**4. Music facilitates neural connectivity**

Music can trigger plastic changes in the brain, as evidenced by the rich history of structural and functional neuroimaging studies of the past decades. Recent advances in functional neuroimaging have furthermore provided new tools for measuring the functional interactions and communication between distinct regions in the brain and for examining their functional connectivity [78]. In an attempt to study the brain as a complex network of functionally and structurally interconnected regions, a fuller understanding of its organisation and function is proposed by relying on the contributions of network science [79], which investigates complex systems in terms of their elements and the relationships and interactions between these elements.

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 between spatially discrete regions [82].

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

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 gen-

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.

Music can trigger plastic changes in the brain, as evidenced by the rich history of structural and functional neuroimaging studies of the past decades. Recent advances in functional neuroimaging have furthermore provided new tools for measuring the functional interactions and communication between distinct regions in the brain and for examining their functional connectivity [78]. In an attempt to study the brain as a complex network of functionally and structurally interconnected regions, a fuller understanding of its organisation and function is proposed by relying on the contributions of network science [79], which investigates complex systems in terms of their elements and the relationships and interac-

periodic sound with less or more stable frequencies [68, 69].

92 Neuroplasticity - Insights of Neural Reorganization

eralise to early processing of speech and sounds in general.

**4. Music facilitates neural connectivity**

tions between these elements.

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 that share common functions.

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 external stimuli or demands, the brain is constantly sharing information. It thus consolidates recent learning and maintains the association of activity of brain areas that are likely to be used together in future [86].

destruction of some areas in degenerative diseases of the brain. This has been shown most typically in the case of Alzheimer's disease (AD), which is characterised by a general and progressive decline in cognitive function, with the first symptom as an impaired episodic memory. Music, in this case, has been reported as one of the domains in which general skill and memory are preserved in spite of otherwise severe impairment [90]. This preserved musical processing, moreover, is not limited to procedural memory but often includes also stories of music, which

Music and Brain Plasticity: How Sounds Trigger Neurogenerative Adaptations

http://dx.doi.org/10.5772/intechopen.74318

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Hence, music may shape the development of normal and healthy human beings over the lifespan, but its potential as a non-pharmacological interventional aid for caregivers to help the cognitive and emotional capacity of patients with neurological and psychiatric brain disorders is receiving growing interest [15]. The use of resting-state fMRI techniques, e.g., with a main focus on the default mode network, seems to be well-suited to examine possible functional disconnectivity effects in disorders such as Alzheimer's disease, depression, dementia and schizophrenia. Also, other neurogenerative diseases like multiple sclerosis and amyotrophic lateral sclerosis seem to show changed connectivity in the default network as well as in other resting-state networks [78]. This may suggest that neurodegenerative diseases would attack interconnected cortical networks rather than single regions in the brain [92] and can thus be targets of a music intervention aimed at stabilising abnormal patterns of functional

Music has been used already as a treatment for some psychiatric and neurological pathologies, such as schizophrenic disorders, Alzheimer's disease, Parkinson's disease, cerebral ischemia, pain, autism, anxiety and depression [15]. Music, furthermore, has been reported to improve also the well-being and cognitive functions in healthy adults, such as autobiographical memory, semantic memory, language ability and cognitive functions, and to alleviate neuropsychiatric symptoms, such as agitation, apathy, depression and anxiety (see [39] for an overview). Effects of music on AD are exemplary of the mechanisms that might mediate the impact of music on human well-being. Latent benefits of musical mnemonics as an aid to standard mnemonic methods, which may seem to be insufficient for AD patients, have been reported (for a review, see [15]). The mechanisms behind these memory-enhancing effects, however, are still not fully understood, but there is strong evidence for a benefit of music as a mnemonic device in a variety of clinical settings [91]. A possible explanation is that the areas of the brain associated with music cognition are preferentially spared in the case of AD. It has been suggested that procedural memory and priming effects for musical stimuli remain intact, whereas short-

term and long-term episodic memory for melodic excerpts is impaired [93].

This dissociation between memory and general performance in AD patients holds in particular for listening to their favourite songs, which seems to recruit previously encoded memories. These memories seem to support and sustain brain introspection via connectivity within the default mode network and also to effectively reprocess autobiographic and episodic memories [84]. An additional explanation for this dissociation is that in patients with general cortical and hippocampal atrophy, which impairs standard episodic learning, musically-associated stimuli allow for a more diversified encoding. Music processing, in that case, encompasses a neural network that is recruiting from multiple areas of the brain, including

can be used as an effective mnemonic device [91].

connectivity between compromised brain areas.

Initial research suggests that musical training might enhance this pattern of increased restingstate connectivity by triggering heightened connections at a functional level between those brain regions that are structurally and functionally altered as the result of training. This is manifested even during a task-free condition, pointing to the "silent" imprint of musical training on the human brain [35]. Research on the differences between musicians and non-musicians in their functional connectivity during rest, however, is still in its infancy [10, 82]. By selecting predefined seed regions for computing connectivity analysis, increased connectivity between contralateral homologue regions has been found in musicians between prefrontal, temporal, inferior-parietal and premotor areas [35]. It is to be questioned, however, whether the study of predefined regions or seed regions does not neglect residual whole-brain dynamics. However, for the seed regions for which plastic changes in musicians have been found already—as evidenced by increased grey matter volume—connectivity analyses have revealed brain areas whose resting-state time series activity was more closely synchronised with one of them. Four networks were found to supply integrative interpretations for the cognitive functions during musical practice: (i) autobiographical memory-related regions belonging to the default mode network, recruited by the encoding, storage and recall of melodies with an emotional and biographical quality; (ii) areas that belong to the salience network with access to semantic memory that is related to the storage of music in terms of verbal labels and auditory structure; (iii) regions that are implied in language processing and the resting-state auditory network and (iv) structures that belong to the executive control network, and which could subserve the motor modulation required for an emotionally expressive interpretation of music. The question whether this practice-related plasticity is triggered by local grey matter volume, however, is not yet satisfactorily resolved, in the sense that other variables may be implicated in the expertise-related resting-state functional reorganisation of musician's plastic brain [10].
