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Scale-free music of the brain.

Wu D, Li CY, Yao DZ - PLoS ONE (2009)

Bottom Line: To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM) and slow-wave sleep (SWS).The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN), 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(kappa = 0.800, P<0.001).The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.

ABSTRACT

Background: There is growing interest in the relation between the brain and music. The appealing similarity between brainwaves and the rhythms of music has motivated many scientists to seek a connection between them. A variety of transferring rules has been utilized to convert the brainwaves into music; and most of them are mainly based on spectra feature of EEG.

Methodology/principal findings: In this study, audibly recognizable scale-free music was deduced from individual Electroencephalogram (EEG) waveforms. The translation rules include the direct mapping from the period of an EEG waveform to the duration of a note, the logarithmic mapping of the change of average power of EEG to music intensity according to the Fechner's law, and a scale-free based mapping from the amplitude of EEG to music pitch according to the power law. To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM) and slow-wave sleep (SWS). The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN), 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(kappa = 0.800, P<0.001). We also applied the method to the EEG data from eyes closed, eyes open and epileptic EEG, and the results showed these mental states can be identified by listeners.

Conclusions/significance: The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy.

Show MeSH

Related in: MedlinePlus

Musical notes obtained from SWS sleep state.Top trace: original brainwaves. Middle trace: the corresponding notes translated from the brainwaves. The vertical columns represent the pitch (height of the columns), duration (width of the columns), and intensity (color of the columns) of the notes. The same time scale is used in the top and middle graphs. Bottom trace: Musical notation obtained from the EEG segment of the beginning. The staves are from MIDI sequences with a tempo of 120 beats per minute.
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pone-0005915-g004: Musical notes obtained from SWS sleep state.Top trace: original brainwaves. Middle trace: the corresponding notes translated from the brainwaves. The vertical columns represent the pitch (height of the columns), duration (width of the columns), and intensity (color of the columns) of the notes. The same time scale is used in the top and middle graphs. Bottom trace: Musical notation obtained from the EEG segment of the beginning. The staves are from MIDI sequences with a tempo of 120 beats per minute.

Mentions: The resulting music pieces are shown in Figure 3, 4. The results demonstrate that REM music (Audio S1) encompasses a wide variety of note pitches. The fast rhythm and lively melody (Figure 3) suggest an active state of the brain in REM. On the contrary, the SWS brainwaves are characterized by a larger amplitude and longer duration, which results in a piece of music (Audio S2) dominated by low pitches and a slower rhythm (Figure 4). It sounds more like a lullaby, which fits nicely with the fact that the brain in SWS is in a tranquil and relaxed state [30]. Interestingly, the pitch distribution of our brainwave music is demonstrated to follow the Zipf's law [16] (Figure 5). This means that the present method retains the scale-free properties of the EEG data and that the values of exponent index are all within the reasonable range of music [16].


Scale-free music of the brain.

Wu D, Li CY, Yao DZ - PLoS ONE (2009)

Musical notes obtained from SWS sleep state.Top trace: original brainwaves. Middle trace: the corresponding notes translated from the brainwaves. The vertical columns represent the pitch (height of the columns), duration (width of the columns), and intensity (color of the columns) of the notes. The same time scale is used in the top and middle graphs. Bottom trace: Musical notation obtained from the EEG segment of the beginning. The staves are from MIDI sequences with a tempo of 120 beats per minute.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2691588&req=5

pone-0005915-g004: Musical notes obtained from SWS sleep state.Top trace: original brainwaves. Middle trace: the corresponding notes translated from the brainwaves. The vertical columns represent the pitch (height of the columns), duration (width of the columns), and intensity (color of the columns) of the notes. The same time scale is used in the top and middle graphs. Bottom trace: Musical notation obtained from the EEG segment of the beginning. The staves are from MIDI sequences with a tempo of 120 beats per minute.
Mentions: The resulting music pieces are shown in Figure 3, 4. The results demonstrate that REM music (Audio S1) encompasses a wide variety of note pitches. The fast rhythm and lively melody (Figure 3) suggest an active state of the brain in REM. On the contrary, the SWS brainwaves are characterized by a larger amplitude and longer duration, which results in a piece of music (Audio S2) dominated by low pitches and a slower rhythm (Figure 4). It sounds more like a lullaby, which fits nicely with the fact that the brain in SWS is in a tranquil and relaxed state [30]. Interestingly, the pitch distribution of our brainwave music is demonstrated to follow the Zipf's law [16] (Figure 5). This means that the present method retains the scale-free properties of the EEG data and that the values of exponent index are all within the reasonable range of music [16].

Bottom Line: To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM) and slow-wave sleep (SWS).The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN), 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(kappa = 0.800, P<0.001).The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.

ABSTRACT

Background: There is growing interest in the relation between the brain and music. The appealing similarity between brainwaves and the rhythms of music has motivated many scientists to seek a connection between them. A variety of transferring rules has been utilized to convert the brainwaves into music; and most of them are mainly based on spectra feature of EEG.

Methodology/principal findings: In this study, audibly recognizable scale-free music was deduced from individual Electroencephalogram (EEG) waveforms. The translation rules include the direct mapping from the period of an EEG waveform to the duration of a note, the logarithmic mapping of the change of average power of EEG to music intensity according to the Fechner's law, and a scale-free based mapping from the amplitude of EEG to music pitch according to the power law. To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM) and slow-wave sleep (SWS). The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN), 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(kappa = 0.800, P<0.001). We also applied the method to the EEG data from eyes closed, eyes open and epileptic EEG, and the results showed these mental states can be identified by listeners.

Conclusions/significance: The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy.

Show MeSH
Related in: MedlinePlus