Neuronal Melodies
In this page, we illustrate examples of “neuronal melodies”, where the simplest translation from spikes to music was used, namely each neuron produces its own note, at the moment it fires. It is surely possible to use more sophisticate ways of translating spikes to music, such as for example using more complex rules of harmonics and associate neuronal activity with more complex musical sequences; see the Spikkiss Page. Human medial-temporal cortex80 to 100 neurons were simultaneously recorded from human temporal cortex from patients prior to neurosurgery. We succeeded in identifying excitatory and inhibitory neurons (see details in Peyrache et al., Proc. Natl. Acad. Sci. USA, 2012). The recorded spikes were converted to MIDI format, by associating each neuron to a given tone, and triggering the tone each time this neuron fired. The MIDI files were then converted to MP3 using freeware programs. The “melody” produced by neuronal spikes gives an idea about the distributed firing activity of those neurons. MP3 files were generated for different cases: when the subject was awake (“Awake Melody”), during slow-wave sleep (“Sleeping Melody”) or during REM sleep (“Dreaming Melody”). It was also done during an epileptic seizure (same patient), starting with awake type of activity then the switch to epileptic activity can be heard very well. The different audio files available are:
The wakefulness can also be viewed as an animated video file, where the colors epresent the LFP, the crosses represent the excitatory (FS) neurons, and circles represent the inhibitory (RS) neurons: In these files, the time base is real time; all recordings are from the same subject, same electrodes and same set of recorded neurons (each recording lasts one minute). Two instruments are present, a woodblock for excitatory neurons and a xylophone for inhibitory cells. From these melodies, one can hear that the distributed firing activity is almost identical during dreaming compared to wakefulness, which emphasizes the high similarity between these two different brain states (see also Destexhe, Curr. Opinion. Neurobiol. 2011). Slow-wave sleep can be heard as an activity similar to wakefulness (“Up” states), with regular “pauses” of the firing activity (“Down states”, which are associated to the slow-waves). During the seizure, the activity is very different and the melody produced is clearly impoverished… These files are also available at the Internet Archive, under a page called Neuronal Melodies. Cat parietal cortexThe same procedure was followed for cat experiments. In this case, 8 multiunit recordings were obtained with a system of 8 pairs of tungsten microelectrodes. Spikes were extracted using the BrainWave software. They were converted to MIDI, by associating each neuron to a given tone, and triggering the tone whennever this neuron fired. The MIDI files were then converted to MP3 using freeware programs. The music scores were generated by importing the MIDI files into the “Guitar Pro 5” program. MP3 files were generated for 4 cases: when the animal was awake (Wake-Neurons), during slow-wave sleep (“Sleeping-Neurons”) or during REM sleep (REM-Neurons), where most dreams occur. The file “Poisson-Wake” is a randomly-generated stream of notes with the same statistics as for “Wake”. Interestingly, the firing of one isolated neuron during wakefulness is undistinguishable from that of random (Poisson) activity (compare the audio file generated by one neuron during Wakefulness The different audio files available are:
(in all audio files, the time base is four times slower than real time; all recordings are from the same experiment) These files (and more files at different audio formats) are also available at the Internet Archive, under a page called Neuronal Tones. Just for fun, see also the music scores for Copyright note: We decided to distribute this music freely, under the protection of a Creative Commons Licence “share alike non commercial” (see below). This means that you are welcome to share and edit the present work, under the condition that you give us proper acknowledgment, and also distribute it freely (and give us a copy!). No commercial application please, unless we have an agreement. The official licence information is pasted below: This work is licensed under a Creative Commons You are free to copy, distribute, display, and perform the work, as (1) the authors are acknowledged, (2) that no commercial use is made, and (3) that the same “Share Alike” licence is given to any use ofthis work. |