**3. Neuroplasticity and music: macrostructural and microstructural adaptations**

**2. Phylogenetic and ontogenetic claims: the role of adaptation**

making and immersion in a culture [41, 42].

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taking the concept of adaptation as a working hypothesis.

Brain plasticity is an adaptation to the environment with an evolutionary advantage. It allows an organism to be changed in order to survive in its environment by providing better tools for coping with the world [40]. This biological concept of adaptation can be approached from two different scales of description: the larger evolutionary scale of the human as a species (phylogeny) and the more limited scale of the human from newborn to old age (ontogeny). This phylogenetic/ontogenetic distinction is related to the "nature/nurture" and "culture/biology" dichotomy, which refers to the neurobiological claims of wired-in circuitry for perceptual information pickup as against the learned mechanisms for information processing and sense-

These approaches may seem to be diverging at first glance, but they are complementary to some extent. This holds, in particular, for the here-hypothesised music-induced plasticity, which espouses a biocultural view that aims at a balance between genetic or biological constraints and historical/cultural contingencies. This places all human beings on equal ground (unity) by stating that diversity in culture is only an epiphenomenon of an underlying biological disposition that is shared by people all over the world [43]. The assumed unity is attributed to the neural constraints that underlie musical processing in general, but these constraints should not be considered as a static dispositional machinery. The picture that emerges from recent research is arguing, on the contrary, for a definition of the neural machinery as a dynamic system that is able to adapt in answer to the solicitations of a challenging environment [6]. The neurobiological approach to music, therefore, deals not only with the nature and evolution of the innate and wired-in neural mechanisms that are the hallmark of the hominid phylogenetic evolution but also with the ontogenetic development of these mechanisms [43]. As such, it makes sense to conflate neurobiological and developmental claims by

The relation between adaptation and development, however, is asymmetrical in the sense that it is possible to conceive of development without adaptation, but no adaptation is conceivable without development. This development, further, can be natural, when it is the outcome of maturation, but it is possible also to intervene in its trajectory by combining development and learning. This is the case when an organism faces continued and long-term exposure to challenging environments, which triggers plastic changes in the structure and the functions of the brain. This brings us to the concept of brain plasticity, which refers to the fact that neuronal circuits are tuned in close interaction with the environment. It was introduced by William James, who defined plasticity as "the possession of a structure weak enough to yield to an influence, but strong enough not to yield all at once" [44] (p. 106). The idea was further developed by Ramón y Cajal, who claimed that to fully understand the phenomenon it is necessary to admit the formation of new pathways in the brain through ramification and progressive growth of the dendritic arborisation and the nervous terminals in addition to the reinforcement of pre-established organic pathways. The same idea was elaborated further by Donald Hebb, who proposed that neuronal cortical connections are strengthened and remodelled by experience. There is, however, another aspect of plasticity that goes beyond the level of The evolutionary claims of adaptation—both at the phylogenetic and ontogenetic level—have received empirical evidence from neuroimaging and morphometric studies. In order to elucidate its underlying mechanisms, there is currently a whole body of research related to the psychobiological approach to the study of action, cognition and perception. A major claim in this research field is that the nervous system provides the immediate, necessary and sufficient mechanisms that underlie all mental processes, and that mental processes are reducible to the function, arrangement and interaction of neurons as the constituent building blocks of the nervous system [46]. This is the axiom of psychobiological equivalence, which claims an equivalence of maintained information from the neural to the psychological state [47]. The related research revolves around three major themes: (i) the localisation of functions in the brain, (ii) the representation or coding and (iii) the dynamic change or learning [46]. The first investigates which brain structures are responsive for particular processes. The second investigates how neural networks represent, encode or instantiate cognitive processes, both at macrostructural and microstructural level of description (see [48]). The third, finally, investigates how our brain adapts to experience and learning, what changes occur in its neural networks and how these changes correspond to externally observed behaviour.

The third theme—dynamic change or learning—concerns the neural correlates of skill acquisition and has been studied mainly at the level of perceptual processing and motor output. Yet, there is also the whole domain of creativity [49], musical aesthetics [6, 50–53] and human interaction [54, 55], which have been poorly investigated in relation to long-term music training. However, the topic is exemplary of a paradigm shift in current neuromusicological research, with a transition from a static conception of brain modules to a conception of reorganisational plasticity of the developing and adult brain [6]. Plasticity, in fact, is a fundamental organisational feature of the human brain, which can be modified throughout the life span in response to changes in environmental stimulation. This has been observed not only during a critical period in the developing brain but also even throughout the whole life span.

Skill learning, such as learning to play a musical instrument, can thus be used for the study of neuroplasticity. It typically starts early in life, while the brain is most sensitive to plastic changes, and continues often throughout life. It involves multiple sensory modalities and motor planning, preparation and execution systems [27, 56]. The role of environmental enrichment—being defined as a combination of complex inanimate and social stimulation [57]—on the other hand, should be stressed also as an emerging area of research. Music, in this view, can be considered as "sounding environment" [42], which is likely to drive brain plasticity. Even in the foetal phase of development, sounds can trigger ways of implicit learning [58]. Neonates and infants also learn to talk and sing quasi-effortless as the result of mere exposure, thus demonstrating implicit learning and developmental plasticity, which is even cross-modal to a large extent, in the sense that loss of one sensory modality may lead to neural organisation of the remaining modalities [2].

been studied in the context of deafferentation studies—in the case of brain lesion—and in the case of motor skill learning [62]. In the former, some cortical remodelling has been found, including microstructural changes, such as the strengthening of existing synapses, the formation of new synapses (synaptogenesis), axonal sprouting and dendrite growth. In the latter, similar changes have been found, including an increased number of synapses per neuron and changes in the number of microglia and capillaries [63], which all lead to volumetric changes

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The bulk of studies on neuroplasticity has been performed in the context of within-modality plasticity, particularly in the domain of sensory and motor modalities. They aim at demonstrating the adaptive capabilities of the human brain to shape the processing of sensory stimuli or to perform motor acts after repeated sensory exposure or action [9]. With regard to the sensory modality, animal studies have shown that environmental change critically affects brain development. Experience-driven neural activity, in fact, regulates the refinement of the neural circuitry by influencing various neural processes, such as synapse formation, pruning and synaptic plasticity (see **Box 1**) with modifications in synaptic connectivity as a result [65]. This enhanced connectivity, further, acts as a basis for learning and memory through alterations at the level of neural circuits [66], such as strengthening or weakening of the synaptic links or altering their number, changes in the number or properties of postsynaptic receptors in transmitter release and the formation of new synapses. The result is an increase in synaptic strength, which may be persistent and facilitate learning and memory so that experiencedependent plasticity could involve selective changes in pre-existing brain circuits [65].

As to the enhanced auditory skills, it has been argued that they may prime the brain for the processing of musical sounds and that these skills may percolate to other domains, such as speech, emotion and auditory processing in general [67, 68]. This has been observed already in the early stages of the auditory pathway, which are located mainly in the brainstem. Musicians have enhanced temporal and frequency coding in the auditory brainstem with

**Myelinisation**: the acquisition, development or formation of a myelin sheath around a nerve fibre. This fatty coating serves as insulation of individual fibres to enhance specificity of connections and increases markedly the quick and

**Pruning**: a process that helps sculpt the adult brain and by which neurons and synaptic connections that are no

**Sprouting**: a process by which a neuron generates additional branches or outgrowths to establish new links between existing neurons, as seen frequently in the case of growth of axons or dendrites from a damaged or intact neuron that

**Synaptic plasticity**: strengthening or weakening of the synaptic links either by modulating the strength of synapses

**Synaptic efficacy**: changes in the number or properties of postsynaptic receptors in transmitter release and the for-

**Adult neurogenesis**: birth of neurons from neural stem cells in the adult brain. In humans, adult neurogenesis has been shown to occur only in the hippocampus (particularly in the sub-granular zone of the dentate gyrus) and in the

longer used or useful are eliminated in order to increase the efficiency of neuronal transmissions.

that are detectable also at the macrostructural level [27, 64].

accurate transmission of electrical current from one nerve cell to another.

**Box 1.** Overview of some basic mechanisms for refinement of the neural circuitry

projects to an area that is denervated.

mation of new synapses (synaptogenesis).

striatum. It differs from developmental neurogenesis.

or by altering their numbers.

Neuroplasticity is also related to the field of sensory-motor learning, with a major role attributed to the challenges of a rich environment. It favours multiple interactions with the world both at the sensory and at the motor level—stressing the interdependency of an organism and its environment through which it "enriches its repertory of genetic adaptations with acquired dispositions that are immediately at hand and mobilizable when confronted with a situation that can be foreseen or recognized as a familiar one" [59] (p. 925).

Musical training, accordingly, may be related to sensory and motor changes in the human brain of professional musicians. As a rule, music training involves years of sensory-motor training, often beginning in early childhood, with the aim to develop an expertise in a chosen instrument or mastery over the own voice, together with an improvement of the ability to attend to the fine-grained acoustics of musical sounds, including pitch, timing and timbre [3]. The brains of musicians might adapt to the demands of their instrumental practice at two levels: the gross anatomical differences between professional musicians and amateurs or laymen, and the subtle functional differences after enhanced musical practice and/or experience, which have to be sought in ever finer modifications of synaptic strength in distributed cortical networks. As such, it is possible to distinguish between macrostructural and microstructural adaptations. The macrostructural differences related to volume, morphology, density and connectivity of brain structures are measured with magnetic resonance imaging (MRI), whereas the microstructural differences in the functional activity of brain regions are measured with functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and neurophysiology (electroencephalography, EEG and magnetoencephalography [MEG]) (see [5] for an overview). It is further hypothesised that functional reorganisation may cause structural adaptation. For instance, bimanual instrument training, such as for the piano, may cause an increase in cortical functionality for symmetric areas involved in motor, auditory and visuospatial processing, as well as in the white matter tracts of the corpus callosum [20] as compared with less bimanual training (such that for the violin) and especially as opposed to laypersons.

At the macrostructural level, studies show differences in the size of the primary motor cortex size, the cerebellum, the planum temporale, the corpus callosum, Heschl's gyrus and the arcuate fasciculus, all of which seem to correlate with the ability of musicians to identify and process acoustic variations [60]. The microstructural adaptations, on the other hand, happen at the level of individual neurons and synapses, with the aim to change the efficacy of neural connectivity. In general, the brain shows adaptation to extraordinary challenges by giving birth to new neurons (neurogenesis) and glial cells and by the formation and remodelling of new connections by the outgrowth of dendrites, axonal sprouting and increasing or strengthening of synaptic connections [61] (see **Box 1** for an overview). Such adaptations have been studied in the context of deafferentation studies—in the case of brain lesion—and in the case of motor skill learning [62]. In the former, some cortical remodelling has been found, including microstructural changes, such as the strengthening of existing synapses, the formation of new synapses (synaptogenesis), axonal sprouting and dendrite growth. In the latter, similar changes have been found, including an increased number of synapses per neuron and changes in the number of microglia and capillaries [63], which all lead to volumetric changes that are detectable also at the macrostructural level [27, 64].

the other hand, should be stressed also as an emerging area of research. Music, in this view, can be considered as "sounding environment" [42], which is likely to drive brain plasticity. Even in the foetal phase of development, sounds can trigger ways of implicit learning [58]. Neonates and infants also learn to talk and sing quasi-effortless as the result of mere exposure, thus demonstrating implicit learning and developmental plasticity, which is even cross-modal to a large extent, in the sense that loss of one sensory modality may lead to neural

Neuroplasticity is also related to the field of sensory-motor learning, with a major role attributed to the challenges of a rich environment. It favours multiple interactions with the world both at the sensory and at the motor level—stressing the interdependency of an organism and its environment through which it "enriches its repertory of genetic adaptations with acquired dispositions that are immediately at hand and mobilizable when confronted with a situation

Musical training, accordingly, may be related to sensory and motor changes in the human brain of professional musicians. As a rule, music training involves years of sensory-motor training, often beginning in early childhood, with the aim to develop an expertise in a chosen instrument or mastery over the own voice, together with an improvement of the ability to attend to the fine-grained acoustics of musical sounds, including pitch, timing and timbre [3]. The brains of musicians might adapt to the demands of their instrumental practice at two levels: the gross anatomical differences between professional musicians and amateurs or laymen, and the subtle functional differences after enhanced musical practice and/or experience, which have to be sought in ever finer modifications of synaptic strength in distributed cortical networks. As such, it is possible to distinguish between macrostructural and microstructural adaptations. The macrostructural differences related to volume, morphology, density and connectivity of brain structures are measured with magnetic resonance imaging (MRI), whereas the microstructural differences in the functional activity of brain regions are measured with functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and neurophysiology (electroencephalography, EEG and magnetoencephalography [MEG]) (see [5] for an overview). It is further hypothesised that functional reorganisation may cause structural adaptation. For instance, bimanual instrument training, such as for the piano, may cause an increase in cortical functionality for symmetric areas involved in motor, auditory and visuospatial processing, as well as in the white matter tracts of the corpus callosum [20] as compared with less bimanual training (such that for the violin) and especially as opposed to laypersons. At the macrostructural level, studies show differences in the size of the primary motor cortex size, the cerebellum, the planum temporale, the corpus callosum, Heschl's gyrus and the arcuate fasciculus, all of which seem to correlate with the ability of musicians to identify and process acoustic variations [60]. The microstructural adaptations, on the other hand, happen at the level of individual neurons and synapses, with the aim to change the efficacy of neural connectivity. In general, the brain shows adaptation to extraordinary challenges by giving birth to new neurons (neurogenesis) and glial cells and by the formation and remodelling of new connections by the outgrowth of dendrites, axonal sprouting and increasing or strengthening of synaptic connections [61] (see **Box 1** for an overview). Such adaptations have

organisation of the remaining modalities [2].

90 Neuroplasticity - Insights of Neural Reorganization

that can be foreseen or recognized as a familiar one" [59] (p. 925).

The bulk of studies on neuroplasticity has been performed in the context of within-modality plasticity, particularly in the domain of sensory and motor modalities. They aim at demonstrating the adaptive capabilities of the human brain to shape the processing of sensory stimuli or to perform motor acts after repeated sensory exposure or action [9]. With regard to the sensory modality, animal studies have shown that environmental change critically affects brain development. Experience-driven neural activity, in fact, regulates the refinement of the neural circuitry by influencing various neural processes, such as synapse formation, pruning and synaptic plasticity (see **Box 1**) with modifications in synaptic connectivity as a result [65]. This enhanced connectivity, further, acts as a basis for learning and memory through alterations at the level of neural circuits [66], such as strengthening or weakening of the synaptic links or altering their number, changes in the number or properties of postsynaptic receptors in transmitter release and the formation of new synapses. The result is an increase in synaptic strength, which may be persistent and facilitate learning and memory so that experiencedependent plasticity could involve selective changes in pre-existing brain circuits [65].

As to the enhanced auditory skills, it has been argued that they may prime the brain for the processing of musical sounds and that these skills may percolate to other domains, such as speech, emotion and auditory processing in general [67, 68]. This has been observed already in the early stages of the auditory pathway, which are located mainly in the brainstem. Musicians have enhanced temporal and frequency coding in the auditory brainstem with

**Myelinisation**: the acquisition, development or formation of a myelin sheath around a nerve fibre. This fatty coating serves as insulation of individual fibres to enhance specificity of connections and increases markedly the quick and accurate transmission of electrical current from one nerve cell to another.

**Pruning**: a process that helps sculpt the adult brain and by which neurons and synaptic connections that are no longer used or useful are eliminated in order to increase the efficiency of neuronal transmissions.

**Sprouting**: a process by which a neuron generates additional branches or outgrowths to establish new links between existing neurons, as seen frequently in the case of growth of axons or dendrites from a damaged or intact neuron that projects to an area that is denervated.

**Synaptic plasticity**: strengthening or weakening of the synaptic links either by modulating the strength of synapses or by altering their numbers.

**Synaptic efficacy**: changes in the number or properties of postsynaptic receptors in transmitter release and the formation of new synapses (synaptogenesis).

**Adult neurogenesis**: birth of neurons from neural stem cells in the adult brain. In humans, adult neurogenesis has been shown to occur only in the hippocampus (particularly in the sub-granular zone of the dentate gyrus) and in the striatum. It differs from developmental neurogenesis.

**Box 1.** Overview of some basic mechanisms for refinement of the neural circuitry

earlier (as early as 10 ms after acoustic onset) and larger responses than non-musicians to both speech and music stimuli. This has been shown for the onset response and the frequencyfollowing response (FFR), i.e., a neuronal ensemble response that phase-locks to the incoming stimulus and that underlies perception of pitch as it relates to the sustained portion of a periodic sound with less or more stable frequencies [68, 69].

Functional connectivity can be defined as the temporal dependence of neuronal activity patterns of anatomically separated and removed regions in the brain, reflecting the level of communication between them [80]. It makes it possible to examine the brain as an integrative network of functionally interacting regions and to gain new insights into large-scale neuronal communication in the human brain. Such whole-brain connectivity patterns can be studied by measuring the synchronisation of spontaneous fMRI or MEEG time-series reflecting neural activity of anatomically separated brain regions, which are recorded during rest. These resting–state networks are believed to reflect the functional communication between brain regions [78, 81] and suggest an ongoing information processing and functional connectivity between them even at rest, which is related to neuronal firing. The pattern of correlations between distinct brain areas, moreover, points at the existence of organisational networks in the brain [81], which seems to be analogous to the networks that are engaged during the performance of sensory-motor and cognitive tasks, and which are dependent upon the brain's anatomical connectivity [10]. Such spontaneous neuronal interaction has been first investigated in motor cortices but were later extended to other cortical systems, such as the visual and auditory networks, the default mode network (DMN) and attention and memory related regions. It has been suggested that at least 10–12 resting-state networks (RSNs) can be detected in the cerebral cortex in resting state, which implicates that they represent some intrinsic form of brain connectivity with temporal correlations

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DMN has been related to specific brain functions, such as self-referential thoughts, emotional perspectives and levels of self-awareness. DMN is believed to be a neural circuit that constantly monitors the sensory environment and displays high activity during lack of focused attention on external events [83]. It seems to function as a toggle switch between outwardly focused mind states and the internal or subjective sense of self [84] and can be used to explore the functional connections of the complex integrative network of functionally linked brain regions, which continuously share information with each other. As such, there are interconnected resting-state neuronal communities or functional brain networks with functional communication between them. Being organised according to an efficient topology, they combine efficient local information processing with efficient global information integration with the most pronounced functional connections found between those regions

Overall, resting-state fMRI oscillations reflect ongoing functional communication between distinct brain regions [78], which makes them indicative of the level of cognitive functioning in general. There seems to be, in fact, a link between an efficient organisation of the brain network and intellectual performance—this is the neural efficiency hypothesis—so that functional connectivity patterns may be used as a powerful predictor for cognitive performance [85]. This resting-state connectivity, further, is not to be considered as an established and fixed property, but as a state that can be modulated by recent experiences and learning episodes, both within and between the networks they recruit. Such modulation points in the direction of a learning consolidation function of resting-state brain activity, as evidenced by the findings that high learners manifest stronger pre-task resting-state functional connectivity between the involved regions than low learners [10]. It thus seems that, even in the absence of

between spatially discrete regions [82].

that share common functions.

The role of auditory brainstem processing of behaviourally relevant sounds such as speech and music is important here. It can be measured by using the onset response and the FFR to see how the brainstem represents pitch, timing and timbre [68]. It has been shown that both temporal and spectral characteristics of sounds are preserved in this subcortical response (see [70] for an overview), reflecting the physical properties of sound with an unrivalled fidelity. As a rule, it occurs automatically at pre-attentive levels of auditory processing but is shaped by both long-term and short-term experience [71–73]. Subcortical function, moreover, is neither passive nor hardwired but interacts dynamically with higher-level cognitive processes refining the transcription of sounds into neural code. Hence, the responses do not originate merely in the brainstem but receive feedback from top-down cortical influences even at the earliest stages of auditory processing [3] via corticofugal feedback pathways [74, 75]. As such, it can be demonstrated that musical practice changes the early sensory encoding of auditory stimuli [68] relying on a top-down feedback system—consisting of efferent effects on cochlear biomechanics—that is continuously and automatically engaged to extract and represent regularities in the auditory system [3]. Musical training is thus not limited to the modification of cortical organisation but the modifications extend to subcortical sensory structures and generalise to early processing of speech and sounds in general.

Moreover, early auditory evoked responses and particularly the negative–positive complex (N19-P30) in the auditory evoked potential [76] localised in the primary auditory cortex (the anteromedial portion of Heschl's gyrus) have been found to be larger in musicians compared to amateurs and non-musicians. Moreover, it has been found that the generating neural tissue, namely the grey matter volume of the primary auditory cortex, was broader in volume for professional musicians [77] as compared to laypersons. It thus seems that music can trigger both macrostructural and microstructural or functional changes, not as separate and distinct levels of adaptations, but as phenomena that are dynamically and tightly interconnected.
