Implications of Neuroscience for Education

What Difference Does it Make? Implications of Neuroscience for Education

May 2011. The accompanying video presentation is available here.

When I applied to the Educational Psychology graduate program last year, I explained that my academic interests were focused on the question, “Are educational practices consistent with cross-disciplinary knowledge?” As I progressed through the program curriculum, I narrowed the scope of my “cross-disciplinary” objective to consider how the latest findings in neuroscience might inform educational theory and practice. The purpose of this paper is to provide an initial report regarding: 1) underlying attitudes or premises about how we think about the brain; 2) six findings from neuroscience that relate to learning; and 3) the consequences or implications of those findings, or what difference does neuroscience make for education?

How we think about the brain, mind, and all things psychological (constructs, behaviors, motivations, etc.) is dependent upon a critical underlying premise. That premise can be stated as a choice between accepting the notion of dualism, which differentiates the substance of “mind” from that of the brain, or rejecting dualism to instead ascribe functions of “mind” to the biological organ of the brain. This paper reflects the point of view of two Nobel laureates, Francis Crick and Eric Kandel, who reject the mind|brain dualistic dichotomy. Each ascribes the behaviors and functions of what are generally attributed to the “mind” to the brain (Crick, 1994; Da Cunha, 2009, Episode 1). In other words, from a scientific orientation, the brain exists as a biological entity whereas what we refer to as “mind” does not exist in a biological sense. The “mind” is more appropriately thought of as “the behavior of our brains” (Crick, 1994, p. 7) or “a series of functions carried out by our brains” (Da Cunha, 2009, Episode 1). Many people who do not consider themselves “scientific” may object to the boldness of this premise and counter with the argument that there must be more than just the brain to account for our thoughts, ideas, intuitions, etc. However, if one purports that position, one must be able to offer a competing theory or explanation — if not in the brain, where? From a scientific perspective, therefore, the hypothesis that “it’s all in the brain” provides a useful and appropriate attitude for understanding these six findings.

1. The brain is continually changing and, in a global sense, learning.

Anytime you engage in what is usually referred to as “learning,” you are also engaged in changing your brain. Virtually every experience you have and every behavior you exhibit results in some level of neural activity that causes structural, chemical, and electrical changes in your brain. Kandel notes that this ongoing change activity results in intellectual growth and also accounts for the impressive degree of plasticity exhibited by the brain in recovering from certain types of damage, injury, and disease (Da Cunha, 2009, Episode 1).

2. The brain constructs your sensory experiences of the world.

From a common sensical view point, we can easily lapse into the conventional understanding that we see and hear exactly what’s there to be seen and heard. We feel that our senses capture whatever sources may stimulate our attention — our eyes see, our ears hear. We accept easily understood analogies such as our visual system is like a camera and our hearing is like a tape recorder.

However, we now know that such common sensical feelings and analogies are naïve and mistaken. The “seeing” and “hearing” that we attribute to our eyes and ears is really the result of the brain processing sketchy and limited data of the outside world that is sensed, captured, and transmitted to the brain. The brain forms the experiences that you become aware of by taking this incomplete sensory data, looking for patterns that match previous experiences, making inferences to fill in the holes of missing data or unexpected patterns, before integrating the different inputs into a unified awareness.

Jeff Hawkins likens the activity in the brain (specifically the cortex) to a densely-packed network of fiber optic wires with a million points of contact. As incoming sense signals enter the brain to be processed, imagine the activated fiber optic network changing its illuminated patterns every millisecond. The patterns changes in both spatial and temporal dimensions and those changes, according to Hawkins, constitute the “currency of the brain … That’s what your brain works on. And believe it or not … your perception of the world is … really a fabrication of your model of the world. You don’t really see light or sound. You perceive it because your model says this is how the world is, and those patterns invoke the model” (J. Robert Oppenheimer Memorial Committee, 2009).

Christof Koch uses a visual demonstration to illustrate the effect known as afterimage. After staring for about twenty seconds at four brightly-colored squares (red, green, yellow, and blue) projected onto a screen, the image on the screen is suddenly changed and the viewer sees four different pastel colors — for a few seconds, then the viewer realizes that the image on the screen is actually four identical gray squares. The viewer has experienced an afterimage resulting from the visual system’s inability to immediately adjust to new input. Koch makes the point that what you see can be influenced by what you have just seen, and what you have just seen may cause you to not accurately see what is presented before you now. He concludes from this demonstration that, “ clearly this naive, realistic view that there’s a world, there’s my head and this simple mapping, it can’t be true” (J. Robert Oppenheimer Memorial Committee, 2005).

3. The brain includes a continuously-running simulator that anticipates motor behavior.

Have you ever tried to assist a waiter, burdened with a full tray of food and drinks, by taking your order from the tray, only to be rebuffed by the waiter who insists, “No thanks, I’ve got it.” Daniel Wolpert refers to this situation in a demonstration he calls the “waiter task,” which illustrates how the brain directs a simulation capability that operates in anticipation of motor behavior (Da Cunha, 2009, Episode 3). He explains that since the feedback capability in the motor system responds relatively slowly (about 250 milliseconds), for tasks that require much quicker responses (like hitting a tennis ball) the brain simulates the action and anticipates or predicts the response. So the brain anticipates the action of the muscles as well as the feedback returning to the brain in response to the action. When your waiter is holding the full tray, his motor system is controlling his muscles and exerting the proper force to suspend the tray. If you reach out and remove your drink, the waiter’s visual system and motor system brain cannot accurately estimate exactly when the weight and balance of the tray is going to shift. So depending on the particulars of how the tray is loaded, your good intentions to help may cost you and your fellow diners another thirty-minute wait, and your waiter a tray load of orders. But the waiter’s own brain simulation can anticipate exactly when his left hand is going to remove your glass from the tray such that the tray remains securely stable on his right hand.

Another brain capability related to both motor and sensory systems was identified by the discovery of mirror neurons by Italian neuroscientist Giacomo Rizzolatti. He observed that when an object such as a banana was offered to a laboratory monkey, the monkey reached for it, which triggered the firing of a certain neuron in the monkey’s brain. But Rizzolatti also discovered that a second monkey, who simply observed the first monkey reach for the object, also registered the same neuron firing in his brain. Rizzolatti isolated this “mirroring” activity to a particular type of neuron he called “mirror neurons.” In humans, these neurons are believed to play a pivotal role in one person being able to feel empathy for another. Rizzolatti also suggests they are necessary for the human ability to imitate others, enabling the perpetuation of rituals, traditions, and ultimately cultures (Da Cunha, 2010). Moreover, Kandel says there is evidence that mirror neurons may allow a child to more rapidly acquire language skills by watching the movement of the mother’s mouth as she speaks (Da Cunha, 2010, Episode 4).

4. The brain responds to stimulation, even when the stimulation is artificial.

The phenomenon known as “phantom limb” occurs when a person feels pain in the location of a limb that has been amputated. The patient experiences pain, but the attributed source of the pain is literally not there. This phenomenon manifested in a patient of neuroscientist V.S. Ramachandran, causing the patient excruciating pain in his phantom right hand. Ramachandran suspected that the brain might be trying to communicate through the motor system to the right hand, but in the absence of feedback from the phantom hand, the brain continue to send commands that could not be executed by the missing hand. He wondered if he could trick the patient’s brain by providing a visual illusion that provided apparent feedback. To test his hunch, Ramachandran constructed a simple box with an open top and two holes in the side in which the patient could insert his good left hand and the nub of his right arm without the amputated hand. In the center of the box, Ramachandran mounted an upright mirror such that the patient could look down at the mirror and see the reflection of his left hand, as if it were his right hand. The mirror illusion was powerful enough to fool the patient’s nervous system and the phantom pain went away, suggesting that “even pain can be a construct of the mind” (NOVA, 2001).

5. To focus attention on one thing, the brain actively suppresses attention elsewhere.

In researching the ability of the human visual system to track a moving object, neuroscientists have discovered two different types of neurons. One type of neuron focuses attention on the object, while the other works to actively suppress the background surrounding the object in order to further highlight the object. Neuroscience researchers, authors, and amateur magicians Stephen L. Macknic and Susana Martinez-Conde report that this mechanism has been exploited by magicians in the many ways in which they distract and misdirect their subjects’ attention in order to accomplish their ‘magical’ illusions (Macknic, Martinez-Conde, & Blakeslee, 2010).

6. Some language habits, such as grammar, take years to develop.

Using EEG imaging, researcher Helen Neville has shown that both adults and children as young as six years old can listen to a story and detect errors of meaning or words that don’t make sense within 200 milliseconds, localized in the posterior of the cortex. When the story narration includes grammatical errors, such as saying words in the wrong sequence or reversing nouns and verbs, adults can detect the errors even more quickly (within approximately 100 milliseconds) in a localized area on the left frontal lobe. However, the response of children to grammatical errors is slower and dispersed over a wide area of the cortex. Neville suggests that it may take 10-15 years for children to fully develop their grammatical recognition capabilities. She notes that this localized area in the left frontal lobe is adjacent to an area that appears to be critical to tool use and sequential planning: “It’s possible that one aspect of language is closely tied to tool use, especially this kind of action planning and sequencing that we have to do in order to talk” (THIRTEEN, 2010).

Researchers such as Patricia Kuhl have concluded that early exposure (prior to age 7) to non-native languages is critical for a child to most efficiently develop non-native language proficiency. She also suggests that language learning is strongly dependent upon the development of social learning skills that babies acquire when they are nine to ten months old. Studies indicate that babies of that age who are exposed to non-native phoneme sounds in the presence of others have no trouble discriminating those sounds. However, babies who are exposed to non-native phonemes from a television set do not learn to discriminate (Da Cunha, 2010, Episode 5).

Given these six findings, what difference does knowledge from neuroscience make — or could make — in educational theory and practice?

Beginning with the most general implications, two seem foundational for teachers, administrators, and policy makers. The first is that the brain (or all brains in the plural) is not a black box. Although neuroscientists would be the first to admit that much remains to be discovered and learned, much is known at present. Authority figures within education can no longer be content to cling to theories and practices based solely on speculative theories, observational studies, and “common sense.” Secondly, they should consider themselves as brain changers. To best teach, they must understand how the brains of children (and adults) change (or learn) in response to myriad environmental stimulations. Educational theory should most fundamentally be based on the fact that the brain naturally seeks to learn. Rather than thinking of education as the dispensing or depositing of “knowledge” into a child’s mind, formal education or schooling could be viewed as a socially-desirable means to guide the child’s natural brain development (learning) in a direction consistent with cultural and social ideals.

We should also recognize that even though we talk about “the brain” in generalized, or even universal, terms, each individual brain is unique. So while we can appropriately generalize about “the” brain’s anatomy, function, capability, and limitations, we should be aware that each brain is different and unique due to effects of genetics, environment, and life experiences.

At the level of the individual, this attitude of difference-within-similarity should become internalized within each child from the beginning of the formal educational process. Each child should develop an informed sense of how he/she is similar to others, but also that he/she is also different from others and unique unto him/herself. Each child should develop a sense of “to-me-ness” that acknowledges the sensations, feelings, descriptions, and experiences of “the world” he/she is aware of are created by his/her own nervous system. Each person experiences “the world” differently, no matter how similar our descriptions of our experiences of that world are.

Educational practitioners should help the individual exploit the learning capabilities inherent not only in the sensory system, but also the motor system. Combining these capabilities with those of mirror neurons, it seems clear that instructional techniques should not rely exclusively on cognitive activities, but also incorporate the manipulation of tools, instruments, and other aids, as well as watching and imitating behavioral models. While such techniques may be common in grades K-6, there is no reason why they should not continue to be effective even for adult learning. Particularly for learning non-native languages after age seven, watching a speaker may significantly facilitate learning over simply listening to the speaker.

The final implication to be made in this paper, and the most specific, applies to the development of individual language habits. If the conclusions from Helen Neville’s research are correct — that it takes years for a child to develop proficient grammatical recognition and localization — it seems logical to devote significant study to determine what kinds of grammatical structure are important to process and evaluate experiences, rather than adherence to grammatical standards that have evolved arbitrarily. Two practical examples of language habits that deserve study in this regard are to reduce reliance on to be verbs (is, am, are, was, etc.) and absolutistic terms (all, every, none, perfect, etc.) Such practices logically result from the “to-me-ness” of individual experience and the limitations of our imperfect nervous systems.

Teller, the normally mute half of the Penn & Teller magic act, makes his living by exploiting the facts, foibles, and limitations of the human nervous system. Like his fellow magicians, his on-stage objective is not merely to entertain the audience, but to lead them to the realization that “it’s really hard to understand the world” (Randall, 2011). For educational practitioners, their objective should be to make it easier for their audience to understand the world. Without a fundamental understanding of neuroscience and how “the” brain effects learning change, educators risk propagating misunderstandings of the world and, by extension, the individuals in that world. Therefore, whether or not educators embrace and incorporate the findings of neuroscience is indeed a difference that makes a difference.


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