Best years ahead for the adult brain
Neurology is providing new insights into how the brain works and develops, literally illuminating how the mind learns at different stages of life. These emerging discoveries are providing a scientific focus that some physical scientists believe will relegate learning theory to the historical dustbin by demonstrating what is happening in the brain and showing the biological processes involved with receiving, storing, and processing information (Kagan, 2008). Likewise, using the input>process>output model of the computer, cognitive psychology is providing a scientific foundation on the structure and function of mental processes that account for human behavior, and providing images of how and where learning occurs in the brain (Hunt & Ellis, 2004).
Particularly important for adult learners, neuroscience is demonstrating that theorists like Freud, Piaget, and Erikson were wrong when they concluded that adulthood marked the end of development and the beginning of decline to death. To the contrary, Cohen (Cohen, 2006) argues that neurology is showing how adulthood is a "time of new possibility" with immense potential to nurture. Cohen said, "It's time we stopped dismissing middle age as the beginning of the end… At 40, the brain's best years are still ahead" (p. 82). Cohen's assertion does not seem to be just "feel good" optimism for fogies; he bases his conclusions on a growing amount of evidence from neuroscientists.
The dynamically developing adult brain
A recent update of dynamic skills theory illuminates the workings of the adult brain, providing insights and suggesting tools for supporting adult learning. Fischer (2007) has integrated his dynamic skills theory with emerging cognitive neuroscience and dynamic systems theory to propose a dynamic skills framework that shows how "thinking and learning relate to physical changes in the brain" (Fischer & Rose, Growth cycles of brain and mind, 1998, p. 56) and that provides a toolkit for showing how development, context, learning, and emotion intertwine to change behavior (2007).
Dynamic skills theory rejects traditional theories that separate logic from emotion and organism from environment, asserting that these traditionally dichotomous categories collaborate to produce human thought and behavior. Dynamic skills theory also rejects classical stage views of development because they lump people into rigid categories that do not account for the complex and diverse nature of human behavior. As described by Fischer and Rose (1998): "In the dynamic skills framework, development is much more variable and flexible and shows complex, dynamic patterns of change with many of the properties described by mathematical theories of complexity, chaos, and catastrophe" (p. 56). Rather than developing in a linear or stepped path, Fischer demonstrates how individuals exhibit complex developmental patterns with interacting cycles of brain growth, cognitive development, and learning. Fischer asserts that "all three cycles seem to involve a common process of growth, and one outcome of the research on these growth patterns is the discovery of a general ruler for development and learning that has many uses in educational assessment and practice" (2007, p. 2). These growth cycles repeat several times, with each cycle presenting "new capacity for thinking and learning that appears to be grounded in an expanded, reorganized neural network". This means that people can learn and relearn skills, and reshape their brains throughout life—especially if they have "strong contextual support, like that from a teacher, a tutor, or a text. Without such support, most thinking and learning occur at lower levels, not at optimal levels" (1998, p. 56).
Fischer uses a developmental web as a metaphor to show how development occurs on multiple parallel strands rather than through linear stages. Using multiple intelligence theory as an example, a child develops different intellectual domains for language, logic and math, music, physical coordination, pattern recognition, interpersonal relations, and intra-personal relations (Gardner, 2006). Within each of these domains, the individual constructs new skills, with each new skill represented by a new strand. Each new skill branches to form an increasingly complex and skill set that may branch and connect with other strands to form an increasingly complex developmental web (Fischer K. W., 2007).
The cyclical development demonstrated by Fischer continues into the mid-twenties, when the frontal lobe becomes fully developed, hard wiring the individual for maturity. However, this is not the end of brain development. In addition to remaining pliable throughout life, Cohen (2006) points to research showing that at least one major developmental phase occurs in the mid-forties, when the left and right hemisphere become more fully integrated. The increased network connections and flow of information between the right and left hemispheres create capacity for greater creativity, while dampening negative emotions. While the individual becomes hardwired for maturity in the mid twenties, the individual seems to become hardwired for wisdom in the mid forties.
Beyond this developmental cycle, the adult brain continues to rewire itself, grow new cells, and create new connections. Showing full color images of thousands of neurons being born each day in transgenic mice, Harvard Medical is providing graphical images of how behavior and environment may influence brain development (Livet, et al., 2007). While the researchers remain unclear about how the new cells connect with the old, they believe that tracing connections may help understand how experience gets transferred from short-term to permanent memory and how memory stealing diseases advance.
Additional research showing the dynamically developing adult brain comes from research at Johns Hopkins Medicine (2008), which demonstrates how mature neurons retain a youthful form of plasticity called motility. The firm trunk of a neuron grows upwards, but extends branches, axons, that spread sideways into the cerebellum, which helps to coordinate movements and sensory information. Rather than being fixed, these branches sway “like kite tails in the wind”, while growing and shrinking. The researchers believe the motility of neurons provides a secondary mechanism for conveying information beyond traditional synapse, and may assist in nerve regeneration.
The ongoing developmental potential of the brain does not mean that the adult continues to learn. Science has also confirmed the "use it or lose it" adage, "showing that the brain grows stronger from use and challenge" (Cohen, 2006, p. 82). The inverse means that the brain starts to decay when the adult stops to actively develop it. In other words, declarations that adulthood is a period of decline can be correct for those who stop learning; the day an individual stops learning is the day the individual’s brain starts to die.
Citing evidence for the “use it or lose it” adage, University of South Wales Researcher Michael J. Valenzuela (Valenzuela, 2005) declares, "It is never too late to build brain reserve." In an international meta-analysis that integrated data from 22 studies and 29,000 subjects, Valenzuela found that complex mental activity throughout life keeps the brain healthy and growing, while reducing risk of dementia by nearly 50%. In other words, adults who actively engage in education, have intellectually challenging jobs, and who engage in a mentally stimulating lifestyle are more likely to keep their brains healthy, reducing the risk of Alzheimer's and other degenerative brain diseases. This brain reserve is neither static nor influenced by early life experiences, adults can built brain reserve at any stage of life. Valenzuela found that "after five weeks of memory-based mental exercise, participants increased brain chemistry markers in the opposite direction to that seen in Alzheimer's disease" (Valenzuela, 2005).
Similarly, research on the brains of Catholic nuns conducted at Rush Alzheimer's Disease Center report found that active learning seems to protect the brain, with a 1% increase in cognitively stimulating activities reducing the risk of Alzheimer’s disease up to 33% (Rush University Medical Center, 2002). A key finding in the Rush research points to repetition as a means to improve cognitive skills and prevent brain damage.
The implications of such findings are significant for adult education. While many adults enter formal learning activities to enhance career opportunities or meet some immediate need, engaging in active learning activities may be a key to longevity, health, and survivability. Of course, the adult is more than just a brain and brain productivity and longevity require more than brain exercise. Research is increasingly connecting physical and psychological health of adults with brain productivity and health. In other words, what is good for the body and the sole also seems to be good for the brain. Exercise, diet, resilience, personal choice, environment, and genetics also play significant roles in brain development.
Researchers are finding that the busiest period for the brain seems to be during sleep (Stickgold & Ellenbogen, 2008). During sleep the brain performs vital database functions that process experiences from the day; sifting, categorizing, relating relevant information, and discerning or disregarding irrelevant information. This database function strengthens memory and aids in problem solving. Memories are created by changing the strengths of connections among millions of neurons, which increases the likelihood that patterns of activity will occur. When an individual activates these patterns of activity, he or she recalls a memory. The brain cells that fire together wire together, which locks the pattern for recall. While people sleep, the brain reactivates the patterns of neural activity that it performed during the day. The unconscious activity selectively rehearses difficult aspects of tasks we performed, activates analysis of new memories, enables problem solving, and infers new information. In short, the brain learns while the individual sleeps. Missing a night’s sleep can compromise memory and disrupt cognitive processes that are vital for learning.
Researchers are finding that what is good for the body tends to also be good for the brain. Diet and exercise have long been understood as ways to keep the body healthy, but are now being connected to brain performance and longevity (Anthes, 2009). Exercise increases blood flow to the brain, delivering oxygen to the neurons. The blood also delivers chemicals necessary for brain development and performance. Called brain-derived neurotrophic factors, these chemicals encourage growth of brain cells, promote survival of neurons, and facilitate communication. Likewise, diet may affect brain performance and longevity, with researchers identifying vegetables and Omega-3 fatty acids as “brain superfoods”. Fruits and vegetables provide antioxidants that counteract atoms that damage neurons, while the Omega-3 fatty acids, like those found in fish, nuts, and seeds, feed the fatty acids in the brain and may help to offset depression, schizophrenia, Alzheimer’s disease, and other disorders.
While pop culture identifies stress as a culprit underlying inability to effectively learn, rising depression rates, heart attacks, rising obesity, and soaring health costs, neuroscientists Kelly Lambert (2008) suggests that “cushy, digitally-driven, contemporary lifestyles… may be at the root of soaring depression” (p. 32). Lambert believes that the brain is hardwired to derive satisfaction from meaningful action that comes from effectively managing complex and challenging tasks. In other words, rising affluence seems to directly correlate with decreasing resilience; what should be a stepping stone seems to be a crutch for some people.
Criticisms and applications
While emerging findings in brain research introduce compelling opportunities for adult learners and educators, influential researchers argue that these discoveries have not translated into practical applications supported by research (Fischer & Immardino-Yang, 2008 [in press]; Merriam, Caffarella, & Baumgartner, 2007; Bruer, 1997). Some educators have developed brain based learning programs that attempt to identify and apply principals derived from knowledge about how the brain works. However, just as adult education practice has introduced disruptive processes and philosophies that threaten traditional education, emerging models from brain research seem to be challenging the way people think about learning, while providing fodder for opportunists to promote questionable programs cloaked in scientific terminology.
From a traditional education perspective, Bruer (1997) declares that “we do not know enough about brain development and neural functions to link that understanding… to educational practice” (p. 4). Likewise, Fischer, and Immordino-Yang (Fischer & Immardino-Yang, 2008 [in press]) have written extensively about the potential their emerging brain research provides for learning practice, but assert that “most of what is called ‘brain based education’ today has no grounding at all in brain or cognitive science” but is merely “beliefs about learning and schooling restated in the language of brain science” (para. 8). Merriam, et al seem to concur, limiting their discussion on brain based education to examples of programs that incorrectly interpret the available research. For example, one program purports to help adults maximize the functioning of the left and right hemispheres, while it promotes the debunked myth that reason and emotion reside in separate hemispheres.
Resistance and hucksters aside, even the most skeptical educator might agree with neuroscientist Jeanette Norden (2007) when she says “everything we see, hear, feel, and think, and all that we do, is the result of underlying brain processes.” Given the vital role the brain plays in learning, it seems educators should be able to justify classroom strategies with available research. For example, one teacher may adhere to the Piagetian philosophy that the child learns best when he or she is left to explore as a lone scientist (Piaget & Inhelder, 2000), while another may adhere to Vygotsky’s philosophy that a child learns best when he or she collaborates with adults (Watson, 2002). Both of these instructors may benefit by reviewing Fischer’s (2007) integration of neurology with dynamic skills theory to show that children can develop steadily alone as their brains develop new capacity, but that their learning can accelerate if they actively engage with knowledgeable adults when their brains develop new neural networks--and that the connections in those neural networks can fade if they are not developed.
In addition to highlighting that science is showing how brain plasticity allows adults to learn throughout life and how environmental factors influence learning, Norden (2007) says that current brain research shows that “our ability to feel, to reason, to abstract, or even to be moral are the result of underlying neural mechanisms” (pp. 3-141) Understanding how these mechanisms work can provide adult learners and educators with strategies and tools for building fulfilling lives and relationships through perpetual learning.
Anthes, E. (2009, February/March). Six ways to boost brainpower. Scientific American Mind , pp. 56-63.
Bruer, J. T. (1997). Education and the brain: A bridge too far. Educational Researcher , 4 (16), 4-16.
Cohen, G. (2006, January 16). The myth of the midlife crisis. Newsweek , pp. 82, 84-86.
Fischer, K. W. (2007). Dynamic cycles of cognitive and brain development: Measuring growth in mind, brain, and education. In A. M. Battro, K. W. Fischer, & P. J. Léna, The educated brain. Cambridge, U.K.: Cambridge University Press.
Fischer, K. W., & Immardino-Yang, M. H. (2008 [in press]). The fundamental importance of the brain and learning for education. In J.-B. Publishers (Ed.), Jossey-Bass reader on the brain and learning. San Francisco: Jossey-Bass Publishers.
Fischer, K. W., & Rose, S. P. (1998). Growth cycles of brain and mind. Educational Leadership , 56 (3), 56-60.
Gardner, H. (2006). Multiple intelligences: New horizons (2nd ed.). New York: Basic Books.
Hunt, R. R., & Ellis, H. C. (2004). Fundamentals of cognitive pscychology (7th ed. ed.). New York: McGraw Hill Higher Education.
Johns Hopkins Medicine. (2008, November 8). Adult brain cells are movers and shakers. Retrieved January 22, 2009, from Johns Hopkins Medicine: http://www.hopkinsmedicine.org/Press_releases/2007/11_08_07.html
Kagan, J. (2008, December). Understanding our personalities requires a lesson in history. (A. Novotney, Ed.) Monitor on Psychology , 39 (11), pp. 26-27.
Lambert, K. (2008, August/September). Depressingly easy. Scientific American Mind , pp. 30 -36.
Livet, J., Weissman, T. A., Kang, H., Draft, R. W., Lu, J., Bennis, R. A., et al. (2007). Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature (450), 56-62.
Merriam, S. B., Caffarella, R. S., & Baumgartner, R. S. (2007). Learning in adulthood: A comprehensive guide. San Francisco: John Wiley & Sons, Inc.
Norden, J. (2007). Understanding the brain (Vols. 1-3). Chantilly, Virginia: The Teaching Company.
Piaget, J., & Inhelder, B. (2000). The psychology of the child (2nd ed. ed.). (H. Weaver, Trans.) New York: Basic Books.
Rush University Medical Center. (2002, February 12). Participation in mentally stimulating activities is associated with a lower risk of alzheime's disease. Retrieved January 13, 2009, from rush.edu: http://www.rush.edu/webapps/MEDREL/servlet/NewsRelease?id=300
Stickgold, R., & Ellenbogen, J. M. (2008, Auguts/September). Quit! Sleeping brain at work. Scientific American Mind , pp. 23-29.
Valenzuela, M. J. (2005). Brain reserve: A three year longitudinal neuropsychological and brain imaging examination of the "use it or lost it" principle. University of South Wales, School of Psychiatry. South Wales: University of South Wales.
Watson, M. W. (2002). Theories of human development (Vol. 1). Chantilly: The Teaching Company.