Brain plasticity and music: Difference between revisions

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{{EZarticle-open-auto|CZ:Guidel 2008 summer course on Music and Brain‎}}
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Neuroplasticity allows the brain to adopt to environmental factors that cannot be anticipated by genetic programming. Like in every learning process there have to be adaptions and changes in the brain during learning an instrument. These cahnges are de novo growth and improvement of new dendrites, synapses and neurons or the disinhibition or inhibition of preexisting lateral connections between neurons by sensory input. Professional musicians need some special skills which are neccessary to interpret and play music, a in several dimensions highly complex and structured matter:
'''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:
- bimanually coordination of many notes (up to 1800 for pianists)
- integration of sensory and motory information, like the translation of visually presented musical symbols into complex sequence fingermovements
- structure tones temporally to become music
- improvisation, memorization of long musical phrases
- identification of tones without reference tone
- memorize immediate past, predict what is going to be next and categorize


- 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 driven to change by temporally inputs in a competitative network. The structure and significance of the stimulus determines the neural changes that result.  
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:
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 the primary motor cortex during exposing to a novel tapping task. This is due to the pre-practice experience, the higher efficiency in professionals by learning new musical skills is represented by the more efficient movement control and recruitment of smaller neural networks in the supplementary motor area (SMA).


1) Fast initial phase of performance gains


The music stimulus mostly influences auditory and motor domaqins. therefore a musicians brain differs anatomically in this regions due to neuroplasticity which adapts the complex hierarchical organization of parallel sound feature processing from primary to secondary auditory areas. The structural differences are more visible when starting professional musician career with an early age.
2) Period of consolidation for several hours
The cortical representation of the left hand digits is larger in string-players because of the independent movement. Main differences were found in the planum temporale, the anterior corpus callosum, the primary temperale correlate with handedness, while the primary hand motor area is bigger at all, but more on the right. When musical trining 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 grey matter has more volume in musician brains, expecially in primary sensorimotor regions, left basal ganglia, the bilateral cerebellum and the left posterior perzsilvian region. A higher grey matter volume means more synapses per neuron, more gliacells and glial volume per Purkinje cell.
The higher amount of the grey matter in the left Heschl's gyrus (HGL), located in the cerebellar lobes HV/HVI (definition after Larsell and Jansen, 1971) is associated with neurophysiological source activity differences while listening to tones. To integrate multimodal sensory information and guide motor operation the superior paretal region (SPCR) is a main factor, professional musicians show higher gray matter volume here as well. [Figure 1 and 2, Gaser&Schlaug]
While playing an instrument the continously projection of the inferotemporal cortex into the ventral prefrontal cortex is neccessary to choose actions procupted by visual stimuli. An increased grey matter volume was found in musicians in these inferior temporal gyrus.


3) Slow learning phase during continued practice


The described neuroplasticity could be due to electrophysical changes in frequency discrimination designs after auditory training, like in musicians.
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).
In accordance to increased grey matter volumes in musicians there are increased signals in the mesial portion of Heschl's gyrus, the posterior superior temporal and inferior anterior parietal brain region (supramarginal gyrus, SMG) after short-term training of the pitch memory in musicians brains. In the study where the results were obtained, the testpersons had to compare tones and solve a motor task by pushing a directed button after a task. To solve pitch discrimination tasks the Heschl gyrus plays a critical role. For the memorization of the tones the testers should compare mainly the short-term auditory memory, like the supramarginal gyrus, has to be activated. [insert Figure 7, Gaab]
When strong musical learners were compared to weak learners (definition due to percentage of correct answers) the importance of teh SMG as short-term auditory storage is evident. mainly in this region an increased signal is visible. In the regions neccessary for episodic memory functions (posterior cilagulate gyrus) and regions for selecting and filtering auditory information for long term storage (parahippocampal) also positive signal increases occured. These can lead to neuroplasticity. It was shown that skilled performances, like these of professional musicians, may involve different and more effective brain regions. Weaker learners used some form of visual encoding of the tonal information in the study.




Before neuroplasticity occurs, short-term plasticity and excicatory as well as inhibitory modulations 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 as followed.
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.  
Short-term plasticity is defined as any feed-forward (bottom-up) and feedback (top-down) inputs, both excicatory and inhibitory, that transiently modulate the responsiveness of the target neurons to a sub-sequent stimulus. It can also change local neuronal population oscillatory properties which influence the processing in other structures of the cortex. As mentioned above it can be driven through different inputs:
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.


''1) bottom-up inputs (auditory stimuli)''
The described neuroplasticity could be due to neural changes in frequency maps after auditory training.
The tuning by this stimulus works due to the supression of neurons of the auditory cortex for several seconds after their initial excicatory response to an auditory stimulus. This phenomenon is called stimulus-specific adaption (SSA). SSA is supprosed to delay and weaken responses to stimuli that slightly differ in frequency and is vital for speech comprehension and working memory tasks where auditory information has to be accessed over a few seconds. SSA in the anterior and posterior cortex give rise to mismatch negativity (MMN). MMN is a frontal negative wave in the eventrelated potential (ERP) and a marker of the 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 al 20 ms in a series of regularly spaced tones. A MMN for slightly inpure records among perfect major chords is also present in professional musicians. The mismatch negativity arises mainly from neurons on the supratemporal plain of the temporal lobe with contributions from the frontal cortex.
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:


''2) top-down inputs (from other cortical areas)''
''1) bottom-up input (auditory stimuli)''
Focusing attention to a given acoustic feature seems to enhance neuronal selectivity in the particular part of the auditory cortex with spezalization for processing this feature. For example human anterior auditory cortex (putative what pathway) has got enhanced selectivity to phonemes with attention to phonetic features. On the other hand the posterior auditory cortex (where processing pathway) was enhanced while attention was directed to stimulus locations. [insert Figure 2, Jaeaeskelinen] The neurophysiological basis of this selective attention 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 surround inhibition. The STRF of a neuron can change during different task conditions. [insert Figure 3b, Jaeaeseklinen]
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.
As shown above top-down inputs are as important as bottom-up inputs for tuning neurons. Therfore the auditory cortex is an interaction suface of the different stimuli. Like in mathematics addition and substraction of stimuli it is easier to direct and maintain attentional focus right after the attended stimulus has occured (equals match of top-down and bottom-up input). [insert Figure 1b, Jaeaeseklinen]


''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 inputs (visual stimuli)''
''3) cross-modal input (visual stimuli)''
A multisensory processing is supported by anatomical connections between auditory and visual cortex, heteromodal cortex and the prefrontal "mirror-neuron" system. It is suggested that visual inputs influence auditory processing through mainly top-down feedback at an early stage. The visual stimuli can either be related to speech or neutral, like audiovisual associations of a complex natural scene. It is suggested that crossmodal inputs initially cause excitation followed by post-stimulus inhibition. The pattern of the response is not random but might help the auditory cortex to better detect relevant features. The reaction strongly depends of the stimulus timing, type and task.
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.
 
There is much evidence that short-term plasticity of the hierarchically organized parallel auditory system supports perceptual long-term training. Overall the neuron adaptions gained during professional musical training are visible in connected regions but far not fully understood.

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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.