Author Archives: Kathryn Mills

Many believe that intelligent quotient (IQ) tests tell you something about an individual’s inherent, and perhaps unchanging, intellectual capacity. But is intelligence really fixed? Current research suggests it’s not.

IQ was once thought to be stable across the lifespan. Then, in 2011 a study tested participants twice in adolescence and found substantial changes in IQ across time for a third of the sample¹. There was an overall increase in the group’s IQ between early adolescence (12-16 years) and late adolescence (16-20 years), with some individuals gaining or losing as much as 18 IQ points! This is substantial, as by many scoring standards, that’s more points than make up a full standard deviation (for reference, approximately 68% of the population is within one standard deviation of average IQ).

These changes in IQ were also associated with changes in brain structure, suggesting an underlying neural mechanism for changes in intelligence across adolescence¹. This finding has since been replicated in a larger group of individuals covering a wider age range².

The roles of nature and nurture

Both genetics and the environment have an influence on IQ. However, this influence changes across development, with genetic influences generally becoming a greater influence as we get older³. There is also some evidence that individuals with high IQ are influenced by the environment longer than individuals with low IQ⁴.

In a study of children aged 4-12 years, both low and high IQ children showed similar levels of environmental influences on their IQ. However, the teenagers (aged 12-18 years) with low IQ were much less influenced by the environment than high IQ teenagers, who showed similar levels of environmental influences as high IQ children⁴. Both low and high IQ adults (aged 18+ years) showed similar (low) levels of environmental influence on IQ.

In other words, according to this research, the environment may have the greatest impact on IQ in childhood, have a continued impact on IQ for high scoring teenagers in particular, and then balance out again to have a lower impact across adults.

It has been suggested that the extended period of heightened environmental influence in high IQ individuals might reflect an extended period of neural plasticity in these individuals. This idea seemed to be supported by an early study investigating brain development in groups of individuals with varying IQ levels⁵. This study appeared to find evidence for more protracted brain development in groups of children with higher IQs, suggesting that children with higher IQs showed a longer period of “cortical thickening” compared to children with lower IQs⁵. Cortical thickening is related to the grey matter (made of primarily of neuronal cell bodies) of the outermost layer of tissue in the brain, which is involved in many complex cognitive functions. However, the methods involved in this study have been recently been called into question^6,7, and the results have not replicated⁸. This sort of trajectory is common in research, and a reminder to look across studies and time for potentially useful patterns.

A more recent study similarly found a relationship between cortical development patterns and IQ, but with different patterns than what was observed in the earlier study⁸. In children, cortical thinning is associated with higher IQ, whereas in adults, cortical thickening is associated with higher IQ⁸. These results highlight the importance of timing in our understanding of how brain changes could relate to cognitive changes, as one type of brain change in childhood could mean something completely different in adulthood. Indeed, changes in cortical thickness was a better predictor of an individual’s IQ than the actual thickness⁸.

Overall, the individuals with the highest IQs in this study also showed the largest changes in brain structure across the lifespan⁸. This could suggest that greater neural plasticity at any age is associated with greater intelligence.

Moving Forward

So how can we increase our neural plasticity? It has been suggested that continued education keeps the brain plastic longer⁹. This could be true, but the needed studies to test this hypothesis are lacking. To see if prolonged education affects the development of our brain, we would need longitudinal studies tracking individuals with differing education levels between childhood and adulthood.

Until that study exists, the best we can do is draw from existing studies examining changes in intelligence in relation to changes in brain structure and function. While education could theoretically change our level of brain plasticity and intelligence, recent work suggests that our genes also play a large role. One longitudinal study of twins found a relationship between changes in total brain volume and IQ, which appeared to be driven by genes influencing both IQ and brain volume¹⁰. A different twin study found evidence for the same genes that influence an adults general intelligence level are also involved in the structural integrity of brain networks¹¹.

In the meantime, it seems fair to conclude at least one thing: intelligence is not set in stone. And behaving as though our own and our students’ brains can continue to improve and learn with the proper supports certainly can’t hurt.

References & Further Reading 

1. Ramsden, S., Richardson, F. M., Josse, G., Thomas, M. S. C., Ellis, C., Shakeshaft, C., … Price, C. J. (2011). Verbal and non-verbal intelligence changes in the teenage brain. Nature, 479(7371), 113–116. [Paper]
2. Burgaleta, M., Johnson, W., Waber, D. P., Colom, R., & Karama, S. (2014). Cognitive ability changes and dynamics of cortical thickness development in healthy children and adolescents. NeuroImage, 84, 810–819. [Paper]
3. McClearn, G. E., Johansson, B., Berg, S., Pedersen, N. L., Ahern, F., Petrill, S. A., & Plomin, R. (1997). Substantial Genetic Influence on Cognitive Abilities in Twins 80 or More Years Old. Science, 276(5318), 1560–1563. [Paper]
4. Brant, A. M., Munakata, Y., Boomsma, D. I., Defries, J. C., Haworth, C. M. A., Keller, M. C., … Hewitt, J. K. (2013). The nature and nurture of high IQ: an extended sensitive period for intellectual development. Psychological Science, 24(8), 1487–1495. [Paper]
5. Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., … Giedd, J. N. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440(7084), 676–679. [Paper]
6. Ducharme, S., Albaugh, M. D., Nguyen, T.-V., Hudziak, J. J., Mateos-Pérez, J. M., Labbe, A., … Brain Development Cooperative Group. (2015). Trajectories of cortical thickness maturation in normal brain development – The importance of quality control procedures. NeuroImage, 125, 267–279. [Paper]
7. Mills, K. L., & Tamnes, C. K. (2014). Methods and considerations for longitudinal structural brain imaging analysis across development. Developmental Cognitive Neuroscience, 9, 172–190. [Paper]
8. Schnack, H. G., van Haren, N. E. M., Brouwer, R. M., Evans, A., Durston, S., Boomsma, D. I., … Hulshoff Pol, H. E. (2014). Changes in Thickness and Surface Area of the Human Cortex and Their Relationship with Intelligence. Cerebral Cortex. [Paper]
9. Steinberg, L. (2014). Age of Opportunity: Lessons from the New Science of Adolescence. Mariner Books.
10. Brouwer, R. M., Hedman, A. M., van Haren, N. E. M., Schnack, H. G., Brans, R. G. H., Smit, D. J. A., … Hulshoff Pol, H. E. (2014). Heritability of brain volume change and its relation to intelligence. NeuroImage, 100, 676–683. [Paper]
11. Bohlken, M. M., Brouwer, R. M., Mandl, R. C. W., Hedman, A. M., van den Heuvel, M. P., van Haren, N. E. M., … Hulshoff Pol, H. E. (2016). Topology of genetic associations between regional gray matter volume and intellectual ability: Evidence for a high capacity network. NeuroImage, 124, Part A, 1044–1053. [Paper]

• Fjell, A. M., Westlye, L. T., Amlien, I., Tamnes, C. K., Grydeland, H., Engvig, A., … Walhovd, K. B. (2013). High-Expanding Cortical Regions in Human Development and Evolution Are Related to Higher Intellectual Abilities. Cerebral Cortex. [Paper]
• Tamnes, C. K., Fjell, A. M., Østby, Y., Westlye, L. T., Due-Tønnessen, P., Bjørnerud, A., & Walhovd, K. B. (2011). The brain dynamics of intellectual development: waxing and waning white and gray matter. Neuropsychologia, 49(13), 3605–3611. [Paper]
• Neuroskeptic. (2012) How intelligent is IQ? [Blog Post]

Adolescence is the period between childhood and adulthood that largely coincides with the years of secondary schooling. This stage of life is characterized by many cognitive changes. One such change is in social signal sensitivity. Recent research has provided evidence for adolescence as a time of heightened receptivity and sensitivity to complex social signals in the environment, which are reflected in typical brain development patterns¹.

Developmental tasks

We are faced with certain developmental tasks at different points in our life. This means that we are expected to acquire certain skills or abilities at certain developmental stages. For instance, infants and young children are tasked to develop certain sensory and motor skills. And the human brain at this period of life reflects this, as it produces an excess number of connections between brain cells (called synapses) in sensory and motor cortices in early infancy, which are then pruned (or lost over time) to their adult levels across the first decade of life.

When it comes to the connections in the brain, more does not always mean better.

In fact, ‘synaptic pruning’ often allows the brain to communicate more efficiently.

The human brain also overproduces synapses in other regions of the cortex during infancy, such as the prefrontal cortex. However, unlike the sensory and motor cortices, the connections formed in this part of the brain continue to be pruned across the teenage years and into the twenties^2,3.

This prolonged development of the prefrontal cortex has intrigued developmental neuroscientists for decades. Given that synaptic pruning coincides with an increase in abilities associated with a given cortical area, perhaps the prolonged synaptic pruning of the prefrontal cortex coincides with the increased abilities associated with this part of the brain? This question underlies many developmental neuroscience studies.

In flux: The prefrontal cortex

The prefrontal cortex is often discussed as the hallmark of human cognition. Many complex cognitive abilities, such as inhibiting inappropriate behavior, planning for the future, and inferring the mental states of others, require the prefrontal cortex. It might be intuitive to many educators that an area of the brain involved in these complex behaviors and abilities is still developing throughout the teenage years.

However, the prefrontal cortex is not the neurological root of all behavioral changes between adolescence and adulthood.

The brain operates on a network level, which means that many different brain regions are constantly communicating with each other. While each region might have its own specific role, it is how the networks interact that ultimately matters. You can think of it as kind of like a team. Each member has its own role to play—and if a member gets weaker or stronger then it can change the way the team works—but the end result is a product of the whole team working together.

In flux: The nucleus accumbens

While the prefrontal cortex is often lauded as the seat of rational behavior, the nucleus accumbens is often demeaned as the cause of human hedonism or impulse. This subcortical brain region, hidden deep within the brain, is best known for its involvement in reward processing. Early research in rodents found evidence for dramatic remodeling of dopamine receptors in the nucleus accumbens during puberty⁴. This means that there was a change in how cells process dopamine, which is a neurotransmitter often connected to the experience of pleasure or rewards. Early fMRI studies then found increased recruitment of the nucleus accumbens in adolescence during reward processing⁵. This finding prompted developmental scientists to hypothesize that adolescent behaviors might be more influenced by nucleus accumbens signaling (or the sensitivity of this area to neurotransmitters like dopamine), which could explain why adolescents are drawn to risky or rewarding behaviors⁶. This heralded a change in thinking in developmental neuroscience. Rather than simply attributing adolescent changes to the developing prefrontal cortex, this new model posited that the changing interactions between the prefrontal cortex and nucleus accumbens underlie behavioral differences between adolescence and adulthood.

Not so simple

The model that I just described is more complex than can be described in a short blog post (see Further Reading). However, at its core is the interplay between two systems: one involved in socio-emotional processing and the other in cognitive control⁶. Subcortical regions such as the nucleus accumbens are considered part of the socio-emotional processing system because they are recruited during rewarding social interactions or emotional scenarios. However, we know that cortical regions are also involved in social cognitive processing (see previous blog post), and therefore these systems are starting to be taken into account when considering the neural correlates of adolescent behavior^7,8.

Social brain development

The network of brain regions involved in understanding or inferring the mental states of others (i.e. mentalizing) continues to develop across adolescence. Although they aren’t exclusively involved in mentalizing, these regions—the dorsomedial prefrontal cortex, temporal parietal junction, posterior superior temporal sulcus and anterior temporal cortex—are consistently recruited when individuals perform tasks that require understanding or inferring the mental states of others. Longitudinal studies of brain structure have found that these regions undergo substantial changes in structure throughout adolescence⁹.

And as described in my previous post, adolescents utilize the medial prefrontal cortex more than adults in tasks that require understanding the mental states of others¹⁰. Taken together, these changes in structure and function provide evidence for the continued development of a brain network involved in complex socio-cognitive processes that influence how we navigate the social world.

The developmental tasks of adolescence

Now, why would we expect adolescence to be a sensitive period for social brain development? The period of adolescence, which can be defined as beginning around puberty, is typically considered finished when one has reached a relatively stable role in society. Therefore, one of the major developmental tasks of adolescence is to learn how to navigate the complex social world of one’s society. Adolescents are more equipped to do this than children because they have the necessary cognitive abilities as well as the motivational drive to learn from their social environment. Educators can build on these capacities in learning settings if social motivation is used to bolster learning rather than seen as another behavior to inhibit in the classroom.

An aside on the nucleus accumbens and risk-taking

Earlier I described the nucleus accumbens being involved in reward processing. While this is true, it is also true that the nucleus accumbens is involved in learning. In a way, we can think of the nucleus accumbens as a sort of salience detector—it helps us know what to pay attention to in the environment. Therefore, the heightened sensitivity of the nucleus accumbens in adolescence presents a great opportunity for learning. Further, risk-taking is not inherently a bad behavior. In fact, we need to take many risks in order to succeed in the modern educational environment.

Encouraging these educational risks, which can be as minor as raising one’s hand to answer a question in front of one’s peers, or as substantial as spending the time to learn a new programming language, might be one way to take advantage of the natural inclinations of being young and flexible.

 

References

1. Blakemore, S.-J., & Mills, K. L. (2014). Is Adolescence a Sensitive Period for Sociocultural Processing? Annual Review of Psychology, 65(1), 187–207. [Paper]
2. Huttenlocher, P. R. (1979). Synaptic density in human frontal cortex — Developmental changes and effects of aging. Brain Research, 163(2), 195–205. [Paper]
3. Petanjek, Z., Judaš, M., Šimic, G., Rasin, M. R., Uylings, H. B. M., Rakic, P., & Kostovic, I. (2011). Extraordinary neoteny of synaptic spines in the human prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 108(32), 13281–13286. [Paper]
4. Andersen, S. L., Rutstein, M., Benzo, J. M., Hostetter, J. C., & Teicher, M. H. (1997). Sex differences in dopamine receptor overproduction and elimination. Neuroreport, 8(6), 1495–1498. [Paper].
5. Galvan, A., Hare, T. A., Parra, C. E., Penn, J., Voss, H., Glover, G., & Casey, B. J. (2006). Earlier Development of the Accumbens Relative to Orbitofrontal Cortex Might Underlie Risk-Taking Behavior in Adolescents. The Journal of Neuroscience, 26(25), 6885–6892. [Paper]
6. Steinberg, L. (2008). A Social Neuroscience Perspective on Adolescent Risk-Taking. Developmental Review: DR, 28(1), 78–106. [Paper]
7. Crone, E. A., & Dahl, R. E. (2012). Understanding adolescence as a period of social-affective engagement and goal flexibility. Nature Reviews. Neuroscience, 13(9), 636–650. [Paper]
8. Pfeifer, J. H., & Allen, N. B. (2012). Arrested development? Reconsidering dual-systems models of brain function in adolescence and disorders. Trends in Cognitive Sciences, 16(6), 322–329. [Paper]
9. Mills, K. L., Lalonde, F., Clasen, L. S., Giedd, J. N., & Blakemore, S. J. (2014). Developmental changes in the structure of the social brain in late childhood and adolescence. Social Cognitive and Affective Neuroscience, 9(1), 123–131. [Paper]
10. Blakemore, S.-J. (2008). The social brain in adolescence. Nature Reviews. Neuroscience, 9(4), 267–277. [Paper]

Further Reading

• Casey, B. J., Getz, S., & Galvan, A. (2008). The adolescent brain. Developmental Review: DR, 28(1), 62–77. http://doi.org/10.1016/j.dr.2007.08.003
• Gardner, M., & Steinberg, L. (2005). Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: an experimental study. Developmental Psychology, 41(4), 625–635. http://doi.org/10.1037/0012-1649.41.4.625
• Mills, K. L., Goddings, A.-L., Clasen, L. S., Giedd, J. N., & Blakemore, S.-J. (2014). The developmental mismatch in structural brain maturation during adolescence. Developmental Neuroscience. http://doi.org/10.1159/000362328
• Somerville, L. H., & Casey, B. J. (2010). Developmental neurobiology of cognitive control and motivational systems. Current Opinion in Neurobiology, 20(2), 236–241. http://doi.org/10.1016/j.conb.2010.01.006
• Somerville, L. H., van den Bulk, B. G., & Skwara, A. C. (2014). Response to: The triadic model perspective for the study of adolescent motivated behavior. Brain and Cognition. http://doi.org/10.1016/j.bandc.2014.01.003
• Steinberg, L. (2010). A dual systems model of adolescent risk-taking. Developmental Psychobiology, 52(3), 216–224. http://doi.org/10.1002/dev.20445

Adolescence is the period between childhood and adulthood. And though it can stretch into our early twenties, we spend many of these years in high school. This stage of life is marked by increased cognitive abilities, social sensitivity, and agency (or increasing independence). These changes make this time particularly perplexing to some adults, as they struggle to make sense of stereotypical adolescent behaviors such as risk taking and increased allegiance to peers.

At the end of the 20th century, it was common to discuss adolescent behavior as being influenced by “raging hormones.” Today, it is becoming increasingly common to discuss adolescent behavior in terms of the “teenage brain.” But what makes the teenage brain different from the child or adult brain? And do these differences have implications for education and learning? This blog will discuss the latest research in adolescent brain development and how the current evidence might inform education during the teenage years. This post outlines three of the most interesting things neuroscience has taught us about the physical changes that take place in the brain during adolescence.

1. The brain continues to change throughout adolescence.

Perhaps the most important consideration to keep in mind regarding the brain during adolescence is that it is continuing to change. There is evidence for this from multiple lines of research, including cellular work on post-mortem human brain tissue¹, as well as longitudinal magnetic resonance imaging (MRI) studies of brain structure and function.

What do we mean by “physically change”?
With MRI, we have the ability to see how the living human brain changes from birth to old age by taking different kinds of pictures. One kind of picture we can take is of the structure–or anatomy–of the human brain, and we can use this picture to look specifically at two components of the brain’s structure: one component is grey matter, which is largely made up of brain cell bodies and their connections. And the other is white matter, which is primarily the long connecting fibers that carry signals between brain regions. The thing that gives white matter its color is “myelin”, which is a fat that wraps around connecting fibers in order to make communication more efficient.

There have been a few studies now where hundreds of participants had their brains scanned multiple times across development, and we know from these studies that the amount of grey matter is greatest during childhood, but decreases during adolescence before roughly stabilizing in the mid- to late- twenties². We also know that the amount of white matter increases almost linearly across adolescence³. These are two major changes happening in the structure of our brain during adolescence.

2. The brain doesn’t all change at once.

Structural changes are not occurring at the same time across the whole brain. Actually, areas of the brain that are involved in basic sensory processing or movement develop earlier than areas of the brain involved in more complex processes such as inhibiting inappropriate behavior, planning for the future, and understanding other people. These and other complex processes rely on areas in the prefrontal, temporal and parietal cortices, which are continuing to change in structure across the second decade of life⁴.

How do these changes happen?
We still do not know the specific cellular mechanisms that underlie developmental changes in measures of grey or white matter. It is often thought that these decreases in grey matter reflect, at least in part, changes in connectivity between brain cells. These changes include decreases in dendritic spine density (which is basically a proxy for how interconnected cell bodies are in the grey matter) and other cellular processes involved in synaptic pruning (which is the way that connections in the brain are broken). Histological work, which involves studying the cells using microscopes, has given us a better understanding of the cellular changes occurring in the human brain across the lifespan.

In one specific study, researchers at the Croatian Institute for Brain Research counted the number of dendritic spines in an area of the prefrontal cortex⁵. They found that the number of spines continued to decrease across the second and third decades of life. So, this finding gives some cellular evidence for the continued structural development of the human brain across adolescence, at least in a section of the prefrontal cortex.

Is this a bad thing?
Not necessarily. The continued reduction in synapses seen in the prefrontal cortex means that the brain is still undergoing changes in organization during adolescence. As humans, we have an excess amount of brain connections when we are children, and almost half of these connections can be lost in adolescence. We know that experience influences what connections are kept and subsequently strengthened. Thus we can think of adolescence as a time of transition rather than a time of loss in certain areas of the brain.

3. The brain is changing in more ways than one.

MRI can also be used to see how blood flows in the brain, which allows researchers to get a sense of how the brain is working. So if MRI alone reveals brain structure, you can think of fMRI (or “functional MRI”) as revealing brain function. Many fMRI studies have also shown changes in brain functionality across adolescence. For example, how we use areas of the brain involved in understanding other people changes between adolescence and adulthood⁶.

This is especially true for “the social brain”.
There are a number of cognitive processes that are involved in interacting with and understanding other people, and we can use functional MRI to see what areas of the brain are active when we engage in important social tasks like understanding the intentions or emotions behind facial expressions or understanding social emotions like guilt or embarrassment. Tasks like these consistently recruit a number of brain regions in the prefrontal and temporal cortex, which is sometimes referred to as the “social brain.”

Although adolescents and adults use the same areas of the brain during a number of social tasks like understanding intentions and social emotions, these tasks all show a similar decrease in activity across age in this medial prefrontal cortex area, which is a part of the brain often related to social processing Adolescents seem to use this part of the prefrontal cortex more than adults when doing certain social tasks⁷.

So what does it all mean?
What is the point in highlighting these biological changes if we cannot connect them to real world behavior? In this post, I discussed how the brain is changing in both its structure and function during adolescence, highlighting in particular the changes involved in areas of the brain used when we attempt to understand the thoughts, intentions and feelings of other people. These changes are relevant because of the developmental tasks that adolescents must accomplish. One of the major developmental tasks of adolescence is to learn how to successfully navigate our highly social world. Having a malleable brain during adolescence is arguably adaptive for this sort of task, as new social skills and higher level cultural rules can be acquired with greater ease. Thinking about how these changes may impact the way students interact with educational environments is also important – considering these environments are often just as social as they are learning-oriented. In the next post, I’ll discuss how the adolescent brain is not just primed to learn from the social environment, but also how it is particularly sensitive to complex social signals.

References & Further Reading

1. Petanjek, Z., Judaš, M., Šimic, G., Rasin, M. R., Uylings, H. B. M., Rakic, P., & Kostovic, I. (2011). Extraordinary neoteny of synaptic spines in the human prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 108(32), 13281–13286. [Paper]
2. Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional differences in synaptogenesis in human cerebral cortex. The Journal of Comparative Neurology, 387(2), 167–178. [Paper]
3. Mills, K. L., & Tamnes, C. K. (2014). Methods and considerations for longitudinal structural brain imaging analysis across development. Developmental Cognitive Neuroscience, 9, 172–190. [Paper]
4. Lebel, C., & Beaulieu, C. (2011). Longitudinal development of human brain wiring continues from childhood into adulthood. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 31(30), 10937–10947. [Paper]
5. Tamnes, C. K., Walhovd, K. B., Dale, A. M., Østby, Y., Grydeland, H., Richardson, G., … Fjell, A. M. (2013). Brain development and aging: Overlapping and unique patterns of change. NeuroImage, 68C, 63–74. [Paper]
6. Blakemore, S.-J., & Mills, K. L. (2014). Is Adolescence a Sensitive Period for Sociocultural Processing? Annual Review of Psychology, 65(1), 187–207. [Paper]
7. Blakemore, S.-J. (2008). The social brain in adolescence. Nature Reviews. Neuroscience, 9(4), 267–277. [Paper]