Abstract
The emerging field of Unconventional Computing is developing new algorithms and computing architectures inspired by or implemented in biological, physical and chemical systems. We are investigating how Unconventional Computing may benefit the future of the music industry and related audio engineering technologies. In this chapter, after a brief introduction to Unconventional Computing, we present our research into harnessing the behaviour of a slime mould called Physarum polycephalum to build new kinds of processors for audio and music. The plasmodium of Physarum polycephalum is a large single cell with a myriad of diploid nuclei, which moves like a giant amoeba in its pursuit for food. The organism is amorphous, and although without a brain or any serving centre of control, can respond to the environmental conditions that surround it. As our research progressed, we have successfully harnessed the organism to implement a sound synthesiser and a musical sequencer, grow biological audio wires, and build an interactive biocomputer that can listen and produce musical responses in real-time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adamatzky, A.: Computing in Nonlinear Media and Automata Collectives. CRC Press, Boca Raton (2001)
Adamatzky, A.: Physarum Machines: Computers from Slime Mould, vol. 74. World Scientific, Singapore (2010)
Adamatzky, A.: Physarum wires: self-growing self-repairing smart wires made from slime mould. Biomed. Eng. Lett. 3(4), 232–241 (2013)
Adamatzky, A., Jones, J.: On electrical correlates of Physarum polycephalum spatial activity: Can we see Physarum Machine in the dark? Biophys. Rev. Lett. 6(01n02), 29–57 (2011)
Adamatzky, A., Schubert, T.: Slime mold microfluidic logical gates. Mater. Today 17(2), 86–91 (2014)
Adamatzky, A., Teuscher, C.: From Utopian to Genuine Unconventional Computers. Luniver Press, Frome (2006)
Adleman, L.M.: Molecular computation of solutions to combinatorial problems. Science 266(5187), 1021–1024 (1994)
Beyls, P.: Cellular automata mapping procedures. In: Proceedings of the ICMC. Citeseer (2004)
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.I (eds.) Sound, Music, and Motion. Lecture Notes in Computer Science, pp. 175–189. Springer International Publishing, Heidelberg (2014)
Braund, E., Miranda, E.: BioComputer music: generating musical responses with Physarum polycephalum-based memristors. In: Computer Music Multidisciplinary Research (CMMR): Music, Mind, and Embodiment. Plymouth, UK (2015)
Braund, E., Miranda, E.: Music with unconventional computing: granular synthesis with the biological computing substrate Physarum polycephalum. In: Computer Music Multidisciplinary Research (CMMR): Music, Mind, and Embodiment. Plymouth, UK (2015)
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.) Evolutionary and Biologically Inspired Music, Sound, Art and Design. Lecture Notes in Computer Science, vol. 9027, pp. 15–26. Springer International Publishing, Heidelberg (2015)
Chua, L.O.: Memristor-the missing circuit element. IEEE Trans. Circuit Theory 18(5), 507–519 (1971)
Cifarelli, A., Dimonte, A., Berzina, T., Erokhin, V.: On the loading of slime mold Physarum polycephalum with microparticles for unconventional computing application. BioNanoScience 4(1), 92–96 (2014)
Gabor, D.: Acoustical quanta and the theory of hearing. Nature 159(4044), 591–594 (1947)
Gale, E., Adamatzky, A., de Lacy Costello, B.: Slime mould memristors. BioNanoScience 5, 1–8 (2013)
Gale, E., Matthews, O., de Costello, B.L., Adamatzky, A.: Beyond Markov Chains, Towards Adaptive Memristor Network-based Music Generation. arXiv preprint arXiv:1302.0785 (2013)
Gale, E., de Lacy Costello, B., Adamatzky, A.: Emergent spiking in non-ideal memristor networks. Microelectron. J. 45(11), 1401–1415 (2014)
Grimnes, S., Lütken, C.A., Martinsen, O.G.: Memristive properties of electro-osmosis in human sweat ducts. In: World Congress on Medical Physics and Biomedical Engineering, 7–12 Sept 2009, Munich, Germany, pp. 696–698. Springer, Heidelberg (2009)
Johnsen, G.K.: An introduction to the memristor-a valuable circuit element in bioelectricity and bioimpedance. J. Electr. Bioimpedance 3(1), 20–28 (2012)
Jones, J.: The emergence and dynamical evolution of complex transport networks from simple low-level behaviours. Ijuc 6(2), 125–144 (2010)
Kirke, A., Shadbolt, P., Neville, A., Antoine, A., Miranda, E.: Q-Muse: A quantum computer music system designed for a performance for orchestra, electronics and live internet-connected photonic quantum computer. In: Conference on Interdisciplinary Musicology (CIM). Berlin (2014)
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)
Meyer, R., Stockem, W.: Studies on microplasmodia of physarum polycephalum V: electrical activity of different types of microplasmodia and macroplasmodia. Cell Biol. Int. Rep. 3(4), 321–330 (1979)
Miranda, E.: Biocomputer music. http://tinyurl.com/kszgm3r
Miranda, E.R.: Cellular automata music: an interdisciplinary project. J. New Music Res. 22(1), 3–21 (1993)
Miranda, E.R.: Granular synthesis of sounds by means of a cellular automaton. Leonardo 28, 297–300 (1995)
Miranda, E.R.: Evolving cellular automata music: from sound synthesis to composition. In: Proceedings of 2001 Workshop on Artificial Life Models for Musical Applications (2001)
Miranda, E.R.: Computer Sound Design: Synthesis Techniques and Programming, vol. 1. Taylor & Francis, UK (2002)
Miranda, E.R., Bull, L., Gueguen, F., Uroukov, I.S.: Computer music meets unconventional computing: towards sound synthesis with in vitro neuronal networks. Comput. Music J. 33(1), 9–18 (2009)
Miranda, E.R., Adamatzky, A., Jones, J.: Sounds synthesis with slime mould of physarum polycephalum. J. Bionic Eng. 8(2), 107–113 (2011)
Pershin, Y.V., La Fontaine, S., Di Ventra, M.: Memristive model of amoeba learning. Phys. Rev. E 80(2), 21,926 (2009)
Stepney, S.: Programming unconventional computers: dynamics, development, self-reference. Entropy 14(10), 1939–1952 (2012)
Strukov, D.B., Snider, G.S., Stewart, D.R., Williams, R.S.: The missing memristor found. Nature 453(7191), 80–83 (2008)
Turing, A.M.: On computable numbers, with an application to the Entscheidungsproblem. J. Math. 58(345–363), 5 (1936)
von Neumann, J.: First Draft of a Report on the EDVAC (1945)
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), e29,056 (2014)
Xenakis, I.: Formalized Music: Thought and Mathematics in Composition, vol. 6. Pendragon, United States (1992)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Miranda, E.R., Braund, E. (2017). Experiments in Musical Biocomputing: Towards New Kinds of Processors for Audio and Music. In: Adamatzky, A. (eds) Advances in Unconventional Computing. Emergence, Complexity and Computation, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-33921-4_29
Download citation
DOI: https://doi.org/10.1007/978-3-319-33921-4_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-33920-7
Online ISBN: 978-3-319-33921-4
eBook Packages: EngineeringEngineering (R0)