Brain plasticity and music

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Neuroplasticity allows the brain to adopt to environmental factors that cannot be anticipated by genetic programming. As in every learning process there have to be adaptations and changes in the brain during learning an instrument. These changes are growth and improvement of new dendrites, synapses and neurons or the disinhibition or inhibition of pre-existing lateral connections between neurons by sensory input. Professional musicians need special skills which are necessary to interpret and play music, a highly complex and multidimensional task, including besides others the following skills:

- Bimanual coordination of many notes (up to 1800 per minute for pianists)

- Integration of sensory and motor information, such as the translation of visually presented musical symbols into complex sequences of finger movements

- Structuring of tones in time (rhythm)

- Improvisation, Memorization of long musical phrases

- Identification of tones without reference tone

- Memorization of the immediate past, prediction of the immediate future and categorization of the input according to its features

In every learning process synapses are altered by temporal input patterns in a competitive network. The structure of the stimulus and its significance determine the resulting neural changes. Motor learning occurs in several phases and leads to gradual performance increases:

1) Fast initial phase of performance gains

2) Period of consolidation for several hours

3) Slow learning phase during continued practice

In musician there is a rapid increase in blood flow in the primary motor cortex during exposition to a novel tapping task. This is due to pre-practice experience. The higher efficiency of professionals in learning new musical skills is represented by a more efficient movement control and recruitment of smaller neural networks in the supplementary motor area (SMA).

Music stimuli mostly influence auditory and motor areas. In line with this, a musician’s brain differs anatomically in these regions. The structural differences are more pronounced when starting a professional career at an early age. The cortical representation of the left hand digits is larger in string-players than in controls because of the independent finger movements required when playing a string instrument. Main anatomical differences between musicians and non-musicians as revealed by Magnetic Resonance Imaging (MRI) were found in the planum temporale, the anterior corpus callosum, the primary hand motor area and the cerebellum. When musical training started before the age of seven, the interaction between the hemispheres is improved due to a higher number of axons that cross the midline. Furthermore, the gray matter has more volume in musician’s brains, especially in primary sensorimotor regions, left basal ganglia, the bilateral cerebellum and the left posterior perisylvian region. A higher gray matter volume means that there are more synapses per neuron, more glia cells and glial volume per Purkinje cell. The higher amount of gray matter in the left Heschl's gyrus (HGL) is associated with differences in source activity while listening to tones.

The superior parietal region (SPCR) is of great importance for the integration of multimodal sensory information and for guiding motor operations. Professional musicians show higher gray matter volume in this area. [Figure 1 and 2, Gaser&Schlaug] While playing an instrument the continuous projection of the inferotemporal cortex into the ventral prefrontal cortex is neccessary to choose actions from visual cues. An increased gray matter volume was found in musicians in the inferior temporal gyrus.

The described neuroplasticity could be due to neural changes in frequency maps after auditory training. In accordance to increased gray matter volumes in musicians, there are also increased signals in the mesial portion of Heschl's gyrus, the posterior superior temporal and inferior anterior parietal brain regions (supramarginal gyrus, SMG) after short-term training of pitch memory in musicians. The study that obtained the above mentioned results required the test subjects to compare tones or to solve a control motor task by pushing a button. Heschl’s gyrus plays a critical role in solving pitch discrimination tasks. Subjects were expected to use mainly the short-term auditory memory for memorizing the tones for comparison. This should mirror in activation of structures like the supramarginal gyrus. [insert Figure 7, Gaab] When strong musical learners were compared to weak learners (definition due to percentage of correct answers) the importance of the SMG as short-term auditory storage became evident. Mainly in this region an increased signal was visible. In the regions necessary for episodic memory functions (posterior cilagulate gyrus) and regions for selecting and filtering auditory information for long term storage (parahippocampal) signal increases equally occurred. This can lead to subsequent long-lasting neural changes. It was shown that skilled performances, as those of professional musicians, may involve different and more elaborate brain regions. On the contrary, weaker learners used some form of visual encoding of the tonal information.

Before long-term neural changes can occur, short-term changes and excitatory as well as inhibitory modulations in response to an auditory stimulus are required. These effects can also be caused by selective attention and cross-modal effects of visual stimulation which are discussed below. Short-term plasticity is defined as any feed-forward (bottom-up) or feedback (top-down) input, excitatory or inhibitory, that transiently modulates the responsiveness of the target neurons to a subsequent stimulus. It can also change the oscillatory properties of local neuronal populations that influence the processing in other cortical structures. As mentioned above it can be driven through by distinct types of input:

1) bottom-up input (auditory stimuli) The tuning via this route works by suppression of neurons of the auditory cortex for several seconds after their initial excitatory response to an auditory stimulus. This phenomenon is called stimulus-specific adaptation (SSA). SSA is supposed to delay and weaken responses to stimuli that slightly differ in frequency and is vital for speech comprehension and working memory tasks for which auditory information has to be accessed over a few seconds. SSA in the anterior and posterior cortex gives rise to mismatch negativity (MMN). MMN is a frontal negative wave in the event related potential (ERP) and a marker of pre-attentive detection of changes in regular sequences of auditory stimuli. MMN occurs in absence of attention to the stimuli and can rise in professional musicians for tones that are mismatched by as little as 20 ms in a series of regularly spaced tones. A MMN for slightly impure chords among perfect major chords is also present in professional musicians. The MMN arises mainly from neurons on the supratemporal plain of the temporal lobe with contributions from the frontal cortex.

2) top-down input (from other cortical areas) Focusing attention on a given acoustic feature seems to enhance neural selectivity by selectively elevating the activity in that part of the auditory cortex that specializes on processing this feature. For example, human anterior auditory cortex (putative “what” pathway) shows enhanced activity to phonemes when attention is drawn to phonetic features. Similarly, the posterior auditory cortex (so-called “where” pathway) is enhanced while attention is directed to stimulus locations. [insert Figure 2, Jaeaeskelinen] The neurophysiological correlate of this selective attention mechanism are spectrotemporal receptive fields (STRF) of A1 neurons. Changes in the STRF correlate with improved behavioral task performance and persist only during the performance. The fields are transiently modulated to encompass the frequency of the targeted tone. It is caused by top-down center excitation spanning one octave around the target frequency and inhibiting the surrounding. The STRF of a neuron can change during different task conditions. [insert Figure 3b, Jaeaeseklinen] As shown above top-down input is as important as bottom-up input for the tuning of neurons. The auditory cortex serves as an interaction surface between bottom-up information from the environment and top-down information representing the goals of the organism. [insert Figure 1b, Jaeaeseklinen]

3) cross-modal input (visual stimuli) Multisensory processing is anatomically supported by connections between auditory and visual cortex, heteromodal cortex and the prefrontal "mirror-neuron" system. It has been suggested that visual input influences auditory processing mainly through top-down feedback at an early processing stage. The visual stimuli can either be related to speech and help speech processing as in the case of lip-reading or they can be as complex as a natural scene, activating audiovisual associations. It has further been suggested that crossmodal input initially causes excitation followed by post-stimulus inhibition. The pattern of the responses are not random and might help the auditory cortex to detect relevant features more easily. The reaction strongly depends on the stimulus timing, its type and the specific task.

There is much evidence that short-term plasticity of the hierarchically organized parallel auditory system supports perceptual long-term training. To conclude, the neuronal adaptations achieved during professional musical training are evident in enhanced connections between specific brain regions but the exact mechanisms are still far from being fully understood.