essay about brain development

InBrief: The Science of Early Childhood Development

This brief is part of a series that summarizes essential scientific findings from Center publications.

Content in This Guide

Step 1: why is early childhood important.

: Brain Hero
: The Science of ECD (Video)
You Are Here: The Science of ECD (Text)

Step 2: How Does Early Child Development Happen?

: 3 Core Concepts in Early Development
: 8 Things to Remember about Child Development
: InBrief: The Science of Resilience

Step 3: What Can We Do to Support Child Development?

: From Best Practices to Breakthrough Impacts
: 3 Principles to Improve Outcomes

The science of early brain development can inform investments in early childhood. These basic concepts, established over decades of neuroscience and behavioral research, help illustrate why child development—particularly from birth to five years—is a foundation for a prosperous and sustainable society.

Brains are built over time, from the bottom up.

The basic architecture of the brain is constructed through an ongoing process that begins before birth and continues into adulthood. Early experiences affect the quality of that architecture by establishing either a sturdy or a fragile foundation for all of the learning, health and behavior that follow. In the first few years of life, more than 1 million new neural connections are formed every second . After this period of rapid proliferation, connections are reduced through a process called pruning, so that brain circuits become more efficient. Sensory pathways like those for basic vision and hearing are the first to develop, followed by early language skills and higher cognitive functions. Connections proliferate and prune in a prescribed order, with later, more complex brain circuits built upon earlier, simpler circuits.

In the proliferation and pruning process, simpler neural connections form first, followed by more complex circuits. The timing is genetic, but early experiences determine whether the circuits are strong or weak. Source: C.A. Nelson (2000). Credit: Center on the Developing Child

The interactive influences of genes and experience shape the developing brain.

Scientists now know a major ingredient in this developmental process is the “ serve and return ” relationship between children and their parents and other caregivers in the family or community. Young children naturally reach out for interaction through babbling, facial expressions, and gestures, and adults respond with the same kind of vocalizing and gesturing back at them. In the absence of such responses—or if the responses are unreliable or inappropriate—the brain’s architecture does not form as expected, which can lead to disparities in learning and behavior.

The brain’s capacity for change decreases with age.

The brain is most flexible, or “plastic,” early in life to accommodate a wide range of environments and interactions, but as the maturing brain becomes more specialized to assume more complex functions, it is less capable of reorganizing and adapting to new or unexpected challenges. For example, by the first year, the parts of the brain that differentiate sound are becoming specialized to the language the baby has been exposed to; at the same time, the brain is already starting to lose the ability to recognize different sounds found in other languages. Although the “windows” for language learning and other skills remain open, these brain circuits become increasingly difficult to alter over time. Early plasticity means it’s easier and more effective to influence a baby’s developing brain architecture than to rewire parts of its circuitry in the adult years.

Cognitive, emotional, and social capacities are inextricably intertwined throughout the life course.

The brain is a highly interrelated organ, and its multiple functions operate in a richly coordinated fashion. Emotional well-being and social competence provide a strong foundation for emerging cognitive abilities, and together they are the bricks and mortar that comprise the foundation of human development. The emotional and physical health, social skills, and cognitive-linguistic capacities that emerge in the early years are all important prerequisites for success in school and later in the workplace and community.

Toxic stress damages developing brain architecture, which can lead to lifelong problems in learning, behavior, and physical and mental health.

Scientists now know that chronic, unrelenting stress in early childhood, caused by extreme poverty, repeated abuse, or severe maternal depression, for example, can be toxic to the developing brain. While positive stress (moderate, short-lived physiological responses to uncomfortable experiences) is an important and necessary aspect of healthy development, toxic stress is the strong, unrelieved activation of the body’s stress management system. In the absence of the buffering protection of adult support, toxic stress becomes built into the body by processes that shape the architecture of the developing brain.

Brains subjected to toxic stress have underdeveloped neural connections in areas of the brain most important for successful learning and behavior in school and the workplace. Source: Radley et al (2004); Bock et al (2005). Credit: Center on the Developing Child.

Policy Implications

The basic principles of neuroscience indicate that early preventive intervention will be more efficient and produce more favorable outcomes than remediation later in life.
A balanced approach to emotional, social, cognitive, and language development will best prepare all children for success in school and later in the workplace and community.
Supportive relationships and positive learning experiences begin at home but can also be provided through a range of services with proven effectiveness factors. Babies’ brains require stable, caring, interactive relationships with adults — any way or any place they can be provided will benefit healthy brain development.
Science clearly demonstrates that, in situations where toxic stress is likely, intervening as early as possible is critical to achieving the best outcomes. For children experiencing toxic stress, specialized early interventions are needed to target the cause of the stress and protect the child from its consequences.

Suggested citation: Center on the Developing Child (2007). The Science of Early Childhood Development (InBrief). Retrieved from www.developingchild.harvard.edu .

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Early Brain Development

The first thousand days of life are a critical and important period of development. Primary care pediatricians and public health professionals play an important role in fostering healthy child development and opportunities to thrive by providing preventive care that promotes safe, stable, and nurturing caregiver relationships. Brain development is cumulative in that early, simple connections and circuits form the foundation for more complex pathways and behaviors. Much like muscles, connections and circuits that are used frequently become stronger and more efficient over time (“neurons that fire together, wire together”). However, those connections and circuits that are not utilized are pruned and eliminated (“if you don’t use it, you lose it”).

Brain plasticity declines with age. Plasticity, or the ability of the brain to rewire itself in response to changes in the environment, is waning by the time children begin kindergarten.

See this Early Brain Development video from PBS.

Translating the Science into Practice

The basic developmental science is clear, but how do we take that science and apply it in the clinical setting?

Brain development is dynamic, with different structures/functions developing at different rates and times. Specifically, structures that underlie the physiologic stress response (e.g., amygdala) appear to mature sooner than those structures that assist in modulating or turning off the stress response (e.g., prefrontal cortex).

Brain development is disrupted by chronic exposure to the mediators of the physiologic stress response (CRH, cortisol, adrenaline, etc.). Significant adversity in childhood can lead to a vicious cycle of stress that is toxic to important structures like the hippocampus and prefrontal cortex. This “toxic stress” is a “common denominator,” a biological mechanism underlying well established associations between various forms of childhood adversity (abuse, neglect, domestic violence, parental mental illness or substance abuse) and less than optimal life course trajectories (see the ACE Study).

View training modules on the following topics:

Early Brain Child Development Core Story
Toxic Stress
Public Health

Supporting Brain Development Through Well-Child Visits

Pediatricians can educate families that young children need safe, stable, and nurturing relationships to assist them in regulating their stress.

Connected Kids : Safe, Strong, Secure offers child healthcare providers a comprehensive, logical approach to integrating violence prevention efforts in practice and the community. The program takes an asset-based approach to anticipatory guidance, focusing on helping parents and families raise resilient children. Connected Kids Includes a Clinical Guide and 21 handouts for parent and teen topics such as bullying, discipline, interpersonal skills, parents, suicide and television violence.

The AAP’s periodicity schedule for recommended preventive health care services provides several opportunities for primary care pediatricians to promote early brain development as well as assess for development, behavioral, and social-emotional concerns.

The well child health visit is an opportunity to

Review a child’s history,
Conduct developmental screening and surveillance,
Conduct psychosocial/behavioral assessment ,
Screen for lead , and
Use anticipatory guidance to discuss child and family strengths and challenges.

Building Partnerships to Support Early Brain Development

Supporting early brain development involves more than anticipatory guidance at well child visits. There are common messages and overlapping services that aim to build children’s brain with early learning environments and/or positive parenting approaches.

See this Early Learning Systems PBS video.

Develop collaborative relationships with the resources in your community that might assist parents and caregivers and prevent and/or mitigate the precipitants of childhood toxic stress.

Home visitation programs (eg, Nurse Family Partnership)
Early Intervention services
Infant and early childhood mental health providers
Parent/Family support systems (eg, Circle of Security, Triple-P, Nurturing Parenting, addressing illiteracy, unemployment, unsafe housing, food scarcity, Parent-Child Interaction Therapy).
Legal Aid and medicolegal partnerships, child care networks/resource and referral agencies.
Community libraries, assistance for victims of domestic violence, care for parents with substance abuse or mental health issues.
Advocate for the development of resources to fill the gaps that exist in your particular community.
Encourage consistent, community-wide messaging (prenatal, home visits, WIC, early intervention, preschools, early childhood PTAs, etc.) on issues related to early brain and child development (e.g., promoting Reach Out and Read, limiting screen time, alternatives to corporal punishment).
Identify (and collaborate with) high quality early education and child care settings.

Communicating with Families

Discuss with parents and caregivers the pivotal and foundation role of the first 1000 days.
Emphasize that early relationships need to be “safe, stable, and nurturing.” Parents and caregivers should therefore “Protect, Relate, and Nurture” – PRN all the time!
Communicate and interact with parents and caregivers to provide anticipatory guidance that assists parents and caregivers in proactively building the critical social-emotional-language skills that buffer toxic stress. Examples include: Bright Futures , Connected Kids, the 6 Ps of Purposeful Parenting (Purposeful, Protective, Personal, Progressive, Positive and Playful), and the 5 Rs of Early Literacy: Reading, Rhyming, Routines, Rewards, and Relationships.
Assess the social-emotional status of the family at every visit (“the Relationship as a Vital Sign” surveillance).

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Caring Relationships: The Heart of Early Brain Development

Two adults at a table playing with two toddlers.

Of all that brain science has taught us over the last 30 years, one of the clearest findings is that early brain development is directly influenced by babies’ day-to-day interactions with their caregivers. Even before birth, babies have a built-in expectation that adults will be available and care for their needs (Shonkoff & Phillips 2000). Their very survival depends on this availability. If babies’ expectations for protection and nurturance are met, their brains experience pleasure and delight. These pleasurable early interactions stimulate the brain, motivating the baby to relate to those who care for them with confidence and ease. If their expectations are less than adequately met, their confidence in getting their needs met through relationships may be challenged. When this occurs, emotional and social development suffer, and, because babies’ emotional base is the foundation for all other learning, so do intellectual and language development (Greenspan 1990; IOM & NRC 2015).

A baby’s early experiences in relationships, whether at home or in an early education environment, set the stage for future brain functioning. The information gathered in these early relationships is at the heart of a rich and complex brain-building process. As babies experience responses from their caregivers, their brains start to form expectations for how they will be treated and how they should respond. For example, when a baby fusses or cries, consistent adult responses that provide comfort help the child anticipate similar responses in the future. As the expectations are strengthened by similar experiences being repeated, babies’ brains construct perceptions of the social and emotional world in which they live. Those perceptions influence how babies understand their environment, relate to others, and engage in learning. When those experiences are primarily positive, children perceive the behaviors and messages of others in positive ways and are motivated to explore more and more of the world (including people and things). When babies have repeated adverse early experiences, they come to expect the behaviors and messages of others to be negative, and they start to perceive new experiences with others in a negative way.

In early brain growth, experience creates expectation, which alters perception.

Whether babies’ early relationships are largely positive or negative significantly impacts their ability to manage stress. From birth to age 3, stress can have an especially adverse effect on brain development (NRC & IOM 2009). When children have positive early relationship experiences, they develop emotionally secure attachments with their caregivers that can buffer stress at various levels of intensity. If stress is severe and persistent, it becomes toxic and the emotional buffers provided by secure relationships are crucially important (Center on the Developing Child 2007). When children have to cope with tolerable (less intense and temporary) stress, emotionally secure relationships help children regulate their responses and, once the stress subsides, refocus on exploration and learning. What we have learned from brain research in the last 30 years is that the “tender loving care” advocated by early childhood educators for many decades is not only the kind way to treat children but a crucial part of early brain development.

Healthy early brain development from birth to age 3

During the first three years of life, children go through a period of “prolonged helplessness,” dependent on others for safety, survival, and socialization (Gopnik 2016). Because babies’ brains are programmed to learn from their caregivers, this period of helplessness is a strength, not a weakness. Infants’ and toddlers’ time with others wires their brains for survival in anticipation of future functioning (Hamburg 1995). The brain builds crucial structures and pathways that serve as the foundation for future social, emotional, language, and intellectual functioning (Schore 2005; Drury et al. 2010). Therefore, the relationships a child experiences each day and the environments in which those relationships play out are the building blocks of the brain. By participating in learning experiences with their caregivers, babies shape their brains to function in the particular physical, social, and linguistic environments of those who care for them. Babies learn, largely by attending to their caregivers’ modeling, how to feel, think, and act. Simple, daily interactions have an enormous impact. For example, a caregiver who performs routines in a gentle way and uses language to help the child anticipate what will happen next teaches the child to learn about caring relationships and supports language development. During this formative period it is critically important for caregivers to create a climate of care with healthy brain growth in mind. Simply stated, young children develop and function well when provided care in safe, interesting, and intimate settings where they establish and sustain secure and trusting relationships with knowledgeable caregivers who are responsive to their needs and interests (Lally 2006).

The infant brain is at once vulnerable and competent; both of these attributes need to be addressed simultaneously for healthy brain development. The vulnerable baby is dependent on relationships with adults for physical survival, emotional security, a safe base for learning, help with self-regulation, modeling and mentoring social behavior, and information and exchanges about the workings of the world and rules for living. Yet at the same time, the baby comes into the world with great competence as a curious, motivated, self-starting learner—an imitator, interpreter, integrator, inventor, explorer, communicator, meaning seeker, and relationship builder. For the brain to grow robustly, it needs a context of caring relationships that simultaneously provide emotional predictability for the baby’s vulnerable side and a climate of intellectual novelty for the competent side (Lally 2013).

Preconception and prenatal development

When do caring relationships start to influence the development of the brain? Earlier than most of us think. Although this article primarily focuses on relationships established during the time period from birth to age 3, the developing brain before birth—and even before conception—deserves some attention. (For more information on supporting growth during preconception and pregnancy, see chapters three and seven in For Our Babies: Ending the Invisible Neglect of America’s Infants [Lally 2013].)

A woman’s health and habits before becoming pregnant shape the development of the embryo. From at least three months before conception, the prospective mother’s food, drinks, drugs, toxins, stresses, and other experiences influence the early womb environment in which the brain develops; this may affect the child’s future learning. Since many women become pregnant while in poor health or while engaging in unhealthy habits, the connection between preconception (particularly from three months before conception to awareness of conception) and healthy brain development needs to be addressed (Atrash et al. 2006; Kent et al. 2006). In addition to a public education campaign for all citizens about the preconception risks to the development of the brain, the United States should provide a safety net of preconception services to women of childbearing age and universal screening for depression and other mental health issues.

Once conception occurs and brain development starts in the womb, the fetal environment may positively or negatively influence the developing brain. Brain growth is more rapid during this period of life than any other, with neurons being produced at an astonishing rate. The neurons then migrate to the area of the brain where they will reside for a person’s entire life, beginning to form connections and differentiate brain functions. Fetuses use information—such as the kind and amount of nutrients received, the stress experienced, and the languages and voices heard—to shape their brains and bodies to anticipate experiences once born. Just two-thirds of the way through pregnancy, a good portion of the basic wiring of the brain is already completed (Thompson 2010).

Birth to 9 months: Caring relationships and the brain during the attachment period

During the first stage of development outside the womb, much of babies’ initial attention focuses on forming and strengthening secure connections with their caregivers. Rather than passively receiving care, babies actively seek it out. They come into the world with physical skills and social competences that prepare them to play an active role in their development. They are wired to react to those around them in ways that elicit interest and increase the likelihood of contact and closeness (Marvin & Britner 2008). Based on the feedback babies receive from early exchanges, they direct attachment behaviors toward developing secure relationships with their primary caregivers. Research has shown that this attachment-seeking fits with the finding that during the first two years of brain development, emotional wiring is the dominant activity. The brain builds crucial structures and pathways of emotional functioning that serve as the base for attachment, future emotional and social activity, and the language and intellectual development that will follow (Schore 2000). In this earliest stage, babies start using messages from caregivers to develop perceptions of the extent to which they are loved. Infants then use these perceptions to create an initial working model for how to engage with others. Thus, the care babies receive during these early exchanges directly affects the quality of attachment they form with their caregivers and influences the emotional stance they will take in interactions with others.

Young babies need relationships with caregivers who are:

Sensitive to their needs and messages
Timely in responding (especially to messages of distress)
Accurate in the reading of their cues
Understanding of appropriate levels of stimulation (Bornstein 2012)

Seven to 18 months: Caring relationships and the brain during the exploration stage

Between 7 and 18 months of age, babies are driven to search out their local environment, objects, and people; to build a primitive definition of self; and to test the strength and use of relationships. Using their emerging motor skills to explore, they venture from the safety of the physical closeness of their caregivers and test the strength of relationships. They come and go while carefully observing their caregiver’s attentiveness and emotional availability. They are, in a sense, practicing independence (Calkins & Hill 2007; Eisenberg, Hofer, & Vaughan 2007). Also at this stage, babies’ brains are preparing for a life that does not revolve entirely around physical proximity to the caregiver. Based on their caregivers’ reactions to their actions, babies and toddlers begin to hold in mind lessons learned, such as which independent explorations are considered socially appropriate and which are not, and what activities are dangerous, like playing near an ungated stairway.

“I am listened to or no t.” “What I choose to do is valued or isn’t .” “How I express my emotions is accepted or isn’t .” “I am allowed to explore or not .” “Mostly my needs are met or not .”

The thoughts, emotions, and shared experiences that the developing brain processes in interactions with adults have a profound impact on the developing child’s self-perception and actions.

Fifteen to 36 months: Caring relationships and the brain during the self-definition stage

During the third stage, young children are developing an awareness of their separateness from their caregivers and peers as well as a sense of themselves as individuals (Vaughn, Kopp, & Krakow 1984). They begin to exhibit self-conscious emotions, are particularly sensitive to others’ judgments, feel shame and embarrassment easily when others critique their behaviors and appearance, and start to develop a conscience. This stage is also characterized by an explosion of brain growth in several areas of development (in addition to the emotional development that was dominant earlier). Intellectually, children hold ideas in their minds briefly, engage in pretend play, and become increasingly able to focus their attention on topics, people, and objects introduced by others. Their use of spoken language increases greatly. They use many new words and complex sentence structures. Children develop perceptual and motor skills that allow them to run fast, climb high, and hit hard—making the development of self-control especially important (Brownell & Kopp 2007).

Fortunately, this self-definition stage also brings the early emergence of executive function skills, which include the development of working memory, mental flexibility, and self-control (Center on the Developing Child 2012). These emerging skills influence all areas of development, increasing children’s capacity to explore and learn about their social environment—and to navigate conflicts with others. As children gain a clearer understanding of independent, separate interests, they realize they have choices, which is quite liberating. However, with choices—particularly those involving caregivers and peers—comes a dawning awareness of responsibility. This choice–responsibility tension is central to the drama of this stage. Once again, caring relationships play a prominent role in how the young brain becomes structured. How adults react during this tension filled period of life greatly affects how young children come to see their rights and others’ rights. Interactions children have with their caregivers, peers, and others shape their brains’ social and emotional future. What toddlers experience in their day-to-day lives forms their expectations for what constitutes appropriate behavior toward others (Barry & Kochanska 2010). These early experiences provide lessons for developing moral and ethical codes, gaining control of impulses and emotions, and learning and adapting to the rules of their family, culture, and society. As young children experience a growing sense of independence and self-control, their brains’ capacity to regulate their behavior continues to develop; but they still need guidance from adults, and this guidance most often comes through caring relationships.

Caring Behavior During the Stage of Self-Definition

The young brain needs adults to act in ways that honor the child’s rights to desire, hope, explore, and show preferences, while also helping the child learn to honor the similar rights of others. Although the child is growing older and more independent, the young brain remains vulnerable. Caring relationships, with clear rules for behavior that are consistently applied in reasoned ways, provide safety while the brain is still being formed, ensuring that individuation experiences and socialization lessons occur in a fair and predictable environment.

What we are learning from brain science helps us better understand the multiple factors that influence young children’s development and provides us with caregiving strategies that are in harmony with the developing brain. In essence, brain development is about the whole child, from the health of the mother to the child’s early experiences in the culture and language of their family, their community, and their early learning program. The foundation of brain development is social and emotional development grounded in caring relationships. If caregivers are mindful of how a child’s whole experience—particularly the emotional tenor—influences the developing brain, they can provide caring relationships that help the child feel secure and open up to an engaging world of exploration and learning throughout the early years.

Atrash, H.K., K. Johnson, M. Adams, J.F. Cordero, & J. Howse. 2006. “Preconception Care for Improving Perinatal Outcomes: The Time to Act.” Maternal and Child Health Journal 10 (Supplement 1): 3–11.

Barry, R.A., & G. Kochanska. 2010. “A Longitudinal Investigation of the Affective Environment in Families With Young Children: From Infancy to Early School Age.” Emotion 10 (2): 237–49.

Bornstein, M.H. 2012. “Caregiver Responsiveness and Child Development and Learning: From Theory to Research to Practice.” In Infant/Toddler Caregiving: A Guide to Cognitive Development and Learning , ed. P.L. Mangione, 2nd ed. Sacramento: California Department of Education.

Brownell, C.A., & C.B. Kopp. 2007. “Transitions in Toddler Socioemotional Development: Behavior, Understanding, Relationships.” Chap. 1 in Socioemotional Development in the Toddler Years: Transitions and Transformations , eds. C.A. Brownell & C.B Kopp, 66–69. New York: Guilford.

Calkins, S.D., & A. Hill. 2007. “Caregiver Influences on Emerging Emotion Regulation: Biological and Environmental Transactions in Early Development.” Chap. 11 in Handbook of Emotion Regulation , ed. J.J. Gross, 229–48. New York: Guilford.

Center on the Developing Child. 2007. The Impact of Early Adversity on Child Development (InBrief). http://developingchild.harvard.edu/resources/inbrief-the-impact-of-early... .

Center on the Developing Child. 2012. Executive Function (InBrief). http://developingchild.harvard.edu/resources/inbrief-executive-function .

Drury, S.S., K.P. Theall, A.T. Smyke, B.J. Keats, H.L. Egger, C.A. Nelson, N.A. Fox, P.J. Marshall, & C.H. Zeanah. 2010. “Modification of Depression by COMT val158met Polymorphism in Children Exposed to Early Severe Psychosocial Deprivation.” Child Abuse and Neglect 34 (6): 387–95.

Eisenberg, N., C. Hofer, & J. Vaughan. 2007. “Effortful Control and Its Socioemotional Consequences.” Chap. 14 in Handbook of Emotion Regulation , ed. J.J. Gross, 287–306. New York: Guilford.

Gopnik, A. 2016. The Gardener and the Carpenter: What the New Science of Child Development Tells Us About the Relationship Between Parents and Children . New York: Farrar, Straus, and Giroux.

Greenspan, S.I. 1990. “Emotional Development in Infants and Toddlers.” In Infant/Toddler Caregiving: A Guide to Social-Emotional Growth and Socialization , ed. J.R. Lally, 15–18. Sacramento: California Department of Education.

Hamburg, D.A. 1995. “President’s Essay: A Developmental Strategy to Prevent Lifelong Damage.” www.carnegie.org/media/filer_public/af/ae/afae9e53-c3c4-47db-a444-a2bfb7... .

IOM (Institute of Medicine) & NRC (National Research Council). 2015. Transforming the Workforce for Children Birth Through Age 8: A Unifying Foundation . Washington, DC: National Academies Press.

Kent, H., K. Johnson, M. Curtis, J.R. Hood, & H. Atrash. 2006. “Proceedings of the Preconception Health and Health Care Clinical, Public Health, and Consumer Workgroup Meetings.” Atlanta, GA: Centers for Disease Control and Prevention, National Center on Birth Defects and Developmental Disabilities. www.cdc.gov/preconception/documents/workgroupproceedingsjune06.pdf .

Lally, J.R. 2006. “Metatheories of Childrearing.” Chap. 2 in Concepts for Care: 20 Essays on Infant/Toddler Development and Learning , eds. J.R. Lally, P.L. Mangione, & D. Greenwald, 7–14. San Francisco: WestEd.

Lally, J.R. 2013. For Our Babies: Ending the Invisible Neglect of America’s Infants . New York: Teachers College Press.

Marvin, R.S., & P.A. Britner. 2008. “Normative Development: The Ontogeny of Attachment.” Chap. 12 in Handbook of Attachment: Theory, Research, and Clinical Applications , eds. J. Cassidy & P.R. Shaver, 2nd ed. New York: Guilford.

NRC (National Research Council) & IOM (Institute of Medicine). 2009. Preventing Mental, Emotional, and Behavioral Disorders Among Young People: Progress and Possibilities . Washington, DC: National Academies Press.

Pawl, J.H., & M. St. John. 1998. How You Are Is as Important as What You Do … in Making a Positive Difference for Infants, Toddlers, and Their Families . Washington, DC: ZERO TO THREE.

Schore, A.N. 2000. “Attachment and the Regulation of the Right Brain.” Attachment and Human Development 2 (1): 23–47.

Schore, A.N. 2003. Affect Dysregulation and Disorders of the Self . Norton Series on Interpersonal Neurobiology. New York: Norton.

Schore, A.N. 2005. “Attachment, Affect Regulation, and the Developing Right Brain: Linking Developmental Neuroscience to Pediatrics.” Pediatrics in Review 26 (6): 204–17.

Shonkoff, J.P., & D.A. Phillips, eds. 2000. From Neurons to Neighborhoods: The Science of Early Child Development . Washington, DC: National Academies Press.

Thompson, R.A. 2010. Connecting Neurons, Concepts, and People: Brain Development and Its Implications . Policy Facts series. New Brunswick, NJ: National Institute for Early Education Research, Rutgers Graduate School of Education.

Thompson, R.A. 2011. “The Emotional Child.” Chap. 2 in Minnesota Symposia on Child Psychology: The Origins and Organization of Adaptation and Maladaptation , eds. D. Cicchetti & G.I. Roisman. Hoboken, NJ: Wiley.

Vaughn, B.E., C.B. Kopp, & J.B. Krakow. 1984. “The Emergence and Consolidation of Self-Control From Eighteen to Thirty Months of Age: Normative Trends and Individual Differences.” Child Development 55 (3): 990–1004.

RELATED RESOURCES FROM NAEYC

Powerful Interactions: How to Connect With Children to Extend Their Learning

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Photographs: 1 © iStock; 2, 3, 4, 5, © WestEd

J. Ronald Lally, EdD, is the codirector of the Center for Child and Family Studies at WestEd, a research development and service agency based in San Francisco. He codirects the Program for Infant and Toddler Care and is one of the founders of ZERO TO THREE: National Center for Infants, Toddlers, and Families.

Peter Mangione, PhD, is codirector of the Center for Child and Family Studies, WestEd, in Sausalito, California. Peter is one of the principal developers of the Program for Infant/Toddler Care, a comprehensive approach to professional development of infant and toddler care teachers. [email protected]

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Parenting & Family Articles & More

Why reading is important for children’s brain development, children living in poverty show poorer brain development. but reading for pleasure may help counteract this..

Early childhood is a critical period for brain development , which is important for boosting cognition and mental well-being. Good brain health at this age is directly linked to better mental heath, cognition, and educational attainment in adolescence and adulthood. It can also provide resilience in times of stress.

But, sadly, brain development can be hampered by poverty. Studies have shown that early childhood poverty is a risk factor for lower educational attainment. It is also associated with differences in brain structure, poorer cognition, behavioral problems, and mental health symptoms.

This shows just how important it is to give all children an equal chance in life. But until sufficient measures are taken to reduce inequality and improve outcomes, our new study, published in Psychological Medicine , shows one low-cost activity that may at least counteract some of the negative effects of poverty on the brain: reading for pleasure.

Wealth and brain health

Higher family income in childhood tends to be associated with higher scores on assessments of language, working memory, and the processing of social and emotional cues. Research has shown that the brain’s outer layer, called the cortex, has a larger surface area and is thicker in people with higher socioeconomic status than in poorer people.

Being wealthy has also been linked with having more grey matter (tissue in the outer layers of the brain) in the frontal and temporal regions (situated just behind the ears) of the brain. And we know that these areas support the development of cognitive skills.

The association between wealth and cognition is greatest in the most economically disadvantaged families . Among children from lower-income families, small differences in income are associated with relatively large differences in surface area. Among children from higher-income families, similar income increments are associated with smaller differences in surface area.

Importantly, the results from one study found that when mothers with low socioeconomic status were given monthly cash gifts, their children’s brain health improved . On average, they developed more changeable brains (plasticity) and better adaptation to their environment. They also found it easier to subsequently develop cognitive skills.

Our socioeconomic status will even influence our decision making . A report from the London School of Economics found that poverty seems to shift people’s focus toward meeting immediate needs and threats. They become more focused on the present with little space for future plans—and also tended to be more averse to taking risks.

It also showed that children from low-socioeconomic-background families seem to have poorer stress coping mechanisms and feel less self-confident.

But what are the reasons for these effects of poverty on the brain and academic achievement? Ultimately, more research is needed to fully understand why poverty affects the brain in this way. There are many contributing factors that will interact. These include poor nutrition and stress on the family caused by financial problems. A lack of safe spaces and good facilities to play and exercise in, as well as limited access to computers and other educational support systems, could also play a role.

Reading for pleasure

There has been much interest of late in leveling up. So what measures can we put in place to counteract the negative effects of poverty that could be applicable globally?

Our observational study shows a dramatic and positive link between a fun and simple activity—reading for pleasure in early childhood—and better cognition, mental health, and educational attainment in adolescence.

We analyzed the data from the Adolescent Brain and Cognitive Development (ABCD) project, a U.S. national cohort study with more than 10,000 participants across different ethnicities and and varying socioeconomic status. The dataset contained measures of young adolescents ages nine to 13 and how many years they had spent reading for pleasure during their early childhood. It also included data on their cognitive health, mental health, and brain health.

About half of the group of adolescents started reading early in childhood, whereas the others, approximately half, had never read in early childhood, or had begun reading later on.

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We discovered that reading for pleasure in early childhood was linked with better scores on comprehensive cognition assessments and better educational attainment in young adolescence. It was also associated with fewer mental health problems and less time spent on electronic devices.

Our results showed that reading for pleasure in early childhood can be beneficial regardless of socioeconomic status. It may also be helpful regardless of the children’s initial intelligence level. That’s because the effect didn’t depend on how many years of education the children’s parents had had—which is our best measure for very young children’s intelligence (IQ is partially heritable).

We also discovered that children who read for pleasure had larger cortical surface areas in several brain regions that are significantly related to cognition and mental health (including the frontal areas). Importantly, this was the case regardless of socioeconomic status. The result therefore suggests that reading for pleasure in early childhood may be an effective intervention to counteract the negative effects of poverty on the brain.

While our current data was obtained from families across the United States, future analyses will include investigations with data from other countries—including developing countries, when comparable data become available.

So how could reading boost cognition exactly? It is already known that language learning, including through reading and discussing books, is a key factor in healthy brain development. It is also a critical building block for other forms of cognition, including executive functions (such as memory, planning, and self-control) and social intelligence.

Because there are many different reasons why poverty may negatively affect brain development, we need a comprehensive and holistic approach to improving outcomes. While reading for pleasure is unlikely, on its own, to fully address the challenging effects of poverty on the brain, it provides a simple method for improving children’s development and attainment.

Our findings also have important implications for parents, educators, and policymakers in facilitating reading for pleasure in young children. It could, for example, help counteract some of the negative effects on young children’s cognitive development of the COVID-19 pandemic lockdowns.

This article is republished from The Conversation under a Creative Commons license. Read the original article .

About the Authors

Barbara jacquelyn sahakian.

Barbara Jacquelyn Sahakian, Ph.D. , is a professor of clinical neuropsychology at the University of Cambridge.

Christelle Langley

Christelle Langley, Ph.D. , is a postdoctoral research associate in cognitive neuroscience at the University of Cambridge.

Jianfeng Feng

Jianfeng Feng, Ph.D. , is a professor of science and technology for brain-inspired intelligence/computer science at Fudan University.

Yun-Jun Sun

Yun-Jun Sun, Ph.D. , is a postdoctoral fellow at the Institute of Science and Technology for Brain-Inspired Intelligence at Fudan University.

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How People Learn: Brain, Mind, Experience, and School: Expanded Edition (2000)

Chapter: 10 conclusions, 10 conclusions.

The pace at which science proceeds sometimes seems alarmingly slow, and impatience and hopes both run high when discussions turn to issues of learning and education. In the field of learning, the past quarter century has been a period of major research advances. Because of the many new developments, the studies that resulted in this volume were conducted to appraise the scientific knowledge base on human learning and its application to education. We evaluated the best and most current scientific data on learning, teaching, and learning environments. The objective of the analysis was to ascertain what is required for learners to reach deep understanding, to determine what leads to effective teaching, and to evaluate the conditions that lead to supportive environments for teaching and learning.

A scientific understanding of learning includes understanding about learning processes, learning environments, teaching, sociocultural processes, and the many other factors that contribute to learning. Research on all of these topics, both in the field and in laboratories, provides the fundamental knowledge base for understanding and implementing changes in education.

This volume discusses research in six areas that are relevant to a deeper understanding of students’ learning processes: the role of prior knowledge in learning, plasticity and related issues of early experience upon brain development, learning as an active process, learning for understanding, adaptive expertise, and learning as a time-consuming endeavor. It reviews research in five additional areas that are relevant to teaching and environments that support effective learning: the importance of social and cultural contexts, transfer and the conditions for wide application of learning, subject matter uniqueness, assessment to support learning, and the new educational technologies.

LEARNERS AND LEARNING

Development and learning competencies.

Children are born with certain biological capacities for learning. They can recognize human sounds; can distinguish animate from inanimate objects; and have an inherent sense of space, motion, number, and causality. These raw capacities of the human infant are actualized by the environment surrounding a newborn. The environment supplies information, and equally important, provides structure to the information, as when parents draw an infant’s attention to the sounds of her or his native language.

Thus, developmental processes involve interactions between children’s early competencies and their environmental and interpersonal supports. These supports serve to strengthen the capacities that are relevant to a child’s surroundings and to prune those that are not. Learning is promoted and regulated by the children’s biology and their environments. The brain of a developing child is a product, at the molecular level, of interactions between biological and ecological factors. Mind is created in this process.

The term “development” is critical to understanding the changes in children’s conceptual growth. Cognitive changes do not result from mere accretion of information, but are due to processes involved in conceptual reorganization. Research from many fields has supplied the key findings about how early cognitive abilities relate to learning. These include the following:

“Privileged domains:” Young children actively engage in making sense of their worlds. In some domains, most obviously language, but also for biological and physical causality and number, they seem predisposed to learn.

Children are ignorant but not stupid: Young children lack knowledge, but they do have abilities to reason with the knowledge they understand.

Children are problem solvers and, through curiosity, generate questions and problems: Children attempt to solve problems presented to them, and they also seek novel challenges. They persist because success and understanding are motivating in their own right.

Children develop knowledge of their own learning capacities— metacognition—very early. This metacognitive capacity gives them the ability to plan and monitor their success and to correct errors when necessary.

Children’ natural capabilities require assistance for learning: Children’s early capacities are dependent on catalysts and mediation. Adults play a critical role in promoting children’s curiosity and persistence by directing children’s attention, structuring their experiences, supporting their

learning attempts, and regulating the complexity and difficulty of levels of information for them.

Neurocognitive research has contributed evidence that both the developing and the mature brain are structurally altered during learning. For example, the weight and thickness of the cerebral cortex of rats is altered when they have direct contact with a stimulating physical environment and an interactive social group. The structure of the nerve cells themselves is correspondingly altered: under some conditions, both the cells that provide support to the neurons and the capillaries that supply blood to the nerve cells may be altered as well. Learning specific tasks appears to alter the specific regions of the brain appropriate to the task. In humans, for example, brain reorganization has been demonstrated in the language functions of deaf individuals, in rehabilitated stroke patients, and in the visual cortex of people who are blind from birth. These findings suggest that the brain is a dynamic organ, shaped to a great extent by experience and by what a living being does.

Transfer of Learning

A major goal of schooling is to prepare students for flexible adaptation to new problems and settings. Students’ abilities to transfer what they have learned to new situations provides an important index of adaptive, flexible learning; seeing how well they do this can help educators evaluate and improve their instruction. Many approaches to instruction look equivalent when the only measure of learning is memory for facts that were specifically presented. Instructional differences become more apparent when evaluated from the perspective of how well the learning transfers to new problems and settings. Transfer can be explored at a variety of levels, including transfer from one set of concepts to another, one school subject to another, one year of school to another, and across school and everyday, nonschool activities.

People’s abilitiy to transfer what they have learned depends upon a number of factors:

People must achieve a threshold of initial learning that is sufficient to support transfer. This obvious point is often overlooked and can lead to erroneous conclusions about the effectiveness of various instructional approaches. It takes time to learn complex subject matter, and assessments of transfer must take into account the degree to which original learning with understanding was accomplished.

Spending a lot of time (“time on task”) in and of itself is not sufficient to ensure effective learning. Practice and getting familiar with subject matter take time, but most important is how people use their time while

learning. Concepts such as “deliberate practice” emphasize the importance of helping students monitor their learning so that they seek feedback and actively evaluate their strategies and current levels of understanding. Such activities are very different from simply reading and rereading a text.

Learning with understanding is more likely to promote transfer than simply memorizing information from a text or a lecture. Many classroom activities stress the importance of memorization over learning with understanding. Many, as well, focus on facts and details rather than larger themes of causes and consequences of events. The shortfalls of these approaches are not apparent if the only test of learning involves tests of memory, but when the transfer of learning is measured, the advantages of learning with understanding are likely to be revealed.

Knowledge that is taught in a variety of contexts is more likely to support flexible transfer than knowledge that is taught in a single context. Information can become “context-bound” when taught with context-specific examples. When material is taught in multiple contexts, people are more likely to extract the relevant features of the concepts and develop a more flexible representation of knowledge that can be used more generally.

Students develop flexible understanding of when, where, why, and how to use their knowledge to solve new problems if they learn how to extract underlying themes and principles from their learning exercises. Understanding how and when to put knowledge to use—known as conditions of applicability—is an important characteristic of expertise. Learning in multiple contexts most likely affects this aspect of transfer.

Transfer of learning is an active process. Learning and transfer should not be evaluated by “one-shot” tests of transfer. An alternative assessment approach is to consider how learning affects subsequent learning, such as increased speed of learning in a new domain. Often, evidence for positive transfer does not appear until people have had a chance to learn about the new domain—and then transfer occurs and is evident in the learner’s ability to grasp the new information more quickly.

All learning involves transfer from previous experiences. Even initial learning involves transfer that is based on previous experiences and prior knowledge. Transfer is not simply something that may or may not appear after initial learning has occurred. For example, knowledge relevant to a particular task may not automatically be activated by learners and may not serve as a source of positive transfer for learning new information. Effective teachers attempt to support positive transfer by actively identifying the strengths that students bring to a learning situation and building on them, thereby building bridges between students’ knowledge and the learning objectives set out by the teacher.

Sometimes the knowledge that people bring to a new situation impedes subsequent learning because it guides thinking in wrong directions.

For example, young children’s knowledge of everyday counting-based arithmetic can make it difficult for them to deal with rational numbers (a larger number in the numerator of a fraction does not mean the same thing as a larger number in the denominator); assumptions based on everyday physical experiences can make it difficult for students to understand physics concepts (they think a rock falls faster than a leaf because everyday experiences include other variables, such as resistance, that are not present in the vacuum conditions that physicists study), and so forth. In these kinds of situations, teachers must help students change their original conceptions rather than simply use the misconceptions as a basis for further understanding or leaving new material unconnected to current understanding.

Competent and Expert Performance

Cognitive science research has helped us understand how learners develop a knowledge base as they learn. An individual moves from being a novice in a subject area toward developing competency in that area through a series of learning processes. An understanding of the structure of knowledge provides guidelines for ways to assist learners acquire a knowledge base effectively and efficiently. Eight factors affect the development of expertise and competent performance:

Relevant knowledge helps people organize information in ways that support their abilities to remember.

Learners do not always relate the knowledge they possess to new tasks, despite its potential relevance. This “disconnect” has important implications for understanding differences between usable knowledge (which is the kind of knowledge that experts have developed) and less-organized knowledge, which tends to remain “inert.”

Relevant knowledge helps people to go beyond the information given and to think in problem representations, to engage in the mental work of making inferences, and to relate various kinds of information for the purpose of drawing conclusions.

An important way that knowledge affects performances is through its influences on people’s representations of problems and situations. Different representations of the same problem can make it easy, difficult, or impossible to solve.

The sophisticated problem representations of experts are the result of well-organized knowledge structures. Experts know the conditions of applicability of their knowledge, and they are able to access the relevant knowledge with considerable ease.

Different domains of knowledge, such as science, mathematics, and history, have different organizing properties. It follows, therefore, that to

have an in-depth grasp of an area requires knowledge about both the content of the subject and the broader structural organization of the subject.

Competent learners and problem solvers monitor and regulate their own processing and change their strategies as necessary. They are able to make estimates and “educated guesses.”

The study of ordinary people under everyday cognition provides valuable information about competent cognitive performances in routine settings. Like the work of experts, everyday competencies are supported by sets of tools and social norms that allow people to perform tasks in specific contexts that they often cannot perform elsewhere.

Conclusions

Everyone has understanding, resources, and interests on which to build. Learning a topic does not begin from knowing nothing to learning that is based on entirely new information. Many kinds of learning require transforming existing understanding, especially when one’s understanding needs to be applied in new situations. Teachers have a critical role in assisting learners to engage their understanding, building on learners’ understandings, correcting misconceptions, and observing and engaging with learners during the processes of learning.

This view of the interactions of learners with one another and with teachers derives from generalizations about learning mechanisms and the conditions that promote understanding. It begins with the obvious: learning is embedded in many contexts. The most effective learning occurs when learners transport what they have learned to various and diverse new situations. This view of learning also includes the not so obvious: young learners arrive at school with prior knowledge that can facilitate or impede learning. The implications for schooling are many, not the least of which is that teachers must address the multiple levels of knowledge and perspectives of children’s prior knowledge, with all of its inaccuracies and misconceptions.

Effective comprehension and thinking require a coherent understanding of the organizing principles in any subject matter; understanding the essential features of the problems of various school subjects will lead to better reasoning and problem solving; early competencies are foundational to later complex learning; self-regulatory processes enable self-monitoring and control of learning processes by learners themselves.

Transfer and wide application of learning are most likely to occur when learners achieve an organized and coherent understanding of the material; when the situations for transfer share the structure of the original

learning; when the subject matter has been mastered and practiced; when subject domains overlap and share cognitive elements; when instruction includes specific attention to underlying principles; and when instruction explicitly and directly emphasizes transfer.

Learning and understanding can be facilitated in learners by emphasizing organized, coherent bodies of knowledge (in which specific facts and details are embedded), by helping learners learn how to transfer their learning, and by helping them use what they learn.

In-depth understanding requires detailed knowledge of the facts within a domain. The key attribute of expertise is a detailed and organized understanding of the important facts within a specific domain. Education needs to provide children with sufficient mastery of the details of particular subject matters so that they have a foundation for further exploration within those domains.

Expertise can be promoted in learners. The predominant indicator of expert status is the amount of time spent learning and working in a subject area to gain mastery of the content. Secondarily, the more one knows about a subject, the easier it is to learn additional knowledge.

TEACHERS AND TEACHING

The portrait we have sketched of human learning and cognition emphasizes learning for in-depth comprehension. The major ideas that have transformed understanding of learning also have implications for teaching.

Teaching for In-Depth Learning

Traditional education has tended to emphasize memorization and mastery of text. Research on the development of expertise, however, indicates that more than a set of general problem-solving skills or memory for an array of facts is necessary to achieve deep understanding. Expertise requires well-organized knowledge of concepts, principles, and procedures of inquiry. Various subject disciplines are organized differently and require an array of approaches to inquiry. We presented a discussion of the three subject areas of history, mathematics, and science learning to illustrate how the structure of the knowledge domain guides both learning and teaching.

Proponents of the new approaches to teaching engage students in a variety of different activities for constructing a knowledge base in the subject domain. Such approaches involve both a set of facts and clearly defined principles. The teacher’s goal is to develop students’ understanding of a given topic, as well as to help them develop into independent and thoughtful problem solvers. One way to do this is by showing students that they already have relevant knowledge. As students work through different prob-

lems that a teacher presents, they develop their understanding into principles that govern the topic.

In mathematics for younger (first- and second-grade) students, for example, cognitively guided instruction uses a variety of classroom activities to bring number and counting principles into students’ awareness, including snack-time sharing for fractions, lunch count for number, and attendance for part-whole relationships. Through these activities, a teacher has many opportunities to observe what students know and how they approach solutions to problems, to introduce common misconceptions to challenge students’ thinking, and to present more advanced discussions when the students are ready.

For older students, model-based reasoning in mathematics is an effective approach. Beginning with the building of physical models, this approach develops abstract symbol system-based models, such as algebraic equations or geometry-based solutions. Model-based approaches entail selecting and exploring the properties of a model and then applying the model to answer a question that interests the student. This important approach emphasizes understanding over routine memorization and provides students with a learning tool that enables them to figure out new solutions as old ones become obsolete.

These new approaches to mathematics operate from knowledge that learning involves extending understanding to new situations, a guiding principle of transfer ( Chapter 3 ); that young children come to school with early mathematics concepts ( Chapter 4 ); that learners cannot always identify and call up relevant knowledge (Chapters 2 , 3 , and 4 ); and that learning is promoted by encouraging children to try out the ideas and strategies they bring with them to school-based learning ( Chapter 6 ). Students in classes that use the new approaches do not begin learning mathematics by sitting at desks and only doing computational problems. Rather, they are encouraged to explore their own knowledge and to invent strategies for solving problems and to discuss with others why their strategies work or do not work.

A key aspect of the new ways of teaching science is to focus on helping students overcome deeply rooted misconceptions that interfere with learning. Especially in people’s knowledge of the physical, it is clear that prior knowledge, constructed out of personal experiences and observations— such as the conception that heavy objects fall faster than light objects—can conflict with new learning. Casual observations are useful for explaining why a rock falls faster than a leaf, but they can lead to misconceptions that are difficult to overcome. Misconceptions, however, are also the starting point for new approaches to teaching scientific thinking. By probing students’ beliefs and helping them develop ways to resolve conflicting views, teachers can guide students to construct coherent and broad understandings of scientific concepts. This and other new approaches are major break-

throughs in teaching science. Students can often answer fact-based questions on tests that imply understanding, but misconceptions will surface as the students are questioned about scientific concepts.

Chèche Konnen (“search for knowledge” in Haitian Creole) was presented as an example of new approaches to science learning for grade school children. The approach focuses upon students’ personal knowledge as the foundations of sense-making. Further, the approach emphasizes the role of the specialized functions of language, including the students’ own language for communication when it is other than English; the role of language in developing skills of how to “argue” the scientific “evidence” they arrive at; the role of dialogue in sharing information and learning from others; and finally, how the specialized, scientific language of the subject matter, including technical terms and definitions, promote deep understanding of the concepts.

Teaching history for depth of understanding has generated new approaches that recognize that students need to learn about the assumptions any historian makes for connecting events and schemes into a narrative. The process involves learning that any historical account is a history and not the history. A core concept guiding history learning is how to determine, from all of the events possible to enumerate, the ones to single out as significant. The “rules for determining historical significance” become a lightening rod for class discussions in one innovative approach to teaching history. Through this process, students learn to understand the interpretative nature of history and to understand history as an evidentiary form of knowledge. Such an approach runs counter to the image of history as clusters of fixed names and dates that students need to memorize. As with the Chèche Konnen example of science learning, mastering the concepts of historical analysis, developing an evidentiary base, and debating the evidence all become tools in the history toolbox that students carry with them to analyze and solve new problems.

Expert Teachers

Expert teachers know the structure of the knowledge in their disciplines. This knowledge provides them with cognitive roadmaps to guide the assignments they give students, the assessments they use to gauge student progress, and the questions they ask in the give-and-take of classroom life. Expert teachers are sensitive to the aspects of the subject matter that are especially difficult and easy for students to grasp: they know the conceptual barriers that are likely to hinder learning, so they watch for these tell-tale signs of students’ misconceptions. In this way, both students’ prior knowledge and teachers’ knowledge of subject content become critical components of learners’ growth.

Subject-matter expertise requires well-organized knowledge of concepts and inquiry procedures. Similarly, studies of teaching conclude that expertise consists of more than a set of general methods that can be applied across all subject matter. These two sets of research-based findings contradict the common misconception about what teachers need to know in order to design effective learning environments for students. Both subject-matter knowledge and pedagogical knowledge are important for expert teaching because knowledge domains have unique structures and methods of inquiry associated with them.

Accomplished teachers also assess their own effectiveness with their students. They reflect on what goes on in the classroom and modify their teaching plans accordingly. Thinking about teaching is not an abstract or esoteric activity. It is a disciplined, systematic approach to professional development. By reflecting on and evaluating one’s own practices, either alone or in the company of a critical colleague, teachers develop ways to change and improve their practices, like any other opportunity for learning with feedback.

Teachers need expertise in both subject matter content and in teaching.

Teachers need to develop understanding of the theories of knowledge (epistemologies) that guide the subject-matter disciplines in which they work.

Teachers need to develop an understanding of pedagogy as an intellectual discipline that reflects theories of learning, including knowledge of how cultural beliefs and the personal characteristics of learners influence learning.

Teachers are learners and the principles of learning and transfer for student learners apply to teachers.

Teachers need opportunities to learn about children’s cognitive development and children’s development of thought (children’s epistemologies) in order to know how teaching practices build on learners’ prior knowledge.

Teachers need to develop models of their own professional development that are based on lifelong learning, rather than on an “updating” model of learning, in order to have frameworks to guide their career planning.

LEARNING ENVIRONMENTS

Tools of technology.

Technology has become an important instrument in education. Computer-based technologies hold great promise both for increasing access to knowledge and as a means of promoting learning. The public imagination has been captured by the capacity of information technologies to centralize and organize large bodies of knowledge; people are excited by the prospect of information networks, such as the Internet, for linking students around the globe into communities of learners.

There are five ways that technology can be used to help meet the challenges of establishing effective learning environments:

Bringing real-world problems into classrooms through the use of videos, demonstrations, simulations, and Internet connections to concrete data and working scientists.

Providing “scaffolding” support to augment what learners can do and reason about on their path to understanding. Scaffolding allows learners to participate in complex cognitive performances, such as scientific visualization and model-based learning, that is more difficult or impossible without technical support.

Increasing opportunities for learners to receive feedback from software tutors, teachers, and peers; to engage in reflection on their own learning processes; and to receive guidance toward progressive revisions that improve their learning and reasoning.

Building local and global communities of teachers, administrators, students, parents, and other interested learners.

Expanding opportunities for teachers’ learning.

An important function of some of the new technologies is their use as tools of representation. Representational thinking is central to in-depth understanding and problem representation is one of the skills that distinguish subject experts from novices. Many of the tools also have the potential to provide multiple contexts and opportunities for learning and transfer, for both student-learners and teacher-learners. Technologies can be used as learning and problem-solving tools to promote both independent learning and collaborative networks of learners and practitioners.

The use of new technologies in classrooms, or the use of any learning aid for that matter, is never solely a technical matter. The new electronic technologies, like any other educational resource, are used in a social environment and are, therefore, mediated by the dialogues that students have with each other and the teacher.

Educational software needs to be developed and implemented with a full understanding of the principles of learning and developmental psychology. Many new issues arise when one considers how to educate teachers to use new technologies effectively: What do they need to know about learning processes? What do they need to know about the technologies? What kinds of training are most effective for helping teachers use high-quality instructional programs? Understanding the issues that affect teachers who will be using new technologies is just as pressing as questions of the learning potential and developmental appropriateness of the technologies for children.

Assessment to Support Learning

Assessment and feedback are crucial for helping people learn. Assessment that is consistent with principles of learning and understanding should:

Mirror good instruction.

Happen continuously, but not intrusively, as a part of instruction.

Provide information (to teachers, students, and parents) about the levels of understanding that students are reaching.

Assessment should reflect the quality of students’ thinking, as well as what specific content they have learned. For this purpose, achievement measurement must consider cognitive theories of performance. Frameworks that integrate cognition and context in assessing achievement in science, for example, describe performance in terms of the content and process task demands of the subject matter and the nature and extent of cognitive activities likely to be observed in a particular assessment situation. The frameworks provide a basis for examining performance assessments that are designed to measure reasoning, understanding, and complex problem solving.

The nature and purposes of an assessment also influence the specific cognitive activities that are expressed by the student. Some assessment tasks emphasize a particular performance, such as explanation, but deemphasize others, such as self-monitoring. The kind and quality of cognitive activities observed in an assessment situation are functions of the content and process demands of the tasks involved. Similarly, the task demands for process skills can be conceived along a continuum from constrained to open. In open situations, explicit directions are minimized in order to see how students generate and carry out appropriate process skills as they solve problems. Characterizing assessments in terms of components of competence and the content and process demands of the subject matter brings specificity to assessment objectives, such as “higher level thinking” and “deep understanding.” This approach links specific content with the

underlying cognitive processes and the performance objectives that the teacher has in mind. With articulated objectives and an understanding of the correspondence between task features and cognitive activities, the content and process demands of tasks are brought into alignment with the performance objectives.

Effective teachers see assessment opportunities in ongoing classroom learning situations. They continually attempt to learn about students’ thinking and understanding and make it relevant to current learning tasks. They do a great deal of on-line monitoring of both group work and individual performances, and they attempt to link current activities to other parts of the curriculum and to students’ daily life experiences.

Students at all levels, but increasingly so as they progress through the grades, focus their learning attention and energies on the parts of the curriculum that are assessed. In fact, the art of being a good student, at least in the sense of getting good grades, is tied to being able to anticipate what will be tested. This means that the information to be tested has the greatest influence on guiding students’ learning. If teachers stress the importance of understanding but then test for memory of facts and procedures, it is the latter that students will focus on. Many assessments developed by teachers overemphasize memory for procedures and facts; expert teachers, by contrast, align their assessment practices with their instructional goals of depth-of-understanding.

Learning and Connections to Community

Outside of formal school settings, children participate in many institutions that foster their learning. For some of these institutions, promoting learning is part of their goals, including after-school programs, as in such organizations as Boy and Girl Scout Associations and 4–H Clubs, museums, and religious education. In other institutions or activities, learning is more incidental, but learning takes place nevertheless. These learning experiences are fundamental to children’s—and adults’ —lives since they are embedded in the culture and the social structures that organize their daily activities. None of the following points about the importance of out-of-school learning institutions, however, should be taken to deemphasize the central role of schools and the kinds of information that can be most efficiently and effectively taught there.

A key environment for learning is the family. In the United States, many families hold a learning agenda for their children and seek opportunities for their children to engage with the skills, ideas, and information in their communities. Even when family members do not focus consciously on instructional roles, they provide resources for children’s learning that are relevant to school and out-of-school ideas through family activities, the funds of

knowledge available within extended families and their communities, and the attitudes that family members display toward the skills and values of schooling.

The success of the family as a learning environment, especially in the early years, has provided inspiration and guidance for some of the changes recommended in schools. The rapid development of children from birth to ages 4 or 5 is generally supported by family interactions in which children learn by observing and interacting with others in shared endeavors. Conversations and other interactions that occur around events of interest with trusted and skilled adults and child companions are especially powerful environments for learning. Many of the recommendations for changes in schools can be seen as extensions of the learning activities that occur within families. In addition, recommendations to include families in classroom activities and educational planning hold promise of bringing together two powerful systems for supporting children’s learning.

Classroom environments are positively influenced by opportunities to interact with parents and community members who take interest in what they are doing. Teachers and students more easily develop a sense of community as they prepare to discuss their projects with people who come from outside the school and its routines. Outsiders can help students appreciate similarities and differences between classroom environments and everyday environments; such experiences promote transfer of learning by illustrating the many contexts for applying what they know.

Parents and business leaders represent examples of outside people who can have a major impact on student learning. Broad-scale participation in school-based learning rarely happens by accident. It requires clear goals and schedules and relevant curricula that permit and guide adults in ways to help children learn.

Designing effective learning environments includes considering the goals for learning and goals for students. This comparison highlights the fact that there are various means for approaching goals of learning, and furthermore, that goals for students change over time. As goals and objectives have changed, so has the research base on effective learning and the tools that students use. Student populations have also shifted over the years. Given these many changes in student populations, tools of technology, and society’s requirements, different curricula have emerged along with needs for new pedagogical approaches that are more child-centered and more culturally sensitive, all with the objectives of promoting effective learning and adaptation (transfer). The requirement for teachers to meet such a diversity of challenges also illustrates why assessment needs to be a tool to help teach-

ers determine if they have achieved their objectives. Assessment can guide teachers in tailoring their instruction to individual students’ learning needs and, collaterally, inform parents of their children’s progress.

Supportive learning environments, which are the social and organizational structures in which students and teachers operate, need to focus on the characteristics of classroom environments that affect learning; the environments as created by teachers for learning and feedback; and the range of learning environments in which students participate, both in and out of school.

Classroom environments can be positively influenced by opportunities to interact with others who affect learners, particularly families and community members, around school-based learning goals.

New tools of technology have the potential of enhancing learning in many ways. The tools of technology are creating new learning environments, which need to be assessed carefully, including how their use can facilitate learning, the types of assistance that teachers need in order to incorporate the tools into their classroom practices, the changes in classroom organization that are necessary for using technologies, and the cognitive, social, and learning consequences of using these new tools.

First released in the Spring of 1999, How People Learn has been expanded to show how the theories and insights from the original book can translate into actions and practice, now making a real connection between classroom activities and learning behavior. This edition includes far-reaching suggestions for research that could increase the impact that classroom teaching has on actual learning.

Like the original edition, this book offers exciting new research about the mind and the brain that provides answers to a number of compelling questions. When do infants begin to learn? How do experts learn and how is this different from non-experts? What can teachers and schools do-with curricula, classroom settings, and teaching methods—to help children learn most effectively? New evidence from many branches of science has significantly added to our understanding of what it means to know, from the neural processes that occur during learning to the influence of culture on what people see and absorb.

How People Learn examines these findings and their implications for what we teach, how we teach it, and how we assess what our children learn. The book uses exemplary teaching to illustrate how approaches based on what we now know result in in-depth learning. This new knowledge calls into question concepts and practices firmly entrenched in our current education system.

Topics include:

How learning actually changes the physical structure of the brain.
How existing knowledge affects what people notice and how they learn.
What the thought processes of experts tell us about how to teach.
The amazing learning potential of infants.
The relationship of classroom learning and everyday settings of community and workplace.
Learning needs and opportunities for teachers.
A realistic look at the role of technology in education.

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September 4, 2023

Reading for Pleasure Helps Kids’ Brain Development

The simple and fun act of reading for pleasure in early childhood produces better cognition, mental health and educational attainment in adolescence

By Barbara Jacquelyn Sahakian , Christelle Langley , Jianfeng Feng , Yun-Jun Sun & The Conversation US

A small child sits barefoot on chair in yard reading a book in Spring

Cavan Images/Getty Images

The following essay is reprinted with permission from The Conversation , an online publication covering the latest research.

Early childhood is a critical period for brain development , which is important for boosting cognition and mental wellbeing. Good brain health at this age is directly linked to better mental heath, cognition and educational attainment in adolescence and adulthood. It can also provide resilience in times of stress.

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Wealth and brain health

Higher family income in childhood tends to be associated with higher scores on assessments of language, working memory and the processing of social and emotional cues. Research has shown that the brain’s outer layer, called the cortex, has a larger surface are and is thicker in people with higher socioeconomic status than in poorer people.

The association between wealth and cognition is greatest in the most economically disadvantaged families . Among children from lower income families, small differences in income are associated with relatively large differences in surface area. Among children from higher income families, similar income increments are associated with smaller differences in surface area.

Our socioeconomic status will even influence our decision-making . A report from the London School of Economics found that poverty seems to shift people’s focus towards meeting immediate needs and threats. They become more focused on the present with little space for future plans - and also tended to be more averse to taking risks.

It also showed that children from low socioeconomic background families seem to have poorer stress coping mechanisms and feel less self-confident.

But what are the reasons for these effects of poverty on the brain and academic achievement? Ultimately, more research is needed to fully understand why poverty affects the brain in this way. There are many contributing factors which will interact. These include poor nutrition and stress on the family caused by financial problems. A lack of safe spaces and good facilities to play and exercise in, as well as limited access to computers and other educational support systems, could also play a role.

Reading for pleasure

There has been much interest of late in levelling up. So what measures can we put in place to counteract the negative effects of poverty which could be applicable globally?

Our observational study shows a dramatic and positive link between a fun and simple activity – reading for pleasure in early childhood – and better cognition, mental health and educational attainment in adolescence.

We analysed the data from the Adolescent Brain and Cognitive Development (ABCD) project, a US national cohort study with more than 10,000 participants across different ethnicities and and varying socioeconomic status. The dataset contained measures of young adolescents ages nine to 13 and how many years they had spent reading for pleasure during their early childhood. It also included data on their cognitive, mental health and brain health.

About half of the group of adolescents starting reading early in childhood, whereas the other, approximately half, had never read in early childhood, or had begun reading late on.

Our results showed that reading for pleasure in early childhood can be beneficial regardless of socioeconomic status. It may also be helpful regardless of the children’s initial intelligence level. That’s because the effect didn’t depend on how many years of education the children’s parents had had – which is our best measure for very young children’s intelligence (IQ is partially heritable).

While our current data was obtained from families across the United States, future analyses will include investigations with data from other countries – including developing countries, when comparable data become available.

Our findings also have important implications for parents, educators and policy makers in facilitating reading for pleasure in young children. It could, for example, help counteract some of the negative effects on young children’s cognitive development of the COVID-19 pandemic lockdowns.

This article was originally published on The Conversation . Read the original article .

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J Can Acad Child Adolesc Psychiatry
v.20(4); 2011 Nov

Language: English | French

Brain Plasticity and Behaviour in the Developing Brain

1 Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Alberta

Robbin Gibb

To review general principles of brain development, identify basic principles of brain plasticity, and discuss factors that influence brain development and plasticity.

A literature review of relevant English-language manuscripts on brain development and plasticity was conducted.

Brain development progresses through a series of stages beginning with neurogenesis and progressing to neural migration, maturation, synaptogenesis, pruning, and myelin formation. Eight basic principles of brain plasticity are identified. Evidence that brain development and function is influenced by different environmental events such as sensory stimuli, psychoactive drugs, gonadal hormones, parental-child relationships, peer relationships, early stress, intestinal flora, and diet.

Conclusions:

Résumé

Présenter les grandes lignes du développement cérébral; expliquer le principe de la plasticité du cerveau; exposer les facteurs qui influencent son développement et sa plasticité.

Méthodologie:

Analyse de la littérature publiée en anglais sur le développement et la plasticité du cerveau.

Résultats:

Le cerveau se développe par étapes, la première étant la neurogénèse, suivie de la migration des neurones, de la maturation, de la synaptogénèse, de l’élagage synaptique et de la myélinisation. Les auteurs présentent huit principes fondamentaux de la plasticité du cerveau. Ils constatent que le développement et le fonctionnement du cerveau sont influencés par divers facteurs environnementaux comme les stimuli sensoriels, les substances psychoactives, les hormones gonadales, les relations parent-enfant, les relations avec les pairs, le stress dans la petite enfance, la flore intestinale et le régime alimentaire.

Conclusion:

Le développement du cerveau va au-delà de la construction de la carte génétique; certaines interactions complexes entre facteurs génétiques et expérimentaux agissent sur le cerveau en formation. Comprendre ces interactions permettra d’étudier le développement normal ou anormal du cerveau.

The development of the brain reflects more than the simple unfolding of a genetic blueprint but rather reflects a complex dance of genetic and experiential factors that shape the emerging brain. Brains exposed to different environmental events such as sensory stimuli, drugs, diet, hormones, or stress thus may develop in very different ways. The goal of the current article is to review the ways the developing brain can be sculpted by a wide range of pre- and postnatal factors. We begin with an overview of brain development, followed by a brief review of principles of brain plasticity and finally a consideration of how factors influence brain development and adult behaviour. Because most of what we know about brain plasticity and behaviour in development comes from studies of the laboratory rat our discussion will focus on the rat but will consider humans when possible. In addition, the discussion will be biased towards plasticity in cerebral structures because most of what we know about modulation of brain development is based upon studies of cerebral development. There is little reason to believe, however, that other brain structures will not be changed in similar ways.

Brain Development

Some 2000 years ago the Roman philosopher Seneca proposed that a human embryo is an adult in miniature and thus the task of development is simply to grow bigger. This idea was so appealing that it was widely believed until well into the 19 th century. It became obvious in the early 20 th century that brain development reflected a series of stages that we can now see as being broadly divided into two phases. In most mammals the first reflects a genetically determined sequence of events in utero that can be modulated by maternal environment. The second phase, which is both preand postnatal in humans, is a time when the connectivity of the brain is very sensitive not only to the environment but also to the patterns of brain activity produced by experiences. More importantly, however, it is now recognized that epigenetic changes, which can be defined as changes in developmental outcomes, including regulation of gene expression, are based upon mechanisms other than DNA itself ( Blumberg, Freeman, & Robinson, 2010 ). For example, gene expression can be altered by specific experiences, and this in turn can lead to organizational changes in the nervous system.

Stages of brain development

Table 1 outlines the general stages characteristic of brain development in all mammals. Cells that are destined to produce the nervous system begin to form about three weeks after fertilization in humans. These cells form the neural tube, which is the brain’s nursery and is later called the subventricular zone. Cells that are destined to form the cerebrum begin division at about six weeks of age and by about 14 weeks the cerebrum looks distinctly human, although it does not begin to form sulci and gyri until about seven months. Most neurogenesis is complete by five months, with one important exception being cells in the hippocampus, which continues to form neurons throughout life. There are about ten billion cells needed to form the human cerebral cortex in each hemisphere. These cells are formed rapidly and it is estimated that at its peak, there are about 250,000 neurons formed per minute. It is obvious that any brain perturbation at this time could have significant consequences.

Once the neurons are formed, they begin to migrate along fibrous pathways formed by radial glial cells, which extend from the subventricular zone to the surface of the cerebral cortex ( Figure 1 ). The subventriucular zone appears to contain a primitive map of the cortex that predisposes the cells formed in a particular subventricular region to migrate to a certain cortical location. As cells migrate they have an unlimited cell-fate potential but as they reach their destination the interaction of genes, maturation, and environmental influences increasingly steer them toward differentiating into a particular cell type. Once cells reach their final destination they begin to mature by: (1) growing dendrites to provide surface area for synapses with other cells; and, (2) extending axons to appropriate targets to initiate synapse formation.

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Object name is ccap20_4p265f1.jpg

Cells migrate from the subventricular zone along radial glia to their eventual adult location ( Kolb & Whishaw, 2009 ).

The formation of dendrites begins prenatally in humans but continues for a long time after birth. Dendrites in newborn babies begin as individual processes protruding from the cell body and over the next two years these processes are elaborated and spines, which are the location of most excitatory synapses, are formed. Dendritic growth is slow, on the order of micrometers per day. Axons grow about 1000 times faster, namely about one mm per day. This differential growth rate is important because the faster growing axons can contact target cells before the dendrites of that cell are completely formed. As a result, axons can influence dendritic differentiation and the formation of cerebral circuits.

Synapse formation in the human cerebral cortex poses a formidable challenge, with a total of more than 100,000 trillion (10 14 ). This enormous number could not possibly be determined by a genetic program, but rather only the general outlines of neural connections in the brain will be genetically predetermined. The vast array of synapses is thus guided into place by a variety of environmental cues and signals. As we shall see, the manipulation of different types of cues and signals can produce dramatic differences in cerebral circuitry.

Owing to the uncertainty in the number of neurons that will reach their appropriate destination and the appropriateness of the connections that they form, the brain overproduces both neurons and connections during development, with the peak of synapse formation being between one and two years, depending upon the region of cortex. Just like a sculptor who creates a statue with a block of stone and a chisel to remove the unwanted pieces, the brain has a parallel system in which unneeded cells and connections are removed by cell death and synaptic pruning. The metaphorical chisels in the brain can be of many forms, including some type of epigenetic signal, a wide range of experiences, gonadal hormones, and even stress.

The effect of this cell loss and synaptic pruning can be seen in changes in cortical thickness over time. That is, the cortex actually becomes measurably thinner in a caudal-rostral gradient beginning around age two and continuing until at least 20 years of age. It is possible to correlate cortical thinning with behavioral development. For example, the results of MRI studies of changes in cortical thickness have shown that increased motor dexterity is associated with a decrease in cortical thickness in the hand region of the left motor cortex in right-handers ( O’Hare & Sowell, 2008 ). One exception to the thinner is better rule is seen in the development of some, but not all, language processes. Thus, MRI studies have shown a thickening of the left inferior frontal cortex (roughly Broca’s area) is associated with enhanced phonological processing (i.e., the understanding of speech sounds). This unique association between cortical thickness and behavior is not characteristic of language functions in general, however. For example, vocabulary development is correlated with decreased cortical thickness in diffuse cortical regions ( O’Hare & Sowell, 2008 ).

The relation between cortical thickness and behavioural development is likely an explanation for the variance in the development of behavioural skills in children. For example, the delayed development of language in children with normal intelligence and motor dexterity (about 1% of children) could be the result of slower than normal changes in cortical thickness. Why this might be is unknown.

The final stage of brain development is glial development to form myelin. The birth of astrocytes and oligodendrocytes begins after most neurogenesis is complete and continues throughout life. Although CNS axons can function before myelination, normal adult function is attained only after myelination is complete, which is after 18 years of age in regions such as the prefrontal, posterior parietal, and anterior temporal cortex.

Brain development, therefore, is composed of a cascade of events beginning with mitosis and ending with myelin formation. The effect of brain perturbations and experiences will therefore vary with the precise stage of brain development. We should not be surprised, for example, that experiences and/or perturbations during mitosis would have quite different effects than similar events during synaptogenesis or later during pruning. Experiences are essentially acting on very different brains at different stages of development.

Special features of brain development

Two features of brain development are especially important for understanding how experiences can modify cortical organization. First, the cells lining the subventricular zone are stem cells that remain active throughout life. These stem cells can produce neural or glial progenitor cells that can migrate into the cerebral white or gray matter, even in adulthood. These cells can remain quiescent in these locations for extended periods but can be activated to produce either neurons and/or glia. The role of these cells is poorly understood at present but they likely form the basis of at least one form of postnatal neurogenesis, especially after injury (e.g., Gregg, Shingo, & Weiss, 2001 ; Kolb et al., 2007 ). In addition, the mammalian brain, including the primate brain, can generate neurons in adulthood that are destined for the olfactory bulb, hippocampal formation, and possibly other regions (e.g., Eriksson et al., 1998 ; Gould, Tanapat, Hastings, & Shors, 1999 ; Kempermann & Gage, 1999 ). The functional role of these cells is still controversial but their generation can be influenced by many factors including experience, drugs, hormones, and injury.

The second special feature is that dendrites and spines show remarkable plasticity in response to experience and can form synapses in hours and possibly even minutes after some experiences (e.g., Greenough & Chang, 1989 ). On the surface, this would appear to be at odds with the process of overproduction of synapses followed by synaptic pruning described earlier. A key point is that although synaptic pruning is an important feature of brain development, the brain does continue to form synapses throughout the lifetime and in fact these synapses are necessary for learning and memory processes. Greenough, Black and Wallace (1987) have argued that there is a fundamental difference between the processes governing the formation of synapses in early brain development and those during later brain development and adulthood. Specifically, they argue that the early forming synapses are “expecting” experiences, which act to prune them back. They call these synapses “experience-expectant” and note that they are found diffusely throughout the cerebrum. In contrast, later synapse formation is more focal and localized to regions involved in processing specific experiences. They label these synapses as “experience-dependent.” One curious aspect of experience-dependent effects on synapses is that not only do specific experiences lead to selective synapse formation but also to selective synaptic loss. Thus, experiences are changing neural networks by both adding and pruning synapses. This leads us to the issue of brain plasticity.

General Principles of Plasticity in Normal Brain

Before we address the experiences that influence brain plasticity, we must briefly review several key principles of plasticity in the normal brain.

1. Changes in the brain can be shown at many levels of analysis

A change in behavior must certainly result from some change in the brain but there are many ways to investigate such changes. Changes may be inferred from global measures of brain activity, such as in the various forms of in vivo imaging, but such changes are far removed from the molecular processes that drive them. Global changes presumably reflect synaptic changes but synaptic changes result from more molecular changes such as modifications in channels, gene expression, and so on. The problem in studying brain plasticity is to choose a surrogate marker that best suits the question being asked. Changes in calcium channels may be perfect for studying synaptic changes at specific synapses that might be related to simple learning but are impractical for understanding sex differences in language processing. The latter might best be studied by in vivo imaging or postmortem analysis of cell morphology (e.g., Jacobs & Scheibel, 1993 ). The appropriate level must be targeted at the research question at hand. Studies investigating strategies for stimulating functional improvement after injury most commonly use anatomical (cell morphology and connectivity), physiological (cortical stimulation), and in vivo imaging. Each of these levels can be linked to behavioral outcomes in both human and nonhuman studies whereas more molecular levels have proven to be much more difficult to relate to behavior, and especially mental behavior.

2. Different measures of neuronal morphology change independently of each other and sometimes in opposite directions

There has been a tendency in the literature to see different neuronal changes as surrogates for one another. One of the most common is to assume that changes in spine density reflect changes in dendritic length and vice versa. This turns out not to be the case as the two measures can vary independently and sometimes in opposite directions (e.g., Comeau, McDonald, & Kolb, 2010 ; Kolb, Cioe, & Comeau, 2008 ). Furthermore, cells in different cortical layers, but in the same presumptive columns, can show very different responses to the same experiences (e.g., Teskey, Monfils, Silasi, & Kolb, 2006 ).

3. Experience-dependent changes tend to be focal

Although there is a tendency to think of plastic changes in response to experiences as being widespread across the brain, this is rarely the case. For example, psychoactive drugs may produce large behavioural changes and have widespread acute effects on neurons, but the chronic plastic changes are surprisingly focal and largely confined to the prefrontal cortex and nucleus accumbens (e.g., Robinson & Kolb, 2004 ). As a result, researchers need to carefully think about where the best places are to look after specific experiences. A failure to find synaptic changes that correlate with behavioural change is not evidence of the absence of changes.

4. Plastic changes are time-dependent

Perhaps the largest changes in synaptic organization can be seen in response to placing lab animals in complex (so-called “enriched”) environments. Thus, there are widespread changes throughout sensory and motor cortex. These changes appear to defy the principle of experience-dependent changes being focal but the generality of the changes is likely due to the global nature of the experiences including experiences as diffuse as visual, tactile, auditory, olfactory, motor, and social experiences. But these plastic changes are not all permanent and they may change dramatically over time.

For example, when rats are placed in complex environments there is a transient increase in dendritic length in the prefrontal cortex that can be seen after four days of complex housing but has disappeared after 14 days. In contrast, there are no obvious changes in sensory cortex after four days but clear, and seemingly permanent, changes after 14 days ( Comeau et al., 2010 ).

The possibility that there are different chronic and transient experience-dependent changes in cerebral neurons is consistent with genetic studies showing that there are different genes expressed acutely and chronically in response to complex environments (e.g. Rampon et al., 2000 ). The difference in how transient and persistent changes in neuronal networks relate to behavior is unknown.

5. Experience-dependent changes interact

Humans have a lifetime of experiences beginning prenatally and continuing until death. These experiences interact. For example, we have shown in laboratory rats that if animals are exposed to psychomotor stimulants either as juveniles or in adulthood, later experiences have a much-attenuated (or sometimes absent) effect. For example, when rats are given methylphenidate as juveniles or amphetamine as adults and then sometime later are placed in complex environments or trained on learning tasks, the later experience-dependent changes are blocked. What is surprising is that although the drugs do not show any obvious direct effect on sensory cortical regions, prior exposure prevents the expected changes in these regions (e.g., Kolb, Gibb, & Gorny, 2003a ). These drug-experience interactions are not unidirectional however. When pregnant rats are given a mild stressor for 20 minutes twice a day during the period of maximal cerebral neurogenesis in their offspring (embryonic days 12–18), their offspring show stress-related changes in spine density in the prefrontal cortex (PFC) but no drug-related effects ( Muhammad & Kolb, in press a ). It is not clear why there is a complete absence of drug-related effects or what this will mean for addiction but it does show that experiences interact in their effects on the brain.

7. Plastic changes are age-dependent

It is generally presumed that the developing brain will be more responsive to experiences than the adult or senescent brain. This is most certainly correct but there is another important wrinkle: there are qualitatively different changes in the brain in response to what appears to be the same experience at different ages. For example, when weanling, adult, or senescent rats were placed in a complex environment, all groups showed large synaptic changes but they were surprisingly different. Specifically, whereas we anticipated an increase in spine density in response to complex housing, this was only true in adult and senescent rats. Rats placed in the environments as juveniles showed a decrease in spine density ( Kolb et al., 2003a ). A similar drop in spine density was found in later studies in which newborn rats were given tactile stimulation with a soft brush for 15 minutes, three times daily over the first ten days of life but not if the stimulation is in adulthood ( Gibb, Gonzalez, Wagenest, & Kolb, 2010 ; Kolb & Gibb, 2010 ). The age-dependent nature of synaptic change is clearly important for understanding how experiences change the brain.

8. Not all plasticity is good

Although the general gist of the literature is that plastic changes in the brain support improved motor and cognitive functions, plastic changes can interfere with behavior too. A good example is the drug-induced changes seen in response to psychomotor stimulants (e.g., Robinson & Kolb, 2004 ). It is reasonable to propose that some of the maladaptive behavior of drug addicts could result from drug-related changes in prefrontal neuronal morphology. There are many other examples of pathological plasticity including pathological pain ( Baranauskas, 2001 ), pathological response to sickness ( Raison, Capuron, & Miller, 2006 ), epilepsy ( Teskey, 2001 ), schizophrenia ( Black et al., 2004 ), and dementia ( Mattson, Duan, Chan, & Guo, 2001 ).

Although there are not many studies of pathological plasticity in the developing brain, an obvious example is fetal alcohol spectrum disorder. Another example is the effects of severe prenatal stress, which has been shown to markedly reduce the complexity of neurons in the prefrontal cortex (e.g., Murmu et al., 2006 ) and in turn can affect normal cognitive and motor functions both in development and in adulthood (e.g., Halliwell, 2011 ). Although the mechanisms underlying these changes are poorly understood it is known that early postnatal stress can alter gene expression in the brain ( Weaver et al., 2004 ; Weaver, Meaney, & Szf, 2006 ).

Factors Influencing Brain Development

When researchers began to study experience-dependent changes in the developing brain in the 1950s and 1960s, there was a natural assumption that changes in brain development would only be obvious in response to rather large changes in experience, such as being raised in darkness. Over the past 20 years it has become clear that even fairly innocuous-looking experiences can profoundly affect brain development and that the range of experiences that can alter brain development is much larger than had been once believed (see Table 2 ). We will highlight some of the most well-studied effects.

Factors influencing brain development and function

1. Sensory and motor experiences

The simplest way to manipulate experience across ages is to compare brain structure in animals living in standard laboratory caging to animals placed either in severely impoverished environments or so-called enriched environments. Raising animals in deprived environments such as in darkness, silence, or social isolation clearly retards brain development. For example, dog puppies raised alone show a wide range of behavioural abnormalities, including a virtual insensitivity to painful experiences ( Hebb, 1949 ). Similarly, raising animals as diverse as monkeys, cats, and rodents in the dark severely interferes with development of the visual system. Perhaps the best-known deprivation studies are those of Weisel and Hubel (1963) who sutured one eyelid of kittens closed and later showed that when the eye was opened there was an enduring loss of spatial vision (amblyopia) (e.g., Giffin & Mitchell, 1978 ). It has only been recently, however, that investigators considered the opposite phenomenon, namely giving animals enriched visual experiences to determine if vision could be enhanced. In one elegant study, Prusky et al. ( Prusky, Silver, Tschetter, Alam, & Douglas, 2008 ) used a novel form of visual stimulation in which rats were placed in a virtual optokinetic system in which vertical lines of differing spatial frequency moved past the animal. If the eyes are open and oriented towards the moving grating, it is impossible for animals, including humans, to avoid tracking the moving lines, if the spatial frequency is within the perceptual range. The authors placed animals in the apparatus for about two weeks following the day of eye opening (postnatal day 15). When tested for visual acuity in adulthood, the animals showed about a 25% enhancement in visual acuity relative to animals without the early treatment. The beauty of the Prusky study is that improved visual function was not based upon specific training, such as in learning a problem, but occurred naturally in response to enhanced visual input.

We have attempted to enhance tactile experience using a procedure first devised by Schanberg and Field (1987) . In these studies infant rats were given tactile stimulation with a small brush for 15 minutes three times per day for 10–15 days beginning at birth. When the infants were studied in adulthood they showed both enhanced skilled motor performance and spatial learning as well as changes in synaptic organization across the cerebral cortex (e.g., Kolb & Gibb, 2010 ). Although the precise mechanism of action of the tactile stimulation is not known, we have shown that the tactile stimulation leads to an increase in the production of a neurotrophic factor, fibroblast growth factor-2 (FGF-2) in both skin and brain ( Gibb, 2004 ). FGF-2 is known to play a role in normal brain development and can stimulate recovery from perinatal brain injury (e.g., Comeau, Hastings, & Kolb, 2007 ). FGF-2 expression is also increased in response to a variety of treatments including enriched housing and psychoactive drugs, both of which stimulate plastic changes in the brain (see below).

Another way to enhance sensory and motor functions is to place animals in complex environments in which there is an opportunity for animals to interact with a changing sensory and social environment and to engage in far more motor activity than regular caging. Such studies have identified a large range of neural changes associated with this form of “enrichment.” These include increases in brain size, cortical thickness, neuron size, dendritic branching, spine density, synapses per neuron, glial numbers and complexity, and vascular arborization (e.g. Greenough & Chang, 1989 ; Siervaag & Greenough, 1987 ). The magnitude of these changes should not be underestimated. For example, in our own studies of the effects of housing young rats for 60 days in enriched environments, we reliably observe changes in overall brain weight on the order of 7–10% (e.g., Kolb, 1995 ). This increase in brain weight reflects increases in the number of glia and blood vessels, neuron soma size, dendritic elements, and synapses. It would be difficult to estimate the total number of increased synapses but it is probably on the order of 20% in the cortex, which is an extraordinary change. Importantly, although such studies show experience-dependent changes at any age, there are two unexpected wrinkles. First, adult rats at any age show a large increase in dendritic length and spine density across most of the cerebral cortex whereas juvenile rats show a similar increase in dendritic length but a decrease in spine density. That is, the young animals show a qualitatively different change in the distribution of synapses on pyramidal neurons compared to older animals ( Kolb et al., 2003a ). Second, when pregnant dams were placed in complex environments for eight hours a day prior to their pregnancy and then throughout the three-week gestation, analysis of the adult brains of their infants showed a decrease in dendritic length and an increase in spine density. Thus, not only is there an effect of prenatal experience but the effect was qualitatively different from experience either in the juvenile period or in adulthood. Curiously, all of the changes in response to the complex housing lead to enhanced cognitive and motor functions.

There are three clear messages from these studies. First, a wide range of sensory and motor experiences can produce long-lasting plastic changes in the brain. Second, the same experience can alter the brain differently at different ages. Third, there is no simple relationship between the details of synaptic plasticity and behaviour during development. What is certain, however, is that these early experiences have a powerful effect on brain organization both during development and in adulthood.

2. Psychoactive drugs

It has long been known that early exposure to alcohol is deleterious for brain development, but it has only recently been shown that other psychoactive drugs, including prescription drugs, can dramatically alter brain development. Robinson and Kolb (2004) found that exposure to psychomotor stimulants in adulthood produced large changes in the structure of cells in PFC and nucleus accumbens (NAcc). Specifically, whereas these drugs (amphetamine, cocaine, nicotine) produced increases in dendritic length and spine density in medial prefrontal cortex (mPFC) and NAcc, there was either a decrease in these measures in orbital frontal cortex (OFC), or in some cases, no change. They subsequently showed that virtually every class of psychoactive drugs also produces changes in PFC, and that the effects are consistently different in the two prefrontal regions. Given that the developing brain is often exposed to psychoactive drugs, either in utero or during postnatal development, we asked what effects these drugs would have on cortical development.

Our first studies looked at the effects of amphetamine or methylphenidate given during the juvenile period (e.g., Diaz, Heijtz, Kolb, & Forssberg, 2003 ). Both drugs altered the organization of the PFC. The dendritic changes were associated with abnormal play behaviour in the drug-treated rats, as they displayed reduced play initiation compared to saline-treated playmates as well as impaired performance on a test of working memory. Psychomotor stimulants thus appear to alter the development of the PFC and this is manifested in behavioural abnormalities on prefrontal-related behaviours later in life.

Children may also be exposed to prescription medications either in utero or postnatally. Three commonly prescribed classes of drugs are antipsychotics, antidepressants, and anxiolytics. All three have dramatic effects on cortical development. Frost, Cerceo, Carroll, and Kolb (2009) analyzed dendritic architecture in adult mice treated with paradigmatic typical- (haloperidol) or atypical (olanzapine) antipsychotic drugs at developmental stages corresponding to fetal (postnatal days 3–10) or fetal and early childhood (postnatal days 3–20) stages in humans. Both drugs produced reductions in dendritic length, dendritic branching complexity, and spine density in both medial prefrontal and orbital cortex. In a subsequent study using rats the authors showed impairments in PFC-related neuropsychological tasks such as working memory.

In a parallel set of studies we have looked at the effect of prenatal exposure to diazepam or fluoxetine in rats ( Kolb, Gibb, Pearce, & Tanguay, 2008 ). Both drugs affected brain and behavioural development, but in opposite ways. Prenatal diazepam increased dendritic length and spine density in pyramidal cells in the parietal cortex and this was associated with enhanced skilled motor functions. In contrast, fluoxetine decreased dendritic measures and this was correlated with impaired spatial learning deficits in adulthood.

One additional question is whether early exposure to psychoactive drugs might alter brain plasticity later in life. We had previously shown that if adult rats are given amphetamine, cocaine, or nicotine and then later placed in complex environments, neuronal plasticity was blocked ( Hamilton & Kolb, 2005 ; Kolb, Gorny, Samaha, & Robinson, 2003b ). In a subsequent study we gave juvenile rats methylphenidate and then in adulthood we placed these animals in complex environments and, once again, we found that the early drug exposure blocked the expected experience-dependent changes in the cortex ( Comeau & Kolb, 2011 ). Furthermore, in a parallel study we showed that juvenile methylphenidate exposure impaired performance on neuropsychological tasks sensitive to prefrontal functioning.

In sum, exposure to both prescription drugs and drugs of abuse has a profound effect on prefrontal development and prefrontal-related behaviours. These effects appear to be long lasting or permanent and can influence brain plasticity in adulthood. The unexpected serious effects of prescription drugs on brain and behavioral development are undoubtedly important in human infant brain development. It is clearly not a simple call on whether pregnant mothers with serious depression, psychosis, or anxiety-disorders should be prescribed medications given that these behavioral conditions are likely to affect brain development in the infant and especially to the extent that there are pathological mother-infant interactions. The research does suggest, however, that such medications should be used in as low an effective dose as can be used and not simply for their “calming” effects on mothers with mild anxiety.

3. Gonadal hormones

The most obvious effect of exposure to gonadal hormones during development is the differentiation of genitals that begins prenatally. In this case the production of testosterone by males leads to the development of male genitalia. Later in life, both estrogen and testosterone affect receptors in many regions of the body, including the brain. MRI studies of human brain development have shown large differences in the rate of brain development in the two sexes ( O’Hare & Sowell, 2008 ). Specifically, the total volume of brain reaches asymptote in females around age 11 and 15 in males and females respectively. But there is more to sexual dimorphism in brain than rate of maturation. For example, Kolb and Stewart (1991) showed in rats that neurons in the mPFC had larger dendritic fields in males and that neurons in OFC had larger cells in females. These differences vanished when animals were gonadectomized at birth. Similarly, Goldstein et al. (2001) did a comprehensive evaluation of the volume of 45 different brain regions from MRI scans of healthy adult subjects. There were sex differences in volume, relative to total cerebral volume, and this was especially true in PFC: females had a relatively larger volume of dorsolateral PFC whereas males had a relatively larger volume of OFC. This sexual dimorphism is correlated with relatively high regional levels of sex steroid receptors during early life in laboratory animals. It thus appears in both humans and laboratory animals that gonadal hormones alter cortical development. This is particularly important when we consider that the effects of other experiences such as exposure to complex housing or psychomotor stimulants are also sexually dimorphic. It seems likely that many other developmental experiences may differentially alter the female and male brains, although few studies have actually made this comparison.

4. Parent-child relationships

Mammalian infants that are born in an immature state face a significant challenge in early life. They are dependent upon their parents and they must learn to identify, remember, and prefer their caregivers. Although we now know that young animals (and even prenatal animals) can learn more than previously recognized (see review by Hofer & Sullivan, 2008 ), there is little doubt that the parent-child relationships are critical and that they play a key role in brain development. Differences in the pattern of early maternal-infant interactions can initiate long-term developmental effects that persist into adulthood ( Myers, Brunelli, Squire, Shindledecker, & Hofer, 1989 ). For example, rodent studies have shown that the time spent in contact, the amount of maternal licking and grooming, and the time the mothers spend in a highly stimulating high-arched resting position correlate with a variety of somatic and behavioural differences. Over the past decade Meaney and his colleagues (e.g. Cameron et al., 2005 ) have been able to show these rodent maternal-infant interactions systematically modify the development of the hypothalamic-adrenal stress response and a variety of emotional and cognitive behaviours in adulthood. These changes are correlated with changes in hippocampal cell membrane corticosterone receptors, which in turn are controlled by changes in gene expression ( Weaver et al., 2006 ).

The effects of variations in maternal care are not restricted to the hippocampus, however, and may be quite widespread. For example, Fenoglio, Chen and Barum (2006) have shown that enhanced maternal care during the first week of life produced enduring changes in cell signaling pathways in the hypothalamus and amgydala (also see review by Fenoglio, Bruson, & Barum, 2006 ).

We are unaware of similar studies looking at neocortical, and especially prefrontal, plasticity in response to differences in maternal-infant interactions, but such changes seem likely. We have shown, for example, that daily maternal separation, which is the procedure that was used to increase maternal-infant interactions in the Fenoglio et al. (2006) study, does increase dendritic length and spine density in both mPFC and OFC in adult rats ( Muhammad & Kolb, 2011 ).

5. Peer relationships

Peer relationships have been known to influence adult behavior since the studies of Harlow (e.g., Harlow & Harlow, 1965 ). One of the most powerful peer relationships is play, which has been shown to be important for the development of adult social competence (e.g., Pellis & Pellis, 2010 ). The frontal lobe plays an essential role in play behaviour. An infant injury to the mPFC and OFC compromise play behavior, although in different ways (e.g., Pellis et al., 2006 ). In view of such results, we hypothesized that the development, and subsequent functioning, of the two prefrontal regions would be differentially altered if play behaviour was manipulated in development. Juvenile rats were thus given the opportunity to play with 1 or 3 adult rats or with 1 or 3 other juvenile animals. There was virtually no play with the adult animals but play behaviour was increased the more juvenile animals that were present. Analysis of cells in the PFC showed that neurons of the OFC responded to the number of peers present, and not whether or not play occurred, whereas the neurons of mPFC responded to the amount of play but not the number of conspecifics ( Bell, Pellis, & Kolb, 2010 ). We have subsequently shown in a series of studies that a variety of early experiences alter rat play behaviour, including prenatal stress, postnatal tactile stimulation, and juvenile exposure to methylphenidate (e.g., Muhammad, Hossain, Pellis, & Kolb, 2011 ) and, in each case, there are abnormalities in prefrontal development. There may be an important lesson here when we consider conditions in which human childhood play is not normal, such as in autism or attention-deficit hyperactivity disorder (ADHD). The abnormalities in play behaviour may influence prefrontal development and later adult behaviour.

6. Early stress

There is enormous literature collected over the past 60 years showing the effects of stress on brain and behaviour in adults but it is only more recently that the role of perinatal stress in infants has been appreciated. It is now known that both gestational and infant stress predisposes individuals for a variety of maladaptive behaviours and psychopathologies. For example, prenatal stress is a risk factor in the development of schizophrenia, ADHD, depression, and drug addiction ( Anda et al., 2006 ; van den Bergh & Marcoen, 2004 ). Experimental studies with lab animals have confirmed these findings with the overall results being that perinatal stress, in rodents as well as non-human primates, produced behavioural abnormalities such as elevated and prolonged stress response, impaired learning and memory, deficits in attention, altered exploratory behaviour, altered social and play behaviour, and an increased preference for alcohol (e.g., review by Weinstock, 2008 ).

The plastic changes in the synaptic organization of brains of perinatally-stressed animals are less well studied, however, and the effects appear to be related to the details of the stressful experience. For example, Murmu et al. (2006) reported that moderate prenatal stress during the third week of gestation resulted in decreased spine density and dendritic length in both the mPFC and OFC of adult degus. In contrast, Muhammad & Kolb (2011) found that mild prenatal stress during the second week of gestation decreased spine density in mPFC but had no effect in OFC and increased spine density in NAcc of adult rats. Analysis of dendritic length showed a somewhat different pattern as there was an increase in dendritic length in mPFC and NAcc but a decrease in OFC. Curiously, Mychasiuk, Gibb and Kolb (2011) found that mild stress during the second gestational week increased spine density in both mPFC and OFC when the brains were examined in juvenile, rather than adult rats. Taken together these studies show that differences in the timing of prenatal stress and the age at which the brain is examined result in differing plastic changes in neuronal circuits. One thing that is clear, however, is that the effects of prenatal stress appear to be different from those of adult stress. For example, Liston et al. (2006) first showed that adult stress led to a decrease in dendritic branching and spine density in mPFC but an increase in OFC.

We are aware of only one study looking at the effects of early postnatal stress (maternal separation) on synaptic organization in adult brains. Thus, Muhammad & Kolb (2011) found that maternal separation increased spine density in mPFC, OFC, and NAcc in adult rats. What is yet to be determined following either prenatal or infant stress is how these differences in synaptic changes relate to later behaviour or how plastic the neurons will be in response to other experiences such as complex housing, play, or infant-parent relationships. Such studies are sure to be the grist of future studies.

7. Intestinal flora

Immediately after birth, mammals are rapidly populated by a variety of indigenous microbes. These microbes influence development of many body functions. For example, gut microbiota have systemic effects on liver function (e.g., Björkholm et al., 2009 ). Because there is a known relation between neurodevelopmental disorders such as autism and schizophrenia and microbioal pathogen infections during the perinatal period (e.g., Finegold et al., 2002 ; Mittal, Ellman, & Cannon, 2008 ), Diaz Heijtz et al. (in press) wondered if such infections could alter brain and behavioural development. They do. The authors compared measures of both motor behaviour and brain in mice that developed with or without normal gut mircrobiota. The authors found that gut bacteria influence signaling pathways, neurotransmitter turnover, and the production of synaptic-related proteins in cortex and striatum in developing mice and these changes were associated with changes in motor functions. This is an exciting finding because it provides insight into the way that infections during development could alter brain development and subsequent adult behaviour.

There is extensive literature on the effects of protein and/or caloric restricted diets on brain and behavioural development (e.g., Lewis, 1990 ) but much less is known about the effects of enhanced diets on brain development. It is generally presumed that the body heals better when it is given good nutrition so it is reasonable to predict that brain development might be facilitated by vitamin and/or mineral supplements. Dietary choline supplementation during the perinatal period produces a variety of changes both to behavior and brain ( Meck & Williams, 2003 ). For example, perinatal choline supplementation leads to enhanced spatial memory in various spatial navigation tests (e.g., Meck & Williams, 2003 ; Tees, & Mohammadi, 1999 ) and increases the levels of nerve growth factor (NGF) in the hippocampus and neocortex (e.g., Sandstrom, Loy, & Williams, 2002 ). Halliwell, Tees and Kolb (2011) did similar studies and found that choline supplementation increased dendritic length across the cerebral cortex and in hippocampal CA1 pyramidal neurons.

Halliwell (2011) has also studied the effects of the addition of a vitamin/mineral supplement to the food of lactating rats. She chose to use a diet supplement that has been reported to improve mood and aggression in adults and adolescents with various disorders ( Leung, Wiens & Kaplan, 2011 ) and decreased anger, activity levels and social withdrawal in autism with an increase in spontaneity ( Mehl-Madrona, Leung, Kennedy, Paul, & Kaplan, 2010 ). Analysis of the adult offspring of lactating rats fed the same supplement found an increase in dendritic length in neurons in mPFC and parietal cortex but not in OFC. In addition, the diet was effective in reversing the effects of mild prenatal stress on the reduction of dendritic length in OFC.

Much is left to be learned about the effects of both dietary restriction and supplementation on the development of neuronal networks and behaviour. Both procedures do alter brain development but as in many of the other factors discussed here, we do not have a clear picture of how the early experiences will interact with later experiences, such as psychoactive drugs, to alter brain and behaviour.

Conclusions

Our understanding of the nature of normal brain development has advanced a long way in the past 30 years but we are just beginning to understand some of the factors that modulate this development. Understanding this modulation will be essential for us to begin to unravel the puzzles of neurodevelopmental disorders and to initiate early treatments to block or reverse pathological changes. An obvious complication is that experiences are not singular events but rather as we go through life, experiences interact to alter both behaviour and brain, a process often referred to as metaplasticity.

As we discussed the various experience-dependent changes in the developing brain we have used the “developing brain” as though it were a single time. This is obviously not so and there is little doubt that we will eventually find that there are critical windows of time in which the developing brain is more (or less) responsive than at other times. In addition, it is likely that different cerebral regions will show different critical windows. We have found, for example, that if the motor cortex is injured in early adolescence there is a poor outcome relative to the same injury at late adolescence ( Nemati & Kolb, 2010 ). Curiously, however, the reverse is true for injury to the prefrontal cortex. Sorting out the areal-dependent critical windows will be a challenge for the next decade.

We have focused here on measures of synaptic plasticity but we certainly recognize that plastic changes in brain organization can be studied at many other levels. Ultimately the fundamental mechanism of synaptic change will be found in gene expression. The difficulty is that it is likely that experiences that alter behaviour significantly will be related to changes in dozens or hundreds of genes. The challenge is to identify the changes that are most closely associated with the observed behavioural changes.

Acknowledgements / Conflicts of Interest

We wish to thank both NSERC and CIHR for their long-term support for the studies related to our work discussed in this review. We also thank Cathy Carroll, Wendy Comeau, Dawn Danka, Grazyna Gorny, Celeste Halliwell, Richelle Mychasiuk, Arif Muhammad, and Kehe Xie for their many contributions to the studies.

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Introductory essay

Written by the educators who created Mapping and Manipulating the Brain, a brief look at the key facts, tough questions and big ideas in their field. Begin this TED Study with a fascinating read that gives context and clarity to the material.

Here is this mass of jelly, three-pound mass of jelly you can hold in the palm of your hand, and it can contemplate the vastness of interstellar space. It can contemplate the meaning of infinity and it can contemplate itself contemplating on the meaning of infinity. VS Ramachandran

The brain may well be our body's most mysterious organ. Unbelievably complex, utterly fascinating, and notoriously difficult to study, we're left wondering: What exactly does the brain do and how does it do it?

Despite two centuries of intensive research, supported in recent decades by impressive technological advances, answers to many of our questions about the brain are still distant. The reason is easy to appreciate: the brain contains more than ten billion cells — a number equivalent to the total human population on Earth — interacting with each other through about 1,000 times as many connections. Imagine that what's going on in your brain is like a shrunk-down version of the global human population interacting through the Internet. The Internet is hard enough to understand even though we created it; now imagine trying to understand a process of similar complexity without the benefit of knowing how it was generated!

As you listen to these TEDTalks and expand your study of neuroscience through other sources, remember that although we might now know a great deal more about the brain than we did at the start of the 19th century, it's a tiny fraction of what there is to know. Bear in mind that many current ideas may prove wrong. Indeed, it's the excitement of generating and testing, and trying to prove or disprove ideas that might explain the great unknown inside our heads that motivates many research neuroscientists around the world.

A brief history of brain science

The Egyptians wrote the first known descriptions of the brain and its anatomy about 3700 years ago, but another 1200 years elapsed before Greek philosophers of the Hippocratic School identified the brain as the organ responsible for our cognitive functions. Around 400 B.C., Hippocrates declared, "Men ought to know that from the brain, and from the brain only, arise our pleasures, joy, laughter and jests, as well as our sorrows, pains, griefs, and tears." However, not everyone agreed: although Plato and Hippocrates thought that the brain was responsible for sensation, intelligence and mental processes, Aristotle believed it was the heart.

Over the next 2500 years, the work of great European intellectuals including Galen of Bergama, Leonardo da Vinci and Rene Descartes improved our understanding of the brain. By the start of the 19th century, the brain's importance as the organ of perception and higher mental function was beyond doubt.

In the early 1800s, scientists made an important conceptual breakthrough when they hypothesized that different brain functions are carried out in specific and distinct brain regions. Brain regionalization, a concept central to several of the TEDTalks we'll watch, remains an important though controversial component of modern neuroscience.

Some of the initial models of brain regionalization were severely misguided, mainly because they were built on little or no evidence. For example, the Viennese physician Franz Joseph Gall (1758-1828) became convinced for the flimsiest of reasons that each of mankind's mental faculties, including our moral and intellectual capabilities, are each controlled by a separate "organ" within the cerebral hemispheres of the brain. The pseudo-science of phrenology that grew out of Gall's claims gained an enormous popular following in the 19th century; advocates believed that skilled practitioners could feel the lumps and bumps on an individual's skull to gain information about the underlying "organs" and thus fully describe the individual's personality and mental abilities.

Although phrenology is now discredited, the fundamental idea that different functions are localized to different areas of the brain turned out to have merit — even if Gall got the details wrong. The story of phrenology also provides a salutary lesson on the dangers of accepting popular beliefs about aspects of brain function and dysfunction that are difficult to critically evaluate through scientific experimentation. Even today, it's common to find that people think they know more than it's currently possible to know about how and why brains work or go wrong; for example, the causes and cures for various types of mental illness, which may contribute to the social stigma that surrounds these conditions.

Through the late 19th and early 20th centuries, scientists including Pierre Paul Broca, Carl Wernicke, Korbinian Brodmann and Wilder Penfield found credible scientific evidence supporting the subdivision of the brain into discrete areas with different specific functions. Their work was based on studies of patients with localized lesions of the brain, of the anatomical differences between different parts of the brain and of the effects of stimulating discrete brain regions on bodily actions. Together, scientists such as these laid the foundations of modern neuroscience. As you watch the TEDTalks in Mapping and Manipulating the Brain , notice how the speakers reference some of the same approaches used by Broca, Wernicke, Brodmann and Penfield, and how they apply the concepts of brain regionalization and localization of function . Bear in mind, however, that although these concepts are useful, they're also controversial -- more on this below.

How brains are built

Spanish scientist Santiago Ramón Y Cajal (1852-1934) is often thought of as the father of modern neuroscience. Through his extensive and beautiful studies of the microscopic structure of the brain, he discovered that the neuron is the fundamental unit of the nervous system. Since Ramón Y Cajal's breakthrough, scientists have sought to understand how the billions of neurons in the brain are organized to support so many complex functions.

This daunting task would likely be easier if we could follow the process by which the brain is generated, but following brain development is very difficult to do in humans. Thus, we often have to infer how the human brain develops by studying the developing brains of other species, so-called "model organisms" selected for their particular advantages in certain experimental procedures. Aside from helping us to work out how the adult brain functions, research on brain development is a major area in neuroscience for other reasons as well. For example, many conditions like schizophrenia and autism can be traced back to abnormalities in earlier brain development.

The great molecular, structural and functional diversity of brain cells, along with their specializations and precise interactions, are acquired in an organized way through processes that build on differences between the relatively small numbers of cells in the early embryo. As more and more cells are generated in a growing organism, new cells diversify in specific ways as a result of interactions with pre-existing cells, continually adding to the organism's complexity in a highly regulated manner. To understand how brains develop we need to know how their cells develop in specific and reproducible ways as a result of their own internal mechanisms interacting with an expanding array of stimuli from outside the cell.

Since, as discussed above, regionalization is a prominent organizing feature in mature brains, when and how is it established during brain development? Some of the most exciting research on brain development in recent years has focused on this question.

For neurons to develop regional identities, they must possess or acquire information on where they are located within the brain so that they can take on the appropriate specializations. How neurons gain positional information has been one of the most prominent themes in developmental neuroscience in the last 50 years or so, as indeed it has in the broader field of developmental biology (positional identity is required not only by brain cells).

The model that has dominated current thinking was famously elaborated in the 1960s by Lewis Wolpert in his French flag analogy. Here, a signal produced by a group of organizer cells diffuses from its source through a surrounding field of cells. In so doing, it forms a concentration gradient with more of the signal present in areas closer to the source. Cells respond to the concentration of this signal. In Wolpert's French Flag analogy, they become blue, white or red (in reality, they would become cells of different types, not different colors). Close to the source, cells receive signals above the highest threshold (to become blue, or type 1). Beyond this, cells respond to a lower dose (to become white, or type 2) while farther still cells do not receive enough of the signal to respond (and become red, or type 3). Here the model is expressed in terms of three outcomes, but there might be a different number of outcomes depending on the locations and/ or stages of development. The important point is that cells can work out where they are based on the level of signal they receive and they respond accordingly by developing different attributes.

Beyond Wolpert's basic model, the issue of how brain regionalization develops is an important question and we have relatively few answers. Regional specification is a prerequisite for the development of the connections that must link each region of the brain in a stereotypical and highly precise way (but allowing room for plasticity at a fine level). How these trillions of connections are made is another of life's great mysteries.

The connectome and connectionism

Since Ramón Y Cajal's first description of the neuron, scientists have vastly expanded our understanding of the structure and function of these individual building blocks of the brain. However, as Tim Berners-Lee comments, this is just the first step in understanding how our brains really work: "There are billions of neurons in our brains, but what are neurons? Just cells. The brain has no knowledge until connections are made between neurons. All that we know, all that we are, comes from the way our neurons are connected."

You'll hear about the "connectome" in Sebastian Seung's TEDTalk. The suffix "–ome" is used with increasing frequency to indicate a complete collection of whatever units are specified in the first part of the word, such as genes (hence genome), proteins (proteome) or connections (connectome). The connectome of the human brain is bewildering in its complexity, but the development of new brain imaging methods has catalyzed the first serious attempts to map it in living brains. At present, the resolution of imaging methods that can be applied to living brains isn't sufficient to follow individual connections (called axons). In these TEDTalks you'll hear about an attempt to come at the problem from the other direction, using very high resolution imaging of non-living brain tissue to reconstruct the ultramicroscopic anatomy of connections around individual cells. The extent to which these approaches are likely to succeed remains controversial.

The theory known as connectionism addresses a somewhat different matter within the field of brain organization: the relationship between connectivity and function. Essentially, the idea is that higher mental processes such as object recognition, memory and language result from the activity of the connections between areas of the brain rather than the activity of specific discrete regions. Whereas connectionists would agree that primary sensory and motor functions (i.e. responses to sensory stimuli and the activation of movements) are strongly localized to defined areas within the brain, they argue that this applies less clearly at higher cognitive levels. The theory emphasizes the relationship between connected brain areas and the function of the brain as a whole, with all parts having the potential to contribute to cognitive function. You should appreciate, therefore, that there is as yet no accepted view of the extent to which our higher mental functions are localized to particular parts of the brain. It is worth remembering this as you listen to the TEDTalks; keep an open mind on these truly fascinating issues.

Ways of studying brain function

In these TEDTalks, you're going to hear about some of the ways in which we can work out what the human brain does and how it does it. One longstanding approach is to examine what happens when people suffer brain lesions. Phineas Gage, a Vermont railroad worker, provides one spectacular historical example from 1848. Gage was packing gunpowder into a hole when it exploded, blowing the tamping rod through the front of his brain. Astonishingly, he survived and recovered, but those closest to him claimed that he had a very different personality. From this example, scientists hypothesized that elements of human personality are localized to the frontal lobes.

In Jill Bolte Taylor's TEDTalk, you'll hear how Taylor's own stroke provides further evidence for localization of brain function. A few words of caution, however: when we study the effects of a lesion on the brain, we're really learning about what the rest of the brain does without the damaged part, which is not quite the same as what the damaged structure itself does. Maybe this seems rather subtle, but in some cases it becomes important, for example if a lesion causes other parts of the brain to alter what they do.

You'll also hear about powerful techniques for observing the activity of living brains, for example using functional magnetic resonance imaging (FMRI; see the TEDTalk by Oliver Sacks). And you'll hear about methods for looking at the fine structure of neurons in post-mortem material, as in Sebastian Seung's TEDTalk. All have advantages and limitations, but together they give ever- increasing insight into the workings of the human mind.

Let's begin the TEDTalks with neuroanatomist Jill Bolte Taylor, who provides a basic overview of the brain and describes what she learned firsthand about its structure and function when at age 37 she suffered a massive hemorrhage in the left hemisphere of her brain.

Jill Bolte Taylor

My stroke of insight, relevant talks.

VS Ramachandran

3 clues to understanding your brain.

Oliver Sacks

What hallucination reveals about our minds.

Sebastian Seung

I am my connectome.

Christopher deCharms

A look inside the brain in real time.

A light switch for neurons

Rebecca Saxe

How we read each other's minds.

Early Brain Development and Health

The early years of a child’s life are very important for later health and development . One of the main reasons is how fast the brain grows starting before birth and continuing into early childhood. Although the brain continues to develop and change into adulthood, the first 8 years can build a foundation for future learning, health and life success .

Brain of baby x-ray graphic 3D rendering

How well a brain develops depends on many factors in addition to genes, such as:

Proper nutrition starting in pregnancy
Exposure to toxins or infections
The child’s experiences with other people and the world

Nurturing and responsive care for the child’s body and mind is the key to supporting healthy brain development. Positive or negative experiences can add up to shape a child’s development and can have lifelong effects . To nurture their child’s body and mind, parents and caregivers need support and the right resources. The right care for children, starting before birth and continuing through childhood, ensures that the child’s brain grows well and reaches its full potential. CDC is working to protect children so that their brains have a healthy start.

The importance of early childhood experiences for brain development

Children are born ready to learn, and have many skills to learn over many years. They depend on parents, family members, and other caregivers as their first teachers to develop the right skills to become independent and lead healthy and successful lives. How the brain grows is strongly affected by the child’s experiences with other people and the world. Nurturing care for the mind is critical for brain growth. Children grow and learn best in a safe environment where they are protected from neglect and from extreme or chronic stress with plenty of opportunities to play and explore.

Parents and other caregivers can support healthy brain growth by speaking to, playing with, and caring for their child. Children learn best when parents take turns when talking and playing, and build on their child’s skills and interests. Nurturing a child by understanding their needs and responding sensitively helps to protect children’s brains from stress. Speaking with children and exposing them to books, stories, and songs helps strengthen children’s language and communication, which puts them on a path towards learning and succeeding in school.

Exposure to stress and trauma can have long-term negative consequences for the child’s brain, whereas talking, reading, and playing can stimulate brain growth. Ensuring that parents, caregivers, and early childhood care providers have the resources and skills to provide safe, stable, nurturing, and stimulating care is an important public health goal.

When children are at risk, tracking children’s development and making sure they reach developmental milestones can help ensure that any problems are detected early and children can receive the intervention they may need.

Learn more about supporting early childhood experiences:

Tracking developmental milestones
Preventing abuse and neglect
Positive parenting tips
Healthy childcare

A healthy start for the brain

To learn and grow appropriately, a baby’s brain has to be healthy and protected from diseases and other risks. Promoting the development of a healthy brain can start even before pregnancy. For example, a healthy diet and the right nutrients like sufficient folic acid will promote a healthy pregnancy and a healthy nervous system in the growing baby. Vaccinations can protect pregnant women from infections that can harm the brain of the unborn baby.

During pregnancy, the brain can be affected by many types of risks, such as by infectious diseases like Cytomegalovirus or Zika virus, by exposure to toxins , including from smoking or alcohol , or when pregnant mothers experience stress, trauma, or mental health conditions like depression . Regular health care during pregnancy can help prevent complications, including premature birth, which can affect the baby’s brain. Newborn screening can detect conditions that are potentially dangerous to the child’s brain, like phenylketonuria (PKU).

Healthy brain growth in infancy continues to depend on the right care and nutrition. Because children’s brains are still growing, they are especially vulnerable to traumatic head injuries , infections, or toxins, such as lead . Childhood vaccines, such as the measles vaccine, can protect children from dangerous complications like swelling of the brain . Ensuring that parents and caregivers have access to healthy foods and places to live and play that are healthy and safe for their child can help them provide more nurturing care.

Learn more about the recommended care:

Before pregnancy
During pregnancy
Around birth
During infancy
During early childhood

What does CDC do to support early brain health?

CDC is committed to supporting early brain health through evidence-based programs and partnerships within communities. Below are just a few examples of CDC programs that support early brain health:

Learn the Signs. Act Early
Legacy for Children TM
Early Hearing Detection and Intervention
Essentials for Childhood
Concussion Prevention
Lead Prevention
Fetal Alcohol Spectrum Disorder Prevention
Childhood Immunization
Treating for Two
Preconception Care
Infant and Toddler Nutrition
Addressing Health Disparities in Early Childhood

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Psychology Discussion

Brain development in humans | essay | psychology.

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Here is an essay on the ‘Brain Development in Humans’ for class 11 and 12. Find paragraphs, long and short essays on the ‘Brain Development in Humans’ especially written for school and college students.

Essay on the Brain Development in Humans

Essay Contents:

Essay on the Theories of Human Functional Brain Development

Essay # 1. Introduction to Brain Development in Humans:

Although both of these aspects of human development have been studied for several decades, it is only recently that investigators have turned their attention to how they relate to one another. In other words, how does the physical growth of the brain relate to the emergence of new behavioural abilities during infancy and childhood? Addressing this question is not just of academic interest, but could have profound implications for clinical, educational and social policies.

Adults have brains that are highly structurally and functionally specialized; for example, discrete regions of our cerebral cortex support components of cognitive functions such as language and face processing. Although much of cognitive neuroscience and neuropsychology is concerned with dissociating and identifying the functions of these regions in adults, the question of how such specializations arise in the first place has received less attention.

One perspective is that the functional specialization of regions of the cerebral cortex arises through intrinsic genetic and molecular mechanisms, and that experience merely has a role in the final ‘fine tuning’. An alternative view is that some aspects of human functional brain development involve a prolonged process of specialization that is shaped by postnatal experience.

A parallel debate to that among developmental neuroscientists rages among developmental psychologists. Some developmental psychologists argue that the human infant is born with ‘innate modules’ and ‘core knowledge’ relevant to the physical and social world. Others propose that many of the changes in behaviour observed during infancy are the result of general mechanisms of learning and plasticity.

Essay # 2. Human Postnatal Neuroanatomical Development:

Human brain development closely follows the sequence of events observed in other primates, albeit on a slower timescale. A model of the evolution of the brain that successfully predicts the timing of different neural developmental events in various mammalian species has recently been extended to human prenatal development.

There are several ways to study postnatal neuroanatomical development in humans. Postmortem analyses have been conducted, but usually with small sample sizes. Developmental positron emission tomography (PET) and magnetic resonance imaging (MRI) studies are becoming more common, but are usually restricted to infants with suspected clinical symptoms.

Data obtained using these methods have now converged sufficiently to allow several conclusions to be drawn. By around the time of birth in humans, most neurons have migrated to their appropriate locations within the cortex, hippocampus, cerebellum and other regions.

However, some neurogenesis continues into adulthood in the hippocampus and possibly in other structures. Subcortical structures can be clearly delineated and resemble their adult forms. Although some of the chief landmarks (sulci and gyri) of the cerebral cortex are visible at birth, it remains relatively immature in terms of its inter- and intraregional connectivity.

For example, whereas there is a rapid increase in synaptogenesis around the time of birth for all cortical areas studied, the most rapid burst of synapse formation and the peak density of synapses occur at different ages in different areas. In the visual cortex, there is a rapid burst of synapse formation between 3 and 4 months, and the maximum density—about 150% of the adult level—is reached between 4 and 12 months. Synaptogenesis starts at the same time in the prefrontal cortex, but the density of synapses increases much more slowly and does not reach its peak until well after the first year.

The differential time course of development of different cortical regions can also be observed in the living human brain by PET imaging. In infants under 5 weeks of age, glucose uptake is highest in sensorimotor cortex, thalamus, brainstem and the cerebellar vermis, whereas by 3 months of age, there are considerable rises in activity in the parietal, temporal and occipital cortices, basal ganglia and cerebellar cortex.

Maturational rises are not found in the frontal and dorsolateral occipital cortex until approximately 6-8 months of age. An adult-like distribution of resting activity within and across brain regions is observed by the end of the first year. These measures, like the measures of synapse density, also show an increase above adult levels.

There is a continuing rise in overall resting brain metabolism (glucose uptake) after the first year of life, with a peak—about 150% of adult levels—at around 4-5 years of age for some cortical areas.

As with other species, regressive events are commonly observed during human brain development. For example, in the primary visual cortex the mean density of synapses per neuron starts to decrease at the end of the first year. In humans, all cortical regions studied are subject to this rise and fall in synaptic density, which declines to adult levels during later childhood.

The postnatal rise-and-fall developmental sequence can also be seen in other measures of brain physiology and anatomy. For example, PET studies show that although the overall level of glucose uptake reaches a peak during early childhood that is much higher than that observed in adults, the rates return to adult levels after about 9 years of age. The extent to which these changes relate to those in synaptic density is being investigated further.

Although there is some controversy about the interpretation of images from infants under 6 months, the consensus is that brain structures have the overall appearance of those in the adult by 2 years of age, and that all the main fibre tracts can be observed by 3 years of age. Whether this decline is due to dendritic and synaptic pruning remains unknown, although in some studies the time courses of the rise and fall coincide.

Changes in the extent of white matter are of interest because they are presumed to reflect interregional communication in the developing brain. Although increases in white matter continue through adolescence into adulthood, particularly in frontal brain regions, the most rapid changes occur during the first 2 years.

Myelination seems to begin at birth in the pons and cerebellar peduncles, and by 3 months has extended to the optic radiation and selenium of the corpus callosum. At around 8-12 months of age, the white matter associated with the frontal, parietal and occipital lobes becomes apparent.

Essay # 3. Cognitive and Perceptual Development in Human Infants:

Considerable knowledge about the cognitive and perceptual abilities of human infants has accumulated as a result of behavioural testing.

A major challenge to the developing perceptual system is to segment parts of the visual input into separate objects. In natural scenes, object information is often ambiguous, underspecified and continually changing. The perceptual system must develop the ability to define object boundaries, fill in missing information and bind together different features to compose whole unitary objects.

Various experiments have sought to establish the extent of these abilities at birth, and the extent to which they are derived from experience of complex visual scenes. It is clear that even newborns have some structure to their perceptual representations, but the point at which children effortlessly perceive objects as independent bounded entities in the way that adults do is the subject of debate, especially because there are several compelling examples of failures of babies in what are (to adults) simple tasks.

For example, until 9 months of age, infants will often fail to reach for a desirable object when it is hidden or occluded, fail to detect that an object has changed while passing behind an occluding surface, and not be surprised when two dissimilar independent objects suddenly start to move as if they are one.

These failures are particularly striking when compared with infants’ successes in other object processing tasks. For example, 4-month-old infants perceive two ends of a moving rod to continue behind a surface that occludes the middle, and expect objects to be solid and not compressible.

Focusing more on the success of infants in these paradigms, one influential view is that, from early in life, we have core knowledge about the basic properties of objects. According to this hypothesis, babies are able to perceive unitary objects in scenes on the basis of innate ‘principles’ such as those of solidity and spatio-temporal continuity.

Experiments using behavioural habituation have provided evidence that infant of 4 months and older are sensitive to these principles in some testing paradigms. Although it is tempting to interpret such evidence in terms of precocial ‘adult-like’ abilities in infants, there are several reasons for caution.

First, even 4 months of life represent hundreds of hours of potentially relevant visual experience, and some neural network computational models capable of learning aspects of object properties very rapidly show similar patterns of successes and failures in simulated versions of infant test paradigms.

Second, when babies younger than 4 months are tested in studies, they fail unless several different perceptual cues are presented. Third, infants rely more on spatial and temporal information, and less on object-specific feature information, than do adults in many object processing tasks.

And finally, recent studies show changes in the neural basis of object processing during the first year of life. Although the newborn human brain is clearly biased to process objects in certain ways, and to learn rapidly about their properties, it is not until the second year of postnatal life that children seem to perceive and process objects in the way we do as adults.

In addition to inanimate (non-social) objects, the visual world of the baby is also inhabited by animate (social) objects, such as fellow human beings. Perceiving and acting on information from caregiver adults is clearly critical for the survival and development of babies. The obvious importance of social information processing, and the evidence for specialization of the adult brain for language and face processing, has led some to speculate that there are pre-specified modules within the infant brain to process socially relevant information.

An extreme alternative view is that as infants are raised in an intensely social environment, experience-sensitive neural circuits are moulded by this early experience, and so indirectly give rise to a ‘social brain’.

However, as with the processing of inanimate objects, there is now an emerging consensus centred on the middle-ground, namely that infants are born with biases to attend to and process certain stimuli differently, and that these biases shape subsequent learning and plasticity.

For example, numerous studies have shown that newborns preferentially look towards simple face-like patterns. Although the exact visual cues that elicit this preference remain unclear, uni-dimensional psychophysical properties of the stimuli, such as their spatial frequency spectra, cannot provide a complete explanation.

One purpose of this early tendency to fixate on faces might be to establish bonding with adult caregivers. However, an equally important effect is to bias the visual input to plastic cortical circuits. This biased sampling of the visual environment over the first days and weeks of life might ensure the appropriate specialization of later developing cortical circuitry.

The relatively prolonged postnatal development of the human brain gives the opportunity for teaching and instruction by adults. However, to benefit from this from an early age, the infant must be attuned to such situations.

From 3 months of age (and possibly earlier), infants orient more rapidly to peripheral visual targets when they are cued by a change in the direction of eye gaze of a centrally presented face or by an object that interacts with them in a contingent way.

From 12 months onwards, infants also seem to interpret the behaviour of adults in terms of their goals or intentions. Early abilities such as these allow the infant to share ‘joint attention’ with adults to objects and events, providing perhaps the earliest form of education, and cues for early word learning.

An emerging picture from behavioural studies of infants is that they are born to learn, in the specific sense that simple tendencies to orient and attend to novel and socially relevant stimuli and events ensure that developing brain circuits receive more input from relevant sources. In this sense, the infant is an active participant in its own subsequent development

Essay # 4. Interactive Specialization Approach to Human Brain Development:

In contrast to the maturational approach, in which behavioural developments are attributed to the onset of functioning in one region or system, an alternative viewpoint assumes that postnatal functional brain development, at least within the cerebral cortex, involves a process of organizing inter-regional interactions.

Referring to adult brain imaging data, Friston and Price point out that it might be an error to assume that particular cognitive functions can be localized within a certain cortical region. Rather, they suggest that the response properties of a specific region are determined by its patterns of connectivity to other regions, and their current activity states.

By this view, “the cortical infrastructure supporting a single function may involve many specialized areas whose union is mediated by the functional integration among them”. Extending this idea to development means that we should observe changes in the response properties of cortical regions during ontogeny as regions interact and compete with each other to acquire their roles in new computational abilities.

The onset of new behavioural competencies during infancy will be associated with changes in activity over several regions, and not just with the onset of activity in one or more regions. In further contrast to the maturational approach, this view predicts that during infancy, patterns of cortical activation during behavioural tasks might differ from, and be more extensive than, those observed in adults. Within broad constraints, even behaviours that seem to be the same in infants and adults could involve different patterns of cortical activation.

Recent evidence indicates that the same behaviour in infants and adults can be mediated by different structures and pathways, and that there are dynamic changes in the cortical processing of stimuli during infancy. Experiments with scalp-recorded electrical potentials have indicated that, for both word learning and face processing, there is increasing spatial localization of selective processing with age or experience of a stimulus, class.

For example, in word recognition tasks, differences between known words and control stimuli are initially found over large areas, but this difference narrows to the leads over the left temporal lobe only when vocabulary reaches around 200 words, irrespective of maturational age. In parallel with changes in the patterns of regional activation are changes in the ‘tuning’ of individual regions.

For example, when event-related potentials are recorded during passive exposure to faces, the resulting component that is sensitive to upright human faces (the N170) in adults is much more broadly tuned in infants. Specifically, in adults, the N170 shows a different amplitude and latency to human upright faces than to animal or inverted faces.

In infants, the equivalent event-related potential component responds similarly to upright and inverted human faces. This evidence for dynamic changes in cortical processing during infancy is consistent with a process in which inter-regional interactions help to shape intraregional connectivity such that several regions together come to support particular perceptual and cognitive functions.

Further evidence for this viewpoint comes from studies of developmental disorders of genetic origin in which functional brain development unfortunately goes awry. Neuroimaging studies of groups with disorders such as autism and Williams’ syndrome have yet to produce a clear consensus on the neural basis of these disorders.

However, it is agreed from structural imaging studies that abnormalities in white matter are at least as extensive as those in grey matter, and from functional imaging that several cortical and subcortical regions are involved in these disorders. These general conclusions indicate that initial brain abnormalities are subsequently compounded by deviant patterns of interaction and connectivity between regions.

This idea is supported by the observation that cortical activation patterns are different in patients with these disorders, even in areas of behaviour in which they perform as successfully as control subjects. This view stands in contrast to the maturational account, in which developmental disorders could result in a deficit localizable to a particular cortical area with an associated specific cognitive deficit.

Essay # 5. Theories of Human Functional Brain Development:

Until the last decade, the study of human psychological development was largely conducted independently of any consideration of the underlying neural substrate. Similarly, human developmental neuroscience was largely descriptive, with little attempt made to understand the functional causes and consequences of changes in neuroanatomy.

Much of the research that has attempted to relate neural and behavioural development in humans has been from a maturational viewpoint in which the goal is to relate the anatomical maturation of specific regions of the brain, usually regions of cerebral cortex, to newly emerging sensory, motor and cognitive functions.

Evidence concerning the differential neuroanatomical development of cortical regions is used to determine an age when a particular region will probably become functional. Success in a new behavioural task at this age is attributed to the maturation of a new brain region, and comparisons are often made between the behavioural performance of adults with acquired lesions and behaviours during infancy.

One example of this approach comes from the neurodevelopment of visual orienting and attention. Several researchers have argued that control over visually guided behaviour is initially achieved by subcortical structures, but that with age and development, posterior cortical regions and finally anterior regions come to influence behaviour.

The characteristics of visually guided behaviour in human infants over the first month of life resemble those observed in adult primates with cortical damage. For example, saccades at this age do not seem to be under endogenous control but are mainly elicited by external stimuli (exogenous); the visual tracking of moving stimuli is not smooth, but a series of separate refoveations, and temporal visual field input dominates over nasal input.

At around one month of age, infants go through a phase of ‘sticky fixation’ during which they have difficulty in shifting their gaze from one stimulus to another. Some have attributed this to the onset of competition between cortical and subcortical vasomotor pathways, whereas others have drawn comparisons with Balint’s Syndrome in adults.

Patients with Balint’s syndrome have acquired bilateral parietal cortex damage and experience similar difficulties in ‘disengaging’ from one stimulus to saccade to another, indicating that immaturity of the parietal cortex in the infant has similar behavioural consequences.

By 2-3 months of age, these markers of subcortical control are replaced by behavioural advances such as acquiring the ability to disengage easily from one stimulus to orient to another, consistent with the maturation of regions of the parietal cortex and associated structures.

Further developments at 4-6 months, such as gaining the ability to inhibit reflexive saccades and to make saccades in anticipation of a visual target being shown in a particular location, has been associated with developments in the frontal cortex. So, a general progression of maturation from posterior to anterior cortical regions might account for aspects of infant visually guided behaviour.

In another example, maturation within the frontal lobes has been related to advances in the ability to reach for desirable objects towards the end of the first year. As we know that, infants younger than 9 months often fail to accurately retrieve a hidden object after a short delay period if the object’s location is changed from one where it was previously successfully retrieved.

Instead, they perseverate by reaching to the location where the object was found on the immediately preceding trial. This error is similar to those made by human adults with frontal lesions and monkeys with lesions to the dorsolateral prefrontal cortex, leading to the proposal that the maturation of this region in human infants allows them to retain information over space and time, and to inhibit prepotent responses.

In turn, these developments allow successful performance in object retrieval paradigms. Although converging evidence for this claim comes from associations with resting frontal electroencephalographic responses and impairments in children with a neurochemical deficit in the prefrontal cortex resulting from Phenylketonuria, as yet no direct functional imaging on human infants during such object retrieval tasks has been possible.

Despite the successes of the maturational approach, and its support from some animal studies, there are reasons to believe that it might not explain all aspects of human functional brain development.

For example, a view of human functional brain development in which regions mature sequentially cannot easily account for the dynamic changes in patterns of cortical activation observed during postnatal development, or for activity in frontal cortical regions during the first months of life.

Furthermore, a comparison of the performances of pre-term versus full-term infants on the object retrieval task indicates that the length of experience in the postnatal environment is critical.

The Skill-Learning Hypothesis:

Recent neuroimaging evidence from adults has highlighted changes in the neural basis of behaviour that result as a consequence of acquiring perceptual or motor expertise. One hypothesis is that the regions active in infants during the onset of new perceptual or behavioural abilities are the same as those involved in skill acquisition in adults. This hypothesis predicts that some of the changes in the neural basis of behaviour during infancy will mirror those observed during more complex skill acquisition in adults.

In contrast to more precocial mammals, one of the most striking features of human infants is their initial inability to perform simple motor tasks, such as reaching for an object. Work on complex motor-skill-learning tasks in adult primates shows that the prefrontal cortex is often activated during the early stages of acquisition, but that this activation recedes to more posterior regions as expertise is acquired.

In addition to the examples of prefrontal involvement, activity in this region, or at least within the frontal lobe, has been reported in several infancy studies where action is elicited, and early damage to prefrontal structures has more severe long-term effects than damage to other cortical regions.

For example, Csibra and colleagues examined the cortical activity associated with the planning of eye movements in 6-month-old infants. Infants with damage to the frontal quadrants of the brain show long- lasting deficits in visual orienting tasks, but infants with the more posterior damage that causes deficits in adults do not.

With regard to perceptual expertise, Gauthier and colleagues have shown that extensive training of adults with artificial objects, Greebles, eventually results in the activation of a cortical region previously associated with face processing, the fusiform face area. This indicates that the region is normally activated by faces in adults, not because it is pre specified for faces, but owing to our extensive expertise with that class of stimulus, and encourages parallels with the development of face processing skills in infants.

The extent of the parallels between adult perceptual expertise and infant perceptual development remains unclear. However, in both cases, event-related potential studies have shown effects of stimulus inversion only after substantial expertise has been acquired with faces or greebles. Future experiments need to trace in more detail changes in the patterns of cortical activation during training in adults and development in infants.

From the view of functional brain development, it is interesting to study cases in which there has been a period of visual deprivation early in postnatal life. As predicted by this account, after the surgical restoration of vision following a period of deprivation, there is often rapid improvement in abilities to close to normal levels.

However, in some important domains, such as the configural processing of faces, recovery is never complete, with deficits still remaining after many years of visual experience. These findings indicate that the order in which motor and perceptual skills are acquired during development might be important, and that there are periods of development during which the brain is particularly sensitive to certain types of experience.

Human postnatal functional brain development is not just the passive unfolding of a maturational sequence, but is an activity-dependent process, albeit guided and constrained by initial biases. Although progress has been made by considering functional brain development in terms of the sequential maturation of different cortical regions and their associated functions, it is becoming evident that new cognitive functions during infancy and childhood might be the result of emerging patterns of interactions between different regions.

Some of these changing patterns of interactions between regions might also be characteristic of perceptual and motor skill learning in adults. By directing the infant to orient and attend to certain types of external stimulus, some brain systems effectively ‘tutor’ others with appropriate input for subsequent specialization. In this sense, the human infant has an active role in its own functional brain specialization.

Further assessment of the three perspectives on human functional brain development presented here will require improved methods for non-invasive functional imaging, such as near infrared spectroscopy, and more detailed computational models that generate predictions about both neuroanatomy and behaviour.

Whatever the outcome of these investigations, a better understanding of functional brain development in human infants and children will have profound consequences for educational and social policies.

Functions of Reticular Activating System (RAS) | Brain | Neurology
Role of Sense Organs in Receiving and Transferring Information to Brain
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New state of mind: rethinking how researchers understand brain activity.

Understanding the link between brain activity and behavior is among the core interests of neuroscience. Having a better grasp of this relationship will both help scientists understand how the brain works on a basic level and uncover what specifically goes awry in cases of neurological and psychological disease.

One way that researchers study this connection is through what are known as “brain states,” patterns of neural activity or connectivity that emerge during specific cognitive tasks and are common enough in all individuals that they become predictable. Another, newer, approach is the study of brain waves, rhythmic, repetitive patterns of brain cell activity caused by synchronization across cells.

In a new paper, two Yale researchers propose that these two ways of thinking about brain activity may not represent separate events but two aspects of the same occurrence. Essentially, they suggest that though brain states are traditionally thought of as a snapshot of brain activity while waves are more like a movie, they’re capturing parts of the same story.

Reconsidering these two approaches in this context, the researchers say, could help both fields benefit from the methods and knowledge of the other and advance our understanding of the brain.

Inspired by ecological, conservation, and Indigenous philosophies, Maya Foster, a third-year Ph.D. student in the Department of Biomedical Engineering, began pursuing this idea once she joined the lab of Dustin Scheinost , an associate professor in the Department of Radiology and Biomedical Imaging at Yale School of Medicine.

They are co-authors of the new paper , published April 5 in the journal Trends in Cognitive Sciences.

“ We’re arguing that rather than a brain state being one single thing, it’s a collection of things, a collection of discrete patterns that emerge in time in a predictable way,” she said.

In an interview with Yale News, Foster and Scheinost describe their proposal, and discuss how they might help researchers better understand the mysteries of the brain. This interview has been edited and condensed.

When did you start to consider these might be two aspects of the same occurrence?

Maya Foster: This has been on my mind even before I came to this lab. I was reading a book — “Erosion: Essays of Undoing” by Terry Tempest Williams — and she talks about how human-made machinery like helicopters cause vibrations that interrupt the natural pulse of things and cause things like rock formations to fall apart. Relatedly, there are a lot of Indigenous populations that believe everything has a pulse. And that got me thinking of the brain and whether we have some type of resonance or vibration that can be disrupted.

Then I joined this lab and Dustin let me experiment with a lot of different things. During one of those experiments, I input some data into a particular analysis and the outputs looked wave-like, and patterns emerged and then repeated. That took me down a whole rabbit hole of research literature and there was a lot of evidence for this idea of wave-like patterns in brain states.

What are the benefits of considering brain states as wave-like?

Foster: I think it creates a synergy where both sides — the brain state folks and the brain wave folks — benefit by learning from each other. And maybe the gaps in knowledge we have now when it comes to how brain activity relates to behavior might be filled by both groups working together.

Dustin Scheinost: Brain waves are newer in this field and they’re complex. And any time you can take something new and relate it to something old — brain states in this case — it gives you a natural jumping off point. You can bring along everything you’ve learned so far. It’s kind of like not throwing the baby out with the bath water. We don’t need to drop brain states. They’ve informed us, but we can go in a different direction with them too.

How are you proposing researchers consider brain states and brain waves now?

Foster: Borrowing from physics, when you analyze light, it can be a discrete point — a photon — or it can be wave-like. And that’s one way we’re thinking about this. Similarly, depending on how you analyze brain states you can get static patterns, much like a photon, or you if you look at activity more dynamically, certain patterns start to occur more than once over time, kind of like a wave.

So we’re arguing that rather than a brain state being one single thing, it’s a collection of things, a collection of discrete patterns that emerge in time in a predictable way.

For example, if we measured four distinct patterns in brain activity as someone completed a cognitive task, a brain state could be that pattern one emerges, then pattern three, then two, then four, and that series might repeat over time. And when that repetition stops, that would be the end of that particular brain state.

You also draw comparisons to the musical technique known as “fugue.” How does that fit with how you’re visualizing these phenomena?

Foster: I’m a music person, so that’s where this came from. In a fugue, you have a basic melody and then that melody emerges later in the music in different forms and formats. For instance, the melody will play, then some other music comes in, then the melody returns with the same rhythm and time sequence but maybe it’s in a different key.

Fugues are cyclical and wave-like, they have distinct groups of notes, and there’s a systematic repetition and sometimes layering of the main melody. We’re arguing that brain states are also wave-like, have distinct patterns of brain activity, and display systematic repetition and layering of sequential patterns.

How are you hoping other researchers respond to your argument?

Foster: I would love feedback, honestly. There is evidence for what we’re proposing but when it comes to implementing these ideas going forward, it would be helpful to have a conversation about how that might work. There are a lot of different strategies and I’m interested in a broader conversation about how we as researchers might go about studying this.

What’s it like as someone who has been in this field for a while to have a student come in with a new idea like this?

Scheinost: You can get set in your ways as a researcher and you need new ideas, new creativity. Sometimes they may sound outlandish when you first hear them. But then you ruminate, and they start to take form. And it’s fun. That’s really where the fun of this job is, to hear new ideas and see how people discuss and debate them.

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11 April 2024

This fMRI technique promised to transform brain research — why can no one replicate it?

McKenzie Prillaman 0

McKenzie Prillaman is a freelance science journalist in Washington DC.

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Coloured functional magnetic resonance imaging of a healthy brain at rest. Credit: Mark & Mary Stevens Neuroimaging and Informatics Institute/Science Photo Library

It was hailed as a potentially transformative technique for measuring brain activity in animals: direct imaging of neuronal activity (DIANA), held the promise of mapping neuronal activity so fast that neurons could be tracked as they fired. But nearly two years on from the 2022 Science paper 1 , no one outside the original research group and their collaborators have been able to reproduce the results.

Now, two teams have published a record of their replication attempts — and failures. The studies, published on 27 March in Science Advances 2 , 3 , suggest that the original results were due to experimental error or data cherry-picking, not neuronal activity after all.

But the lead researcher behind the original technique stands by the results. “I’m also very curious as to why other groups fail in reproducing DIANA,” says Jang-Yeon Park, a magnetic resonance imaging (MRI) physicist at Sungkyunkwan University in Suwon, South Korea.

Science said in an e-mail to Nature that, although it’s important to report the negative results, the Science Advances studies “do not allow a definitive conclusion” to be drawn about the original work, “because there were methodological differences between the papers”.

‘Extraordinary claim’

In conventional functional MRI (fMRI), researchers monitor changes in blood flow to different brain regions to estimate activity. But this response lags by at least one second behind the activity of neurons, which send messages in milliseconds.

Park and his co-authors said that DIANA could measure neuronal activity directly, which is an “extraordinary claim”, says Ben Inglis, a physicist at the University of California, Berkeley.

The DIANA technique works by applying minor electric shocks every 200 milliseconds to an anaesthetized animal. Between shocks, an MRI scanner collects data from one tiny piece of the brain every 5 milliseconds. After the next shock, another spot is scanned. The software stitches together data from all the spots, to visualize changes in an entire slice of brain over a 200-millisecond period. The process is similar to filming an action pixel by pixel, where the action would need to be repeated to record every pixel, and those recordings stitched together, to create a full video.

Park and his colleagues claimed that this approach suppressed the slower-paced signal produced by changes in blood flow, which is what conventional fMRI tracks, and could measure the faster-paced signals produced when several neurons change their voltage.

Missing slices

But Park says that, as far as he knows, researchers outside his collaborative spheres have not been able to reproduce the results.

One published attempt 2 was led by Seong-Gi Kim, an MRI researcher at the Institute for Basic Science in Suwon, who has previously worked with Park but did not contribute to DIANA. Kim and his colleagues copied the original paper’s protocol, with some enhancements. They found a DIANA-like signal resembling brain activity when they averaged data from 50 brain slices per mouse, but only if they removed data that didn’t fit with the desired response. And the signal vanished when data from more than 1,000 brain slices from six mice were averaged.

In fMRI, averaging more brain slices should strengthen, not weaken, the brain-activity signal, says Kim. Without enough data, he adds, background noise can look like brain activity.

In the original Science paper, the team collected 48–98 brain slices per mouse, but examined only 40 for each animal, Park reports. The researchers say they excluded slices so that they could compare a consistent number across all animals, and removed those with the most background noise. But Park did not mention this until his team shared information with other laboratories hoping to use DIANA. He says that not including that step in the methods was an oversight.

Park adds that if the team non-selectively averaged data from just the first 40 brain slices per mouse, and from all animals for up to about 700 brain slices, the DIANA response was weaker but still statistically significant.

Last August, Science added an editorial expression of concern to the original paper, stating that “the methods described in the paper are inadequate to allow reproduction of the results” and “the results may have been biased by subjective data selection”. The statement says that Science has asked Park to provide more methods and data, and Park says he will submit the additional information by August. He says it takes time to re-analyse the relevant data and prepare detailed methods for reproducing DIANA.

Sequence of events

Valerie Phi Van, a radiologist and bioengineer at the Massachusetts Institute of Technology (MIT) in Cambridge and a co-author of the other Science Advances paper 3 , initially thought she had recreated the DIANA brain responses in a rat study.

But she also saw those signals when the electrical-stimulation tool was disconnected, and even when dead rats were being scanned.

Looking more closely at the sequence of events, she noticed a 12-microsecond delay between when the electric shock was triggered and when the animal was actually shocked. When Phi Van removed the time gap, the supposed DIANA signal disappeared.

Co-author Alan Jasanoff, a bioengineer and neuroscientist at MIT, says the delay caused “a little fluctuation in the [baseline] MRI signal” that looked like a DIANA response.

Park disagrees that the observed response in the original paper was due to mistimed electrical stimulation, because he says he had previously corrected for a similar aberration in the MRI baseline.

Park has continued to refine the DIANA method and says he has reproduced it in ongoing animal and human studies. He encourages researchers who have had difficulties to contact him, and says he has already shared data with scientists at nearly a dozen institutions.

However, the latest Science Advances papers have cast doubt on the original findings. It’s clear that the signals DIANA detects are “not necessarily related to neural signal”, says Shella Keilholz, an MRI physicist and neuroscientist at Emory University in Atlanta, Georgia. Although, she says, it’s possible that brain activity contributed to the detected signals.

Neuroscientists will continue to explore the cause of the conflicting results. And that could have an upside, says Noam Shemesh, an MRI researcher at the Champalimaud Foundation in Lisbon. The original paper and attempts to replicate or rebut it could lead researchers towards developing and finessing more-direct ways to measure neural activity, he says.

doi: https://doi.org/10.1038/d41586-024-00931-x

Toi, P. T. et al. Science 378 , eabh4340 (2022).

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Choi, S.-H. et al. Sci. Adv. 10 , eadl0999 (2024).

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Phi Van, V. D., Sen, S. & Jasanoff, A. Sci. Adv. 10 , adl2034 (2024).

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Brain Development in Adolescence and Childhood Essay (Critical Writing)

There appear to be three areas that recent research has shown brain development in adolescence and emerging childhood. The areas of the research were considering the aspects of synaptic pruning, myelination and cerebellum which were viewed within the problem of overproduction. Thus the synaptic pruning takes place actively in the age of 12-20 years, when “the average brain loses 7 to 10 percent of its grey matter” (Arnett, 2007). Thus such simplification of synapse improves the work of the human brain; but there is one disadvantage, as the work of brain becomes more specialized, it gets less flexible.

The next issue is myelination, which was considered to act within the period of puberty, but now the scientists think it lasts through the period of teens. The function of myelination is the same with the synaptic pruning: the brain operates faster and more effectively, but then it becomes less flexible. But the result of the recent research that I find most poignant is that cerebellum is of crucial importance for making decisions, understanding humor and other aspects; besides the cerebellum continues to grow until the mid-20s.

I would like to tell you about two stages of Kohlberg’s theory of moral development. The first stage concerns the first level of preconventional reasoning, which presupposes that a person obeys the rules in order to avoid punishment. I believe this stage is a feature of children who do not understand yet what is right and what is wrong; and try to follow the rules not to be punished. For example, the kid is not allowed to play on the carriageway, his mother prohibited him to do that and if she appears to see that he plays there, he is sure to be punished; this is the only reason for him to obey the rule.

The next stage I am going to describe is the third one. It presupposes that a person tries to conform to some specific rules and principles of behavior. Thus the ‘good’ wife is believed to be a caring mother, a passionate lover, a devoted friend, a business woman and a housewife.

I am going to describe the relation of moral reasoning, moral evaluations and moral behaviors in terms of worldviews approach to moral development according to Jensen. A person wants to know what is right and what is wrong; the aspect of moral reasoning answers this question by giving explanations for different kinds of behavior. Then a person comes to know about the right and wrong behavior and makes conclusions on the issue and can judge upon the behavior; it concerns the aspect of moral evaluation, which “in turn prescribe moral behavior” (Arnett, 2007).

Moral behaviors become basic principles for worldviews. Thus there exist three types of ‘ethics’, which are based on people’s actions and worldviews; the ‘ethic of autonomy’ presupposes that individual has right to do whatever they like without doing harm to others. The aspect of ‘ethic of community’ presupposes that a member of the community has certain obligations towards other members of this community. According to the aspect of ‘ethic of divinity’ the individual is a “spiritual entity, subject to the prescriptions of a divine authority” (Arnett, 2007); thus obeys religious traditions of society.

The next issue I am going to discuss is media influences in terms of gender socialization in adolescence. The media possess great influential rates in terms of forming the views and opinions. Adolescents are very perceptive towards outer influences and attempts to influence their opinion. The media influences gender socialization in adolescence with help of magazines which represent strict gender diversities. Other types of mass media are also aimed at focusing on gender socialization in adolescence.

Works Cited

Arnett, Jeffrey Jensen. (2007). Adolescence and Emerging Adulthood: a Cultural Approach . New Jersey: Pearson Prentice Hall.

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IvyPanda. (2021, November 26). Brain Development in Adolescence and Childhood. https://ivypanda.com/essays/brain-development-in-adolescence-and-childhood/

"Brain Development in Adolescence and Childhood." IvyPanda , 26 Nov. 2021, ivypanda.com/essays/brain-development-in-adolescence-and-childhood/.

IvyPanda . (2021) 'Brain Development in Adolescence and Childhood'. 26 November.

IvyPanda . 2021. "Brain Development in Adolescence and Childhood." November 26, 2021. https://ivypanda.com/essays/brain-development-in-adolescence-and-childhood/.

1. IvyPanda . "Brain Development in Adolescence and Childhood." November 26, 2021. https://ivypanda.com/essays/brain-development-in-adolescence-and-childhood/.

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IvyPanda . "Brain Development in Adolescence and Childhood." November 26, 2021. https://ivypanda.com/essays/brain-development-in-adolescence-and-childhood/.

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Are lab-grown brain tissues ethical? There is no no-brainer answer

Insights into ethical and legal ramifications of growing brain organoids from human fetal brain tissue.

Brain organoids, though often referred to as "mini brains," are not truly human brains. But the concerns over these lab-grown brain tissues, especially when they are developed from human fetal tissues, can be very human indeed.

Researchers from the Graduate School of Humanities and Social Sciences at Hiroshima University offer valuable insights into the complexities inherent in brain organoid research, making significant contributions to the ongoing discourse surrounding this innovative biotechnology and paving the way for informed decision-making and legal and ethical stewardship in the pursuit of scientific advancement.

Their paper was published on March 4 in EMBO Reports .

Brain organoids are three-dimensional human brain tissues derived from stem cells, which are capable of developing into many different cell types. They replicate the complexity of the human brain in a laboratory setting, allowing researchers to study brain development and diseases in the hopes of acquiring vital insights and making innovative medical advancements.

Traditionally, brain organoids are grown from pluripotent stem cells, an especially potent sub-type that is typical of early embryonic development, but new technologies now make it possible to generate these organoids from human fetal brain cells. This method comes, however, with even more heated legal and ethical debates about brain organoids -- debates that are already intense in conventional organoid research.

"Our research seeks to illuminate previously often-overlooked ethical dilemmas and legal complexities that arise at the intersection of advanced organoid research and the use of fetal tissue, which is predominantly obtained through elective abortions," said Tsutomu Sawai, an associate professor at Hiroshima University and lead author of the study.

The study highlights the urgent need for a sophisticated and globally harmonized regulatory framework tailored to navigate the complex ethical and legal landscape of fetal brain organoid (FeBO) research. The paper emphasizes the importance of informed consent protocols, ethical considerations surrounding organoid consciousness, transplantation of organoids into animals, integration with computational systems, and broader debates related to embryo research and the ethics of abortion.

"Our plan is to vigorously advocate for the development of thorough ethical and regulatory frameworks for brain organoid research, including FeBO research, at both national and international levels," said Masanori Kataoka, a fellow researcher at Hiroshima University.

"Rather than being limited to issues of consciousness, it's imperative, now more than ever, to systematically advance the ethical and regulatory discussion in order to responsibly and ethically advance scientific and medical progress," Sawai said.

Moving forward, the research duo plans to continue supporting the advancement of ethical and regulatory discussions surrounding brain organoid research. By promoting responsible and ethical progress in science and medicine, they aim to ensure that all research involving brain organoids, including FeBOs, is conducted within a framework that prioritizes human dignity and ethical integrity.

Brain Tumor
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Journal Reference :

Tsutomu Sawai, Masanori Kataoka. The ethical and legal challenges of human foetal brain tissue-derived organoids . EMBO Reports , 2024; DOI: 10.1038/s44319-024-00099-5

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