Abstract and Statement of the Problem
Before delving into the dense vocabulary of cognition nomenclature I want to give you an abstract view of where this silly titled blog is going. The systematic teaching of young music students through middle school and high school leaves a gaping hole, not in intonation, but the more fundamental concept of recognition. How is it out of tune? Or better yet, why is it out of tune?

How is a young student supposed to recognize (create expectation) whether or not they are out of tune if they are not aware they are actually out of tune? This is not an attempt to strike up a conversation concerning the tone deaf few – most of them misdiagnosed – but rather an attempt to explain to you the fact that the brain of a young student is, more often that not, disallowed any opportunity to adjust to a situation and would rather gladly accept that an Ab as simply that… an Ab, without any concern with frequency and interaction with other environmental factors.

By exposing you to various authors and teachers oozing cognitive, psychological, and neuroscientific material you will be put in a better position to recognize your student’s quality of pitch recognition (or lack thereof) and better diagnose possible fundamental auditory problems. Once recognized you can present them with the tools needed in order to facilitate a basic understanding of pitch comparison (context), function, and contour. The learning tool I will present in this blog is the use of a drone and I propose that a constant, properly coached use of the drone method will result in exceptionally positive qualities in expectation, categorization, and schema development which goes into developing highly sensitive, relative pitch.

Working Memory
In order to properly teach the younger generation, it is important to get a grasp how the brain of our students respond to input. Bob Snyder put together a good (although complicated) illustration (p. 6) of how the brain encodes the data it receives from the ear. I will attempt to give you an accurate “upper atmosphere” view of the encoding, categorization, and storage process. Once a sound has reached the ear the information is neurally transmitted to the brain via echoic memory where data is turned into nerve impulses that represent the frequency and amplitude of individual acoustical vibrations. This new set of “processable data” is then sent on to perceptual categorization where data is extracted from these vibrations into coherent events and then bound together into categories.

These categories are then simultaneously compared to data in different parts of working memory: Short Term Memory, interaction with Long Term Memory, and the Focus of Conscious Awareness. Cognitive theorist Kris Shaffer and psychologist Alan Baddeley have created a useful “birds eye view” model and comparison for working memory. In Baddeley’s model working memory consists of a central executive (CE) – which is responsible for processing cognitive data – and several independent resources for short-term storage, traditionally called short-term memory (STM). When stimuli are detected by the sensory organs, the perceived data enters the appropriate region of the STM; the CE is responsible for processing the data and encoding appropriate data in long-term memory (LTM). A personal computer is a reasonable analog for this system, with the CE being represented by the CPU (central processing unit), the STM by RAM (random access memory) and the LTM by the hard disk drive (Shaffer, see sources, p 6).

Working memory (WM) has the ability to temporarily hold and manipulate information for cognitive tasks. What WM holds are chunks of information that have been categorized based on the environmental experience and/or recollection (from LTM) of that moment. Chunking involves taking elements of data and compressing them into smaller “chunks” of data and organizing them hierarchically based on need at that moment. Examples of this process will be explored later in the second blog.  Let’s delve a little deeper into the brain by discussing schemas and their role in avoiding overgeneralization. David Huron describes a schema as an expectational “set.”

What does a young music student have available in their “schematic library?” Very little. It is at this juncture where diligent and accurate practice will develop the schemas – the expectational set – needed in order to create a strong relative pitch scenario. You have heard of the popular saying, “Practice Makes Permanent, Perfect Practice Makes Perfect.” Huron gives a relatively simple example which can be expressed to younger students by delineating the distinction between major and minor modes. By having an educated teacher provide something as simple as associating major mode with ‘happy’ and the minor mode with ‘sad’ the young student will have developed a fixed schema that will be rehearsed until s/he is of the maturity where they can offer an additional association if they wish to do so – how happy? how sad? what type of happiness/sadness, etc.

Examination of Absolute/Relative Pitch and its Relation to the Cognitive Process
In order to develop absolute/relative pitch, we need to efficiently create schemas that will best cue chunks from LTM (gathering data from the hard drive) and provide the most efficient rehearsal possibilities within STM in order to provide an accurate comparison for droning against a fixed pitch. Although there are studies out there (http://perfectpitch.ucsf.edu/study/), obtaining absolute pitch is generally thought of as a learned trait. Absolute Pitch (AP) is the ability to identify the pitch of tones without the use of any external reference. Cognitive theorists suggest that even if genetics play a role, existing research suggests that a critical learning period is involved. This “research” is alluding to assertions that one of the best generalizations on can make about “perfect pitch” (AP) is that its possessors typically begin musical instruction or involvement at a comparatively early age – often before the age of six or seven years.

Because you are reading this the balance of probability suggests that you are a western trained musician or a non-musician who has been bathed in western music since a very early age. To claim to have AP limits the scope of your ability to recognize tones to that of only western music. If you were to be thrown into a gamelan ensemble (traditional Indonesian music ensemble) where instruments are rarely pitched the same from ensemble to ensemble you would find yourself unable to properly recognize a tonal center based on your AP skills alone. You would need to rely on a secondary skill set used by those with highly tuned relative pitch (RP) – the reliance on intervals, scalar patterns, and perhaps reliance on a fixed tonal marker such as personal vocal range or specific instrument timbre.

An article concerning Identifying Absolute Pitch Possessors proved that early and extensive musical training may be necessary but they are not sufficient to produce AP (Weisman, Balkwill, Hoeschele, Moscicki, Strudy 2012). None of this is to say that AP is fake and unattainable but what good does it do without congruently developing schemas similar to those with highly tuned RP? Gary Karpinski articulated it best, “AP listeners should develop the same kinds of relative listening strategies non-AP listeners use. Functional strategies are particularly important: tonal music derives a great deal of its meaning from these functions; identifying a series of unrelated pitches does not promote the understanding of this meaning.” (p. 58)

Earlier I stated that AP was thought of as a learned trait. Daniel Levitin put together an article regarding a study concerning learned melodies. Within the article, he explained what is called the Two-Component Theory of Absolute Pitch. Levitin postulates that AP is merely a small extension of memory abilities that are widespread in the music population and AP consists of two distinct component abilities: (1) Pitch Memory and (2) Pitch Labeling.

Pitch Memory is the ability to maintain stable, long-term representations of specific pitches in memory and to access them when required. They are highly categorized schemas which can be cued at an efficient level if trained properly (think RAM!).

Pitch Labeling is the ability to attach meaningful labels to pitches. This attachment is thought to be coded implicitly through an alternate set of perceptual categories (perhaps the genetic advantage?) used in sound processing in LTM. Below is a diagram put together by Cognitive Theorist, Ian Quinn while recently lecturing at the University of Colorado in November of 2014. The diagram outlines (in simple illustrations) where the populace lies in regards to having non-absolute pitch (NAP) or absolute pitch (AP). As discussed earlier, for one to truly have absolute pitch it would be appropriate, if not mandatory, that an AP user possess the cognitive proclivity for both pitch memory and pitch labeling.

There are two conclusions I will point out from this post. (1) It is important to know that if you do possess AP do not simply rely on it to help you with intervallic relationships and function. To put it another way, identifying pitch out of context is irrelevant and even meaningless to music (Miyazaki 1993). (2) Music theory and aural skill training (the earlier the better!) is directly responsible to the relevance of relative pitch and the development of proper schemas (solfeggio method of sight-reading/singing). I earlier described a schema as an expectational set. The second blog post will delve into creating schemas and developing those schemas using motivation, preparation, and representation with the application of the drone method to create strong relative pitch.

Jason Michael Johnston

DMA Candidate, University of Colorado at Boulder

#muscog

Sources for 1st and 2nd blog

Ecker, U. K. H., Lewandowsky, S., Oberauer, K., & Chee, A. E. H., “The components of working memory updating: An experimental decomposition and individual Differences.” Journal of Experimental Psychology: Learning, Memory and Cognition, 36 (2010): 170-189.

Hogan, Patrick Colm. Cognitive Science, Literature, and the Arts. New York: Routledge, 2003.

Huron, David. Sweet Anticipation: Music and the Psychology of Expectation. Cambridge: MIT Press, 2007.

Karpinski, Gary S.  Aural Skills Acquisition: The Development of Listening, Reading, and Performing Skills in College-Level Musicians.New  York: Oxford University Press, 2000.

Leuba, Christopher. A Study of Musical Intonation. Vancouver: Prospect Publications, 1992.

Levitin, Daniel.  “Absolute memory for musical pitch: Evidence from the production of learned melodies.”  Perception & Psychophysics, 1994, 56  (4), 414-423.

Miyazaki, Ken’ichi.  “Absolute Pitch as an Inability: Identification of Musical Intervals in a Tonal Context.”  Music Perception: An  Interdisciplinary Journal, 1993, Vol. 11, No. 1, 55-71.

Moody, Gary. “A Practical Method for the Teaching of Intonation.” Diss. U of Northern Colorado, Greeley, 1995.

Patel, Aniruddh D. Music, Language, and the Brain. New York: Oxford University Press, 2008.

Shaffer, Kris. “Listening and Learning: Working Memory, Repeated Listening, and the Development of Stylistic Knowledge.” Independent Study  of Yale University, 2006.

Snyder, Bob. Music and Memory: An Introduction. Cambridge: MIT Press, 2000.

Weisman, Ronald G., Laura-Lee Balkwill, Marisa Hoeschele, Michelle K. Moscicki, and Christopher Sturdy.  “Identifying Absolute Pitch  Possessors Without Using a Note-Naming Task.”  Psychomusicology: Music, Mind & Brain, 2012, Vol. 22, No. 1 46-54.

White, Harvey E.. and Donald H. White. Physics and Music: The Science of Sound. New York: Dover Publications, 2014.