas of interest that not only improve their own teaching practice, but can also lead to higher student achievement and a love of learning. Explore all the ways in which you can strengthen your teaching skill set and boost your earning potential with an advanced degree.

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Brain-Based Learning: 15 Strategies to Improve Student Learning & Retention

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What exactly is brain based learning, and what does it look like? An introduction to the science of learning, plus brain based learning strategies and examples.

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The human brain wasn't designed for industrial education.

It was shaped over millions of years of sequential adaptation in response to ever-changing environmental demands. Over time, brains grew in size and complexity; old structures were conserved and new structures emerged. As we evolved into social beings, our brains became incredibly sensitive to our social worlds.

This mixture of conservation, adaptation, and innovation has resulted in an amazingly complex brain, capable of everything from monitoring respiration to creating culture. This added complexity came with a cost. Not only do all of these systems have to develop and interconnect, but they also have to stay balanced and properly integrated for optimal performance.

This evolutionary history poses a challenge for educators. While findings from social neuroscience can provide some welcome guideposts for teachers, they cannot substitute for the flexibility needed in the classroom to accommodate a range of students. Students and teachers are not uniform raw materials or assembly-line workers, but a diverse collection of living, breathing human beings with complex evolutionary histories, cultural backgrounds, and life stories.

If we are going to move forward, we will have to admit that a one-size-fits-all model of education is doomed to fail the majority of students and teachers.

And through understanding how students' brains actually work and using that knowledge to benefit classroom learning, we may be able to positively influence classroom education and prepare students to better face unknowable futures. Here are nine scientific insights that educators might want to keep in mind.

1. The brain is a social organ.

Our brains require stimulation and connection to survive and thrive. A brain without connection to other brains and without sufficient challenge will shrink and eventually die-moreover, the modern human brain's primary environment is our matrix of social relationships. As a result, close supportive relationships stimulate positive emotions, neuroplasticity, and learning.

That's why it pays for teachers to create positive social experiences in the classroom. From a neurobiological perspective, the position of the teacher is very similar to that of the parent in building the child's brain. Optimism, encouragement, and giving someone the benefit of the doubt have been shown to positively impact performance-and so does a caring and positive regard for students. Promoting social-emotional learning programs that decrease student conflict and create positive social climates in the classroom are invaluable to learning.

2. We have two brains.

The cerebral hemispheres have differentiated from one another and developed specialized functions and skills. In general, the left hemisphere has taken the lead on language processing, linear thinking, and pro-social functioning while the right hemisphere specializes in visual-spatial processing, strong emotions, and private experience.

Most tasks, though, involve contributions from both hemispheres. So, it is important to understand how to engage both in the classroom context.

Good teachers intuitively grasp this in their students, and they will seek to balance the expression of emotion and cognition, encouraging overly rational students to be aware of and explore their feelings while helping anxious students develop the cognitive capabilities of their left hemispheres to regulate their emotions.

Storytelling can help here, as stories can serve as powerful organizing tools for neural network integration. A story that is well told, containing conflicts and resolutions and thoughts flavored with emotions, will shape brains and connect people.

3. Early learning is powerful.

Much of our most important emotional and interpersonal learning occurs during our first few years of life, when our more primitive neural networks are in control. Early experiences shape structures in ways that have a lifelong impact on three of our most vital areas of learning: attachment, emotional regulation, and self-esteem. These three spheres of learning establish our abilities to connect with others, cope with stress, and feel that we have value.

Every time children behave in a way they (or we) don't understand, a teacher has the opportunity to engage in an exploration of their inner world. When painful experiences can be consciously thought about, named, and placed into a coherent narrative, children gain the ability to reintegrate dissociated neural networks of affect, cognition, and bodily awareness.

Encouraging students to write about their experiences in diaries and journals can help, as it lets students become the masters of their experience and reducing anxiety and stress. Research has shown that writing about your experiences can increase well-being and help with emotional regulation, which may have been impaired through early traumatic experiences.

4. Conscious awareness and unconscious processing occur at different speeds, often simultaneously.

Conscious awareness and explicit memory are but a small fraction of the vast amount of neural processing that occurs each millisecond.

Think of how many things you do without having to think about them: breathing, walking, balancing, even constructing the syntax of a sentence, is handled automatically. The brain is able to process incoming information, analyze it based on a lifetime of experience, and present it to us in half a second. The brain then creates the illusion that what we are experiencing is happening right now and that we are making decisions based on our conscious thought processes.

Because of this, it is especially important to teach students to question their assumptions and the possible influences of past experiences and unconscious biases on their feelings and beliefs.

This is especially true when thinking about prejudice. Because fear conditioning does not require conscious awareness, the brain's knee-jerk reaction to individuals of other races is unrelated to our conscious attitudes. Open discussion and increased interracial exposure can work against prejudice being turned into conscious beliefs and negative behaviors.
5. The mind, brain, and body are interwoven.
Physical activity exerts a stimulating influence on the entire brain that keeps it functioning at an optimal level. Exercise has been shown to stimulate the birth of new neurons in the hippocampus and to pump more oxygen through the brain, stimulating capillary growth and frontal-lobe plasticity.

Proper nutrition and adequate sleep are also essential to learning. Although the brain is only a fraction of our body's weight, it consumes approximately 20 percent of our energy, which makes good nutrition a critical component of learning. Sleep boosts cognitive performance and augments learning while sleep deprivation limits our ability to sustain vigilance and attention. Sleep deprivation has also been shown to impair flexible thinking and decision-making.

An awareness of these biological realities can lead to changes in school start times, lunch programs, and recess schedules. Teachers can teach students about the importance of sleep and make suggestions for better sleep habits, such as how to create a good sleep environment and promote relaxation. Good nutrition and regular exercise can be incorporated into the school environment. Teaching about the interconnections among the brain, the body, and how we learn will provide students with important scientific knowledge, which could improve their academic performance and physical health.

In addition, learning can be enhanced by certain environmental conditions and hampered by others. Inadequate school facilities, poor acoustics, outside noise, and inadequate classroom lighting all correlate with poorer academic performance. Chairs with poor support hamper blood supply to the brain and impede cognition while temperatures above 74-77 degrees Fahrenheit have been shown to correlate with lower reading comprehension and math scores. A more hospitable climate for learning can help performance by providing for the physical needs of the body.
6. The brain has a short attention span and needs repetition and multiple-channel processing for deeper learning to occur.
Curiosity, the urge to explore and the impulse to seek novelty, plays an important role in survival. We are rewarded for curiosity by dopamine and opioids (feel-good chemicals in the brain), which are stimulated in the face of something new. Because our brains evolved to remain vigilant to a constantly changing environment, we learn better in brief intervals.

This is likely one reason why variation in materials, breaks, and even intermittent naps facilitate learning. It is probably important for teachers to reestablish attention in their students every five to 10 minutes and continue to shift the focus of attention to new topics.

Learning also involves the strengthening of connections between neurons. "What fires together wires together," say neuroscientists, which is why repetition supports learning while the absence of repetition and exposure results in its decay. Teachers would do well to make sure they repeat important points in their lessons to deepen learning.

Given that visual, semantic, sensory, motor, and emotional neural networks all contain their own memory systems, multichannel learning engaging each of these networks increases the likelihood of both storage and recall. We have an amazing capacity for visual memory, and written or spoken information paired with visual information results in better recall. There is a greater likelihood that learning will generalize outside the classroom if it is organized across sensory, physical, emotional and cognitive networks.

7. Fear and stress impair learning.

Evolution has shaped our brains to err on the side of caution and to trigger fear whenever it might be remotely useful. Fear makes us less intelligent because amygdala activation-which occurs as part of the fear response-interferes with prefrontal functioning. Fear also shuts down exploration, makes our thinking more rigid, and drives "neophobia," the fear of anything new.

Stressful situations trigger the release of the stress hormone cortisol, which interferes with neural growth. Prolonged stress impairs our ability to learn and maintain physical health.

Success in school depends upon a student's ability to somehow decrease their stress. The inclusion of stress-management techniques into the curriculum is an obvious application of neuroscience to education that can improve learning, emotional well-being, and physical health. Teachers can use their warmth, empathic caring, and positive regard to create a state of mind that decreases fear and increases neuroplasticity and learning.

8. We analyze others but not ourselves: the primacy of projection.

Our brains have evolved to pay attention to the behaviors and emotions of other people. Not only is this processing complex, but it is lightning fast, shaping our experience of others milliseconds before we even become consciously aware of their presence. We automatically generate a theory of what is on their mind-our ideas about what they know, what their motivations may be, and what they might do next. As a result, we are as quick to think we know others as we are slow to become aware of our own motives and faults.

Taking our thoughts about others and trying them on for size has the potential to teach us about ourselves and increase our empathic abilities. Simple exercises that guide students to examine what and how what they think and feel about others may be true for themselves can open a window of self-awareness, empathy, and insight. Teachers can ask students to examine the lives of historical figures and characters from books and movies to help them gain a third-eye perspective on their own strengths, motivations, and flaws.
9. Learning is enhanced by emphasizing the big picture-and then allowing students to discover the details for themselves.
When problems are represented at higher levels of abstraction, learning can be integrated into larger schemas that enhance memory, learning, and cognitive flexibility. Starting with major concepts and repeatedly returning to them during a lecture enhances understanding and memory, a phenomenon that increases when students create their own categories and strategies of organizing information. Chunking material into meaningful segments makes it easier to remember, and improves test performance while increasing prefrontal activity during encoding.

When it comes to discovering the details, bear in mind that our brains evolved to learn is through trial-and-error exploration. This is true of learning and adapting to both our social and physical environments. Therefore, using what we learn to attempt to solve real-world problems and adjusting our behaviors or ideas based on the results augments the retention of skills and information. We are born to explore, and teachers who make use of that will probably find more success in the classroom.

Greater Good wants to know: Do you think this article will influence your opinions or behavior?

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Nine Things Educators Need to Know About the Brain

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In an excerpt from his new book, psychologist Louis Cozolino applies the lessons of social neuroscience to the classroom.

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The brain is the most complex organ in our body. And it can do incredible things. Ultimately, the brain is responsible for our thinking, learning and memory. If we want to understand the most effective ways to teach and learn, we need to begin by understanding the neuroscience of learning.
"The brain controls your ability to think, talk, feel, see, hear, remember things, walk and much more. It even controls your breathing."
How learning happens in the bran is not entirely understood. However, neuroscientists and cognitive psychologists have a very good idea about how the main processes work. The main point is that our brains literally change when we learn something new. That is, our brain cells are physically and chemically changed. When we recall something we learned before, those changes are reactivated in the brain.

But our brain cells don't act alone; they are connected to other brain cells by neuronal circuits. And this is why connections and associations are important to increase our understanding of topics. If our knowledge is isolated, we may be able to recall it, but won't be able to use it to solve a problem. On the other hand, if we try to link new information to things we already know, remembering one of them will activate the other ones and will improve our ability to answer a complex question.

Before we continue to delve into brain cells and connections, it is important to talk about Memory. Memory can be defined as the process of taking in information from the outside world, storing it in our brain, and later recalling the information to answer a task, solve a problem, make a decision and other responses. There are three basic stages in memory processing.

This diagram from Queen's University illustrate the three stages of memory processing.

The first step involves the perception of things that happen around us. It is a selective process, as it is impossible for us to register everything that happens at all times. Some factors that facilitate encoding are emotional content, novelty, attention levels.

After an event is encoded, it may be consolidated. This happens via physical and chemical changes in our brain. These changes are called memory traces.

Retrieval is the actual act of remembering something. That is, bringing that information back to mind. We must access our stored information in order to respond to the world around us.

Every time we retrieve information, that memory trace becomes vulnerable and susceptible to further changes. This process can make memories weaker or stronger.

It is important to note that we have several types of memory. The distinction between working memory and long-term memory is fundamental to understand how cognitive sciences can be applied to teaching and learning.

Long-term memory is our storage box. It can store unlimited information for an entire lifetime.

Working memory is our processing unit, where we process and manipulate information to solve a problem. It has a very limited capacity.

We can think of working memory as a shoe box. It offers limited space and can break if you add too much to it. We can think of long-term memory as Mary Poppins' bag. You can fit as much as you want there and still be able to walk (or fly!) around.

So now we have talked about working memory - where we process information - and long-term memory - where we store it. What about understanding? How can we go from processing content, memorising it to actually understanding it and being able to use it to solve new problems? A very nice model to understand this is the one created by Dr Efrat Furst.. In the model, she explains how we go from simply knowing we have seen something before to properly mastering that knowledge.

In the first stage, we can simply differentiate something old from something new. It's like students could tell from a list of names, which ones they have already studied. That doesn't mean they actually remember information about those historical characters - they simply recognise the name.

The next stage is to understand a piece of information, that is, to give meaning to it. In order to do that, pupils need to link the new knowledge to something they already master. For example, we can recognise a word in another language, but we only understand it, when we can relate its meaning to the word in your native language, which we already master.

But even when we understand the meaning of something, it still doesn't guarantee we will remember it for a long time. To go from understanding to mastering, we need to use that knowledge - over and over again. Let's go back to the example of learning a new language. If you ask someone fluent on a second language how they managed to learn it. They will probably tell you that they lived in that country, or knew someone to talk to, or some way in which they actually practiced over and over again. And if they were practising by listening to the same audio, the results would not be as effective as when they practised putting themselves in different situations and using the language in different contexts.

This is Dr Furst's model of how we learn by practicing until we master a knowledge:

Remember when we said working memory is like a limited shoebox? How relevant is this to teaching and learning? Well, a lot. Some even say it is the most important thing for teachers to know.

Cognitive load theory is about using techniques that optimise learning while respecting students' working memory capacity. It has two main assumptions:

1. Our working memory has limited capacity. There is only so much new knowledge we can process at one point.2. Our ability to use information already stored in memory is unlimited.

One aim of CLT is to manage working memory load. This term refers to how much of our Working Memory "shoebox" is being used at one moment. If the box is too empty, there is enough room to process information but there won't be much to be learned. If the box is too full, there is a lot to be learned but we won't have the necessary free space to do so.

Many researchers have tried to link findings from cognitive science to day-to-day classroom practice. Some famous teaching and learning strategies have little or no support in research, like learning styles. Two very influencial articles report strategies that do have a solid scientific basis. They are Rosenshine's Principles of Instruction and Dunlosky's Strategies to boost learning.

Prof Barak Rosenshine from the University of Illinois created 10 principles of instructionbased on cognitive sciences, real experiences of successful teachers and academic research.

1. Begin a lesson with a short review of previous learning2. Present new material in small steps followed by student practice3. Ask questions and check answers4. Use models5. Guide practice6. Check for understanding7. Obtain a high success rate8. Provide scaffolds in difficult tasks9. Stimulate and monitor independent practice10. Conduct weekly and monthly review

Prof John Dunlosky from Kent State University thoroughly investigated 10 commonly used learning strategies and ranked them from the least to the most effective ones according to cognitive sciences. From the least to the most effective, they are:

10. Imagery for text9. Keyword mnemonic8. Summarisation7. Highlighting6. Rereading5. Self-explanation4. Elaborative interrogation3. Interleaved practice2. Distributed practice1. Practice testing

The Learning Scientists are a group of researchers in the US and the UK that conduct experiments and liaise with schools to help teachers and pupils use the 6 most effective teaching and learning strategies. The icons were drawn by Oliver Caviglioli.

1. Spaced Practice

To use Spaced Practice, help your students plan early for their exams and important tasks. When reviewing content in class, make sure you review not only the previous lesson but older content as well. Objectively, there isn't an optimal spacing interval. However, researchers agree that the "sweet spot" is when remembering the content is doable, but effortful, so information can be reconsolidated and strengthened.

2. Retrieval Practice

To use retrieval practice, you can ask students to put away their books and write down all they can remember about a topic. Then, they should check and complement their answers. It is important that accuracy is checked to avoid misconceptions. A very good and effective idea is to provide them with as many practice tests as possible. Students can also create their own questions and exchange them with colleagues. Frequent low-stake quizzes at the beginning of each lesson are highly recommended.

3. Elaboration

This technique involves asking students to describe and explain the content in as many details as possible as well as linking it to other content and personal experiences. The advantage of using this technique is that they create multiple connections between the new piece of information and things they already know, making it easier for the relevant memory traces to be reactivated in the future. One straightforward way of using the technique of Elaboration is to tell students to pretend they are the teachers and try to explain the content to their colleagues.

Watch Dr Cal Newport explaining one way to use Elaboration in your studies:

Another way to use Elaboration in the classroom is to ask a lot of How and Why questions. Why is this like this? How does this happen? What is the cause of this? What is the consequence of this? When did this happen?

4. Interleaving

Switching between topics and ideas is a way to use interleaving. Mixing up problems and questions that demand different solving strategies is also interleaving. Using interleaving when students are very new to a topic may not be effective as they may confuse the information. This strategy is best used when pupils are more advanced in their knowledge.

5. Concrete Examples

When teaching, use as many examples as possible, linking the content to each example. The connection between examples and concept should be made clear and detailed.

6. Dual Coding

Dual Coding is the strategy of using different media to teach and learn. For example, the use of diagrams, timelines, infographics, mindmaps, and colours helps students understand concepts and also remember them better. However, be careful not to use too many sources at the same time, as this may considerably increase pupils' working memory load.

You can see that Rosenshine, Dunlosky and the Learning Scientists all recommend the use of frequent quizzes as a way to help students bring information to mind and create stronger memory traces. Every time you answer a question and actively bring something back to mind, you are reactivating the memory changes and making them stronger. This is complete opposition to reading notes or revision guides, as these are passive ways of studying, in which students are absorbing information from the book without actually thinking about it.

Here are some of the ways you can stimulate your students engage in Retrieval Practice. Give them past papers to answer Create frequent low-stake quizzes Ask them to draw mind maps indicating the connection between ideas Give them braindump tasks, in which they need to write down or sketch everything they can remember about a topic without checking notes Ask them to explain the content to others Stimulate the use flashcards

Research by Dr Megan Sumeracki shows that one way is not better than the others. Listen to her explanation here.

However, the more variety of questions you give to students, the stronger their memory traces will be. It is easier to understand this if you think about a maze where the center is the exam question and the exit is the correct answer to that question. If pupils spend their revision answering the same question over and over again, they will only have one path that leads to the exit. If they practice multiple choice answers, long answers, drawing, oral explanation, and others, it is like they create multiple paths that take to the exit of the maze. Ultimately, they will be more prepared for exams and further learning.

Your students may be frustrated at the beginning because retrieval practice will feel more difficult and less useful than using passive strategies. It is supposed to be like this! We learn better when learning is effortful. Being "stuck" and finally moving forward is a great way to learn something and never forget it.

So there you go. Our brain learns through physical and chemical changes in the brain cells that connect to other brain cells. The more and stronger connections we have, the closer to mastering a knowledge we are. The best way to get there is by actively trying to recall information, answering varied questions, and solving problems. It is even better to space out practice and interleave subjects.

Originally published on SenecaLearning.com

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Introduction to Neuroscience Of Learning

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The brain is the most complex organ in our body. And it can do incredible things. Ultimately, the brain is responsible for our thinking, learning and memory. If we want to understand the most effective ways to teach and learn, we need to begin by understanding the neuroscience of learning.

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The brain is the ultimate organ of adaptation. It takes in information and orchestrates complex behavioral repertoires that allow human beings to act in sometimes marvelous, sometimes terrible ways. Most of what people think of as the "self"-what we think, what we remember, what we can do, how we feel-is acquired by the brain from the experiences that occur after birth. Some of this information is acquired during critical or sensitive periods of development, when the brain appears uniquely ready to take in certain kinds of information, while other information can be acquired across broad swaths of development that can extend into adulthood. This spectrum of possibilities is well captured by coinciding evidence of both the remarkably rapid brain development that characterizes the early childhood period and the brain's lifelong capacity for growth and change. The balance between the enduring significance of early brain development and its impressive continuing plasticity lies at the heart of the current controversy about the effects on the brain of early experience.

The past 20 years have seen unprecedented progress in understanding how the brain develops and, in particular, the phenomenal changes in both its circuitry and neurochemistry that occur during prenatal and early postnatal development. As discussed in Chapter 2, knowledge of the ways in which genes and the environment interact to affect the maturation of the brain has expanded by leaps and bounds. The years ahead will bring even more breathtaking progress as, for example, knowledge of the human genome is increasingly transformed into knowledge about how genes are expressed in the brain. This promises a dramatic expansion in the ability to understand the interweaving of genetic and environmental influences as they affect both brain and behavioral development (see Nelson and Bloom, 1997).

Growth in brain knowledge naturally leads to questions about what it means for raising children and, specifically, for improving their development. Accordingly, efforts to translate this emerging knowledge for public consumption have proliferated in recent years. Some of this information has been portrayed well and accurately, but some has not. The challenge of deciphering what this information means for what parents, guardians, and teachers of young children should do is enormous. There are actually few neuroscience studies of very young children, and those that exist have not usually focused on the brain regions that affect cognition, emotions, and other complex developmental tasks.

Much of the fundamental knowledge about brain development is based on experimental studies of animals. The translation of this information from basic neuroscience into rules for application to humans can be quite straightforward when the mechanisms involved are very similar in humans and animals, as is the case with the developing visual system. But the interpretation of other data from animals, or even some data from humans (such as estimates of the density of synapses in various brain regions at various ages), can be extraordinarily complex or inappropriate when the brain mechanisms of cognition, language, and social-emotional development are addressed. In this context, it is essential to balance excitement about all the new learning with caution about the limits of what is understood today.

This chapter about the developing brain focuses on the role of experience in early brain development. Following a brief discussion of how to study the developing brain is an overview of early brain development from conception through the early childhood years. We then turn to a discussion of how early experiences contribute to brain development. Four themes run throughout this section:

1.

Developmental neuroscience research says a great deal about the conditions that pose dangers to the developing brain and from which young children need to be protected. It says virtually nothing about what to do to create enhanced or accelerated brain development.

2.

The developing brain is open to influential experiences across broad periods of development. This openness to experience is part of what accounts for the remarkable adaptability of the developing mind. Although there are a few aspects of brain growth that require particular kinds of experience at particular times, as far as we know at present, this is more the exception than the norm for human brain growth.

3.

The kinds of early experiences on which healthy brain development depends are ubiquitous in typical early human experience-just as nature intended. This means, however, that concern should be devoted to children who, for reasons of visual impairment, auditory processing problems, major perceptual-motor delays, and other basic deficits cannot obtain these experiences on which the developing nervous system depends.

4.

Abusive or neglectful care, growing up in a dangerous or toxic environment, and related conditions are manifest risks for healthy brain development. Beyond these extremes, the nature and boundaries of the environmental conditions necessary for healthy brain growth are less well known, partly owing to the complexity and the cumulative achievements of cognitive, language, and socioemotional growth. Exploration in this area is cutting-edge research.

WHAT DEVELOPS IN EARLY BRAIN DEVELOPMENT?

The development of the brain has a long trajectory, beginning within a few days after conception and continuing through adolescence and beyond. The nervous system undergoes its most dramatic development during the first few years of life. Yet the processes that establish the structure and functioning of the brain, made possible by the developing networks of synapses that interconnect nerve cells and by the progressive fine-tuning of the neurons for the roles they will play within their synaptic networks, continue well into adolescence. The milestones of brain development from the prenatal period until school entry involve the development and migration of brain cells to where they belong in the brain, embellishments of nerve cells through the sprouting of new axons or by expanding the dendritic surface; the formation of connections, or synapses, between nerve cells; and the postnatal addition of other types of cells, notably glia. Fascination with the earliest stages of brain development is understandable. During this period, the spinal cord is formed, nearly all of the billions of neurons of the mature brain are produced, the dual processes of neural differentiation and cell migration establish the neuron's functional roles, and synaptogenesis proceeds apace. These processes represent an elaborate interplay between gene activity and the surrounding environments both inside and outside the child.

There have been significant changes over time in the aspects of brain development that have captured public attention. Twenty years ago, people were fascinated by the ability to measure developmental changes in the degree to which neurons in different areas of the brain become wrapped in the white, fatty matter-myelin-that insulates nerve cells and affects the speed with which nerve impulses are transmitted from one cell to another. Myelination is, in fact, affected by the young child's behavioral experiences and nutrition, as discussed below. Today, the public is more focused on information, not all of it new, about the rate of synapse development, particularly on studies showing that there is a tremendous burst of synapse formation early in life, followed by a decline in synapse number, apparently extending into adolescence in some areas of the brain. Combined with evidence that synapses that are used are retained and those not used are eliminated, there has been a frenzy of concern expressed as "use it or lose it" in the first years of life. It turns out, however, that synapse elimination is a normal part of development. In comparison to the brain's wiring, far less attention has been paid to the neurochemistry of early brain development, which is essential to the brain's capacity to learn from experience and is likely to play an important role in the regulation of behavior.

Development of the Brain's Wiring Diagram

Brain development proceeds in overlapping phases: making the brain cells (neurulation and neurogenesis), getting the cells to where they need to be (migration), growing axons and dendrites, which are structures needed to link with other nerve cells (neuronal differentiation and pathfinding), developing synapses or points of communication with other cells (synaptogenesis), refining those synapses (maturation and pruning), and, finally, forming the supportive tissue that surrounds the nerve cells and makes for efficient communication among them (gliagenesis or myelination).

The brain and spinal cord arise from a set of cells on the back (dorsal part) of the developing embryo called the neural plate. Two rows of rapidly dividing cells arise from the plate on each side along its length and fold over centrally into the neural tube. The anterior or head end of the neural tube forms a set of swollen enlargements that give rise to the various parts of the brain-the forebrain containing the cerebral hemispheres, the midbrain containing important pathways to and from the forebrain, and the hindbrain containing the brainstem and cerebellum. The remainder of the neural tube becomes the spinal cord, peripheral nerves, and certain endocrine, or hormone, glands in the body. Under the control of regulatory genes, the brain cells migrate to where they belong in accord with the functions they will ultimately serve. These genes provide developmental directions to particular groups of cells, which tell them what to do and where to go in the embryonic brain.

Within the neural tube, the innermost cells divide repeatedly, giving rise first to the cells that primarily become nerve cells, or neurons, and later giving rise to both neurons and the supportive tissue components called glia. Once the nerve cells are formed and finish migrating, they rapidly extend axons and dendrites and begin to form connections with each other, called synapses, often over relatively long distances. These connections allow nerve cells to communicate with each other. This process starts prenatally and continues well into the childhood years. There is evidence in many parts of the nervous system that the stability and strength of these synapses are largely determined by the activity, that is, the firing, of these connections. The speed with which neurons conduct nerve impulses is determined by the development of myelin, a substance that wraps itself around nerve axons. By insulating the nerve cell axon, myelin increases conduction velocity. The development of myelin is a protracted process extending well into the postnatal period. The rate and extent of myelination is also affected by experience. Most myelinated pathways are laid down in the early years, but for some, as in the frontal cortex, myelination continues into the third decade of life. The unique wiring diagram that brain development produces in each individual brain guides thoughts, memories, feelings, and behaviors.

Synaptic Overproduction and Loss

Beginning 20 years ago, Huttenlocher (e.g., Huttenlocher, 1979; Huttenlocher and Dabholkar, 1997) first showed that there is a pattern to synaptogenesis in the human cerebral cortex characterized by the rapid proliferation and overproduction of synapses, followed by a phase of synapse elimination or pruning that eventually brings the overall number of synapses down to their adult levels. This process is most exuberant during the first few years of life, although it can extend well into adolescence. Within this developmental span, however, different brain regions with different functions appear to develop on different time courses (see Figure 8-1). Huttenlocher estimated that the peak of synaptic overproduction in the visual cortex occurs about midway through the first year of life, followed by a gradual retraction until the middle to the end of the preschool period, by which time the number of synapses has reached adult levels. In areas of the brain that subserve audition and language, a similar although somewhat later time course was observed. However, in the prefrontal cortex (the area of the brain where higher-level cognition takes place), a very different picture emerges. Here the peak of overproduction occurs at around one year of age, and it is not until middle to late adolescence that adult numbers of synapses are obtained.

Scientists have pondered the purpose of synaptic overproduction and loss for a very long time. One of the earliest observations was made by Spanish neuroanatomist and Nobel laureate Santiago Ramon y Cajal (Ramon y Cajal, 1989[1917]):

I noticed that every ramification, dendritic or axonic, in the course of formation, passes through a chaotic period, so to speak, a period of trials, during which there are sent out at random experimental conductors most of which are destined to disappear. . . . What mysterious forces precede the appearance of the processes, promote their growth and ramification . . . and finally establish those protoplasmic kisses, the intercellular articulations, which seem to constitute the final ecstasy of an epic love story?

A more modern formulation of the love story began with the Cragg (1975) report that the cat visual cortex produced a greater number of synapses during development than it actually retained into adulthood. Subsequent work in monkeys and cats by Hubel and Wiesel and their collaborators (e.g., LeVay et al., 1980) demonstrated that as the physiological functioning of the visual cortex became more refined and precise, the anatomical synaptic connections were also refined. Those that fit the intended pattern were retained, and those that did not were eliminated.

Scientists also showed that visual experience played a necessary role in this process. If experience was distorted, so that one eye got much more stimulation than the other, for example, its connections were pared back less drastically than usual, and the connections with the inexperienced eye were pruned more than usual. In short, the development of patterned organization in the visual cortex was dependent on visual experience and involved the selective loss of connections that were not appropriate to the pattern. Synapses appear to be programmed to be eliminated if they are not functionally confirmed, based on some not fully known aspects of their activity history. In general, frequently active connections, like those of the more experienced eye, are more likely to survive.

While the data are not as complete for other senses, it is reasonably clear that building the organized neural systems that guide sensory and motor development involves the production of excess connections followed by some sort of pruning that leaves the system in a more precisely organized pattern. Moreover, in both humans and animals, the effects of experience on these systems-normal or abnormal-become increasingly irreversible over time. In kittens, irreversible deficits in vision will result with deprivation lasting for only 2-3 months after birth. In humans, irreversible deficits in vision are present when corrections for such optical conditions as strabismus (in which, due to muscular weakness, one eye deviates from and cannot be brought into alignment with the other normally functioning eye) are not made by the time the child reaches elementary school. Deficits become more pronounced with more prolonged visual deprivation. Thus, a sensitive period exists for vision, but rather than being sharply demarcated, it gradually tapers off.

A useful way to consider how experience becomes incorporated into the developing synaptic connections of the human brain, discussed briefly in Chapter 2, has been offered by Greenough and Black (Black and Greenough, 1986; Greenough and Black, 1992). They distinguish between experience-expectant and experience-dependent mechanisms guiding brain development. Experience-expectant synaptogenesis refers to situations in which a species-typical experience (that is, something that all members of a species experience, barring highly aberrant conditions) plays a necessary role in the developmental organization of the nervous system. Normal brain growth relies on these forms of environmental exposure. For example, the visual cortex "expects" exposure to light and patterned visual information and is genetically programmed to utilize these inputs for normal development. Deprivation of these ubiquitous and essential forms of environmental input can permanently compromise behavioral functioning, which is why it is essential to detect and treat early sensory deficits (e.g., cataracts, strabismus, auditory deficits) that interfere with the detection and registering of expected experiences.

Experience-dependent synaptogenesis, in contrast, refers to encoding new experiences that occur throughout life, foster new brain growth and the refinement of existing brain structures, and vary for every individual. This process optimizes the individual's adaptation to specific and possibly unique features of the environment. Whereas in experience-expectant development, all brains depend on the same basic experiences to develop normally, in experience-dependent development, individual differences in brain development depend on the idiosyncratic experiences that are encountered across the life span. Experience-dependent development is also linked to synaptogenesis, but in this case all we know is that experience triggers more plentiful connections among neurons. We do not know if this occurs through a process of overproduction and pruning, or if a more continuous pattern of growth is involved. Whatever the specific mechanism, experience-dependent brain development is a source of enduring plasticity and of adaptability to the demands of everyday life. And it is important to note that there appears to be no abrupt transition from utilization of experience-expectant processes to utilization of experience-dependent processes of brain development. In fact, it seems likely that the greater potential for recovery from deprivation or damage that characterizes young animals probably reflects the availability of both mechanisms.

Postnatal Neurogenesis

We now need to add the possibility of postnatal neurogenesis-the postnatal production of new nerve cells-to the repertoire of mechanisms by which the human brain continues to develop after the early childhood years. Prevailing knowledge about brain development, notably that the adult human brain does not produce new neurons, has recently been challenged by new insights into adult brain development. Specifically, important forebrain regions, such as the hippocampal dentate gyrus (which is involved in establishing memory for facts and relationships among events and places in one's experience), continue to receive new nerve cells into adulthood in humans (e.g., Eriksson et al., 1998). Recent findings in monkeys indicate that new neurons are also being formed each day and migrating to areas that include the prefrontal cortex, the seat of planning and decision making (Gould et al., 1999). Although it remains to be determined how significant neuronal additions in adulthood are to the functioning of the brain, it certainly lends further support to the argument that the brain continuously remodels itself.

Neurochemistry of Early Brain Development

The sending and receiving of messages in the nervous system depends on chemical messengers. A number of these chemical messengers affect gene expression in nerve cells in ways that have long-lasting effects on how nerves grow, respond to stimulation, and function. They are thus intimately involved in the growth and development of the nervous system and in neural plasticity. The past two decades have seen an explosion of information about these chemical messengers. In addition to the classic neurotransmitters, over 60 other peptide and steroid molecules have been identified that have direct effects on the brain. Currently, what can be confidently applied from this field directly to human development is limited. However, the study of neurochemistry is already revolutionizing the way people think about the nervous system, and a brief overview of some basic ideas from this work is warranted.

Chemical messengers that affect the brain operate through receptors, most of which are located in the dendrites and synapses of nerve cells. Like locks and keys, the physical structure of the messenger (the key) has to fit the physical structure of the receptor (the lock) for the chemical messenger to have any effect on the nerve cell. Receptors are specific. They typically recognize or bind with only one natural molecule. For many years, this type of specificity gave rise to the hope that science would be able to link specific neurochemicals to specific behaviors, allowing highly focused manipulations of behavior through drug therapy. However, despite what filters its way into the popular press (e.g., low serotonin levels cause aggression), the way the biochemistry of the brain operates is vastly more complex than a match of one chemical with one behavior. For example, it now appears that many of the chemicals that affect brain function are able to unlock several different receptors. This allows the same (or quite similar) chemical to have different functions and to play a role in multiple (often related) behavioral systems.

The brain is also able to alter its sensitivity to a chemical messenger by changing the presence, conformation (structure), and availability of the chemical's receptors. Receptor changes often reflect the history of the nerve cell's experience with its neurochemical. High levels of the chemical operating on the receptor frequently result in a decrease in the nerve's receptors for that chemical (a process called down-regulation); sometimes a dearth of a chemical important in a nerve's functioning results in an increase in receptor number (i.e., up-regulation). Up- and down-regulation takes place over hours and days, partially explaining why some psychoactive drugs take time before they begin to influence behavior and why some drugs, with time, need to be taken in higher and higher dosages to have the same effects. Some of these shifts in chemical messenger-receptor systems appear to be relatively permanent, perhaps especially those that occur during periods of rapid development; others are more transient, reflecting the normal turnover (production, decline, replacement) of receptors. This complexity may complicate things for those who are trying to decipher the mysteries of the brain, but it does allow the brain to be highly plastic, toning its functioning in highly nuanced ways, often quite rapidly.

Neurochemical-receptor systems also lie at the heart of how the brain alters its physical structure. A variety of different nerve growth factors (i.e., chemicals that play a role in the growth of dendrites and synapses) have been identified. These growth factors are present in different quantities and locations at different points in development of the brain, regulated by genes involved in normal brain development. They also change in their concentration in response to nerve damage, playing a role in the brain's attempts to adapt to and restore functioning following trauma. Receptor systems play critical roles in both experience-dependent and experience-expectant neural plasticity. The NMDA (N-methyl-D-aspartate) receptor is one receptor, but not the only one, that plays a role in neural plasticity. It appears to support learning by helping to foster what is termed "long-term potentiation." Long-term potentiation, a memory "model" involving increased synaptic strength, is brought about by sustained, rapid activity in the neural circuits involved in newly acquired information, analogous to repeating a new phone number in order to memorize it. It also appears that at critical points in the development of neural systems, there is sometimes an increase in NMDA receptors. This increase seems to open the window for the development of that neural system, allowing stimulation to have large effects, with the window closing when the number of NMDA receptors decreases.

Changes in chemical messenger systems and their receptors tend to tone the nervous system, altering sensitivity to stimuli and probabilities of responses, rather than necessarily causing particular behaviors. The following thought experiment provides a good example. You have been on a low-calorie diet (and have stuck to it) for several weeks. Numerous neurochemical changes in your brain have been set into motion by this semi-starvation. All of these changes do not mean that you will eat that luscious steak the waiter just set in front of you (the fact that you are dieting, are a vegetarian, and did not order the steak will hopefully rule the day). But the myriad of neurochemical changes in your brain set into motion by semi-starvation will probably make you more sensitive to how good the steak smells, make you salivate more, make you remember that steak for a long time, and so on; all changes orchestrated to help increase the probability that you will break down and eat the steak that your body might, in fact, "need." As this thought experiment indicates, the behavioral impact of changes in neurochemistry are dependent on the context and the individual's history. Like one's temperament, the changes tend to orchestrate a bias or propensity to respond in particular ways rather than rigidly determine that a behavior will always be expressed. A number of researchers believe that in order to understand the neural bases of temperament and emotions, they will need to understand the genetic and experiential processes that regulate these complex neurochemical systems of the brain throughout development.

Characteristically, the neurochemical systems of the brain are open both to input from the environment and to events occurring in the body other than the brain. There is increasing animal evidence that the environment plays a role in regulating aspects of brain neurochemistry. For example, the licking and grooming that the mother rat does of her pups (infant rats) appear to enhance the production of serotonin and thyroid hormone, both important in the neurochemistry of brain development. There is also increasing evidence that elements of early caregiving may help modulate the neurochemicals involved in pain and distress. Thus, the fats and sugars in breast milk appear to stimulate taste receptors linked to central opioid (natural painkiller) pathways, stimulating mild analgesia. Similarly, tactile stimulation of the mouth appears to operate through neurochemical mechanisms, not involving opioids, that affect brain pathways controlling distress. Some of these effects have been demonstrated in human infants. The evidence that the regulation of neuroactive chemical systems extends into basic caregiving activities is exciting, even though much of it still has been demonstrated only in animals. This evidence promises to help explain how alterations in the environment early in life may have wide-ranging effects on brain development and may alter patterns of behavioral responding for children with different rearing histories.

HOW THE BRAIN IS AFFECTED BY EARLY EXPERIENCE

This account of early brain development emphasizes the ways in which the nervous system is designed to recruit and incorporate experience into its developing architecture and neurochemistry. Normal experience (e.g., good nutrition, patterned visual information) supports normal brain development, and abnormal experience (e.g., prenatal alcohol exposure, occluded vision) can cause abnormal neural and behavioral development (Black et al., 1998). Plasticity is a double-edged sword that leads to both adaptation and vulnerability. The process of synaptic overproduction and loss is dependent on environmental information, although the evidence is largely restricted to sensory systems. Similarly, the brain's neurochemistry is exquisitely sensitive to behavioral and environmental stimuli. Scientists are far, however, from linking specific types or amounts of experience to the developing structure or neurochemistry of the immature human brain, and, conversely, from understanding how early brain development affects the ways in which young children process the abundance of information and experiences that their environments present to them. Answers to questions about when during development particular experiences must occur and when, in fact, timing is important and when it is not also lie, to a large extent, beyond the boundaries of current knowledge. Research on the developing brain can nevertheless provide a framework for considering the effects of early experience on development more generally. The questions that have been asked by neuroscientists have their parallels in research on behavioral development.

Two issues have played pivotal roles in guiding scientific inquiry about early experience and the brain. The first concerns the nature of early experiences. Those who raise and work with young children are deeply concerned about whether they are providing them with the right experiences and protecting them from harmful ones. What harm is done by exposure to inappropriate experiences, and how reversible are the effects? What degree of enhancement can be achieved by exposure to enriched experiences, and how long do beneficial effects last? Much more is known about the negative consequences for brain development of harmful environments than about the benefits of advantageous environments. And relatively more is known about the effects of pre- and perinatal environments on the developing nervous system than about environmental influences after the first few months of life.

The second issue concerns the timing of experience and is often expressed in terms of critical or sensitive periods. Much of the contemporary discussion of the importance of the first three years of life is framed in the terminology of sensitive periods. But does it really matter when the child is exposed to particular experiences? Do specific experiences need to occur during specific windows of time in order for the brain to develop normally? Can the brain recover or compensate when critical experiences are missed? In addition to the examples regarding the visual system described above, there are some very dramatic instances of timing effects, again primarily in other species. For example, an injury to the rat's cortex on the first day after birth causes more ultimate damage to brain tissue and greater loss of normal behavioral functioning than a similar injury on day 5 (Kolb and Whishaw, 1998). The presence of testosterone in the third trimester of human fetal development organizes the physiological characteristics of brain regions such as the hypothalamus in the male direction, so that release of hormones that govern sexual and reproductive functions follows the noncyclic pattern seen in the post-adolescent male (Cooke et al., 1998). Although estrogen and testosterone can affect neural structures after this time, nothing can duplicate or reverse the effects of this in utero hormone exposure. Normal development of the zebra finch's song (reviewed in Clayton, in press) requires exposure of the young male to an adult tutor during a sensitive period in juvenile life (Immelmann, 1969). The shortest period demonstrated to be sufficient for development of a relatively normal song extends from approximately day 20 to day 35 (Böhner, 1990). Zebra finches continue to be sensitive to the effects of further tutoring up to the age of about 65 days (Jones et al., 1996).

In developmental science, the term "sensitive period" is generally preferred to "critical period" because it implies less rigidity in the nature and timing of formative early experiences (Immelmann and Suomi, 1982). Sensitive periods can be defined as unique episodes in development when specific structures or functions become especially susceptible to particular experiences in ways that alter their future structure or function (Bornstein, 1989; Thompson, in press(a)). This susceptibility can operate in two ways: first, certain early experiences uniquely prepare the young children for the future by establishing certain capabilities at a time when development is most plastic and responsive to stimulation. Second, the young child is highly vulnerable to the absence of these essential experiences, and the result may be permanent risk of dysfunction.

In fact, it is extraordinarily difficult to study issues of timing in human development given that it is profoundly unethical to deprive children of needed experiences in order to introduce them at different developmental stages. We are thus dependent on animal studies, which are generating fascinating evidence of timing effects (see, for example, Bornstein, 1989; Knudsen, 1999) but have limited translations to humans, and on so-called experiments of nature, such as prenatal exposures that occur at different points in fetal development (discussed below) and research on children with sensory deficits, such as the case of deaf children who do not experience normal spoken language inputs, and children who have sustained brain injuries. In the latter case, as we saw in Chapter 6, unilateral brain lesions incurred prior to age 5 or 6 appear to have few lasting effects on language development, whereas when damage occurs after this age language development is often compromised. However, there can be significant deficits in certain aspects of memory and verbal functioning when these lesions are accompanied by seizure disorders and these deficits do not appear to be sensitive to the age at which the seizures occur (Vargha-Khadem et al., 1997, 1992). This exemplifies the complexity of what is presently known about sensitive periods in childhood.

Within these limitations, it is well known that a variety of environmental factors play a significant role in modulating early brain development. Some of the greatest insights have come from research on the detrimental consequences of early biological insults, deprivations, and stress. We have also learned a great deal from research on the neurobiological consequences of prematurity. We turn to this research following a brief overview of the studies that generated excitement about the brain's receptivity to environmental influence.

The Contribution of Environmental Variation

Documented differences in the brains and behaviors of animals that have experienced markedly discrepant early environments have emerged from the laboratory of Greenough and his colleagues (Black and Greenough, 1998; Black et al., 1998; Greenough and Black, 1992). Rats, not babies, were the subjects of study. They were either housed from the time of weaning or placed as adults in cages that varied in the degree of stimulation offered. The "complex" cages contained play objects and other animals. Animals reared since weaning or placed in these cages as adults outperformed rats raised alone or placed in typically barren laboratory cages on a variety of learning and problem-solving tasks. The brains of the rats reared in the complex environments also showed more mature synaptic structure, more dendritic spines, larger neuronal dendritic fields, more synapses per neuron, more supportive glial tissue, and increased capillary branching that increases blood volume and oxygen supply to the brain (see Box 8-1).

It is important to note that these effects did not appear to be characterized by a critical period. The indicators of both superior performance and more developed brains characterized the rats exposed to the complex environments as adults, as well as those housed in these environments since weaning. Both early and later exposure to greater environmental stimulation had beneficial consequences, although the effects occurred more rapidly and to a greater degree in the younger animals. Moreover, while long-term neuron and synapse studies have not been conducted, the effects of exposure to a complex environment on learning ability diminished overtime if the rats were removed from the environment. The intervention provided by the complex cages thus functioned more like the tetanus vaccine, which requires regular boosters, than the smallpox vaccine, which inoculates against disease with a single injection. As this book shows, most early interventions for humans act more like the tetanus than the smallpox vaccine.

Studies of complex environments in rats have also revealed the role that such environments can play in processes of recovery. For example, the detrimental behavioral effects of prenatal exposure to low to moderate levels of alcohol in rats (e.g., motor dysfunction and impairments in learning spatial tasks) can be greatly attenuated by raising the animals in a complex environment (Hannigan et al., 1993). A program of forced motor skill training in alcohol-exposed rats nearly eliminated motor dysfunction, and it also increased synapse number in their cerebellar cortex (Klintsova et al., 1997, 1998). Finally, increasing the complexity of the environment before or after brain damage in developing and adult rats enhanced recovery from the impairments produced by damage to various brain areas, probably through mechanisms that involve the development of alternative strategies rather than the direct recovery of lost functions (see Kolb and Whishaw, 1998).

This research on complex environments certainly suggests that better environments with greater diversity can have beneficial effects. However, it would be misleading to locate the complexity of the animal environments near the enriched part of the continuum from deprivation to enrichment. In fact, the environments in these experiments were probably less complex than the rats' natural wild habitats. Nevertheless, these studies do point to the existence of a multidimensional continuum of environments and indicate that development (and recovery) is improved as one moves toward the anchor point of enrichment. Moving from these animal studies to research on the neurological aspects of human cognitive, linguistic, and social-emotional development is a big leap, but one that warrants a major investment of time and resources. The need for research that can illuminate how environments that exceed some minimal threshold of adequacy affect human brain development is especially needed, in light of the fact that most of the research on how experience affects the developing brain explores the detrimental consequences of harmful experiences.

Early Biological Insults and the Developing Brain

Research on early biological insults provides fundamental insights into the vulnerability and resilience of the developing central nervous system. This area of research also offers a compelling illustration that plasticity cuts both ways, leaving the developing fetus and young child simultaneously vulnerable to harm and receptive to positive influences. It also suggests that the current emphasis on the years from birth to age 3 may have unwittingly bypassed an important stage of development: the prenatal period is when damaging environmental conditions may have some of the most devastating effects on development and, consequently, is when preventive efforts may have the greatest benefits.

Environmental factors that play a significant role in modulating prenatal and early postnatal brain development include substances and circumstances that are necessary for normal brain development, as well as exposures to chemicals, diseases, and stressors that are toxic or disruptive. As with psychosocial risks, such as poverty and family violence, their effects on development are probabilistic; they increase, but do not seal, the odds of impaired development. Table 8-1 lists some of the environmental factors that are beneficial and some that are detrimental. The factors listed, by no means exhaustive, are examples selected on the basis of clinical importance, availability of basic research on brain effects, and existence of relevant clinical studies of human infants. We consider below a few of these detrimental conditions and substances in more detail: an infectious disease (rubella); a developmental neurotoxin (alcohol), and a nutrient deficiency (lack of iron).

Infectious Disease

Rubella (German measles) is a classic example of an infectious disease that causes harm in utero. Exposure to rubella early in prenatal development affects the organs (e.g., eyes, ears) that are developing at the time that the virus crosses the placental barrier. Because the development of most organs is largely complete by the end of the first trimester, fetal development during the second and third trimesters of pregnancy is relatively more protected from the negative effects of the rubella virus.

The rubella story demonstrates how long it has often taken to recognize that a particular condition or exposure can put the fetus or child at risk. It was widely believed that few diseases were as benign as rubella until 1942, when the first report of the devastating effects of maternal infection during pregnancy was published (Gregg, 1942). One of the puzzles is why the medical community did not figure out the link between maternal rubella and congenital malformations earlier. Some qualities of rubella, which exist in other conditions as well, made it difficult to make the connection (Beswick et al., 1949). For example, it is not always clear that a fetus has been exposed to a particular infectious illness or toxic agent during pregnancy. In the case of rubella, there are many causes of fever, rash, and other symptoms that are seen. To complicate matters further, effects on the developing fetus or child may also be quite variable. For instance, rubella may affect the fetus's eyes, ears, brain, or heart, among other organs. Furthermore, the very idea that the fetus could be vulnerable to harm was novel before the rubella syndrome was accepted. This is now known to be true for many conditions, such as some of those in Table 8-1.

The rubella story also illustrates a triumph in prevention. As better methods of diagnosing rubella became available in the 1960s (Forbes, 1969), there was more certainty about which rashes and nonspecific symptoms in early pregnancy were due to rubella and which were not. Today, public health policy requiring universal immunization against rubella has virtually eliminated the problem of the congenital rubella syndrome in the United States.

Developmental Neurotoxins

Substances such as drugs and chemicals that are damaging to the developing nervous system are known as developmental neurotoxins. Table 8-1 indicates a number of these agents. Their effects on brain and behavior have been summarized in several comprehensive volumes (Kimmel et al., 1990; Slikker and Chang, 1998), as well as in thousands of original research reports. We use prenatal alcohol exposure as an example of this class of early biological insult. The effects of prenatal alcohol have been studied extensively, and the current state of knowledge was recently considered in depth in an Institute of Medicine report (Institute of Medicine, 1996). Major points related to questions of early brain and behavior development are highlighted here.

The adverse effects of prenatal alcohol exposure are now so widely known and accepted that it is hard to believe that the first report was issued only 30 years ago. Fetal alcohol syndrome was first described in the English-language medical literature in 1973 (Jones and Smith, 1973). Maternal alcohol consumption during pregnancy can lead to facial deformities, loss of neurons, severe neurobehavioral impairment, and impaired cognitive functioning, among other problems. Its consequences appear to persist throughout life (Connor and Streissguth, 1996; Institute of Medicine, 1996; Jacobson et al., 1993; Sampson et al., 1994; Streissguth et al., 1996a). They are not, however, inevitable. One of the perplexing aspects of fetal alcohol exposure is that, even with high doses of alcohol, not all fetuses develop symptoms of fetal alcohol syndrome or alcohol-related neurodevelopmental disorder (see below). Its importance lies in its prevalence and preventability, not its inevitability. Nonetheless, this is a very common cause of harm to the fetus that can be prevented.

Survey data collected by the Centers for Disease Control and Prevention show that the incidence of drinking at levels sufficient to put the fetus at risk for neurobehavioral impairment was 3.5 percent in 1995 (the most recent year for which data are available), with binge drinking the predominant pattern (87 percent of the cases) (Ebrahim et al., 1998). The proportion of women who consume alcohol during pregnancy has decreased since the mid-1980s (Serdula et al., 1991), although much of the decline is due to the changed habits of light drinkers. Women who drink heavily, who pose the greatest risk to their fetus, appear to be more resistant to prevention efforts. Heavy drinking and the consequent incidence of fetal alcohol syndrome are much higher among black Americans than among white Americans (Abel, 1995; Faden et al., 1997) and are also high among American Indians (Duimstra et al., 1993).

Fetal alcohol syndrome is the most severe form of prenatal alcohol effects. Defined by a specific pattern of facial and other physical deformities accompanied by growth retardation, fetal alcohol syndrome identifies a relatively small proportion of children prenatally affected by alcohol. The Institute of Medicine (1996) recently suggested that the term "alcohol-related neurodevelopmental disorder" be used to focus specifically on brain dysfunctions in the presence of significant prenatal alcohol exposure but without physical deformities. Fetal alcohol syndrome is estimated to occur at a rate of 1-3 per 1,000 live births; alcohol-related neurodevelopmental disorder is estimated to be at least 10 times more prevalent. Brain dysfunctions in alcohol-exposed children without fetal alcohol syndrome are often as severe as those in children with the full impairment.

A variety of neurobehavioral changes have been observed in children exposed to alcohol prenatally. These effects range from problems with attention and memory to poor motor coordination to difficulty with problem solving and abstract thinking. Infants and toddlers may be delayed in reaching important milestones, may have difficulty tuning out excess sensory stimuli, and often are hyperactive. About half of all individuals with fetal alcohol syndrome are mentally retarded (IQ < 70). Both severely and more mildly affected children demonstrate slower information processing and longer reaction times and appear to have specific problems with arithmetic (Jacobson et al., 1994). These effects have been documented through the early adolescent years and into adulthood. Such results demonstrate the importance of assessing functions other than IQ. In fact, these measures often detect effects of early biological insults in the absence of IQ differences, and behavioral disturbances may create more functional impairment than a lower IQ. In addition, more specific and sensitive measures may indicate differing effects of various developmental neurotoxins (Jacobson, 1998).

The importance of considering timing (when a condition occurs during development), severity (degree or dose), and chronicity (how long it lasts) in attempting to understand the effects of early biological insults is well illustrated by prenatal alcohol exposure. In general, the prenatal period appears to be distinguished by its sensitivity to a large array of harmful conditions. But even within the prenatal period, timing matters. For instance, alcohol exposure early in gestation has different effects on the developing brain from similar exposure later on. Case reports from autopsies and, more recently, neuroimaging studies (Riley et al., 1995; Sowell et al., 1996; Swayze et al., 1997) give an indication of central nervous system effects in humans. However, animal models-with experimental manipulation of alcohol exposure and direct examination of brain tissue-continue to provide crucial information. In the mouse, for example, exposure to alcohol on days 7 and 8 of gestation results in not only the typical facial deformities of fetal alcohol syndrome but also brain anomalies, such as small overall size and deficiencies in cerebral hemispheres, striatum, olfactory bulbs, limbic structures, the corpus callosum, and lateral ventricles. Exposure later in gestation generally does not produce such gross structural malformations but nonetheless kills nerve cells and interferes with synaptogenesis, formation of myelin, and other biochemical processes, including reduction of NMDA receptor binding in the hippocampus.

Research with humans also shows that the timing of prenatal alcohol exposure has differential effects (Connor and Streissguth, 1996; Institute of Medicine, 1996; Jacobson et al., 1993, 1998; Sampson et al., 1994; Streissguth et al., 1996a, 1996b). The unusual facial features of fetal alcohol syndrome in the human infant (e.g., low-set ears, short philtrum, cleft palate, cleft lip) appear to be due to heavy exposure early on, in the first trimester, when the structures that come together to form the face are developing. Fetal exposure to alcohol during the second and especially the third trimester of pregnancy appears to be a time of particular vulnerability for the impaired neurobehavioral development, although some data suggest that these effects extend throughout pregnancy. Dividing cells appear to be particularly sensitive to the toxic effects of alcohol, and hence a period during which extensive neurogenesis occurs would be a time of acute sensitivity to the effects of alcohol. The cognitive effects associated with exposure to alcohol later in pregnancy, for example, may be associated with the high level of neuronal cell division in pertinent parts of the brain that occurs during the third trimester.

The severity of exposure is another important factor in understanding ill effects, perhaps as important as the timing. For prenatal alcohol use, greater exposures are associated with worse effects. In addition, episodic binge drinking appears to be more harmful to the developing brain than equivalent levels of alcohol consumed steadily. Experimental animal studies indicate that ingestion of a given dose of alcohol over a short period of time generates a greater peak blood alcohol concentration than the same dose ingested over several days (Bonthius and West, 1990). Thus, the developing fetus is actually exposed to a higher level of alcohol in binge drinking and has been found in animal research to experience greater neuronal (Bonthius and West, 1990) and behavioral (Goodlett et al., 1987) impairment. In humans, binge drinking is more of a problem than is usually recognized, because moderate drinkers, who consume 1-2 drinks per day on average, in fact, tend to concentrate their drinking on 1-2 days per week, thus drinking 4 or more drinks per occasion (Jacobson and Jacobson, 1999). When juxtaposed with evidence on the timing of alcohol exposure, the detrimental effects of binge drinking suggest that any bouts of drinking during pregnancy run the risk of damaging some aspect of the developing brain.

Chronicity is another important factor in understanding the effects of early biological insults. In the case of prenatal alcohol exposure, it appears that the effects on the fetus worsen with successive pregnancies. Specifically, older mothers who are moderate-to-heavy drinkers are at higher risk for having an affected offspring (Institute of Medicine, 1996). This may be due to reduced ability to metabolize alcohol by women who have been drinking heavily for several years (Jacobson et al., 1993, 1994). In the case of alcohol exposure, chronicity should thus be thought of as a dimension of risk both within and between pregnancies.

Research on early biological insults has also yielded information on modifiability or brain plasticity. Environmental interventions to reduce the effects of alcohol exposure (other than specific treatment of a toxin or deficiency) have been studied for only a few conditions. Prenatal alcohol exposure is perhaps the best researched in recent years. In animal models, a variety of interventions has been shown to ameliorate some of the central nervous system effects of alcohol (Greenough and Black, 1992; Hannigan et al., 1993; Klintsova et al., 1997; Weinberg et al., 1995). Effective interventions include motor training, procedures that enhance maternal care-giving behaviors, and a postweaning environment that is physically and socially stimulating. However, one should not conclude that the process is trivial. For instance, getting a rat to do motor training may require quite heroic efforts on the part of the investigator, and interventions typically do not bring the brain and behavior of exposed animals fully back to the levels of animals who never experienced the biological insult. As common sense would suggest, protecting the developing brain from early biological insults is a more desirable and effective strategy than trying to correct the deficits once they have occurred. Fetal alcohol research provides a particularly compelling case for preventive interventions, as well as for early detection and treatment of associated difficulties.

Nutrient Deficiency

Both before and after birth, nutritional adequacy is important for optimal brain development and function (see Georgieff and Rao, 1999, and Morgan and Gibson, 1991, for recent reviews). The effects of generalized undernutrition (lack of sufficient protein, energy, and other nutrients) on the developing brain have been studied extensively over several decades (Dobbing and Smart, 1974; Morgane et al., 1993; Strupp and Levitsky, 1995; Winick and Rosso, 1969). This research has demonstrated that the timing of nutrient supplementation or deficiency is important. For example, nutritional deprivation in the second trimester of pregnancy has been shown to result in deficient numbers of neurons, whereas deprivation in the third trimester affects numbers of glial cells and the maturation of neurons (e.g., Dickerson, 1981). Postnatal nutrition also appears to show timing effects, with the first 2 to 3 years of life being an especially vulnerable time for effects on brain growth. The earlier the malnutrition occurs, the greater the reduction in brain size, and the longer the malnutrition continues, the greater the effect on the brain (Morgan and Winick, 1985; Winick, 1976). Nevertheless, as the literature on orphanage-reared infants illustrates (reviewed in the next chapter), young children can show remarkable recovery in growth and behavior even after gross early (postnatal) generalized malnutrition when they are fed adequately.

Although sufficient nutrient intake is important throughout life, certain nutrients have a more profound effect on the developing brain than others. The following discussion summarizes research on iron deficiency, an area in which there has been a recent burst of relevant research. Iron deficiency is probably the world's most common single nutrient disorder. Approximately 20 to 25 percent of babies worldwide have iron-deficiency anemia, and a much higher proportion have iron deficiency without anemia (deMaeyer and Adiels-Tegman, 1985; Joint Committee on Health Policy of the World Health Organization and UNICEF, 1994). The latter is common even in countries where public health interventions have reduced anemia. In the United States, for instance, the prevalence of iron-deficiency anemia has decreased dramatically (Looker et al., 1997), due to fortification of infant formula and cereal and increased breast-feeding, among other factors. However, poor and minority children are still at considerable risk for iron deficiency with or without anemia (Ogden, 1998). In a recent U.S. national survey, nonpoor white toddlers had the lowest prevalence of iron deficiency (about 3 percent), while Mexican-American toddlers were at highest risk regardless of economic status, affecting approximately 18 percent of poor and 12 percent of nonpoor Mexican-American children (Ogden, 1998).

Altered behavior and development are among the most worrisome concerns about iron deficiency in infancy. Iron-deficient anemic infants generally test lower in mental and motor development (see review by Nokes et al., 1998). Other behavioral differences, such as increased fearfulness, fatigue, and wariness, have also been noted (Honig and Oski, 1984; Lozoff et al., 1985, 1986, 1996, 1998; Walter et al., 1983, 1989). Although one study reported that test scores improved with a full course of iron treatment (Idjradinata and Pollitt, 1993), the other available studies found that a majority of infants with iron-deficiency anemia continued to have lower developmental test scores (Aukett et al., 1986; Lozoff et al., 1987, 1996; Walter et al., 1989), despite iron therapy for 2-6 months and correction of anemia; other behavioral differences were also still observed (Lozoff et al., 1998). Differences thus appear to persist.

Follow-up studies have sought to determine if differences persist beyond infancy. Several studies have shown that, at early school age, children who were anemic as infants continue to have lower test scores than their peers who did not experience anemia (Dommergues et al., 1989; Lozoff et al., 1991; Palti et al., 1983, 1985; Walter et al., 1990). A comprehensive follow-up at the transition to adolescence (Lozoff et al., 2000) found that children who had been treated for severe, chronic iron deficiency in infancy still scored lower on measures of mental and motor functioning, specifically in arithmetic achievement and written expression, motor functioning, and some specific cognitive processes such as spatial memory and selective recall. They were also more likely to have repeated a grade. Parents and teachers rated the formerly iron-deficient children as showing more anxiety or depression, social problems, and attention problems. In a different, population-based study (Hurtado et al., 1999), children who were anemic in infancy (presumably due to iron deficiency) were at increased risk for mild to moderate mental retardation at age 10. Thus, severe, chronic iron deficiency in infancy identifies children who continue to be at developmental and behavioral risk more than 10 years later.

Basic research and animal studies indicate some possible mechanisms for such behavioral and developmental differences. Iron is required for many processes, including neurotransmitter synthesis (dopamine being the most studied), myelination, and oxidative metabolism (reviewed in Georgieff and Rao, 1999). Maximal transport of iron into the brain corresponds with the brain growth spurt, and iron deficiency during this period results in a deficit of brain iron in animal models. These observations suggest that the developing brain may be particularly vulnerable to the effects of this nutrient deficiency. Conversely, free or excess iron is toxic to cell membranes and may contribute to neuronal damage following a brain injury.

New studies that utilize neurophysiological and electrophysiological methods are now providing data on iron-deficient human infants and demonstrating close links to results in animal models. In one such study (Roncagliolo et al., 1998), 6-month-old infants with iron-deficiency anemia had slower nerve conduction in the auditory pathway. Differences in nerve conduction velocity between anemic and nonanemic infants increased over the following year despite iron therapy. A disruption or defect in myelination was considered to be a promising explanation, given that brain iron is required for myelination, young iron-deficient animals have been noted to be hypomyelinated, and the auditory system is rapidly myelinating in the first two years after birth in the human infant (reviewed in Roncagliolo et al., 1998).

The hippocampus, which is a key structure in the circuit that subserves recognition memory, also appears to be vulnerable to early iron deficiency (de Ungria et al., 2000; Erikson et al., 1997). In animal models, iron deficiency results in markedly reduced neuronal metabolism (as indicated by cytochrome coxidase activity) in all subareas of the hippocampus and other regions involved in higher cognitive functions (de Ungria et al., 2000). Preliminary evidence from a study of infants of diabetic mothers (who are at risk for lower levels of iron in the liver, heart, and brain in addition to hyper- and hypoglycemia and hypoxia), using electrophysiological techniques, has revealed impaired recognition memory despite normal iron status at 6 to 8 months of age (de Regnier et al., in press). These findings are consistent with a hippocampally based memory deficit, and iron deficiency may be a contributing factor. Disruptions in recognition memory, in turn, may be a subtle early effect that could contribute to learning disabilities later on.

It is important to emphasize that early biological risks and insults, such as iron deficiency, often do not occur in isolation (see Figure 8-2). In fact, they typically are increased among infants who also grow up in disadvantaged environments. Iron deficiency, for example, is more prevalent among poor infants in the United States (McLoyd and Lozoff, 2000). Thus, in human studies, it can be exceedingly difficult to disentangle poor development and behavioral outcomes that are due to the biological exposure, from those due to the problematic environment.

Prematurity and Early Brain Development

One of the true marvels of human brain development is that an infant can be born prematurely in the early part of the third trimester and not only survive, but also achieve something resembling his or her potential in mental and motor behavior. Highly sophisticated intensive care techniques have improved survival rates of premature infants. The KidsCount data of the Annie E. Casey Foundation shows that the percentage of low-birth-weight babies increased in each of the 50 states between 1990 and 1997 (Annie E. Casey Foundation, 2000). Low-birthweight babies were 7.5 percent of all births in 1997, compared to 7.0 percent in 1990. This represents a 7 percent increase over just this 7-year period (National Center for Health Statistics of the Centers for Disease Control, 1993, 1999).

The borders of viability (approximately 24 weeks of gestation), however, have not changed since 1980 (Richardson et al., 1998). Greater than 95 percent of infants born after 28 weeks of gestation and greater than 50 percent of infants born at 24-28 weeks survive (Hack et al., 1991). At the very borders of viability (22-24 weeks of gestation), mortality remains high. Of the infants who survive, a high percentage have sustained damage to developing neurological structures and have significant neurological morbidity (Allen et al., 1993). Moreover, recent research with toddlers suggests that even low-risk preterm infants (those born between 27 and 34 weeks gestational age) cannot be assumed to have caught up with their full-term counterparts in all aspects of cognitive development (de Haan et al., 2000). Nevertheless, it is safe to say that, over the past decade, neonatology has begun to concern itself less with survival (mortality) and more with outcome (morbidity) (Richardson et al., 1998). The corresponding challenges that these infants at the border of viability present to society are only beginning to be addressed.

It is useful to consider preterm infants as fetuses who develop in extrauterine settings at the time when their brains are growing more rapidly than at any other time in their life (Als, 1997; McClellan, 1972). Prematurity has two main negative effects on brain development. First, premature birth predisposes the infant to pathological events that directly injure the brain. These events can be thought of as damage committed by factors that the human at this gestational age would not normally encounter. These can be as seemingly benign as the wrong mixture of nutrients to more obvious neuropathologies such as intracranial hemorrhage. Second, premature birth interrupts the normal process of intrauterine brain development by denying it expected intrauterine stimuli and factors important for growth (e.g., nutrients such as docosohexaenoic acid). One can consider this to be disruption due to omission of factors that are critical for normal development. Ultimately, the morbidity seen at any gestational age is the result of the combination of the number and severity of exposure to both types of influence.

The first principle of assessing the effect of prematurity on neurological outcome is to note that the child's general developmental status and intelligence scores decrease with reductions in gestational age (Saigal et al., 1991). Thus, an infant born at 24 weeks is at greater risk than an infant born at 26 weeks, who in turn is at higher risk than an infant born at 28 weeks. Infants born at 24 weeks not only have a less complete brain than those born at 26 weeks, but they also are far more prone to intracranial hemorrhage, hypoglycemia, and postnatal malnutrition, all of which adversely affect the more primitive parts of the brain. Once one moves out of the high-risk groups, however, outcomes become highly variable.

Insults Due to Prematurity

The literature on neonatal outcomes is replete with studies assessing the effects of intracranial hemorrhage (Papile et al., 1983), periventricular leucomalacia (Feldman et al., 1990; Lowe and Papile, 1990), hypoglyecmia (Duvanel et al., 1999), and malnutrition (Georgieff et al., 1985, 1989; Hack and Breslau, 1986) on head growth and developmental outcome. Besides gestational age and socioeconomic status, the next most important factor in assessing risk of adverse neurological outcomes is the degree of illness of the infant during the newborn period. Infants whose overall physiology is more compromised are more developmentally delayed at 2 years and appear to be at greater risk of prefrontal deficits at age 8 (Brazy et al., 1991; Luciana et al., 1999).

Intracranial hemorrhage (also known as intraventricular hemorrhage) is the most extensively studied noxious event that affects the premature infant's brain. This is probably due to the fact that it is easily visualized by cranial ultrasonography and quantifiable into Grades I (least severe) to IV (most severe). Approximately 20 percent of infants between 28 and 34 weeks gestation have intraventricular hemorrhage, with the vast majority (> 60 percent) rated as Grade I or II. In contrast, 60 percent of infants born between 24 to 28 weeks have intraventricular hemorrhage, and their hemorrhages tend to be the more severe Grade III and IV varieties. Accordingly, the risk of major handicaps, both motor and cognitive, is increased. Infants with lower-grade hemorrhages do not appear to be at any greater risk of major handicap (cerebral palsy, mental retardation) than infants who did not bleed (Papile et al., 1983), although they are at higher risk of minor handicaps (e.g., behavior problems, attention problems, memory deficits) (Lowe and Papile, 1990; Ross et al., 1996).

Omission of Factors Important for Normal Brain Development

A premature infant with a benign neonatal course nevertheless remains at increased risk of neurological morbidity. Although one can never be assured that all noxious events (both prenatal and postnatal) have been accounted for in any given study, there is mounting evidence that transferring brain growth and development from an intrauterine to an extrauterine environment prematurely is less than optimal even in the absence of other definable neurological risk factors (Chapieski and Evankovich, 1997; Cherkes-Julkowski, 1998; Huppi et al., 1996). Recent research, for example, has demonstrated poorer performance on elicited imitation tasks (a medial temporal lobe function) at age 18 months in 27- to 34-week gestational age preterm infants with completely benign neonatal courses compared with term infants tested at the same post-conceptional age (de Haan et al., 2000). These emerging data strongly suggest that the human brain continues to develop in a unique way in utero until the end of gestation and that early termination of pregnancy disrupts that development with subsequent behavioral consequences.

A more pernicious effect of extrauterine life on brain development in small preterm infants is the general problem of malnutrition. Neonatal illness not only predisposes preterm infants to definable adverse events (e.g., intraventricular hemorrhage, hypoxia) but also blocks provision of adequate nutritional substrates to promote normal brain growth and development. Studies have estimated that greater than 50 percent of very low-birthweight infants fall below the 5th percentile for head growth sometime during their hospitalization (rendering them, by definition, microcephalic) (Georgieff et al., 1985). Fortunately, one of the most amazing aspects of early human life is the ability of the head (and brain) to demonstrate catch-up growth. After a period of no growth, the head exhibits a remarkable increase in growth velocity to double or triple normal rates, given adequate protein-energy intakes (Georgieff et al., 1985; Sher and Brown, 1975). There is, however, a point of diminishing return. If the infant has had no growth for more than a month, the subsequent catch-up rate is markedly reduced, almost as if the potential for catch-up has been lost (Georgieff et al., 1985; Hack and Breslau, 1986; Sher and Brown, 1975). Premature infants with more striking postnatally acquired microcephaly due to malnutrition indeed have smaller head circumferences and poorer scores on the Bayley Scales of Infant Development at age 12 months (Georgieff et al., 1985). Reduced head circumference at 8 months postnatally bodes poorly for developmental outcomes measured at age 3 and 8 years (Hack and Breslau, 1986). These studies suggest that although catch-up head growth is a marvelous compensatory response, it is better to have never experienced the growth deficit in the first place. Extrapolating further, it argues for important windows of opportunity for brain growth late in the third trimester that, if interrupted by premature birth and lack of head growth, may result in the brain being "constructed" in an alternative manner (de Haan et al., 2000).

In sum, prematurity confers a significant risk to the developing brain. The risk emanates from both insults that arise during the course of illness in the premature infant and from interruptions of the provision of the expected substrates and environment apparently necessary for normal brain development. We have used examples for which there is a substantial literature (e.g., intraventricular hemorrhage), but hasten to add that other potentially neuropathological factors that are more difficult to isolate and quantify (e.g., hypoxia-ischemia, hypoglycemia, neurotoxic medications such as steroids) are likely to play important roles as well. The ultimate risk to any single premature infant is likely to be a composite of all the known and unknown risk and protective factors that characterize that infant, and on the infant's general extent of biological and environmental vulnerability. Thus the premature infant born to a lower-income mother with few resources who received poor prenatal care is likely to have a much more difficult neonatal course, and therefore be at higher neurodevelop-mental risk, than an infant of the same gestational age born to a mother who received better prenatal care and has more resources. Perhaps this helps explain the overall down-shifting of developmental scores in premature infants from families of lower socioeconomic status (Saigal et al., 1991).

Growing awareness of environmentally based differences in the outcomes of premature infants has fueled multiple intervention efforts ranging from dramatic changes in the care these infants receive in neonatal intensive care units (see reviews by Als, 1997; Hernandez-Reif and Field, 2000) to comprehensive initiatives that provide a range of services to the infants and their families from the time they leave the hospital to several months or years after discharge. The best known of the comprehensive approaches is the Infant Health and Development Program (see Box 8-2) (Gross et al., 1997), which included a randomized trial and extensive follow-ups of the participating families.

The evaluation literature on these interventions offers good news about the capacity of early childhood programs, which emphasize individualized developmental care, as well as initiatives focused on parental coping and training in optimal parenting skills, to improve health outcomes and decrease developmental delays in premature infants. It thus appears that the developmental problems associated with prematurity and low birthweight can be mitigated by intervention. However, this is such a complex biological phenomenon that relatively nonspecific interventions may not be the most productive approach. Moreover, virtually all experts in this area agree that efforts focused on preventing low birthweight need to be the top priority.

Stress and the Developing Brain

Research on premature infants has provided substantial evidence of the importance of the caregiving environment for the baby's later progress. This theme emerges, as well, from research on animals regarding how stress affects the developing brain. This research provides preliminary insights into how alterations of the early caregiving environment affect neurochemical aspects of early brain development. Extending this evidence to the human species is not yet warranted, however. There is, for example, only one scientifically reviewed study that has imaged the brains of maltreated children (De Bellis et al., 1999a) (discussed in Chapter 9). The animal evidence, however, is suggestive of the physiological processes that may underlie associations found between highly dysfunctional caregiving and problematic child outcomes, particularly those that lie in the realm of self-regulatory behaviors. This, in turn, points to promising directions for future collaborative research among behavioral and brain scientists.

The term "stress" is used by psychologists, physiologists, and the lay public and means different things to each (Engle, 1985). In this report, stress refers to the set of changes in the body and the brain that are set into motion when there are overwhelming threats to physical or psychological well-being (Selye, 1973, 1975). Stress can have dramatic effects on health and development (Johnson et al., 1992). This happens because the physiology of stress produces a shift in the body's priorities. When threats begin to overwhelm one's immediate resources to manage them, a cascade of neurochemical changes that begin in the brain temporarily puts on hold the processes in the body that can be thought of as future-oriented: finding, digesting, and storing food; fighting off colds and viruses; learning things that don't matter right now but may be important sometime in the future; reproducing and rearing offspring. Many of these neurochemical changes take place in the very same brain structures (e.g., hypothalamus and brainstem) that function to regulate heart rate, respiration, food intake and digestion, reproduction, growth, and the building up versus breaking down of energy stores (Stratakis and Chrousos, 1995).

These brain regions also play a role in regulating the production of stress responses in the rest of the body. Specifically, the adrenal glands, located on the top of the kidneys, produce adrenaline and cortisol (Axelrod and Reisine, 1984). Adrenaline is part of the sympathetic nervous system. Increases in sympathetic nervous system activity support vigilance, focus attention, increase heart rate, shunt blood to muscles and away from the digestive system, break down fat stores making energy available to cells, and dampen activity of the immune system. Cortisol is a steroid hormone that plays a myriad of roles in stress physiology. It helps to break down protein stores, liberating energy for use by the body. It suppresses the immune system, suppresses physical growth, inhibits reproductive hormones, and affects many aspects of brain functioning, including emotions and memory.

Current understanding of how psychological stimuli, such as experiences of fear and anxiety, set in motion stress physiology is centered on an area of the brain called the amygdala (Miller and Davis, 1997; Rolls, 1992; Schulkin et al., 1994), which has close back-and-forth communication with areas of the brain involved in attention, memory, planning, and behavior control. In animals, experimentally causing a hyperstimulation of the amygdala (a process termed "kindling") seems to create a hypersensitization of the fear-stress circuits of the brain and changes in behavior that look like an animal version of posttraumatic stress disorder (Rosen et al., 1996). It is as if the fear circuits get locked in the "on" mode and have trouble shutting off. These circuits course through the amygdala and an area called the bed nucleus of the stria terminalis. They appear to be pathways through which circumstances outside the body set in motion the cascade of events inside the body and the brain that undergird fear-stress responses. These events involve the elevation of cortisol and stimulation of the sympathetic arm of the stress response. In animals, flooding the brain with cortisol for prolonged periods of time produces changes in this process that may lower the threshold for activating the fear-stress system (Makino et al., 1994). The result is an animal that more readily experiences fear, anxiety, and stress and may have a harder time dampening or regulating these responses.

The amygdala is a fairly mature brain area at birth in humans and seems to be fully mature at least as early as a child's first birthday. All anatomical evidence suggests that by the end of the first year, young children should be capable of experiencing psychologically driven fear, anxiety, and stress. Indeed, fear reactions to strangers (Bronson, 1971; Schaffer, 1966; Waters et al., 1975) and anxiety reactions to separation from familiar caregivers (Ainsworth and Bell, 1970; Bowlby, 1973; Sroufe, 1979) are hallmarks of emotional development in late infancy. Brief periods of stress are not expected to be problematic. Indeed, survival requires the capacity to mount a stress response. However, because the stress system functions to put growth-oriented processes on hold, frequent or prolonged periods of stress may negatively affect development.

Evidence from research on rodents and primates suggests that experiences of neglect early in life constitute the kinds of stressful experiences to which young offspring are especially sensitive and may result in a more reactive stress system. In studies of rats, for example, when experimenters do things to the nest that affect maternal behavior (such as handle the pups), they can affect the development of the rat's stress system (Denenberg, 1999; Levine and Thoman, 1970). Doing things to the nest that result in better organized maternal behavior results in infant rats that develop into less fearful, less stress-reactive adults, whereas doing things that disrupt maternal behavior results in more fearful and stress-reactive adult rats. Researchers have also shown that strains of rodents that are known to be more stress-reactive are characterized by maternal care that involves less licking and grooming (Liu et al., 1997; Meaney et al., 1996; Plotsky and Meaney, 1993). Cross-fostering genetically high stress-reactive infants to mothers from low stress-reactive strains results in the development of a more stress-resilient animal. These effects of early experience in the rat appear to operate through the development of the receptor system in the brain that influences the reactivity of the fear-anxiety circuits. Plenty of input early in life that keeps the stress system dampened down results in the development of a stress-modulating receptor system that can quickly turn off stress reactions. Without this input, the fear-stress system appears to get "shaped" so that the rat pup becomes a more highly reactive adult who has difficulty modulating these responses. In short, the development of a less stress-reactive rat seems to revolve around enhancing and supporting qualities of the caregiving environment.

There are monkey analogues of these rat studies, although details of the biobehavioral mechanisms have not been worked out as thoroughly. Infant monkeys deprived of normal social stimulation grow into socially incompetent, fearful adults (Harlow et al., 1971; Young et al., 1973). More recent studies have documented that monkeys reared on cloth surrogates, but exposed every day to several hours of play with other infant monkeys, are not as socially incompetent as monkeys raised in isolation, but they show numerous physiological signs of being very anxious and fearful (Suomi, 1991). They produce higher levels of stress hormones when threatened and they have high levels of anxiety-related brain neurochemicals in the cerebrospinal fluid, which bathes and nourishes the brain and spinal cord. Monkeys reared only with other infant monkeys (i.e., no cloth surrogates to call their own), show similar patterns of high reactivity to stress (Champoux et al., 1989, 1992).

A high stress-reactive adult monkey can also be produced by procedures that cause stress to its mother (Coplan et al., 1995, 1996; Rosenblum and Andrews, 1994; Rosenblum et al., 1994; Schneider, 1992a, 1992b; Schneider et al., 1992, 1998). One technique for stressing the mother is to make her food resources unpredictable. This has the effect of deeply disturbing the mother's social relationships with other adult monkeys in her group. The infant monkeys in these unpredictable food studies (who are roughly equivalent in developmental age to 1- to 2-year-old human children) experience high levels of stress hormones (like their mothers) and grow up into highly fearful, socially less competent adult animals (Rosenblum and Andrews, 1994; Rosenblum et al., 1994). These effects were obtained even though food was never uncertain for the young monkeys themselves, and thus seem to be influenced by what this uncertainty and disturbance in the social environment does to their mothers.

There is a great deal to learn about how the social environment connects with the biology of growth and the regulation of stress physiology in human infants and children. Intriguing research is emerging, however, to suggest that the development of stress regulation in young children may be a very promising place to look for brain-experience dynamics. For example, both failure to thrive and psychosocial dwarfism (Gohlke et al., 1998; Skuse, 1985), in which children's pituitary glands fail to secrete sufficient growth hormone (Skuse et al., 1996), are associated with failures in the social environment (Alanese et al., 1994). Removing the child from the problematic social system reverses the disorder and growth increases rapidly. This research, as well as that on orphanage-reared infants discussed in Chapter 9, raises extremely important questions about the plasticity and self-righting tendencies inherent in the human (as well as the animal) brain. In general, there is much to learn about the extent to which the neurological pathways between caregiving environments and dysfunctional behavior that are emerging in the animal literature apply to human offspring and about the effects of remedial experiences that attempt to enhance the development of children from early abusive and neglectful environments.

In sum, neuroscience evidence from animal research is increasingly pointing to experiences of neglect, stress, and trauma within the caregiving environment as a source of compromised brain development. Research on rodents and primates indicates that the ways in which the brain learns to respond to stressful and fear-inducing circumstances are profoundly affected by the capacity of the infant's caregivers to regulate the developing stress system. Disruptions to the caregiving environment that produce stress in the mother appear to alter the offspring's developing reactivity to stress, as seen behaviorally in high levels of fearfulness and neurologically in how the brain releases and modulates stress hormones. Alternatively, supportive and nurturant caregiving can protect offspring from these consequences. Although this evidence is compelling with regard to the significance of early rearing environments as they affect the developing brain, we are barely at the beginning of exploring these issues in human babies (Kimmel et al., 1990; McLoyd and Lozoff, 2000; Morgane et al., 1993).

SUMMARY AND CONCLUSIONS

Basic research on the development of the brain is a rapidly moving frontier. Abundant evidence indicates that brain development begins well before birth, extends into the adult years, and is specifically designed to recruit and incorporate experience into its emerging architecture and functioning. For some systems, environmental inputs need to occur prenatally or relatively early in life, after which time the brain becomes decreasingly capable of developing normally. But available evidence indicates that such critical periods are more exceptional than typical in human development. For the vast majority of brain development, including areas of the brain involved in cognitive, emotional, and social development, either questions regarding critical or sensitive periods have not been explored or it appears that the brain remains open to experiences across broad swaths of development. This makes sense. Adaptation depends on the rapid consolidation of capabilities essential to survival and the life-long flexibility to adjust to changing circumstances and learn new skills. As a result, assertions that the die has been cast by the time the child enters school are not supported by neuroscience evidence and can create unwarranted pessimism about the potential efficacy of interventions that are initiated after the preschool years.

Nevertheless, what happens early matters. Concerns about protecting the developing brain need to begin well before birth. During the prenatal months, the developing brain is highly vulnerable to intrinsic hazards (such as errors of neural migration) and external insults resulting from drug or alcohol exposure, viral infection, malnutrition, and other environmental harms. This directs attention to efforts to protect brain development during pregnancy and the earliest months of life, including the importance of prenatal and postnatal medical care, as well as expanded public health efforts to improve nutritional quality and reduce drug and viral exposure. It also argues for continued efforts to reduce the incidence of premature births and to ameliorate the adverse consequences of prematurity. Neuroscience evidence also directs attention to the early detection, identification, and treatment of problems such as visual impairments, auditory deficits, and major perceptual-motor delays that have profound effects on children's capacity to access and incorporate the stimulation needed to organize the developing nervous system. For these aspects of development, there is solid evidence that the timing of corrective efforts matters a great deal.

Beyond this evidence regarding detrimental influences on brain development, neuroscience offers few insights into how early environments can function to enhance development beyond what might otherwise be expected. The experiments with complex environments conducted on rats reveal the benefits of more enriched environments, indicate that younger brains react more rapidly and to a greater degree to environmental variation, and suggest that removal from complex environments results in decreasing benefits over time. Nevertheless, we do not yet have the evidence on infant brains to translate these findings from animal research into tangible recommendations for early interventions aimed at children's cognitive or social-emotional development. For these insights, additional behavioral evidence from human development is needed.

A final implication of research on early brain development concerns the detrimental effects of early and sustained stressful experiences, particularly those that derive from aberrant or disrupted caregiving environments. Evidence from research on animals suggests that such experiences overactivate neural pathways that regulate fear-stress responses in the immature brain, perhaps placing them on a "high alert" setting that may alter patterns of behavioral responding in adult animals with different rearing histories. Translations of these findings to human development are largely speculative. However, emerging evidence regarding the physiology of children subjected to serious deprivation and trauma early in life are consistent with the animal studies, as is the richer body of behavioral data on young children exposed to such early adverse experiences. This is an especially promising area for research that integrates animal and human studies, using both neuroscience and behavioral approaches, and explores not only the negative consequences of early stress and trauma but also the capacity of the brain to reorganize itself following highly depriving circumstances early in life.

In sum, the neuroscientific research on early brain development says that the young children warranting the greatest concern are those growing up in environments, starting before birth, that fail to provide them with adequate nutrition and other growth-fostering inputs, expose them to biological insults, and subject them to abusive and neglectful care. Children with undetected sensorimotor difficulties (whose developing brains may not receive the stimulation they need) also warrant concern. The brain research also reassures that brain development is probably on course for the vast majority of young children who are protected from these conditions and, in many instances, can be affected positively by timely corrective interventions focused on early insults and deficits.

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The brain is the ultimate organ of adaptation. It takes in information and orchestrates complex behavioral repertoires that allow human beings to act in sometimes marvelous, sometimes terrible ways. Most of what people think of as the "self"-what we think, what we remember, what we can do, how we feel-is acquired by the brain from the experiences that occur after birth.

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The Role of Academic Emotions in Learning: Addressing Student Motivation, Performance, and Learning Strategies

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Emotions are inherently connected with and affect cognitive skills such as attention, memory, and problem solving, all of which play a critical role in learning. Emotions are also one of the driving forces behind motivation. The school setting creates a context for various emotional experiences that have the potential to influence the educational process. These diverse emotions influence students’ motivation to persist, performance, and strategies for learning. Two important dimensions describing emotions are valence and activation. Regarding valence, enjoyment can be distinguished from anxiety. Concerning activation, activating excitement can be differentiated from deactivating relaxation. By grouping affective states as positive or negative, and as activating or deactivating, the circumplex can be remodeled into a 2 × 2 taxonomy involving four broad categories of emotions. Emotions are not only biologically determined but also shaped by one’s culture. In addition, while there is evidence that men and women differ in their experience of emotions, gender has often been overlooked as an important variable in academic emotions research. Therefore, our vision for this review was to provide a comprehensive scholarly overview of the current state of research in the area, while also challenging our readers with new directions for future scholarship on academic emotions.

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Five Brain-Based Learning Strategies to Boost Learning, Retention,…

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Five strategies to use different brain-based learning approaches in your teaching practice.