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May 1, 2020
Vol. 77
No. 8

Picturing the Brain

New brain-imaging methods are helping us better understand how children learn.

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Social-emotional learningInstructional Strategies
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Credit: Credit: Roy Scott / Alamy Stock Photo
Two of society's most inspiring and daunting missions are (1) educating our children so that they flourish as adolescents and adults, and (2) understanding how the human brain endows us with such remarkable capacities of learning, thought, and feeling. These missions converge when we think about the growth and development of the student's mind and brain, because the mind is what the brain does. Everything a student learns, from facts to skills to emotional regulation, is manifested by how the brain changes in response to experience (brain plasticity). We have known this in principle for a long time, but the invention of new noninvasive brain imaging methods, especially magnetic resonance imaging (MRI), has allowed us for the first time to directly visualize and measure the structure and function of children's brains, from infancy through young adulthood.
The convergence of education and neuroscience has been termed "education neuroscience," and this convergence has been both promising and the focus of debate. The debate centers on how neuroscientific knowledge about learning in the brain can inform teaching practices and educational policies. Knowing, for example, that emotional experience enhances memory via the amygdala or that motivation enhances memory via interactions between the subcortical reward system and the hippocampus does not (and frankly, should not) alter how a teacher plans or delivers a lesson. Without knowledge of this neural circuitry, effective teachers already know that students learn best when engaged via emotion and motivation.
So, what role then can neuroscience play in education? I believe neuroscience can play a useful but indirect role by corroborating and helping to validate research in psychological science and education. School leaders and teachers need to know which research findings are so solid that they should guide changes in practice and policy. Research findings are most credible when they are supported by multiple sources of convergent evidence (not a single finding or headline). Neuroscience can be such a source of convergent evidence in partnership with psychological and education science.

The Power and Peril of Neuromyths

The danger is that, if not done carefully, the dialogue between education and neuroscience can take a clearly faulty pathway.
The remarkable pictures we now have of children's brains may inadvertently fuel neuromyths about students' minds and brains. Such myths include the existence of different specific learning styles (visual vs. auditory vs. kinesthetic), for instance, the "Mozart effect" of benefits of early exposure to classical music on reasoning, the negative impact of sugar on attention, the dichotomy of right brain vs. left brain learners, the view that a common sign of dyslexia is seeing letters backward, and the belief that we use only 10 percent of our brains.
There is neither psychological nor neuroscience evidence supporting any of these myths, and considerable psychological evidence contradicting them (although we all have moments when we may feel like we are only using 10 percent of our brains). Yet the general public endorses about 68 percent of such neuromyths, educators endorse 56 percent, and even people with high neuroscience exposure endorse 46 percent (Macdonald et al., 2017). Thus, training in education and neuroscience decreases but does not eliminate beliefs in neuromyths.
This underscores the importance of improving communication between educators and neuroscientists to jointly develop an understanding of the actual brain science that might be relevant for education.

Mindfulness in the Minds and Brains of Students

How can neuroscience strengthen behavioral research that is relevant to educational practices? One way is to provide convergent objective biological evidence about subjective experiences, such as feelings of stress in students, and about how educational practices can transform both the mind and brain, for instance so that students feel less stress. Such convergent evidence can make educators and scientists more certain of the validity of the scientific findings, and more motivated to enact practices and policies that build on those findings to promote learning and well-being in students.
One example comes from recent research on mindfulness in schools (Bauer et al., 2019). Mindfulness is the human ability to be fully present, aware of where we are and what we are doing, and not overreact to or become overwhelmed by what's going on around us. Multiple studies with children and adults have shown that mindfulness training reduces self-reported feelings of stress. Mindfulness has become of particular interest to schools and families because of evidence that feelings of stress are currently rising in adolescents and young adults, which may contribute to the striking 52 percent increase in depression (Twenge et al., 2019) and 100 percent increase in emergency room visits for suicide attempts or suicidal thinking among adolescents (Burstein, Agostino, & Greenfield, 2019) over the past decade.
More directly related to schools, there is now evidence that for students in grades 5–8, higher levels of mindfulness are associated with better grades, better statewide test scores, fewer suspensions, and fewer absences (Caballero et al., 2019). This research I led on school-based mindfulness training was performed as a partnership between a school and scientists in a randomized controlled trial, the strongest kind of research design because it can determine causality (in contrast to correlational evidence) (Bauer et al., 2019). Half the 6th graders were assigned randomly to an instructor-led mindfulness course, and half to an instructor-led computer programming course (students rated the two courses equally in terms of enjoyment and effort). Before and after the eight-week courses, students were evaluated in a number of ways. Half the families also agreed to have their children participate in MRI scanning. The main findings showed that students who received mindfulness training reported feeling less stress and less negative feelings after the training (there was no such change in the students enrolled in computer programming).
Stress and negative feelings were measured by student self-reports on widely used research questionnaires. This might raise the concern that students in the mindfulness group may have been biased to report less stress and fewer negative feelings because they thought that these were the correct answers to provide after the mindfulness training. This is where objective brain evidence can support subjective reports of stress and negative feelings. From a great deal of animal and human research, we know that the amygdala—part of the brain's limbic system that is associated with emotional reactivity—is responsive to negative stimuli. This includes negative facial expressions, especially the expression of fear (in fact, patients with injuries to the amygdala have severe problems in recognizing fearful facial expressions).
At the outset of this study, students who reported greater stress in their lives had a greater amygdala response to fearful facial expressions than students who reported less stress. After the courses, only students who received mindfulness training exhibited a reduction of their amygdala response to fearful faces. Thus, the objective brain evidence aligned with subjective self-reports of reduced feelings of stress. Because two independent measures converged on the same conclusion about the benefit of mindfulness instruction, educators can be more confident in the value of such instruction.
These findings may be especially relevant for children growing up in adversity and exposed to trauma. Multiple studies have found that amygdala responses to negative stimuli are altered in such children and that these changes can persist into adulthood. The fact that mindfulness training reduced negative feelings suggests that such programs in schools may be helpful, not only to diminish stress but also to enhance learning.

Reading Intervention and Brain Plasticity

Another example of how neuroscience evidence can support the understanding of education outcomes involves a summer reading intervention for 1st and 2nd graders who were falling behind in reading skills (Romeo et al., 2018). These children, who came from diverse families in terms of socioeconomic status, participated in a randomized controlled trial summer program in which some children received 100 hours of small-group intervention to boost their reading skill (others received the intervention after the summer). They also underwent MRI scanning to measure brain structure, and specifically the thickness of the neocortex (the part of the cerebral cortex supporting high-level human abilities, such as language and reading).
As often occurs in any form of education or intervention, some children responded well to the intervention and exhibited gains in reading ability. About half of the children, however, did not exhibit improvement in their reading. The best predictor of who did or did not benefit was family socioeconomic status—children who came from families with less income and less formal education gained the most in reading skill. And strikingly, only the children whose reading improved exhibited brain plasticity by a change in the anatomy of their brain from before to after intervention: There was a widespread thickening of the neocortex only in these children (see fig. 1). In other words, effective instruction changed their brains (and no less important, their reading ability).

Figure 1. Only Effective Education Changes the Brain

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The figure above, which shows side views of the left and right hemispheres, depicts differences in brain anatomy (neocortical thickness) from before to after a summer reading intervention for struggling readers. There were no significant anatomical changes in the control group that did not receive the intervention or in the group that received the intervention but did not make reading progress (top). The group that did make reading progress (bottom) exhibited widespread thickening of the neocortex signified by the red/yellow coloration. Family socioeconomic status was the best predictor of which kids benefited.
The education-induced thickening of neocortex in the children who made progress in reading is curious because, in general, the human neocortex thins from early childhood into young adulthood. This thinning is thought to reflect massive pruning in the brain; many neurons and many connections between neurons are eliminated via development and experience so that only the most functionally valuable neurons and connections remain. From ages 4–22, however, a thicker neocortex is associated with both better academic achievement and higher SES (Hair et al., 2015; Mackey et al., 2015). We do not know what specific aspects of socioeconomic status influence brain development in children, though, because socioeconomic status is associated with so many factors, including school quality, home experience, healthcare, and nutrition.
Importantly, however, the summer reading study revealed profound brain plasticity in response to effective instruction, and this plasticity was greatest in children from lower socioeconomic status families.

Brain Measures that Predict Education Outcomes

In the studies I've highlighted, measures of brain changes corroborated reductions in stress and improvements in reading that could also be measured by questionnaires and by tests of reading ability. But can brain measures answer questions about effective educational practices better than questionnaires and tests? Some intriguing studies have shown that brain measures can uniquely predict which students will or will not benefit from an educational practice.
In one study, children with dyslexia were, around age 14, individually measured with tests of reading, language, and other abilities and also underwent MRIs (Hoeft et al., 2011). Then the same children were reexamined 2.5 years later to see how much they had improved in reading, specifically their accuracy and speed for reading single words and accuracy in paragraph comprehension. About half the children exhibited substantial gains in reading, while the other half persisted in their reading difficulties. Interestingly, none of the standard reading, language, or IQ measures predicted future reading gains, but the brain measures did predict students' future reading progress. In fact, the MRI measures were over 90 percent accurate in predicting whether an individual student would be in the improving group or the persistently struggling group 2.5 years later. Similarly, another study found that a brain measure (specifically the size and function of the right hippocampus, a brain structure important for memory) predicted which children would or would not benefit from a math-tutoring program far better than behavioral tests of math abilities or IQ (Supekar et al., 2013).
These brain imaging studies are the beginnings of an education neuroscience that may offer powerful insights in connection with personalized learning. Currently, teachers choose an instructional approach to use with a student struggling in reading or math without any evidence whether that specific approach will help that specific student. We only know if it did not work when, despite a teacher's best efforts, the student fails to show the hoped-for progress.
These MRI studies suggest that there may be something about a student that can be measured beforehand to predict if a student is likely or not to benefit from a particular instructional approach. While it may be unrealistic that students will be sent for MRIs to help a teacher choose an educational approach for each student, the MRI studies show that there is the possibility to better understand which students will benefit from which educational approaches (instead of the current trial-and-error practice). An ethically responsible research program that develops practical measures associated with the MRI measures could yield major progress in personalized learning for students in greatest need of effective instruction in core reading and math skills. Without the MRI measures that predicted future gains in reading and math, we would not know such prediction is possible.

What Brain Science May Contribute to Education

In my view, brain science should be a partner with psychological science and education research to build a firm scientific basis for understanding how students learn, and how they learn differently from one another. In medicine, there has been a strong and direct link between basic biomedical research in the laboratory and clinical practice in the medical office and hospital. There are many challenges in the pipeline from bench to bedside, but there is continuing growth of that pipeline. This growth is augmented by all physicians learning science and having both basic and clinical research occur in academic medical centers.
This has not been the historical evolution in education. Schools of education have been separated from the study of the human mind (psychological science) and human brain (neuroscience). We need a much more vigorous exchange of ideas and partnerships of action among educators and scientists to avoid the fog of neuromyths and to be realistic about what role neuroscience can play in education. The need for a better and deeper understanding of how students learn is urgent. On the socio-emotional side, there is a rising tide of mental health challenges for adolescents. On the academic side, the most recent reports from the National Assessment of Educational Progress reveal little progress over the past decades in reading or math scores, with persistent opportunity gaps for minorities. Neuroscience can offer limited, specific contributions to the learning sciences; but solid, valid research findings that are supported by both education and brain measures can offer teachers and school leaders a firm basis for how to best educate our children's minds and brains.

Reflect & Discuss

➛ How might findings from neuroscience inform your instructional practice?

➛ Does this article make you think differently about teaching or the future of learning?

➛ How could stronger links be created between educators and neuroscience researchers?

References

Bauer, C. C. C., Caballero, C., Scherer, E., West, M., Mrazek, M. D., Phillips, et al. (2019). Mindfulness training reduces stress and amygdala reactivity to fearful faces in middle-school children. Behavioral Neuroscience, 133(6), 569–585.

Burstein, B., Agostino, H., & Greenfield, B. (2019). Suicidal attempts and ideation among children and adolescents in U.S. emergency departments, 2007–2015. JAMA Pediatrics, 173(6), 598–600.

Caballero, C., Scherer, E., West, M., Mrazek, M. D., Gabrieli, C. F. O., & Gabrieli, J. D. E. (2019). Greater mindfulness is associated with better academic achievement in middle school. Mind, Brain, & Education, 13(3), 157–166.

Hair, N. L., Hanson, J. L., Wolfe, B. L., & Pollak, S. D. (2015). Association of child poverty, brain development, and academic achievement. JAMA Pediatrics, 169(9), 822–829.

Hoeft, F., McCandliss, B. D., Black, J. M., Gantman, A., Zakerani, N., Hulme, C. et al. (2011). Neural systems predicting long-term outcome in dyslexia. Proceedings of the National Academy of Sciences of the United States of America, 108(1), 361–366.

Macdonald, K., Germine, L., Anderson, A., Christodoulou, J., & McGrath, L. M. (2017). Dispelling the myth: Training in education or neuroscience decreases but does not eliminate beliefs in neuromyths. Frontiers in Psychology, 8(10), 1314.

Mackey, A. P., Finn, A. S., Leonard, J. A., Jacoby-Senghor, D. S., West, M. R., Gabrieli, C. F. O., et al. (2015). Neuroanatomical correlates of the income achievement gap. Psychological Science, 26(6), 925–933.

Romeo, R. R., Christodoulou, J. A., Halverson, K. K., Murtagh, J., Cyr, A. B., Schimmel, C., et al. (2018). Socioeconomic status and reading disability: Neuroanatomy and plasticity in response to intervention. Cerebral Cortex, 28(7), 2297–2312.

Supekar, K., Swigart, A. G., Tenison, C., Jolles, D. D., Rosenberg-Lee, M., Fuchs, L., et al. (2013). Neural predictors of individual differences in response to math tutoring in primary-grade school children. Proceedings of the National Academy of Sciences of the United States of America, 110(20), 8230–8235.

Twenge, J. M., Cooper, A. B., Joiner, T. E., Duffy, M. E., & Binau, S. G. (2019). Age, period, and cohort trends in mood disorder indicators and suicide-related outcomes in a nationally representative dataset, 2005–2017. Journal of Abnormal Psychology, 128(3), 185–199.

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