The Cognitive Neuroscience of Improvisation
Abstract and Keywords
Cognitive neuroscience research has begun to elucidate the neural substrates and cognitive processes that are involved in musical improvisation. In turn, the study of improvisation from the perspective of cognitive neuroscience has provided new insights about the brain and cognition. This chapter reviews brain imaging research studies of improvisation and explores the relevance of this work to musicians, musicologists, music educators, and cognitive neuroscientists with respect to the practice and pedagogy of improvisation, comparisons between music and language cognition, mirror neuron systems, and neural plasticity.
The relationship between music and the mind has fascinated some of Western history’s greatest thinkers, including Pythagoras, Galileo, and Descartes.1 Broadly defined, the field referred to as “music cognition” or “the psychology of music” seeks to answer two complementary questions:
1. How does the brain carry out musical processes?
2. What can the study of music tell us about how the brain works?
The first question examines which cognitive processes—and their neural substrates—allow for the perception, understanding, and production of music. For example, research addressing this first question has sought to understand how we recognize, remember, read, understand, compose, perform, and have an emotional response to music, and what regions of the brain may be responsible for these features of music cognition.2
The second question treats music as a specialized substrate through which to study more general cognitive processes. For example, studying the ability to know how a piece of music sounds by looking at the score allows for the exploration of mental imagery, as well as transformations between one sensory modality and another.3 High-level musical performance is a case study in expertise.4 Investigating musical learning and memory can provide insights into these higher-order cognitive processes and their neural substrates outside the verbal or visual domains.5 If areas of the brain are discovered to be involved in musical processes in addition to previously ascribed roles, such findings can provide insights into the more general functionality of these brain regions.
Most early research in music cognition explored music perception, but more recent work has also begun to explore the psychology and neurobiology of musical (p. 57) performance.6 From a cognitive perspective, musical performance requires extraordinary motor dexterity, control, and coordination; the ability to link the motor system with the auditory system; and, in the case of performance traditions that use written scores, the transformation of visual input into motor output. Improvised performance additionally requires the capacity to generate spontaneously novel musical structures in real time. This chapter explores the two complementary questions presented at the beginning of the chapter with respect to improvisation: What can studying the brain tell us about improvisation? What can studying improvisation tell us about the brain?
Exploring the neural basis of musical improvisation can aid in understanding the more general cognitive processes called upon in this specialized instance of auditory-motor expertise and creativity. This inquiry has the potential to provide insights into both practice and pedagogy. In turn, discovering which areas of the brain are involved in musical improvisation may influence how the function(s) of these regions are understood.
Improvisation can be defined most generally as “the creation of a musical work, or the final form of a musical work, as it is being performed.”7 Spontaneous creation in the moment is of course not unique to music. Improvisation occurs in theater, dance, and to some degree in any artistic expression that evolves in real time. Improvisation is also part of our everyday speech and movement. Just as infinite possibilities exist in how the blues or a Beethoven cadenza can be improvised while still maintaining its stylistic and formal identity, so too can we create infinite possible sentences, all the while using a finite vocabulary and obeying the finite grammatical rules that together allow for the comprehensibility of a novel utterance. Our everyday actions also incorporate some degree of improvisation, as we dexterously enact spontaneously created motor solutions to challenges as mundane as balancing grocery bags while we unlock the front door and as important as life-saving, split-second maneuvers to avoid accidents while driving.8 Therefore, while musical improvisation is a fascinating feat of human cognition worthy of study in its own right, it also provides a specific instance of a much more general phenomenon in human behavior: spontaneous rule-based combinations of elements to create novel sequences that are appropriate for a given moment in a given context. This chapter presents data from recent brain imaging studies that explore the neural basis of improvisation. It then discusses findings of these studies from the perspective of the questions: What can studying the brain tell us about improvisation? What can studying improvisation tell us about the brain?
The Neural Basis of Improvisation
To date there have been five published studies of the neuroscience of improvisation.9 This review focuses on the studies of Berkowitz and Ansari (2008 and 2010) and Limb and Braun (2008), since their work is complementary both at the methodological level and with respect to results, and because both studies use functional magnetic resonance imaging (fMRI) to assess brain activity during improvisation.
(p. 58) fMRI uses a magnetic field to detect changes in blood oxygenation in the brain as an index of the relative activity of different brain regions when the brain is engaged in a cognitive process. Because many areas of the brain are highly active even at rest, fMRI studies often employ a subtraction technique in an attempt to precisely localize activation during a cognitive task of interest by comparing this with a control condition. When using a subtraction technique, brain activity during a control task is “subtracted” from brain activity during the cognitive task of interest. For example, if neural activity were to be examined while someone listens to music, many areas involved in more general cognitive processes would be involved (e.g., basic auditory perception, attention). While these regions are surely involved in music perception, their role would not necessarily be specific to music perception. Comparing brain activity while listening to music with that during a control task, such as listening to a less complex auditory stimulus (e.g., pure tones or white noise), allows for the subtraction of the activity stimulated by these more basic processes. This subtraction would thus demonstrate the areas involved in music perception above and beyond basic cognitive functions such as auditory perception and general attention to an external stimulus.10
Berkowitz and Ansari (2008)
To study improvisation with fMRI, we designed a simple experimental set-up that consisted of four tasks allowing for varying degrees of improvisatory freedom.11 These tasks were performed on a five-key piano-like keyboard. In the most constrained task, subjects played simple patterns that were taught to them before the experiment, and they performed these patterns in the order of their choosing, with one note per beat with a metronome click. This experimental condition will be referred to here as Patterns/Metronome. The only freedom of choice provided during this condition was that of which pattern to play at any given time; the internal melodic and rhythmic structure of each pattern was fixed. Two conditions provided freedom in one musical parameter only (melody or rhythm): in Melodic Improvisation/Metronome, subjects invented five-note melodies, but these melodies were rhythmically constrained by the metronome (one note per beat); in Patterns/Rhythmic Improvisation, subjects were free to improvise the rhythms of the pre-learned five-note patterns. In the final condition, Melodic Improvisation/Rhythmic Improvisation, subjects improvised five-note melodies and their rhythms. Comparing brain activity in Melodic Improvisation tasks with that during Patterns tasks allowed for the isolation of the neural correlates of melodic improvisation, whereas comparison of Rhythmic Improvisation tasks with the Metronome tasks demonstrated the regions of brain involved in rhythmic improvisation.
Melodic improvisation requires creativity in the pitch domain (or, from a motor perspective, in the spatial domain), whereas rhythmic improvisation can be thought of as the generation of novel musical structures in the temporal realm. Melodic and (p. 59) rhythmic generativity would be expected to have distinct but overlapping neural networks underlying them.12 Areas of nonoverlap between melodic and rhythmic improvisation would presumably be taking part in processes unique to spatial/melodic and temporal/rhythmic generativity, respectively. We were particularly interested in the areas subserving both melodic improvisation and rhythmic improvisation. The areas of overlap between these two types of improvisation would ostensibly be the brain regions giving rise to musical generativity at the most fundamental (or, alternatively, the “supra-domain”) level, irrespective of whether the improvisation involves pitch/space or rhythm/time. We thus performed a conjunction analysis of melodic improvisation (brain activity in Melodic Improvisation tasks minus brain activity in Patterns tasks) and rhythmic improvisation (brain activity in Rhythmic Improvisation tasks minus brain activity in Metronome tasks) in order to identify the network of brain regions involved in improvisation, whether that improvisation is in the melodic or rhythmic domain.
This conjunction analysis revealed three areas of the brain that participated in both melodic and rhythmic improvisation: the dorsal premotor cortex (dPMC), the anterior cingulate cortex (ACC), and the inferior frontal gyrus/ventral premotor cortex (IFG/vPMC).
The dPMC is involved in the selection and execution of movement sequences.13 It would thus be expected to be involved in any task involving motor activity. Our results show that this area is more active in improvisation as opposed to playing patterns and/or playing with a metronome, consistent with a possible increased demand on this brain region as movement complexity increases.
The ACC is known to play a role in a wide variety of cognitive tasks, including monitoring conflict between stimuli or responses, unrehearsed movements, decision making, voluntary selection, and willed action.14 These cognitive functions are of course intertwined. Making a decision involves voluntary, willed choice between potentially conflicting responses to a stimulus. Improvisation involves near-constant decision making among a multitude of musical possibilities available to the improviser at any given moment. A brain-imaging study of performance of a memorized composition by Bach compared to playing scales did not show differential activation of this region,15 thus suggesting that the ACC plays a role in our experiment in improvisation specifically (i.e., beyond a role in mere musical or motor complexity, since in that role it would likely have been active in the Bach versus scales comparison of the cited study).
The IFG/vPMC has been found to play a role in language perception and production as well as music perception.16 The aforementioned study of piano performance of a memorized composition did not show activation of this area in that context, suggesting that its role in our experiment is unique to the improvisatory/generative nature of our experimental tasks. Given that this region is involved in both perception and production of language and music, it can be postulated that, on the most general level, it subserves “analysis, recognition, and prediction of sequential auditory information”17 as well as the production of such sequential auditory-motor information.
(p. 60) Limb and Braun (2008)
Our experiment sought to isolate and study one particular aspect of improvisation: spontaneous generation of novel sequences. Charles Limb and Allen Braun designed more ecologically valid tasks in their 2008 study to explore a broader array of neural activity in improvisation. In the main experimental condition, jazz musicians improvised over the chord structure of a jazz composition. Brain activity during this task was compared to that in a control condition in which subjects played a fixed composition from memory.
Since their tasks were far more complex than those of Berkowitz and Ansari and allowed their subjects to improvise based on an actual compositional structure that evolved in time, Limb and Braun elicited changes in brain activity in over forty regions when comparing their improvisation tasks to control tasks, including the network of IFG/vPMC, ACC, and dPMC described in Berkowitz and Ansari (2008). Additional areas included the superior temporal lobe (likely to be involved in processing and memory for musical materials), limbic regions (probably involved in emotion and memory), the medial prefrontal cortex (MPFC) (activation is associated with self-expression and higher-level goals and intentions), and the lateral orbital prefrontal cortex (LOFC) and dorsolateral prefrontal cortex (DLPFC) (deactivation is suggestive of inhibition of regions involved in monitoring and correction). With regard to these latter findings in the prefrontal cortex, the authors suggest that
Musical creativity vis-à-vis improvisation may be a result of the combination of intentional, internally generated self-expression (MPFC-mediated) with the suspension of self-monitoring and related processes (LOFC—and DLPFC-mediated) that typically regulate conscious control of goal-directed, predictable, or planned actions.18
In conjunction, the studies of Berkowitz and Ansari and Limb and Braun complement one another. The precise focus of Berkowitz and Ansari on a limited type of improvisation with a very small set of possibilities allowed for relatively specific attribution of functional roles to the brain areas that were active but probably did not activate the full range of regions of the brain involved in real-world improvisation. By studying improvisation in as close to its real-world form as possible in the laboratory, Limb and Braun offer a more panoramic view of the full panoply of neural activity involved in improvising.
Berkowitz and Ansari (2010)
In a follow-up study to Berkowitz and Ansari (2008), the brain activity in musicians and nonmusicians was compared during the performance of the four improvisation tasks described earlier.19 The behavioral results were essentially equivalent between the two groups in that the degree of novelty of the improvised melodies did not differ between them. Comparison of the three areas described earlier (IFG/vPMC, ACC, and dPMC) (p. 61) showed no difference in activation between the two groups. The neural substrates of the generation, selection, and execution of musical sequences therefore appear to be fundamental to the process of spontaneous motor performance, whether the intention behind it is that of a trained musician or not. The pattern of neural activation did, however, reveal one difference outside of this network. The single difference in brain activity between the two groups was in an area known as the right temporoparietal junction (rTPJ), which plays a role in attention. While nonmusicians did not show any significant change in the activity in this area when melodic improvisation was compared to pattern performance, musicians showed deactivation of this region. The difference between a musical mind approaching improvisation and an untrained mind performing the same task therefore appears to be not one of generativity, selection, or execution, but rather one of attention.
Activation of the rTPJ region is associated with stimulus-driven or bottom-up attention (i.e., the type of attention stimulated by salient characteristics of the stimulus itself).20 Deactivation of the rTPJ occurs in contexts of goal-driven, or top-down attention (i.e., the type of attention driven by intention based on one’s pre-existing knowledge, experience, and memory about a particular stimulus). Specifically, the rTPJ is involved in the reorienting of attention to task-relevant but unexpected stimuli. Imagine the example of an archer aiming an arrow at a target. The target, the tension in the bow, and the wind are all relevant to whether the archer will succeed in hitting the target. However, the archer would ideally want to “tune out” any task-irrelevant stimuli that could be distracting—for example, a bird chirping or the shifting shadows of a tree branch blowing in the wind in the archer’s peripheral vision. This “tuning out” of stimuli that could cause an inappropriate reorientation of attention away from one’s intended focus is thought to be accomplished in part by deactivating the rTPJ. That is, during sustained attention, the rTPJ is deactivated to allow for focus on one task while filtering out potentially disruptive stimuli to which reorientation would prove disruptive to the goal behavior.
Musicians’ deactivation of the rTPJ when improvising as compared to nonmusicians performing the same tasks suggests that musical training may allow for an increase in goal-directed attention and the filtering out of task-irrelevant stimuli in this context. Such an effect can also be interpreted as an increase in top-down processing of improvisational output as musicians may have chunked their phrases as musical units rather than strings of individual notes in sequence; the latter may have been the cognitive strategy utilized by nonmusicians.21
What Can Studying the Brain Tell Us about Improvisation?
Underlying Processes: Loci for Practice and Pedagogy
The fundamental cognitive processes supporting improvisation appear to be the generation and recombination of musical sequences (IFG/vPMC), the selection among such sequences (ACC), and the execution of the chosen sequence (dPMC). In addition, (p. 62) when trained musicians improvise, they appear to enter a top-down state of goal-directed attentional control (deactivation of rTPJ) when compared to nonmusicians performing the same tasks. Broken down into its cognitive components, this portrait of the improvising brain provides insights into loci for improvisational practice and pedagogy.22
In order to generate musical sequences appropriate for a given musical context, the improviser must be well versed in a stylistic idiom. For jazz musicians, this entails the knowledge of chords, scales/modes, forms, and a large vocabulary of “riffs,” some self-composed, others absorbed through transcription and imitation of solos by the great masters.23 For Indian musicians, a long germination period in which fixed compositions and melodic and rhythmic patterns are learned in various ragas (modes) and talas (rhythmic cycles) precedes the stage at which the musician can improvise.24 Robert Levin, a classical pianist who has learned to improvise in the styles of many classical composers, first internalized the composed repertoire of those composers.25 It is this learned material that provides the primordial musical soup from which materials are recombined and selected in the moment of improvised performance.
With this knowledge base in place, the improviser must learn how to navigate it to draw on stylistically idiomatic and artistically coherent sequences of musical materials in the moment of musical improvisation.26 Such selection is governed by “history” on a number of levels: the history of the style in which the performer is improvising, the history of all of the improvisational choices by the performer up to that performance, and the more local history of the musical choices up to that moment in the performance. The education of an improviser therefore involves not only the internalization of fundamental musical elements and forms, but also the acquisition of the ability to appropriately select from them in real time in a stylistically idiomatic way. To learn to improvise therefore involves rehearsal of the act of improvisation itself. In this rehearsal process, the improviser-in-training acquires experiential knowledge about how to navigate through the knowledge base and develops a personal style for doing so.
These aspects of learning to improvise ostensibly train the network of IFG/vPMC-ACC-dPMC in the actions of sequence generation, recombination, selection, and execution. In a review of the pedagogy of improvisation in a wide variety of musical traditions across different cultures, I have described how these principles are incorporated seemingly universally in improvisational pedagogy and learning.27 Beyond these principles, improvisers across cultures describe a particular state of mind when improvising in which creation and a partially detached observation of what is being created are carefully balanced, referred to as being both “creator and witness” by Levin and “inventor and recipient” by Paul Berliner in his study of jazz musicians.28 These ideas seem to resonate with Limb and Braun’s interpretation of their findings in the prefrontal cortex as representing a balance between self-expression and self-monitoring. Thus, the neuroscience of improvisation reflects a near-universal intuitive understanding by improvising musicians of the component processes necessary for improvisation and how to cultivate them in practice and pedagogy, and also appears to correlate with improvisers’ subjective experience of improvisation.29
(p. 63) Music and Language Comparisons
One widely explored area in music cognition research has been the comparison of music and language cognition.30 Broadly speaking, these two systems of human sound communication can be compared at three loci: production (i.e., the speaker or musical performer), the sound systems themselves (i.e., the underlying sound structures and the rules that govern them), and perception/comprehension (i.e., how the listener understands the utterance of the speaker or musical performer). The majority of research and theoretical speculation comparing music and language cognition has focused on the latter two. Improvisation is ideally suited to the study of production because it can be considered analogous to spontaneous speech; in both improvisation and spontaneous linguistic production, one needs both a knowledge base (e.g., vocabulary, grammatical rules, pronunciation in language; melodic figures, rhythms, timbres, harmonies, musical structures, and stylistic parameters in music) and the skill set to generate recombinations of the elements of this knowledge base in real time in a way that follows linguistic or stylistic norms so that utterances are comprehensible to the listener.
In Berkowitz and Ansari (2008), we demonstrated that the IFG/vPMC, an area known to be important in language, is also involved in musical improvisation. In fact, the triad of regions elicited in this study (i.e., dPMC, ACC, and IFG/vPMC) is also at the core of a network that brain imaging studies have shown to be involved in spontaneous speech.31 Musical improvisation and spontaneous speech therefore appear to be analogous at both theoretical and neurobiological levels. Many parallels can also be drawn between how musicians learn to improvise and how languages are learned.32 This begs the tantalizing question of whether training in musical improvisation can facilitate language learning and/or whether the data and experience derived from the extensive research in the pedagogy and learning of language can be applied to training methods for musical improvisation. Given the effects of musical training on the brain (discussed later in the chapter), this seems to be an area ripe for research that could have implications for both language pedagogy and music pedagogy.
Is music a language? Or, as David Lidov once titled a collection of essays, “Is language a music?”33 Music and language clearly share much in terms of cognitive processes, the neural substrates that appear to underlie them in both perception and performance, and the learning processes involved in acquiring these two systems of sound communication. The exploration of such connections between music and language provides one example of the types of insights that the study of music cognition may provide about brain function more generally.
What Can Studying Improvisation Tell Us about the Brain?
The research described demonstrates that musical improvisation, albeit a highly specialized capacity, occurs through the coordinated activity of brain regions that are involved in numerous other domain-general cognitive processes such as motor sequencing, (p. 64) decision making, and attention, to name a few. This underscores the fact that such networks of brain areas are highly flexible in the functions in which they can participate. Just as studying the neural basis of improvisation can yield insights into the nature of its component cognitive operations, so too can the study of improvisation provide insights into the functions of the brain regions upon which improvisation relies.
Our finding that the IFG/vPMC is involved in musical generativity complements data showing that this area is involved in music perception.34 A dual role in production and perception in this region has also been described for language. Such perception-action coupling in the brain is referred to as a “mirror system.”35 A mirror system is one involved in both the performance of actions and the understanding of such actions as performed by others. Such systems may encode an overarching (or underlying) concept of an action that can be utilized both in the performance of that action and in the understanding of the intention behind the action when observing it performed by someone else. Roles for such systems in higher-level cognitive functions such as language and empathy have been postulated.36 What purpose might such a mirror system serve in music? Itvan Molnar-Szakacs and Katie Overy propose that a mirror system for music “allows for co-representation of the musical experience, emerging out of the shared and temporally synchronous recruitment of similar neural mechanisms in the sender and the perceiver of the musical message.37
As described previously, non-generative musical performance (e.g., playing from a score) does not appear to stimulate activity in the IFG/vPMC. It was therefore through the study of the neurobiological basis of improvisation that it was discovered that this area plays a role in music production. This finding, in conjunction with previous work identifying that this region participates in music perception, provides possible evidence for a mirror system for music in this region, and it expands our conception of the range of such a system’s possible functionality beyond the realms of intentional action and linguistic communication. As Molnar-Szakacs and Overy summarize, “a mirror neuron system may provide a domain-general neural mechanism for processing combinatorial rules common to language, action, and music, which in turn can communicate meaning and human affect.”38
Music, Language, and Neural Plasticity
As discussed earlier, improvisation provides an ideal musical substrate for comparison with linguistic processes. In a now (in)famous and oft-quoted statement, psychologist of language Steven Pinker referred to music as “auditory cheesecake, an exquisite confection crafted to tickle the sensitive spots of … our mental faculties.”39 Pinker argues that the brain did not evolve for music, per se, but rather that music “tickles” brain regions (p. 65) evolved for other purposes (e.g., language). He has even gone so far as to suggest that music is “useless” from an evolutionary perspective, and that it could “vanish from our species and the rest of our lifestyle would be virtually unchanged.”40 Pinker’s suggestions have, understandably, been controversial,41 and indeed others have proposed the alternative possibility that language may have evolved from music.42 We will probably never know whether music or language “came first,” evolutionarily speaking, although intriguing theories exist for how music and language may have co-evolved from a common progenitor.43 Perhaps what is most striking about the accumulating evidence that music and language share neural resources and cognitive processes in both perception and production is what this signifies with respect to the extraordinary flexibility of the brain. An area such as the IFG/vPMC may have evolved, generally speaking, for the production and perception of sequences, with the capacity to produce and perceive music and language, as well as a wide variety of combinations of elements of actions. Music is probably not “auditory cheesecake,” tickling innate linguistic areas, nor is language the “auditory bread and butter” of a musically predisposed neural architecture. Rather, highly flexible neural circuits can process a veritable buffet of inputs and outputs. Just as improvising musicians can produce infinite musical possibilities out of a finite set of musical elements and rules for combining them, so too can the improvising mind support an infinite variety of processes out of a finite number of neurons and their interconnections.
This versatility begs the question of whether musical training can actually foster such flexibility beyond merely drawing on it. A growing literature suggests that music does indeed change the brain. These changes are both structural and functional. In terms of structure, musicians have been shown to have 10 percent more fibers in the corpus callosum, the fiber tract that connects the left and right hemispheres of the brain.44 This data on increased size of fiber tracts has been complemented by more recent data using newer imaging techniques that reveal increases in fiber tract organization in trained musicians.45 In addition to such changes in white matter tracts that connect brain regions, increases in the volume of gray matter in such regions throughout the brain (not merely in auditory and motor areas) have been demonstrated in musicians.46
Functionally, it has been shown that musical training expands auditory and sensory representations in the brain.47 Also, in certain contexts, musicians demonstrate different patterns of brain activity when perceiving and processing auditory input,48 as well as in performance of motor tasks,49 when compared to nonmusicians. Research by Nadine Gaab and Gottfried Schlaug has shown that musicians are more successful—and utilize a different set of neural substrates and cognitive operations—in the performance of a pitch memory task when compared to nonmusicians.50 In a follow-up study, Gaab and colleagues showed that when training nonmusicians on a pitch memory task yielded improved performance in certain subjects, there was a concomitant shift from using the network of brain regions that they were using previously (with poorer performance) to recruiting the group of areas used by trained musicians.51 These studies reflect that musical training can lead to shifts in how the brain processes auditory input and motor output, demonstrating the neural correlates of musical expertise.
(p. 66) Such findings raise the age-old nature-nurture question: Are certain individuals born with brains predisposed to music, and do these individuals therefore excel at it and seek musical training—or does musical training itself lead to such changes? Through studies comparing brain and cognitive development of children receiving musical training with that of those who do not, evidence is emerging that musical training changes the brain.52
What insights can the study of the neurobiology of improvisation provide about neural plasticity? As described above, activation in areas involved in auditory processing and motor production appears to be identical between the two groups. The unique difference was that the musicians deactivated the rTPJ, an area involved in bottom-up stimulus-driven attention that is deactivated in top-down, goal-directed attention. The finding of rTPJ deactivation in improvising musicians as compared to nonmusicians suggests that musical training appears to yield cognitive benefits that are not merely music-related. If improvisation training leads to a shift in the ability to activate goal-directed, top-down attention, further research could explore whether training in improvisation actually enhances the ability to modulate attention in this way, and whether this remains limited to improvisatory tasks or is available across domains.
Improvisation is one of many musical processes that have inspired recent investigation with the experimental techniques of cognitive neuroscience. These studies allow for a deeper understanding of the cognitive processes—and the neural correlates of such processes—that support such highly specialized feats of human behavior. Discovering the networks of brain regions that are involved in music contributes to our understanding of the more generalized function of such networks and underscores their remarkable plasticity. Musical training draws on such plasticity in the development of auditory-motor expertise, but it also appears to cultivate changes in brain structure and function that extend beyond musical perception and performance.53 The brain itself can therefore be considered an improviser in its own right, and the study of improvisation and other musical processes has and will continue to play a role in shaping our understanding of this improvising mind.
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Iacoboni, M. “Imitation, Empathy, and Mirror Neurons.” Annual Review of Psychology 60 (2009): 653–670.Find this resource:
Koelsch, S. “Significance of Broca’s Area and Ventral Premotor Cortex for Music-Syntactic Processing.” Cortex 42 (2006): 518–520.Find this resource:
(p. 72) Krings, T. et al. “Cortical Activation Patterns During Complex Motor Tasks in Piano Players and Control Subjects. A Functional Magnetic Resonance Imaging Study.” Neuroscience Letters 278 (2000): 189–193.Find this resource:
Levitin, D. J., and V. Menon. “Musical Structure is Processed in ‘Language’ Areas of the Brain: A Possible Role for Brodmann Area 47 in Temporal Coherence.” NeuroImage 20 (2003): 2142–2152.Find this resource:
Levitin, Daniel. This Is Your Brain on Music: The Science of a Human Obsession. London: Penguin Group, 2006.Find this resource:
Lidov, David. Is Language a Music?: Writings on Musical Form and Signification. Bloomington: Indiana University Press, 2004.Find this resource:
Limb, Charles J., and Allen R. Braun. “Neural Substrates of Spontaneous Musical Performance: An fMRI Study of Jazz Improvisation.” PLoS ONE 3 (2008): e1679. doi:10.1371/journal.pone.0001679Find this resource:
Lotze, M., et al. “The Musician’s Brain: Functional Imaging of Amateurs and Professionals During Performance and Imagery.” NeuroImage 20 (2003): 1817–1829.Find this resource:
McMullen, Erin, and Jenny Saffran. “Music and Language: A Developmental Comparison.” Music Perception 21 (2004): 289–311.Find this resource:
Molnar-Szakacs, I., and K. Overy. “Music and Mirror Neurons: From Motion to ‘E’motion.” Social Cognitive and Affective Neuroscience 1 (2006): 235–241.Find this resource:
Nettl, B. “Introduction: An Art Neglected in Scholarship.” In In the Course of Performance: Studies in the World of Musical Improvisation, edited by Bruno Nettl and Melinda Russell, 1– 26. Chicago: University of Chicago Press, 1998.Find this resource:
Nettl, B. et al. “Improvisation.” In Grove Music Online. Oxford Music Online. http://www.oxfordmusiconline.com/subscriber/article/grove/music/13738 (accessed May 17, 2011).
Pantev, C. et al. “Increased Auditory Cortical Representation in Musicians.” Nature 392 (1998): 811–814.Find this resource:
Patel, Aniruddh. Music, Language, and the Brain. New York: Oxford University Press, 2007.Find this resource:
Peretz, Isabelle, and Robert J. Zatorre. The Cognitive Neuroscience of Music. New York: Oxford University Press, 2010.Find this resource:
Pinker, Stephen. How the Mind Works. New York: W.W. Norton and Company, 1997.Find this resource:
Pressing, Jeff. “Cognitive Processes in Improvisation.” In Cognitive Processes in the Perception of Art, edited by W. Ray Crozier and Anthony J. Chapman, 345–366. Amsterdam: Elsevier, 1984.Find this resource:
Pressing, Jeff. “Improvisation: Methods and Models.” In Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition, edited by John Sloboda, 129–178. Oxford: Oxford University Press, 1988.Find this resource:
Pressing, Jeff. “Psychological Constraints on Improvisational Expertise and Communication.” In In the Course of Performance: Studies in the World of Musical Improvisation, edited by Bruno Nettl and Melinda Russell, 47–68. Chicago: University of Chicago Press, 1998.Find this resource:
Rizzolatti, G., et al. “The Mirror-Neuron System.” Annual Review of Neuroscience 27 (2004): 169–192.Find this resource:
Ruckert, George, and Richard Widdess. “Hindustani Raga.” In The Garland Encyclopedia of World Music. Vol. 5, South Asia: The Indian Subcontinent, edited by Alison Arnold, 64–88. New York: Routledge, 1999.Find this resource:
Ryle, Gilbert. “Improvisation.” Mind 85, no. 337 (1976): 69–83.Find this resource:
Sawyer, R. Keith. “The Improvisational Performance of Everyday Life.” Journal of Mundane Behavior 2 (2001): 149–162.Find this resource:
(p. 73) Sawyer, R. Keith. Creating Conversations: Improvisation in Everyday Discourse. Cresskill: Hampton, 2001.Find this resource:
Schlaug, G. et al. “Increased Corpus Callosum Size in Musicians.” Neuropsychologia 33 (1995): 1047–1055.Find this resource:
Schlaug, G., et al. “Training-induced Neuroplasticity in Young Children.” Annals of the New York Academy of Science 1169 (2009): 205–208.Find this resource:
Slawek, Stephen. “Keeping It Going: Terms, Practices, and Processes of Improvisation in Hindustani Music.” In In the Course of Performance: Studies in the World of Musical Improvisation, edited by Bruno Nettl and Melinda Russell, 335–368. Chicago: University of Chicago Press, 1998.Find this resource:
Sloboda, John. “Musical Expertise.” In Toward a General Theory of Expertise, edited by K. A. Ericsson and J. Smith, 153–171. Cambridge: Cambridge University Press, 1991.Find this resource:
Tolbert, Elizabeth. “Theorizing the Musically Abject.” In Bad Music: The Music We Love to Hate, edited by Christopher Washburne and Maiken Derno, 104–119. New York: Routledge, 2004.Find this resource:
Wan, C. Y., and G. Schlaug. “Music Making as a Tool for Promoting Brain Plasticity Across the Life Span.” Neuroscientist 16 (2010): 566–577.Find this resource:
(1.) Diana Deutsch, et al., “Psychology of Music,” in Grove Music Online. Oxford Music Online, http://www.oxfordmusiconline.com/subscriber/article/grove/music/42574 (accessed May 17, 2011); Robert Gjerdingen, “The Psychology of Music,” in The Cambridge History of Western Music Theory, ed. Thomas Christensen (Cambridge: Cambridge University Press, 2002), 956–981.
(2.) Isabelle Peretz and Robert J. Zatorre, The Cognitive Neuroscience of Music (New York: Oxford University Press, 2010); Diana Deutsch, ed., The Psychology of Music, 2nd ed. (San Diego, CA: Academic Press, 1999).
(3.) D. A. Hodges, W. D. Hairston, and J. H. Burdette, “Aspects of Multisensory Perception: The Integration of Visual and Auditory Information in Musical Experiences,” Annals of the New York Academy of Sciences 1060 (2005): 175–185.
(4.) Jeff Pressing, “Psychological Constraints on Improvisational Expertise and Communication,” in In the Course of Performance: Studies in the World of Musical Improvisation, ed. Bruno Nettl and Melinda Russell (Chicago, IL: University of Chicago Press, 1998), 47–68.
(5.) N. Gaab and G. Schlaug, “The Effect of Musicianship on Pitch Memory in Performance Matched Groups,” Neuroreport 14 (2003): 2291–2295; N. Gaab, C. Gaser, and G. Schlaug, “Improvement-related Functional Plasticity Following Pitch Memory Training,” NeuroImage 31 (2006): 255–263.
(6.) For discussion, see Diana Deutsch, et al. “Psychology of Music,” in Grove Music Online. Oxford Music Online, http://www.oxfordmusiconline.com/subscriber/article/grove/music/42574pg4 (accessed May 27, 2011).
(7.) Bruno Nettl et al., “Improvisation,” in Grove Music Online. Oxford Music Online, http://www.oxfordmusiconline.com/subscriber/article/grove/music/13738 (accessed May 17, 2011). For a review of a wide range of published definitions of improvisation, see Bruno Nettl, “Introduction: An Art Neglected in Scholarship,” in In the Course of Performance: Studies in the World of Musical Improvisation, ed. Bruno Nettl and Melinda Russell (Chicago, IL: University of Chicago Press, 1998), 10–12.
(8.) The improvisatory nature of human behavior is eloquently described in Gilbert Ryle, “Improvisation,” Mind 85, no. 337 (1976): 69–83; R. Keith Sawyer, “The Improvisational Performance of Everyday Life,” Journal of Mundane Behavior 2 (2001): 149–162; and R. Keith Sawyer, Creating Conversations: Improvisation in Everyday Discourse (Cresskill: Hampton, 2001). For further discussion, see Aaron L. Berkowitz, The Improvising Mind: Cognition and Creativity in the Musical Moment (Oxford: Oxford University Press, 2010), 1–14, 177–184.
(9.) S. Brown, et al., “Music and Language Side by Side in the Brain: A PET Study of the Generation of Melodies and Sentences,” European Journal of Neuroscience 23 (2006): 2791–2803; S. L. Bengtsson, M. Csíkszentmihályi, and F. Ullén, “Cortical Regions Involved in the Generation of Musical Structures During Improvisation in Pianists,” Journal of Cognitive Neuroscience 19 (2007), 830–842; Aaron L. Berkowitz and Daniel Ansari, “Generation of Novel Motor Sequences: The Neural Correlates of Musical Improvisation,” NeuroImage 41 (2008): 535–543; Charles J. Limb and Allen R. Braun, “Neural Substrates of Spontaneous Musical Performance: An fMRI Study of Jazz Improvisation,” PLoS ONE 3 (2008): e1679. doi:10.1371/journal.pone.0001679; Aaron L. Berkowitz and Daniel Ansari, “Expertise-related Deactivation of the Right Temporoparietal Junction During Musical Improvisation,” NeuroImage 49 (2010): 712–719. By neuroscience studies, I refer to studies actually examining brain activity during improvisation with brain imaging techniques. For theoretical work on the cognitive psychology of improvisation, see the following brilliant discussions by Jeff Pressing: “Cognitive Processes in Improvisation,” in Cognitive Processes in the Perception of Art, ed. W. Ray Crozier and Anthony J. Chapman (Amsterdam: Elsevier, 1984), 345–366; “Improvisation: Methods and Models,” in Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition, ed. John Sloboda (Oxford and New York: Oxford University Press, 1988), 129–178; “Psychological Constraints on Improvisational Expertise and Communication,” in In the Course of Performance: Studies in the World of Musical Improvisation, ed. Bruno Nettl and Melinda Russell (Chicago, IL: University of Chicago Press, 1998), 47–68.
(10.) For an example of a very elegant solution to creating a control task to be compared in order to elicit the areas involved in hearing musical structure, see D. J. Levitin and V. Menon, “Musical Structure Is Processed in ‘Language’ Areas of the Brain: A Possible Role for Brodmann Area 47 in Temporal Coherence,” NeuroImage 20 (2003): 2142–2152.
(11.) Berkowitz and Ansari, “Generation of Novel Motor Sequences.” For discussion, see also Berkowitz, The Improvising Mind, 131–144.
(12.) For discussion of the neural correlates of melodic and rhythmic performance, see S. L. Bengtsson et al., “Dissociating Brain Regions Controlling the Temporal and Ordinal Structure of Learned Movement Sequences,” European Journal of Neuroscience 19 (2004): 2591–2602; S. L. Bengtsson and F. Ullén, “Dissociation between Melodic and Rhythmic Processing During Piano Performance from Musical Scores,” NeuroImage 30 (2006): 272–284.
(13.) For review, see P. A. Chouinard and T. Paus, “The Primary Motor and Premotor Areas of the Human Cerebral Cortex,” Neuroscientist 12 (2006): 143–152.
(14.) For review and discussion, see Berkowitz and Ansari, “Generation of Novel Motor Sequence,” 541; Berkowitz, The Improvising Mind, 139–140.
(15.) L. M. Parsons et al., “The Brain Basis of Piano Performance,” Neuropsychologia 43 (2005): 199–215.
(16.) S. Koelsch, “Significance of Broca’s Area and Ventral Premotor Cortex for Music-Syntactic Processing,” Cortex 42 (2006): 518–520.
(20.) For review and discussion see M. Corbetta and G. L. Shulman, “Control of Goal-directed and Stimulus-driven Attention in the Brain,” Nature Reviews Neuroscience 3 (2002): 201–215; M. Corbetta, G. Patel, and G. L. Shulman, “The Reorienting System of the Human Brain: From Environment to Theory of Mind,” Neuron 58 (2008): 306–324.
(21.) For further discussion, see Berkowitz and Ansari “Expertise-related Deactivation of the Temporoparietal Junction,” 7–8.
(23.) For review and discussion, see Paul Berliner, Thinking in Jazz (Chicago: University of Chicago Press, 1994).
(24.) For review and discussion, see Stephen Slawek, “Keeping It Going: Terms, Practices, and Processes of Improvisation in Hindustani Music,” in In the Course of Performance: Studies in the World of Musical Improvisation, ed. Bruno Nettl and Melinda Russell, (Chicago: University of Chicago Press, 1998), 335–368; George Ruckert and Richard Widdess, “Hindustani Raga,” in The Garland Encyclopedia of World Music, Vol. 5, South Asia: The Indian Subcontinent, ed. Alison Arnold (New York: Routledge, 1999), 64–88.
(26.) See Berkowitz, The Improvising Mind, 39–96 and 121–130; Pressing, “Improvisation: Methods and Models.” In Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition, ed. John Sloboda (Oxford: Oxford University Press, 1988), 129–178; Pressing, “Cognitive Processes in Improvisation”; Pressing, “Psychological Constraints on Improvisational Expertise and Communication.”
(30.) For comprehensive review and discussion, see Aniruddh Patel, Music, Language and the Brain (Oxford: Oxford University Press, 2007). See also Berkowitz, The Improvising Mind, 97–120 and 145–152; Erin McMullen and Jenny Saffran, “Music and Language: A Developmental Comparison,” Music Perception 21 (2004): 289–311.
(33.) David Lidov, Is Language a Music?: Writings on Musical Form and Signification (Bloomington: Indiana University Press, 2004).
(34.) For review and discussion, see Koelsch, “Significance of Broca’s Area and Ventral Premotor Cortex for Music-Syntactic Processing.”
(35.) G. Rizzolatti et al., “The Mirror-Neuron System,” Annual Review Neuroscience 27 (2004): 169–192; F. Binkofski, “The Role of Ventral Premotor Cortex in Action Execution and Action Understanding,” Journal of Physiology Paris 99 (2006): 396–405.
(36.) For recent review, see M. Iacoboni, “Imitation, Empathy, and Mirror Neurons,” Annual Review of Psychology 60 (2009): 653–670.
(37.) I. Molnar-Szakacs and K. Overy, “Music and Mirror Neurons: From Motion to ‘E’motion,” Social Cognitive and Affective Neuroscience 1 (2006): 235–236.
(39.) Stephen Pinker, How the Mind Works (New York: W.W. Norton and Company, 1997), 534.
(41.) See for example, Ian Cross, “Music and Biocultural Evolution,” in The Cultural Study of Music, ed. Martin Clayton, Trevor Herbert, and Richard Middleton (New York: Routledge, 2003), 19–30; Elizabeth Tolbert, “Theorizing the Musically Abject,” in Bad Music: The Music We Love to Hate, ed. Christopher Washburne and Maiken Derno (New York: Routledge, 2004), 104–119; Philip Ball, The Music Instinct: How Music Works and Why We Can’t Do Without It (New York: Oxford University Press, 2010), 1–31; Daniel Levitin, This Is Your Brain on Music (London: Penguin Group, 2006), 241–262.
(42.) For review and discussion, see W. Tecumseh Fitch, “The Biology and Evolution of Music: A Comparative Perspective,” Cognition 100 (2006): 173–215.
(43.) Stephen Brown, “The ‘Musilanguage’ Model of Music Evolution,” in The Origins of Music, ed. Nils L Wallin, Bjorn Merker, and Steven Brown (Cambridge: MIT Press, 2000), 271–300.
(44.) G. Schlaug et al., “Increased Corpus Callosum Size in Musicians,” Neuropsychologia 33 (1995): 1047–1055.
(45.) S. L. Bengtsson et al., “Extensive Piano Practicing Has Regionally Specific Effects on White Matter Development,” Nature Neuroscience 8 (2005): 1148–1150.
(46.) M. Bangert and G. Schlaug, “Specialization of the Specialized in Features of External Human Brain Morphology,” European Journal of Neuroscience 24 (2006): 1832–1834; C. Gaser and G. Schlaug, “Brain Structures Differ Between Musicians and Nonmusicians,” Journal of Neuroscience 23 (2003): 9240–9245.
(47.) T. Elbert et al., “Increased Cortical Representation of the Fingers of the Left Hand in String Players,” Science 270 (1995): 305–307; C. Pantev et al., “Increased Auditory Cortical Representation in Musicians,” Nature 392 (1998): 811–814.
(48.) N. Gaab, C. Gaser, and G. Schlaug, “Improvement-related Functional Plasticity Following Pitch Memory Training,” NeuroImage 31 (2006): 255–263.
(49.) M. Hund-Georgiadis and D. Y. von Cramon, “Motor-Learning-Related Changes in Piano Players and Non-Musicians Revealed by Functional Magnetic-Resonance Signals,” Experimental Brain Research 125 (1999): 417–425; T. Krings et al., “Cortical Activation Patterns During Complex Motor Tasks in Piano Players and Control Subjects. A Functional Magnetic Resonance Imaging Study,” Neuroscience Letters 278 (2000): 189–193; M. Lotze et al., “The Musician’s Brain: Functional Imaging of Amateurs and Professionals During Performance and Imagery,” NeuroImage 20 (2003): 1817–1829.
(52.) K. L. Hyde et al., “Musical Training Shapes Structural Brain Development,” Journal of Neuroscience 29 (2009): 3019–3025. G. Schlaug et al., “Training-induced Neuroplasticity in Young Children,” Annals of the New York Academy of Science 1169 (2009): 205–208.
(53.) For discussion, see C. Y. Wan and G. Schlaug, “Music Making as a Tool for Promoting Brain Plasticity Across the Life Span,” Neuroscientist 16 (2010): 566–577.