What the Biology of the Brain Tells Us About Learning - ASCD
Skip to main content
ascd logo

December 1, 1993

What the Biology of the Brain Tells Us About Learning

Not a computer, but more like a jungle ecosystem, is how some scientists are conceptualizing the human brain. What implications does this revolutionary new theory have for the classroom?

An impenetrable skull and awesomely complex neural networks have long hampered our understanding of the developing three-pound brain that defines our profession. Our practical solution was to focus instead on the observable behaviors that emerged out of our brain's ill-understood cognitive processes. And so, behaviorism as well as various forms of professional folklore have dominated educational thought and practice. Over time, we discovered what behaviors would occur, but not why. For example, we knew that more boys than girls had reading problems, but we didn't know why.

Dramatic developments in brain research and imaging technology are rapidly advancing our understanding of the human brain. Scientists who use brain imaging technology now need only a few hours to gather some types of data from a normal human brain that formerly took 20 years of inferential laboratory work with nonhuman primates. Further, Functional Magnetic Resonance Imaging machines can now distinguish between neuronal groups that are only one millimeter apart (Blakeslee 1993).

These recent developments have sparked new brain theories, which, along with developments in genetics, may spark a Century of Biology, just as Albert Einstein's theories sparked the advancements in physics that have dominated this century.

The new biologically based brain theories focus on the developmental relationship between a brain's ancestors and its current environment: the nature-nurture issue. Our profession has tended to think of the nurture side as being dominant, but these new theories argue that nature plays a far more important role than previously believed. They also suggest that many current beliefs about instruction, learning, and memory are wrong. The theories will become culturally controversial because they will require reconceptualizations of such concepts as parenting, teaching, learning, identity, free will, and human potential. Further, some people may misuse the theories to support racist, sexist, and elitist beliefs. Certainly those who reject Darwinian evolution will be disturbed by the evolutionary base of the new theories.

When these brain theories and their strong supporting evidence shortly reach general public awareness, educators will be asked to comment on them. Because their thrust raises fundamental issues about our professional assignment, we'd better understand them.

Gerald Edelman's Theory of Neuronal Group Selection (or Neural Darwinism, as it's more commonly called) appears to be the most completely developed biological brain theory. Edelman has developed it through four books published since 1987. Bright Air, Brilliant Fire (1992) presents the most complete and informal explanation of Edelman's complex theory. This is the best resource for educators with a limited background in science (although it's still a bit of a stretch to read it). Michael Gazzaniga's Nature's Mind (1992) and Robert Ornstein's The Evolution of Consciousness (1991) provide a useful introduction to the issue in an informative, nontechnical way.

A Brief Introduction to Neural Darwinism

Our immune system is a sort of loose brain, in that most immune cells float free in our body, while our brain's neurons function within a highly interconnected web. Both systems are functionally similar, however, because both are highly integrated systems that respond to a wide variety of potentially helpful and hurtful stimuli. Out of the sensory information that reaches our skin's surface, our brain creates an internal mental model of external objects and events and then responds appropriately to friend or foe. Similarly, our immune system examines the shapes of antigens that invade our body and destroys those that pose any danger.

Gerald Edelman won the Nobel Prize in 1972 for his discovery that the immune system doesn't operate through an instruction/memory model, as had been thought, but rather through evolutionary natural selection procedures. The earlier belief was that generic antibody cells learned to recognize harmful invaders such as bacteria and viruses. The immune system then destroyed the antigens, and the system remembered the shape of the invader in the event of subsequent invasions. Edelman found, rather, that through natural selection processes occurring over eons of time, we are born with a vast number of specific antibodies that each recognize and respond to a specific type of harmful invader that shares our environment. If we lack such a natural immunity to a specific invader (such as the AIDS virus), we may die if infected. Our immune system can't learn how to destroy the invader; it simply has or hasn't the capacity at birth.

Edelman then studied our functionally similar brain to see whether it also operates principally on natural selection, rather than on instruction and learning. His controversial theory, Neural Darwinism, argues that our brain does operate on the basis of natural selection—or at least that natural selection is the process that explains instruction and learning.

A New Brain Model

We tend to use simple models to understand complex phenomena, but these models sometimes hinder our understanding. The computer is the prevailing (and an appealing) model of our brain, but Edelman argues that it's inappropriate because a computer is developed, programmed, and run by an external force and our brain isn't. (Terms such as teacher and parent come to mind as the programmers for our brain.) A computer model biases our thoughts toward a filing system that differs significantly from the way our brain processes information. Further, the powerful role that emotion plays in regulating brain activity, and the preponderance of parallel (rather than linear) processing in our brain, all suggest to Edelman that a useful model for our brain must come out of biology, not technology.

Edelman suggests a better model. He proposes that the electrochemical dynamics of our brain's development and operation resemble the rich, layered ecology of a jungle environment. A jungle has no external developer, no predetermined goals. Indeed, it's a messy place characterized more by organic excess than by goal-directed economy and efficiency. No one organism or group runs the jungle. All plants and animals participate in the process, each carrying out a variety of ecological functions. A tree is a single organism, but it also participates in many symbiotic activities with other organisms (such as insects, birds, vines, and moss). It doesn't develop its limbs as a nesting site for birds, but birds use the limbs.

Further, the jungle environment doesn't instruct organisms how to behave in an ecologically appropriate manner—for example, by teaching trees how to position their limbs and roots to get sunlight and soil nutrients. It's more a matter of natural selection, in an evolutionary sense. All trees have the innate capacity to reach the sun and soil nutrients, and those that do it successfully thrive and reproduce. Those that do not, die, and other organisms take their place. An environment doesn't inform its organisms how to change so that they'll increase their ability to survive. Evolution works by selection, not instruction. The environment selects from among the built-in options available—it doesn't modify (instruct) the competing organisms.

From Model to Brain

So it is with our brain, the theory argues. Think of the vast number of highly interconnected neural networks that make up our brain as the neural equivalent of the complex set of jungle organisms responding variously to environmental challenges. The natural selection processes that shape a jungle over long periods of time also shape our brain and its neural networks within our lifetime.

Our brain is made up of tens of millions of relatively small basic neural networks, and just as each type of immune antibody responds to a specific environmental antigen, so each neural network processes a very specific element of the external world—a single sound, a diagonal line. Various interconnected combinations of these networks process more complicated related phenomena—from phonemes and triangles to words and pyramids.

Thus, we have a modular brain, in that a relatively small number of standard nonthinking components combine their information to create an amazingly complex cognitive environment. For example, when we observe a red ball rolling along a table, our brain processes the color, shape, movement, and location of the ball in four separate brain areas.

It's not yet clear how the complex communications among four such areas result in our brain's creation of a unified picture of a rolling red ball—but then, it's also not all that clear how the members of a jazz quartet communicate with one another as each improvises separately on a simple theme and the group creates a unified song out of the separate efforts.

Genetic processes that evolved over eons of time create a generic human brain that is fully equipped at birth with the basic sensory/motor components a human needs to function successfully in the normal physical world. Our species needs to hardwire its basic survival networks (for example, circulation, respiration, reflexes), but individuals also need the flexibility of adaptable or softwired networks, so that they can respond to specific environmental challenges (to learn French or to drive a car).

An infant brain doesn't have to learn how to recognize specific sounds and line segments; such basic neural networks are operational at birth. We don't teach a child to walk or talk; we simply provide opportunities for adaptations to an already operational process.

Gazzaniga (1992) argues that all we do in life is discover what's already built into our brain. What we see as learning is actually a search through our brain's existing library of operating networks for the combinations of those that best allow us to respond to the immediate challenge (much as college students in a library select and synthesize materials from pre-existing sources to write their term papers).

On the other hand, our DNA couldn't possibly encode our brain's networks for every possible combination of sights/sounds/smells/textures/tastes/movements that our brain can process. Instead, it encodes a basic developmental program that regulates how neurons will differentiate and interconnect. The fetal brain thus develops general areas that are dedicated to various basic human capabilities within a certain range of variation, such as our ability to process language. Infant brains are born capable of speaking any of the 3,000+ human languages, but they're not born proficient in any of them.

When infants begin to interact with the local language, their brains can already recognize the sounds of the language. The larger neural networks that process the specific language they'll speak form as the various combinations of sounds in the language occur frequently. The amount of use selectively strengthens and weakens specific language networks. The networks for sounds that aren't in the local language may atrophy over time, for lack of use, and/or be used for other language purposes. Scientists call it “neural pruning.” A good example is the difficulty that adult Japanese have with our l and r sounds, which aren't in their language. A Japanese adult who learned English as a child would have no trouble with the two sounds.

To those who argue that they taught their child to speak a language, the theories ask, in effect, “When and how did you teach your child your native accent, prepositional phrases, and the rules for forming the past tense?” Further, children master most of the complexities of grammar with practically no explicit instruction from their parents (although it's obvious that extensive parent/child verbal interactions do provide an important environment for language development).

Thus, learning becomes a delicate but powerful dialogue between genetics and the environment—the experience of our species from eons past interacts with the experiences we have during our lifetime. Our brain is powerfully shaped by genetics, development, and experience—but it also then actively shapes the nature of our own experiences and of the culture in which we live.

Parenting and teaching are probably something like a facilitating agent, but it's not yet clear how these theories will eventually reconceptualize such concepts. Hubel (1988) certainly underscored the important role adults play in facilitating stimulating early life experiences when he studied the development of the visual cortex in kittens. Kittens reared in a research environment that lacked certain specific line orientations (such as vertical or horizontal lines) suffered a dramatic decline in the viability of the neural networks that normally process the type of line orientation that had been eliminated from the kitten's experience.

Technology as a Solution to Biological Problems

Unfortunately, biological evolution proceeds at a much slower pace than cultural evolution. Thus, we're forced to grapple with current social and environmental issues with a brain that biological evolution has tuned to the far different cognitive challenges of 30,000 years ago. At such a time, physical dangers were signaled by rapid changes in the environment, not by gradually developing problems (like pollution, overpopulation, and acid rain).

Part of the problem is that evolutionary modifications occur within the existing biological system. Evolutionary processes don't dismantle an existing mechanism, such as our brain, and start again from scratch. Evolutionary modifications may therefore differ considerably from what intelligent engineers might have developed if they could have redesigned our brain from scratch to meet current needs (Churchland and Sejnowski 1993).

We've compensated by seeking technological solutions to our current problems. In effect, we've added a layer of technological brain (for example, autos, books, computers, and drugs) outside of our skull—a layer that continually interacts with our internal biological brain. But each such technological advance also creates new human problems. Our profession will be challenged to reconceptualize formal education as new brain theories evolve, and then to discover how best to reset our brain during its development so that humans might one day develop sound biological solutions to many technological problems that currently seem to defy solution (Sylwester 1990, Sylwester and Cho 1992/93).

The Biological Nature of Consciousness

Neural Darwinism seeks to define the biological nature of consciousness, a very important, but formidable challenge for any brain theory.

Edelman divides consciousness. Primary consciousness is a state of being mentally aware of objects and events currently in the immediate environment. But these mental images aren't accompanied by any sense of being an organism with a past or future. An animal with primary consciousness sees a room the way a beam of light illuminates it—with an awareness of only the illuminated areas, and with no ability to connect what it sees to other areas. Edelman calls it the remembered present. Primary consciousness does, however, permit a brain to create a complex mental scene that connects the immediate perceptions of a situation to the parts of the brain that process such survival values as food, light, and warmth—and so it takes a very subjective (that is, eat-or-be-eaten) view of everything it confronts.

Higher-order consciousness is perhaps a distinctly human condition that allows us to build on primary consciousness—going beyond it to recognize our own personal actions and values. It uses language and other symbols in such processes as reflection and generalization that can emotionally detach us from the here and now, and lead us into purely imaginative mental scenes. It suggests a new linking of the brain areas that process primary consciousness to the areas of symbolic memory and conceptualization—to add the past and future to the present, and a sense of the inner self to the world out there.

Thus, memory combines a built-in species bias for such values as food, warmth, and survival with current short-term events. Long-term memory is an adaptive (but currently ill-understood) cognitive technique that operates within a single lifetime. It's a necessary capability in order to direct conscious behavior from within—to get beyond pure stimulus/response behavior. Laws and traditions become cultural memories that can last beyond a single lifetime.

Seeking Educational Applications

Finding practical educational applications in Edelman's theory is difficult at this point. Applications will come later, after the kind of study that leads to such understanding.

His model of our brain as a rich, layered, unplanned jungle ecosystem is especially intriguing, however, because it suggests that a jungle-like brain might thrive best in a jungle-like classroom that includes many sensory, cultural, and problem layers that are closely related to the real-world environment—an environment that best stimulates the neural networks genetically tuned to it.

The classroom of tomorrow might focus more on drawing out existing abilities than on precisely measuring a student's success with imposed skills; encourage the personal construction of categories rather than impose existing categorical systems; and emphasize the individual, personal solutions of an environmental challenge—even if inefficient—more than the efficient group manipulation of symbols that merely represent the solution. Educators might then view classroom misbehavior as an ecological problem to be solved within the curriculum, rather than aberrant behavior to be squashed. The curriculum might increase the importance of such subjects as the arts and humanities, which expand and integrate complex environmental stimuli, and deemphasize basic skills and forms of evaluation that merely compress complexity.

The “brain-based” curriculum might resemble some current practices, but it may also differ considerably from what schools are now doing. To muse on such recent widely acclaimed developments as thematic curriculums, cooperative learning, and portfolio assessment is interesting; all require more effort from teachers than do traditional forms of curriculum, instruction, and evaluation. Is the appeal to educators that these seem to be inherently right for a developing brain, even though they require more professional effort, and aren't nearly as economical and efficient as traditional forms?

For now, Edelman and his growing band of fellow brain theorists provide us with rich (and, at times, jungle-like) book environments for professional reading and contemplation. The theories will continue to develop, and educational leaders must enter into the process now, or else biologists may well redefine our profession for us.

References

Alkon, D. (1992). Memory's Voice: Deciphering the Mind-Brain Code. New York: Harper-Collins.

Blakeslee, S. (June 1, 1993). “Scanner Pinpoints Sites of Thought as People See or Speak.” New York Times, Section C, 1 and 3.

Calvin, W. (1990). The Ascent of Mind: Ice Age Climates and the Evolution of Intelligence. New York: Bantam.

Cytowic, R. (1993). The Man Who Tasted Shapes. New York: Putnam.

Dozier, R. (1992). Codes of Evolution: The Synaptic Language Revealing the Secrets of Matter, Life, and Thought. New York: Crown.

Edelman, G. (1992). Bright Air, Brilliant Fire: On the Matter of the Mind. New York: Basic Books.

Gazzaniga, M. (1992). Nature's Mind: The Biological Roots of Thinking, Emotions, Sexuality, Language, and Intelligence. New York: Basic Books.

Harth, E. (1993). The Creative Loop: How the Brain Makes a Mind. Reading, Mass.: Addison-Wesley.

Hubel, D. (1988). Eye, Brain, and Vision. New York: Freeman, pp. 191–217.

Ornstein, R. (1991). The Evolution of Consciousness: The Origins of the Way We Think. New York: Simon and Schuster.

Rose. S. (1992). The Making of Memory: From Molecules to Mind. New York: Doubleday.

Sacks, O. (April 8, 1993). “Making Up the Mind.” The New York Review of Books: 42–49. (An excellent extensive review-essay of Bright Air, Brilliant Fire.)

Sylwester, R. (October 1990). “Expanding the Range, Dividing the Task: Educating the Human Brain in an Electronic Society.” Educational Leadership 48, 2: 71–78.

Sylwester, R., and J-Y. Cho. (December 1992/January 1993). “What Brain Research Says About Paying Attention.” Educational Leadership 50, 4: 71–75.

Churchland, P., and T. Sejnowski. (1993). The Computational Brain. Cambridge, Mass.: MIT Press.

Donald, M. (1991). Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition. Cambridge, Mass.: Harvard.

Edelman, G. (1987). Neural Darwinism: The Theory of Neuronal Group Selection. New York: Basic Books.

Edelman, G. (1988). Topobiology: An Introduction to Molecular Embryology. New York: Basic Books.

Edelman, G. (1989). The Remembered Present: A Biological Theory of Consciousness. New York: Basic Books.

Kosslyn, S., and O. Koenig. (1992). Wet Mind: The New Cognitive Neuroscience. New York: Free Press.

Rosenfeld, I. (1988). The Invention of Memory: A New View of the Brain. New York: Basic Books.

Rosenfeld, I. (1992). The Strange, Familiar, and Forgotten: An Anatomy of Consciousness. New York: Knopf.

Scientific American. (September 1993). “Life, Death, and the Immune System.” (A special issue devoted to recent developments in immunology.)

Wills, C. (1993). The Runaway Brain: The Evolution of Human Uniqueness. New York: Basic Books.

ASCD is a community dedicated to educators' professional growth and well-being.

Let us help you put your vision into action.