Conclusion: Cycles of Skill Development and Brain Growth
Each developmental level requires a new type of control system to coordi-nate component skills, and each produces a cluster of discontinuities in behavioral growth and apparently brain growth as well. We hypothesize that each skill level is grounded in a broadly based brain-growth spurt that produces a new type of neural network and thus a new type of control sys-tem. The convergence is remarkable between the growth spurts evident in EEG and other brain-growth findings and the spurts for cognitive and emo-tional developments (summarized in Figure 4.4). Unfortunately, almost all relevant studies have investigated either brain growth or behavior develop-ment, not both, so extensive research will be required to test and improve this model of specific connections between brain-growth discontinuities and developmental changes in behavior.
Development is often analyzed as a linear process similar to climbing a ladder. The growth patterns that we have described suggest a different kind of model based on growth cycles. Biology is replete with cycles, and we propose that developmental science needs to move away from linear growth models toward cyclical models (Fischer & Bidell, 2006). The brain has many parts that work together in complicated ways. One part of the brain growth pattern seems to be that new learning and development begin with a bias toward the right hemisphere, with its more global approach, and then gradually move to more involvement with the left hemisphere and a focus on differentiation and specificity. This promising idea can help ground the search for organizational principles of learning, cognitive devel-opment, and brain growth. It can help explain how brain components work together to produce an emerging developmental level or an emerging set of expert skills. The growth cycles that we propose for skill and brain development provide a beginning.
process music neuropsychologically, moving them beyond initial right-hemispheric analysis to syntactic analyses that heavily recruit the left hemi-sphere.
Dynamic Shifts in Brain Organization
The example of hemispheric biases in music processing is interesting from a historical perspective because it exemplifies a shift in thinking about hemi-spheric capacities from statically localized functions to more dynamically organized processing biases that reflect and affect learning. Modern at-tempts to lateralize music processing date from an abundant period of research in the 1960s. It was then widely held that language was relegated to the left hemisphere, whereas the right hemisphere handled other aspects of auditory analysis, including music and environmental sounds. This belief fit well with the notion that language and music represented clear examples of verbal and nonverbal domains (Peretz, 1993) and reflected the dominant paradigm of localization (Caramazza, 1992; Harrington, 1991), in which the role of expertise in organizing neuropsychological functioning was largely overlooked.
Since then, the study of the lateralization of broad functions such as music processing has become more complex, growing to reflect the dy-namic interactions between the brain hemispheres and cognitive experi-ence. Rather than assigning music to one hemisphere, it is now recognized that such a large domain involves several smaller functions, some of which are processed in the left hemisphere and many of which are processed dif-ferently in novices and experts. For instance, the original relegation of music processing to the right hemisphere came out of a tradition of study-ing only the organization of either isolated pitches or pitches in melodies and chords (Peretz, 1993), especially in nonmusicians. However, scientists now understand that the processing of pitches and melodies changes with domain-specific learning, as different features come to dominate the analy-sis. In nonmusicians, the most salient feature is the contour of the musical phrase (Bever & Chiarello, 1974), or the up and down movements of the pitches, akin to “inner singing.” Because contour analysis is a relatively global, spatial property, it is generally lateralized to the right hemisphere (Patel, Peretz, Tramo, & Labreque, 1998).
Whereas novice listeners tend to rely more on the overall melodic con-tour of the musical phrase in comparing passages of music (Balch, 1984), expert musicians rely more on the formal, syntactic structure of the compo-sition (Bever & Chiarello, 1974). Experts rely on such key characteristics as intervals (the relative difference in pitch between notes), harmonic structure (the ways that intervals are combined in a composition), and temporal
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characteristics of phrasing (divisions of a composition into functional units of musical processing, akin to sentences; Chiappe & Schmuckler, 1997). As musicians develop domain-specific expertise, temporal aspects of music as well as knowledge about the formal harmonic structure become the orga-nizing features of perception and memory (Berz, 1995). Because these fea-tures rely heavily on left-hemispheric analysis (Fabbro, Brusaferro, & Bava, 1990; Ohnishi et al., 2001; Peretz, 1993; Schuppert, Munte, Wieringa, &
Altenmuller, 2000), expert musicians recruit the left hemisphere for music much more than do novices.
In general, music processing involves not one unitary kind of process-ing supported by a sprocess-ingle neuropsychological system, but several kinds of domain-specific processing that reflect recruitment and specialization of various component skills. As novice musicians become experts, they de-velop new kinds of processing that include formal analyses of the music.
From the beginning, the right hemisphere handles the more global aspects such as contour analysis, and with expertise the left hemisphere is recruited for the formal, rule-bound and syntactic aspects, such as harmonic or tem-poral analyses. Neuropsychologically, this change is reflected in an in-creased reliance on left-hemispheric processing, so that music processing in experts shifts from mostly right to bilateral activation patterns.
Evidence for the Hemispheric Shift in Music
Various sources provide neuropsychological evidence for the shift to increased left-hemispheric reliance with formal musical experience. Expert musicians tend to show a right-ear advantage in dichotic listening, indicat-ing a left-hemispheric bias. As revealed by the EEG, they also demonstrate a pattern of approximately equal activations in both hemispheres during music tasks (Davidson & Schwartz, 1977; Hirshkowitz, Earle, & Paley, 1978). In contrast, nonexperts tend to display a different pattern: greater right-hemispheric activation when listening to music and left-ear advan-tages in dichotic listening tasks. Nonexperts include nonmusicians with high aptitude for music (Fabbro et al., 1990), nonmusicians with average aptitude (Berz, 1995), and infants (Balaban, Anderson, & Wisniewski, 1998). Research in cerebral hemodynamics also supports this trend, dem-onstrating through transcranial doppler sonography a left-hemispheric dominance in musicians but a right-hemispheric dominance in nonmusi-cians during various music and melody recognition tasks (Evers, Dannert, Rodding, Rotter, & Ringelstein, 1999; Marinoni, Grassi, Latorraca, Caruso, & Sorbi, 2000; Matteis, Silvestrini, Troisi, Cupini, & Caltagirone, 1997). Similarly, expert musicians, especially those who began musical training before age 7, have been found to have a larger anterior corpus
callosi than nonexpert controls (Schlaug, Jancke, Huang, Staiger, &
Steinmetz, 1995), presumably related to increased interhemispheric com-munication.
In addition to syntactic and contour-based processing, other aspects of musical processing are distributed between the two hemispheres in ways that follow the principle of a bias toward basic music processing in the right hemisphere and increased reliance on left-hemispheric processing with expertise. One general finding is that both expert and untrained musicians use the right hemisphere for long-term storage of familiar melodies, proba-bly because contour information is processed more in the right hemisphere (e.g., Berz, 1995; Patel et al., 1998; Peretz, 1993). This store is probably organized by contour of the melodies, because contour has been shown to be equally salient to musicians and novices (Burns & Ward, 1978;
Dowling, 1978), and novices have been shown to rely primarily on contour in melody recognition (Sloboda & Parker, 1985). Evidence from stroke patients also supports the existence of an autonomous long-term memory store for familiar melodies in the right hemisphere, dissociated from formal syntactic knowledge. One music patient with right-hemisphere damage largely retained her ability to process pitch and rhythmic patterns but lost her memory for familiar songs (Patel et al., 1998). Another stroke patient largely retained her syntactic knowledge of music and ability to play the piano yet could not recognize well-known tunes (Beatty, Zavadil, Bailly, &
Rixen, 1988). By way of a double dissociation, in one professional musi-cian a left-hemispheric lesion to the posterior temporal lobe left her unable to read music or interpret musical syntax, but largely uncompromised in her ability to remember and play both familiar and new melodies (Cappelletti, Waley-Cohen, Butterworth, & Kopelman, 2000). (This wo-man’s case is also evidence for left-hemispheric syntactic store in experts, discussed below.)
With regard to organization, this melodic store seems to be rule-bound in a limited sense, in that even nonmusicians are able to complete unfamil-iar melodies in ways that are consistent with Western tonal frameworks (Jones & Yee, 1993). It is also available for relatively nonstrategic rehearsal in the form of chunked mental replay, as is demonstrated by an experiment in which subjects required more time to compare pitches that were further apart in familiar songs. This added time was presumably due to the sub-jects’ mentally singing through the entire melody in real time (Crowder, 1993; Halpern, 1988).
Separate from the long-term store for familiar melodies, the evidence also points to a left-hemispheric, long-term store of syntactic musical infor-mation that can be used strategically by trained musicians for memory and other purposes (e.g., Balch, 1984; Berz, 1995; Roberts, 1986). Further
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dence for this second long-term store derives from the finding that although novices can transpose familiar melodies (a task that relies on right-hemispheric contour analysis), they have trouble transposing intervals.
That is, novices can sing familiar melodies starting on different notes, but are poor at producing intervals on different starting notes (Attneave &
Olson, 1971). Apparently they are competent at manipulating the right-hemispheric contour-based store, but they have no well-developed syntactic framework or left-hemispheric strategy with which to process isolated intervals. Expert musicians do not show this difference (Deutsch, 1980;
Sigel, McGillicuddy-DeLisi, & Goodnow, 1992).
Another example of musical processing that is organized around the right-to-left hemispheric processing shift with the acquisition of expertise is pitch comparison and categorization. Whereas both musicians and non-musicians share the ability to categorize musical pitches along a continuum, only expert musicians show true “categorical perception” of pitches, espe-cially within intervals and chords (Patel et al., 1998, p. 198). That is, only musicians show the ability to place chords, intervals, and pitches into psychophysically bounded discrete perceptual categories in which “stimu-lus pairs of a given physical difference . . . are easily discriminated when they straddle a category boundary, but poorly . . . discriminated when they lie within a category” (Matzel et al., 2003, p. 198; see also Repp, 1984).
Thus, it appears that knowledge of musical syntax, which defines the previ-ously psychoacoustically arbitrary boundaries between given pitches, influ-ences categorization and learning of pitch stimuli in music. Research with event-related potentials (ERPs, based on EEG to repeated events) compared experts and nonmusicians and found that neuropsychological changes accompanied this cognitive reorganization (Besson & Faieta, 1995). Re-search with functional magnetic resonance imaging (fMRI) showed en-largement of left-hemispheric sensory activations during presentation of piano tones in musicians compared to novices (Pantev et al., 1998).
These effects of expertise and associated cognitive functions suggest an interhemispheric model of music processing in which a right-to-left pro-cessing shift occurs as domain-specific knowledge is acquired (see Figure 4.5). In this model, music processing in both novices and experts likely begins in the right hemisphere, with an analysis of more global or pattern-based features such as contour of the melody. As we have seen, it is likely that the right hemisphere also contains a long-term store for familiar melo-dies as well as the neuropsychological substrate for pitch comparison. Fol-lowing this initial processing, experts then perform additional, more differ-entiated analyses in the left hemisphere based on syntactic knowledge about the music. These analyses probably include constructs such as cate-gorical pitch perception and interval, harmonic, and rhythmic analyses,
and are likely governed by a long-term store of musical syntactic rules, also housed primarily in the left hemisphere.
Besides the finding that music processing shifts from mainly right-hemispheric analysis to combined right- and left-right-hemispheric processing with expertise, researchers have found that the neurological processing of music in experts has important commonalities with language processing.
Specifically, evidence is accumulating that the classical left-hemispheric lan-guage regions—Broca’s and Wernicke’s areas and nearby locations—
are recruited during music processing under certain conditions (Maess, Koelsch, Gunter, & Friederici, 2001). In experts, musical and linguistic processing seems to recruit some of the same neural resources, presumably because both domains involve processing of syntactic (left-hemisphere-related) as well as more global (right-hemisphere-(left-hemisphere-related) features. For example, one study using a combined magnetic resonance imaging (MRI) and positron emission tomography (PET) technique examined the neural correlates of sight reading, playing, and listening to music in 10 profes-sional pianists (Sergent, Zuck, Terriah, & MacDonald, 1992). The authors found a series of asymmetric left-hemispheric activations that paralleled the neural substrates of verbal processing but were partly distinct (Sergent
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FIGURE 4.5. A schematic diagram of the neuropsychological components of music processing, illustrating a shift with musical training from mainly right-hemi-spheric processing to strategies associated with the left hemisphere. The boxes on the right contain the processing components normally associated with the right hemisphere, heavily recruited regardless of expertise. The boxes on the left are asso-ciated with the left hemisphere and are heavily recruited in experts after initial right-hemispheric processing.
et al., 1992). Since that study, other fMRI (Koelsch, 2005; Koelsch et al., 2002), magnetoencephalography (MEG; Koelsch, Maess, Gunter, &
Friederici, 2001), and PET (Brown, Martinez, & Parsons, 2006) studies using chord sequences or other musical stimuli have found activations that overlap significantly with language areas and generally appear to reflect similar aspects of processing in the two domains, such as timing and syn-tactic processing.
Other evidence also suggests that music and language processing use similar neural networks, with both involving distinct regions for syntactic and nonsyntactic (often more global) processing. For example, a series of ERP studies found that prosodic processing in language elicits patterns of brain waves similar to those elicited by melodic and rhythmic processing in music (Besson, 1997, 1998). Conversely, harmonic analyses of music were similar to those for syntactic processing of language. Other studies with diverse tasks indicate distinct processing of syntactic versus nonsyntactic musical information in musicians versus nonmusicians: discrimination of melodic intervals (Crummer, Hantz, Chuang, Walton, & Frisina, 1988), discrimination of timbre from trumpets of different keys (Hantz, Crummer, Wayman, Walton, & Frisina, 1992), harmonic incongruity (Levett & Mar-tin, 1992), and syntactic reanalysis of a musical phrase (Patel, Gibson, Ratner, Besson, & Holcomb, 1998). Complementary work with stroke patients reinforces the syntactic and nonsyntactic associations between pro-cessing in the two domains, indicating that rhythmic and melodic aspects of language and music share neurological substrates (Hofman, Klein, &
Arlazoroff, 1993; Patel et al., 1998; Peretz, 1993).
In summary, music processing requires several kinds of domain-specific processing, and thinking about these aspects of music processing is essential for understanding how and why the right-to-left-hemispheric pro-cessing shift happens in musical expertise. Initially, the right hemisphere processes information about melody and other global aspects of music and then increasing expertise requires the left hemisphere for the rule-bound, syntactic parts of music such as harmonic analysis. In this way, music pro-cessing illustrates how neurological biases and experience interact in learn-ing and development to shape the dynamic organization of the hemi-spheres. Experience leading to expertise organizes the domain-specific music system and shapes the distribution and organization of processing in the brain. The demands that music processing puts on the brain differ between novices, who focus on contour analysis, and experts, who incorpo-rate syntactic analysis. The processing system for music cannot be treated as cognitively static and neurologically localized. Instead, understanding this system requires analyzing the demands that a particular knowledge domain places on the brain as it recruits various kinds of processing along a
continuum of experience. Because experts process according to different criteria from novices, understanding how domain-specific systems are orga-nized and localized in the hemispheres of the brain requires analysis in terms of development and learning.
CASE 3: DEVELOPMENT OF TWO