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BioComputer Music: Generating Musical Responses with Physarum polycephalum-Based Memristors

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Music, Mind, and Embodiment (CMMR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9617))

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Abstract

This paper introduces BioComputer Music, an experimental one piano duet between pianist and plasmodial slime mould Physarum polycephalum. This piece harnesses a system we have been developing, which we call BioComputer. BioComputer consists of an analogue circuit that encompasses components grown from the biological computing substrate Physarum polycephalum. Our system listens to the pianist and uses the memristive characteristics of Physarum polycephalum to generate a musical response that it plays through electromagnets placed on the strings of the piano. Such electromagnets set the strings into vibration, producing a distinctive timbre. Physarum polycephalum is an amorphous unicellular organism that has been discovered to exhibit memristive qualities. The memristor changes its resistance according to the amount of charge that has previously flown through. In this paper, we introduce the general concepts, technology and musical composition behind the BioComputer Music piece. We also discuss our rationale for using Physarum polycephalum.

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References

  1. Adamatzky, A.: Physarum Machines: Computers from Slime Mould, vol. 74. World Scientific, Singapore (2010)

    Google Scholar 

  2. Adamatzky, A.: Physarum machines for space missions. Acta Futur. 6, 53–67 (2013)

    Google Scholar 

  3. Adamatzky, A., Schubert, T.: Slime mold microfluidic logical gates. Mater. Today 17(2), 86–91 (2014)

    Article  Google Scholar 

  4. Adamatzky, A., Teuscher, C.: From Utopian to Genuine Unconventional Computers. Luniver Press, Beckington (2006)

    Google Scholar 

  5. Braund, E.: Unconventional computer music with physarum polycephalum. Master’s thesis, Interdisciplinary for Computer Music Research (ICCMR), Plymouth University (2013)

    Google Scholar 

  6. Braund, E., Miranda, E.: Music with unconventional computing: towards a platform for physarum polycephalum sound synthesis (2013)

    Google Scholar 

  7. Braund, E., Miranda, E.: Music with unconventional computing: a system for physarum polycephalum sound synthesis. In: Aramaki, M., Derrien, O., Kronland-Martinet, R., Ystad, S. (eds.) CMMR 2013. LNCS, vol. 8905, pp. 175–189. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  8. Braund, E., Miranda, E.: Music with unconventional computing: towards a step sequencer from plasmodium of physarum polycephalum. In: Johnson, C., Carballal, A., Correia, J. (eds.) EvoMUSART 2015. LNCS, vol. 9027, pp. 15–26. Springer International Publishing, Switzerland (2015)

    Chapter  Google Scholar 

  9. Braund, E., Miranda, E.R.: Unconventional computing in music. In: Proceedings of the 9th Conference on Interdisciplinary Musicology - CIM 2014, Berlin, Germany (2014)

    Google Scholar 

  10. Braund, E., Sparrow, R., Miranda, E.R.: Physarum-based memristors for computer music. In: Adamatzky, A. (ed.) Advances in Physarum Machines, vol. 21, pp. 755–775. Springer International Publishing, Switzerland (2016)

    Chapter  Google Scholar 

  11. Chua, L.: Memristor-the missing circuit element. IEEE Trans. Circuit Theory 18(5), 507–519 (1971)

    Article  Google Scholar 

  12. Gale, E., Adamatzky, A., de Lacy Costello, B.: Slime mould memristors. BioNanoScience 5, 1–8 (2014)

    Article  Google Scholar 

  13. Gale, E., de Lacy Costello, B., Adamatzky, A.: Observation, characterization and modeling of memristor current spikes (2013). arXiv preprint: arXiv:1302.0771

  14. Gale, E., Matthews, O., de Lacy Costello, B., Adamatzky, A.: Beyond Markov chains, towards adaptive memristor network-based music generation (2013). arXiv preprint: arXiv:1302.0785

  15. Johnsen, G.K., Lütken, C.A., Martinsen, O.G., Grimnes, S.: Memristive model of electro-osmosis in skin. Phys. Rev. E 83(3), 31916 (2011)

    Article  Google Scholar 

  16. Johnsen, G.K.: An introduction to the memristor-a valuable circuit element in bioelectricity and bioimpedance. J. Electr. Bioimpedance 3(1), 20–28 (2012)

    Article  Google Scholar 

  17. Kosta, S.P., Kosta, Y.P., Bhatele, M., Dubey, Y.M., Gaur, A., Kosta, S., Gupta, J., Patel, A., Patel, B.: Human blood liquid memristor. Int. J. Med. Eng. Inform. 3(1), 16–29 (2011)

    Google Scholar 

  18. McPherson, A.: The magnetic resonator piano: electronic augmentation of an acoustic grand piano. J. New Music Res. 39(3), 189–202 (2010)

    Article  Google Scholar 

  19. Miranda, E.: Harnessing the intelligence of physarum polycephalum for unconventional computing-aided musical composition. IJUC 10(3), 251–268 (2014)

    Google Scholar 

  20. Miranda, E.: Biocomputer Music. http://tinyurl.com/kszgm3r. Accessed 12 Feb 2015

  21. Miranda, E., Adamatzky, A., Jones, J.: Sounds synthesis with slime mould of physarum polycephalum. J. Bionic Eng. 8(2), 107–113 (2011)

    Article  Google Scholar 

  22. Pershin, Y.V., La Fontaine, S., Di Ventra, M.: Memristive model of amoeba learning. Phys. Rev. E 80(2), 21926 (2009)

    Article  Google Scholar 

  23. Strukov, D.B., Snider, G.S., Stewart, D.R., Williams, R.S.: The missing memristor found. Nature 453(7191), 80–83 (2008)

    Article  Google Scholar 

  24. Tero, A., Kobayashi, R., Nakagaki, T.: Physarum solver: a biologically inspired method of road-network navigation. Phys. Sect. A 363(1), 115–119 (2006)

    Article  Google Scholar 

  25. Tsuda, S., Zauner, K.P., Gunji, Y.P.: Robot control with biological cells. Biosystems 87(2), 215–223 (2007)

    Article  Google Scholar 

  26. Volkov, A., Reedus, J., Mitchell, C.M., Tucket, C., Forde-Tuckett, V., Volkova, M.I., Markin, V.S., Chua, L.: Memristors in the electrical network of Aloe vera L. Plant Signal. Behav. 9(4), e29056 (2014)

    Article  Google Scholar 

  27. Wohlfarth-Bottermann, K.E.: Oscillatory contraction activity in physarum. J. Exp. Biol. 81(1), 15–32 (1979)

    Article  Google Scholar 

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Authors and Affiliations

  1. Interdisciplinary Centre for Computer Music Research (ICCMR), Plymouth University, Plymouth, UK

    Edward Braund & Eduardo R. Miranda

Authors
  1. Edward Braund
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  2. Eduardo R. Miranda
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Correspondence to Edward Braund .

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Editors and Affiliations

  1. CNRS - LMA, Marseille Cedex 20, France

    Richard Kronland-Martinet

  2. CNRS - LMA, Marseille, France

    Mitsuko Aramaki

  3. CNRS - LMA, Marseille, France

    Sølvi Ystad

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Braund, E., Miranda, E.R. (2016). BioComputer Music: Generating Musical Responses with Physarum polycephalum-Based Memristors. In: Kronland-Martinet, R., Aramaki, M., Ystad, S. (eds) Music, Mind, and Embodiment. CMMR 2015. Lecture Notes in Computer Science(), vol 9617. Springer, Cham. https://doi.org/10.1007/978-3-319-46282-0_26

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  • DOI: https://doi.org/10.1007/978-3-319-46282-0_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46281-3

  • Online ISBN: 978-3-319-46282-0

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