Music, the Brain, and Learning

Relax and let the music flow through you.

Wait! Is that really what happens? What does listening to your favorite music reveal about your brain? Quite a bit, actually! In This is Your Brain on Music: The Science of a Human Obsession, author and neuroscientist Daniel J. Levitin traces the brain’s processing of heard music.

Two cognitive processes, feature extraction and feature integration, create the experience of hearing music. Interestingly, these processes mirror two processes, comprehension and elaboration, that enable learning.

Feature extraction happens in the brain’s posterior regions. As sound waves cause the eardrum to vibrate, the brain receives sensory input. “The brain extracts basic, low-level features from the music, using specialized neural networks that decompose the signal into information about pitch, timbre, spatial location, loudness, reverberant environment, tone durations, and the onset times for different notes (and for different components of tones)” (p. 103). As feature extraction begins, feature integration also activates.

In the brain’s frontal areas, feature integration integrates the extracted features “into a perceptual whole” (p. 105). According to Levitin, the brain constructs a “represenation of reality” from the component features identified during feature extraction (p. 103). That representation is what you experience, the music you actually “hear.”

What can this tell us about learning? First, note the basic processing of music. Individual components of sensory data are identified first as the brain perceives “elemental or building-block attributes of a sensory stimulus” (p. 104). The brain first identifies, sorts, and labels new sensory data. This “low-level processing” is followed by “higher-level” processing. The brain’s frontal regions construct meaning from the sensory data’s “building blocks.” The basic elements form patterns that the brain recognizes, attributing meaning and significance to the sensory data. The brain receives data, sorts and identifies data, and constructs meaning from the data.

Second, note the necessity of both processes for the sensory data to become meaningful. If the brain only engaged in feature extraction, listening to music would generate a frustrating amount of isolated data. Coherence and meaning would be lost, and music as we experience it would not exist. Now transfer this to learning. Memorizing data on its own, void of any higher-level processing, produces the elemental building blocks of understanding. However, understanding cannot be achieved solely through feature extraction. As the brain must engage both processes to experience music, the brain must also engage both process to construct understanding of new instructional material.

And you thought the music just flowed through you!

Levitin, Daniel J. (2007). This is your brain on music: The science of a human obsession. New York: Plume.

Elaboration: Thinking Differently to Deepen Learning

Wiggins and McTighe (2006) define understanding as “a realization that the learner experiences about the power of an idea” (p. 27). Understanding enriches a learner’s ability to function successfully, influencing decision making, critical thinking, evaluation, and several other beneficial cognitive processes. The potential power of an idea is only available to the individual who understands the idea.

Understanding differs from knowledge. For example, common knowledge recognizes that conditions on the moon differ from those on earth, but only understanding those conditions can create the craft and clothing needed to explore the lunar surface. Knowledge recognizes facts; understanding constructs a web of connections that give knowing practical and creative value.

Unfortunately, the typical cycle of teaching, testing, and moving to new topics can overlook elaboration, the cognitive process that constructs understanding. Learners construct deep understanding when they process the same ideas in multiple representations. Howard Gardner’s (2006) multiple intelligences offer one index of representational variety. Gardner’s nine intelligences include:

• linguistic: ideas represented in spoken or written language
• logical-mathematical: ideas represented numerically or in an analysis of “what has happened, and what may happen, under various scenarios” (p. 32)
• musical: ideas represented through heard or produced music
• spatial: ideas represented in spatial organizations, such as flow charts and concept maps
• bodily-kinesthetic: ideas represented through physical stances and movement
• naturalist: ideas represented in taxonomies of natural elements
• interpersonal: ideas represented in characterizations, exploring individuals’ distinctives, motivations, and needs
• intrapersonal: ideas represented in self-awareness elements, such as “feelings, goals, fears, strengths, and weaknesses” (p. 39)
• existential: ideas represented in “the biggest questions,” such as those found in “religious, artistic, philosophical, and mythic” systems of thought (p. 41)

During elaboration, teachers can engage understanding’s constructive processes by engaging students in rethinking new content via alternate representations. For example, linguistic intelligence likely provided the means of content transmission as students heard the spoken words of the teacher’s lectures and read the written words of the textbook. During elaboration, the teacher could engage the students in reviewing the new content’s critical details in preparation for re-presenting the ideas in an alternate form. How would the phases of the American Revolution sound musically? How would a model of the human ear look if constructed from students’ bodies? How would a spatial representation of a mathematical equation look?

Note what the learner must do in response to such challenges. The original material must be reviewed in such a way that connections between it and elements of the new representation emerge. These connections, which arise from the learner’s life experience, create a web that forms the infrastructure of understanding. In transforming the resulting representation back to linguistic forms via an explanation, the same processes recur. The connections strengthen, the understanding deepens, and what was merely knowledge becomes beneficial apprehension.

While rich with possibility, Gardner’s multiple intelligences present only one of many possible tools for developing instructional activities that engage elaboration. Research indicates that memory formation and creative thinking activate similar brain structures (Miller, 2007). Creative experiences can form effective reference points for constructing new understanding, and processes of creativity can spark elaborative thinking.
In a penetrating study, Robert and Michèle Root-Bernstein (2001) identify thirteen “thinking tools” employed by creative individuals. These tools cross disciplines, and creative breakthroughs in multiple professional fields illustrate their influence. The tools include:
observation: perceiving fully through “concentrated attention” (p. 32)
imaging: visualizing or imagining things not in the immediate environment
(p. 51)

• abstracting: reducing “complex visual, physical, or emotional ideas” to their essence, “revealing, through simplicity, the power of purity” (p. 72)
• recognizing patterns: discerning “connections between things previously perceived as being unrelated” (p. 94)
• forming patterns: merging two or more elements to compose a “synthetic pattern that may be much more than, and far different from, the sum of its parts” (p. 115)
• analogizing: identifying “a functional resemblance between things that are otherwise unlike” (p. 137)
• body thinking: attending to “the feel of muscle movement or physical tension or touch” (p. 162) (Note the similarity to Gardner’s bodily-kinesthetic intelligence.)
• empathizing: perceiving, feeling, thinking, and/or acting as if one were someone else (p. 182) (Note the similarity to Gardner’s interpersonal intelligence.)
• dimensional thinking: “moving from 2-D to 3-D or vice versa; mapping, or transforming information provided in one set of dimensions to another set; scaling, or altering the proportions of an object or process within one set of dimensions; and conceptualizing dimensions beyond space and time as we know them” (p. 204) (Note the similarity to Gardner’s spatial intelligence.)
• modeling: rendering concepts “immediately perceivable in abstract, dimensionally altered terms” (p. 226)
• playing: “doing and making without responsibility…wandering according to the whims of curiosity and interest” (p. 248)
• transforming: using multiple imaginative tools serially or simultaneously so that “one (set of) tool(s) acts upon another (set)” (p. 273)
• synthesizing: using thinking tools in such a way that “first, we synthesize sensory impressions and feelings and, second, we fuse our sensory synthesis with the abstract knowledge that exists in our memories as patterns, models, analogies, and other higher-order mental constructs” (p. 297-298)

During elaboration, teachers can engage understanding’s constructive processes by engaging students in creative thinking processes. For example, the teacher could engage the students in reviewing the new content’s critical details to identify possible material for creative considerations, such as:

• dimensional thinking (scale): What if the American Civil War occurred literally within an actual “house divided”?
• abstracting: If each step of the sequence for finding the quotient for long division problems were a color, what color sequence would result?
• analogizing: What are well placed adjectives like and why/how?

Again, note the processing such thinking requires. The learner must explore connections between the original material and elements of the creative form. These connections, which arise from the learner’s life experience, deepen understanding and move the learner forward from knowledge toward valuable conceptualization.

Within the Architecture of Learning Instructional Design Model (see www.clerestorylearning.com), recurring elaboration “cells” and an entire “strand” of elaboration engages students in such processing. The model enables teachers to design learning that matches the brain’s needs for deep understanding.

Without elaboration, instruction tends to engage only low levels of thinking, confusing “fast answers with wise answers, ignoring that quality thinking takes time” (Zaltman, 2003, p. 17). Why is this so important? Because we are educating students for successful living in a time and place we cannot currently know. Therefore, students need “deep understanding” so they can “apply the knowledge they gain from data to new situations” (p. 17). As students re-form ideas via elaboration, deep understanding develops, increasing the likelihood that the learning is for a lifetime.

Gardner, H. (2006). Changing minds: The art and science of changing our own and other people’s minds. Boston: Harvard Business School Press.

Miller, G. (2007). A surprising connection between memory and imagination.
Science 315, 312.

Root-Bernstein, R. & Root-Bernstein, M. (2001). Sparks of genius: The 13 thinking tools of the world’s most creative people. Boston: Mariner Books.

Wiggins, G. & McTighe, J. (2006). Examining the teaching life. Educational Leadership 63(6), 26-29.

Zaltman, G. (2003). How customers think: Essential insights into the mind of the market. Boston: Harvard Business School Press.