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Alain Destexhe and Luc Foubert June 2016. Music from neuronal activity during dreamsIn the present page, we give more detail on how we have translated human brain activity into music, for recordings made while the subject was sleeping, in the “rapid eye movement” (REM) sleep, also called “paradoxical sleep”, where most dreams occur. This corresponds to the song “REMiniscence” Excitatory neuronal activity during REM sleepOne of the most striking feature of REM sleep is that the activity of the brain is very similar — almost undistinguishable — from that during wakefulness. Like in the waking state, the activity of neurons is very irregular and asynchronous. We recorded neurons during REM sleep, and 14 excitatory neurons were played on synthetic bells. To listen to that example, click on “Dreaming Bells”. One can hear very well the irregular aspect of the neuronal spikes (compare with the similar sound during wakefulness, “Neuronal Bells”). One can also play the excitatory cells above to a very high sound, like that of clochettes (small bells). In that case, 18 excitatory neurons were used. To listen to that example, click on “Dreaming Clochettes”. We can also use bell sounds at more medium frequencies, using 18 other excitatory cells. This complement very well the clochettes. To listen to that sound, click on “Dreaming midBells”. As done in other songs, one can also use excitatory neurons to drive slow sounds. For example, one can take one of the sets of 18 excitatory neurons played on the same slow “Woo-Woo” sound considered in Wake Beats, click on “Dreaming Woo”. Finally, to better illustrate the strangeness of dreams, we also have used sounds that remind this strange character, such as voices (also from 18 neurons). To listen to that sound, click on “Dreaming Voices”. We also used other sounds that remind screams (from the same set of 18 neurons). To listen to that sound, click on “Dreaming Screams”. These are all generated from the same ensemble of excitatory neurons, split into groups of 18 cells. Activity of inhibitory neurons during REM sleepLike in other brain states, the inhibitory neurons are very rhythmic, and we can exploit this rythmicity to form the bass and drum sections. In the REM sleep song, we have given a particlar emphasis on this rhythmicity. As a first example, we have chosen a set of 7 particularly rhythmic inhibitory cells and used these neurons to drive a drum kick. To listen to this sound, click on “Dreaming Kick”. To further enhance the rhythm, we have duplicated this kick, and shifted the duplicate by about half a second, which yields a double kick, with particularly striking rhythmicity. To listen to this sound, click on “Dreaming Double Kick”. Finally, we have used 2 very rhythmic inhibitory neurons to pilot a “Virus” type of synthesizer, and tuned by hand the filtering of the sound. This provides a changing rhythm, which was also used in the rhythmic section. To listen to that sound, click on “Dreaming Virus”. Assembling it all togetherLet us now listen to the full song, where all of the above sounds were used: In this song, although the activity was very similar to that of wakefulness, we voluntarily made it sound very different. We have emphasized the rhythmic character of the inhibitory neurons. Similar to the Wake Beats or Slow Waves songs, the activity of the different neurons is strictly respected, as well as the respective timing of the spikes of the different cells. We have used in addition a drumkit and a bass, but all the rest of the music comes from neuronal activity. PublicationsAlain Destexhe and Luc Foubert. Composing music from neuronal activity – The Spikiss Project. In: Exploring Transdisciplinarity in Art and Sciences, Edited by Kapoula, Z., Volle, E., Renoult, J. and Andreatta, M. Springer, New York, pp. 237-253, 2018. www.spikiss.org (available soon…) 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 Attribution-NonCommercial 4.0 International License. You are free to copy, distribute, display, and perform the work, as well to make derivatives based on this work, but under conditions that (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. |
