Relevant bibliographies by topics / Computer music

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computer music'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 June 2025

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Journal articles on the topic "Computer music"

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Owens, Robert J., Laszlo Dubrovay, Ricardo Mandolini, and Tamas Ungvary. "Computer Music." Computer Music Journal 13, no. 1 (1989): 65. http://dx.doi.org/10.2307/3679860.

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Schüler, Nico. "Reflections on the History of Computer-Assisted Music Analysis I: Predecessors and the Beginnings." Musicological Annual 41, no. 1 (December 1, 2005): 31–43. http://dx.doi.org/10.4312/mz.41.1.31-43.

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This article is the first of a series that focuses on the history of computer-assisted music analysis. This first article discusses the philosophical basis of computer-assisted music analysis, i.e. the application of information theory to aesthetics, as well as representative applications of statistical and information-theoretical measurements to music analysis and other computational approaches to music analysis that did not include the use of electronic computers. In most cases, those approaches were direct models for computer-assisted applications. Finally, this article provides a short historical account of the development of early computers and summarizes the earliest computer-applications to music analysis, carried out during the 1950s.
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Dannenberg, Roger B., Nicolas E. Gold, Dawen Liang, and Guangyu Xia. "Methods and Prospects for Human–Computer Performance of Popular Music." Computer Music Journal 38, no. 2 (June 2014): 36–50. http://dx.doi.org/10.1162/comj_a_00238.

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Computers are often used in performance of popular music, but most often in very restricted ways, such as keyboard synthesizers where musicians are in complete control, or pre-recorded or sequenced music where musicians follow the computer's drums or click track. An interesting and yet little-explored possibility is the computer as highly autonomous performer of popular music, capable of joining a mixed ensemble of computers and humans. Considering the skills and functional requirements of musicians leads to a number of predictions about future human–computer music performance (HCMP) systems for popular music. We describe a general architecture for such systems and describe some early implementations and our experience with them.
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Kiraly, Zsuzsanna. "Solfeggio 1: A Vertical Ear Training Instruction Assisted by the Computer." International Journal of Music Education os-40, no. 1 (May 2003): 41–58. http://dx.doi.org/10.1177/025576140304000105.

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The aim of this paper is to describe the process of solfège learning when assisted by computers. The research was conducted in the Länsi-Uusimaa Music Institute in Finland. The study focused on pupils’ attitudes, opinions, motivation, and learning-outcomes using computer-based music learning. We also examined how Solfeggio 1, the new electronic ear-training material, works. Jukka Louhivuori (1990) has examined the didactical questions of computer-assisted music education. He emphasized that learning music with a computer does not mean the replacement of “real” music. The notions of learning and teaching can change in quality, mainly in the area of “learning-by-doing” and “discovery learning” in the computer-assisted music classroom. It was found that computer-assisted music learning is more agreeable and effective than traditional music learning. Although results showed that we need a well-functioning, modern environment and a well-educated “researcher-teacher,” well-motivated pupils are the most important aspects.
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Larrieu, Maxence. "A Consideration of the Code of Computer Music as Writing, and Some Thinking on Analytical Theories." Organised Sound 24, no. 3 (November 29, 2019): 319–28. http://dx.doi.org/10.1017/s1355771819000384.

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This article focuses on the analysis of computer music, that is, music which uses programming languages so that what the listener hears is the result of computer code. One key point in this article is that this music exists with some writing, that is, the computer code. I note that this key point has not been addressed in the latest theories for analysing computer music. Indeed, we often see this music as part of the electroacoustic field, where the audio signal is essential, and where we usually read that those musics are non-written music. After an introduction on this topic, in the second section I will make a distinction between ‘before the signal’ and ‘from the signal’ to organise the theories to analyse electroacoustic music. In the third section, I will focus on computer music and I will show the historical difficulty in considering ‘code’ in musical analysis, mainly with an important exchange between two pioneers, Marco Stroppa and Jean-Claude Risset. In the fourth section I will explain with Jean-Claude Risset and Horacio Vaggione the specificity of computer music: this music is written. Finally, I will look into a recent analysis theory, the Interactive Aural Analysis by Michael Clarke, which seems to fit with the latter specificity.
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Rowe, Robert, Barlow, Dashow, Kaske, Lansky, Roads, and Waisvisz. "New Computer Music." Computer Music Journal 14, no. 3 (1990): 83. http://dx.doi.org/10.2307/3679967.

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Mailer, Albert, M. Bagella, N. Sani, S. Tamburini, G. Nottoli, and F. Galante. "Computer Music Concerto." Computer Music Journal 15, no. 2 (1991): 80. http://dx.doi.org/10.2307/3680924.

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Gresham-Lancaster, Scot. "Computer Music Network." Leonardo 47, no. 3 (June 2014): 266–67. http://dx.doi.org/10.1162/leon_a_00771.

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The social climate and cultural atmosphere of the San Francisco Bay Area in the late 70's early 80's plus the emergence of the nascent microcomputer industry made for a social network and approach that fostered the creation of a new type of collaborative electronic music ensemble with techniques that have come to be known as “Computer Music Network”. A transformation from initial heterogeneous to a more homogeneous underlying paradigm has brought with it aesthetic questions about the reason and evolution of this new genre.
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Rudi, Jøran. "Computer music animations." Organised Sound 3, no. 3 (December 1998): 193–98. http://dx.doi.org/10.1017/s1355771898003033.

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Electroacoustic music, since its inception, has been situated in a cross-disciplinary no-man's-land, with areas of interest spread in many directions; from ideas of musical structures ordered through traditional pitch-classes to research on physical modelling and analysis of sound and compositional structures through the use of neural networks. Much of the material found in computer music has been developed through processes of appropriation, both from sound recordings of physical events and from the application of various principles found in the natural sciences.
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Wilmink, Jan. "Computer music I." Microprocessing and Microprogramming 24, no. 1-5 (August 1988): 433. http://dx.doi.org/10.1016/0165-6074(88)90091-9.

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Dissertations / Theses on the topic "Computer music"

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Tibbetts, Tracey D. "Computer generated music : a methodology for computer music composition." Virtual Press, 1999. http://liblink.bsu.edu/uhtbin/catkey/1125059.

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This study will prove the fact that computers provide unprecedented opportunities to create music. Several distinct levels of computer participation can exist in the creative process. The lowest level, involving record-keeping functions, results in programs that serve as compositional aids. The intermediate level incorporates stochastic (literally "random") processes on a limited basis, and represents the midpoint between computer-assisted and computercomposed works. The highest level focuses on the design of algorithms that result in compositions determined in most of their details by stochastic processes and computer decision making. Although there is no clear dividing line between levels of computer/composer interaction, it is possible to characterize the degree to which the computer has provided outcomes for a given work, from low-level random generation of pitches to high-level Markovian chain distributions.<br>Department of Computer Science
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Faia-Harrison, Carl. "Collaborative computer music composition and the emergence of the computer music designer." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/11917.

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This submission explores the development of collaborative computer music creation and the role of the Musical Assistant, or Computer Music Designer, or Live Electronics Designer, or RIM (Réalisateur en informatique musicale) and does so primarily through the consideration of a series of collaborations with composers over the last 18 years. The submission documents and evaluates a number of projects which exemplify my practice within collaborative computer music creation, whether in the form of live electronics, tape-based or fixed media work, as a live electronics performer, or working with composers and others to create original tools and music for artistic creations. A selection of works is presented to exemplify archetypes found within the relational structures of collaborative work. The relatively recent development of this activity as an independent metier is located within its historical context, a context in which my work has played a significant role. The submission evidences the innovative aspects of that work and, more generally, of the role of the Computer Music Designer through consideration of a number of Max patches and program examples especially created for the works under discussion. Finally, the validation of the role of the Computer Music Designer as a new entity within the world of music creation is explored in a range of contexts, demonstrating the ways in which Computer Music Designers not only collaborate in the creation of new work but also generate new resources for computer-based music and new creative paradigms.
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Yu, ChÅ ng. "Computer generated music composition." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10901.

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Frisk, Henrik. "Improvisation, computers and interaction : rethinking human-computer interaction through music /." Malmö : Malmö Academy of Music, Lund University, 2008. http://www.lu.se/o.o.i.s?id=12588&postid=1239899.

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Phelps, James D. (James Dee). "Computer Simulacra." Thesis, University of North Texas, 1989. https://digital.library.unt.edu/ark:/67531/metadc331100/.

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Computer Simulacra is a musical work composed for amplified instrumental ensemble and computer instruments on tape. It is a computer-assisted work, composed with the help of a stochastic compositional algorithm, called PTERIO, designed by the composer.
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Stubenvoll, Matthias. "Musiklernen am Computer : zur Qualität von Musik-Lernsoftware und ihrer empirischen Überprüfung /." Essen : Verl. Die Blaue Eule, 2008. http://d-nb.info/990141454/04.

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Britton, Sam. "Towards hypertextual music : digital audio, deconstruction and computer music creation." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/14949.

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This is a study of the way in which digital audio and a number of key associated technologies that rely on it as a framework have changed the creation, production and dissemination of music, as witnessed by my own creative practice. The study is built on my own work as an electronic musician and composer and draws from numerous collaborations with not only other musicians but also researchers and artists, as documented through commissions, performances, academic papers and commercial releases over an 9 year period from 2007 to 2016. I begin by contextualising my own musical practice and outlining some prominent themes associated with the democratisation of computing that the work of this thesis interrogates as a critical framework for the production of musical works. I go on to assess how works using various techniques afforded by digital audio may be interpreted as progressively instantiating a digital ontology of music. In the context of this digital ontology of music I propose a method of analysis and criticism of works explicitly concerned with audio analysis and algorithmic processes based on my interpretation of the concept of `hypertext', wherein the ability for computers to analyse, index and create multi-dimensional, non-linear links between segments of digital audio is best described as hypertextual. In light of this, I contextualise the merits of this reading of music created using these affordances of digital audio through a reading of several key works of 20th century music from a hypertextual perspective, emphasising the role information theory and semiotics have to play in analyses of these works. I proffer this as the beginnings of a useful model for musical composition in the domain of digital audio which I seek to explore through my own practice. I then describe and analyse, both individually and in parallel numerous works I have undertaken that seek to interrogate the intricacies of what it means to work in the domain of digital audio with audio analysis, machine listening, algorithmic and generative computational processes and consider the ways in which aspects of this work might be seen as contributing useful and novel insights into music creation by harnessing properties intrinsic to digital audio as a medium. Finally, I emphasise, based on the music and research presented in the thesis, the extent to which digital audio and the harnessing of increasingly complex computational systems for the production and dissemination of music has changed the ontology of music production, a situation which I interpret as creating both substantial challenges, but also great possibilities for the future of music.
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Page, Stephen Dowland. "Computer tools for music information retrieval." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293399.

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Albright, Larry E. (Larry Eugene). "Computer Realization of Human Music Cognition." Thesis, University of North Texas, 1988. https://digital.library.unt.edu/ark:/67531/metadc330819/.

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This study models the human process of music cognition on the digital computer. The definition of music cognition is derived from the work in music cognition done by the researchers Carol Krumhansl and Edward Kessler, and by Mari Jones, as well as from the music theories of Heinrich Schenker. The computer implementation functions in three stages. First, it translates a musical "performance" in the form of MIDI (Musical Instrument Digital Interface) messages into LISP structures. Second, the various parameters of the performance are examined separately a la Jones's joint accent structure, quantified according to psychological findings, and adjusted to a common scale. The findings of Krumhansl and Kessler are used to evaluate the consonance of each note with respect to the key of the piece and with respect to the immediately sounding harmony. This process yields a multidimensional set of points, each of which is a cognitive evaluation of a single musical event within the context of the piece of music within which it occurred. This set of points forms a metric space in multi-dimensional Euclidean space. The third phase of the analysis maps the set of points into a topology-preserving data structure for a Schenkerian-like middleground structural analysis. This process yields a hierarchical stratification of all the musical events (notes) in a piece of music. It has been applied to several pieces of music with surprising results. In each case, the analysis obtained very closely resembles a structural analysis which would be supplied by a human theorist. The results obtained invite us to take another look at the representation of knowledge and perception from another perspective, that of a set of points in a topological space, and to ask if such a representation might not be useful in other domains. It also leads us to ask if such a representation might not be useful in combination with the more traditional rule-based representations by helping to eliminate unwanted levels of detail in a cognitive-perceptual system.
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Prechtl, Anthony. "Adaptive music generation for computer games." Thesis, Open University, 2016. http://oro.open.ac.uk/45340/.

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This dissertation explores a novel approach to game music that addresses the limitations of conventional game music systems in supporting a dynamically changing narrative. In the proposed approach, the music is generated automatically based on a set of variable input parameters corresponding to emotional musical features. These are then tied to narrative parameters in the game, so that the features and emotions of the music are perceived to continuously adapt to the game's changing narrative. To investigate this approach, an algorithmic music generator was developed which outputs a stream of chords based on several input parameters. The parameters control different aspects of the music, including the transition matrix of a Markov model used to stochastically generate the chords, and can be adjusted continuously in real time. A tense first-person game was then configured to control the generator's input parameters to reflect the changing tension of its narrative---for example, as the narrative tension of the game increases, the generated music becomes more dissonant and the tempo increases. The approach was empirically evaluated primarily by having participants play the game under a variety of conditions, comparing them along several subjective dimensions. The participants' skin conductance was also recorded. The results indicate that the condition with the dynamically varied music described above was both rated and felt as the most tense and exciting, and, for participants who said they enjoy horror games and films, also rated as the most preferable and fun. Another study with music experts then demonstrated that the proposed approach produced smoother musical transitions than crossfades, the approach conventionally used in computer games. Overall, the findings suggest that dynamic music can have a significant positive impact on game experiences, and that generating it algorithmically based on emotional musical features is a viable and effective approach.
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Books on the topic "Computer music"

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A, Jerse Thomas, ed. Computer music. New York, NY: Schirmer, 1985.

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Wells, Colin. Music computer cookbook. Reading: University of Reading Music Education Information and Research Centre for NCET, 1990.

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Lazzarini, Victor. Computer Music Instruments. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63504-0.

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Miranda, Eduardo Reck, and John Al Biles, eds. Evolutionary Computer Music. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-600-1.

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Miranda, Eduardo Reck, ed. Quantum Computer Music. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13909-3.

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Denis, Baggi, ed. Computer-generated music. Los Alamitos, Calif: IEEE Computer Society Press, 1992.

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Collins, Nick. Introduction to computer music. [Hoboken]: John Wiley & Sons, 2009.

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Lazzarini, Victor. Computer Music Instruments II. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13712-0.

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Collins, Nick. Introduction to computer music. [Hoboken]: John Wiley & Sons, 2009.

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Roads, Curtis. The computer music tutorial. Cambridge, Mass: MIT Press, 1996.

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Book chapters on the topic "Computer music"

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Cook, Perry R. "Computer Music." In Springer Handbook of Acoustics, 747–78. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0755-7_17.

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Cook, Perry. "Computer Music." In Springer Handbook of Acoustics, 713–42. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-30425-0_17.

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Alvaro, Jesús L., and Beatriz Barros. "Computer Music Cloud." In Exploring Music Contents, 163–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23126-1_11.

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Maz, Andrew. "Computer Music Notation." In Music Technology Essentials, 193–207. London: Focal Press, 2023. http://dx.doi.org/10.4324/9781003345138-11.

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Lazzarini, Victor. "Computer Music Platforms." In Computer Music Instruments, 295–306. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63504-0_9.

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Weekhout, Hans. "Recording on the Computer." In Music Production, 99–115. Third edition. | New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429459504-11.

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Chau, Kai Ton. "Computer and Music Pedagogy." In Digital Da Vinci, 237–53. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0536-2_10.

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Hartmann, William Morris. "Electronic and Computer Music." In Encyclopedia of Acoustics, 1679–85. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470172544.ch138.

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Buongiorno, Federica. "Reduction in Computer Music." In The Case for Reduction, 175–90. Berlin: ICI Berlin Press, 2022. http://dx.doi.org/10.37050/ci-25_09.

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In the age of pervasive computing the way our body interacts with reality needs to be reconceptualized. The reduction of embodiment is a problem for computer music since this music relies heavily on different layers of (digital) technology and mediation in order to be produced and performed. The article shows that such a mediation should not be conceived of as an obstacle but rather as a constitutive element of a permanent, complex negotiation between the artist, the machinery, and the audience, aimed at shaping a different temporality for musical language (as the Italian artist Caterina Barbieri develops).
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Miranda, Eduardo Reck. "Quantum Computer: Hello, Music!" In Handbook of Artificial Intelligence for Music, 963–94. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72116-9_34.

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Conference papers on the topic "Computer music"

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Raphael, Christopner. "Face the Music: Summarizing Unscripted Music Practice from Audio." In 6th International Special Session on Computer Supported Music Education, 685–91. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013493800003932.

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Shekhawat, Raman, Sai Harshith Tedla, J. Selvin Paul Peter, and Priya Esther B. "Syncing Music With Emotions Using Computer Vision." In 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT), 522–27. IEEE, 2024. http://dx.doi.org/10.1109/iccpct61902.2024.10672743.

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Li, Haolun, Yixuan Zeng, Ziqian Bai, Wenhao Li, Kai Wu, and Jing Zhou. "EEG-fNIRS-Based Music Emotion Decoding and Individualized Music Generation." In 2024 5th International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI), 394–97. IEEE, 2024. https://doi.org/10.1109/ichci63580.2024.10808139.

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Romani, Michele, Gregorio Andrea Giudici, Domenico Stefani, Devis Zanoni, Alberto Boem, and Luca Turchet. "BCHJam: a Brain-Computer Music Interface for Live Music Performance in Shared Mixed Reality Environments." In 2024 IEEE 5th International Symposium on the Internet of Sounds (IS2), 1–9. IEEE, 2024. http://dx.doi.org/10.1109/is262782.2024.10704087.

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Lin, Yan-Bo, Yu Tian, Linjie Yang, Gedas Bertasius, and Heng Wang. "VMAs: Video-to-Music Generation via Semantic Alignment in Web Music Videos." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 1155–65. IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00120.

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Cook, Perry R., Curtis Roads, and Joe Paradiso. "Computer music." In ACM SIGGRAPH 2004 Special sessions. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1186187.1186190.

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Ye, Xiangyang. "Music Creation with Computer Music Production Software." In 2022 International Conference on Electronics and Devices, Computational Science (ICEDCS). IEEE, 2022. http://dx.doi.org/10.1109/icedcs57360.2022.00041.

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Chiu, Shih-Chuan, and Man-Kwan Shan. "Computer Music Composition Based on Discovered Music Patterns." In 2006 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icsmc.2006.384827.

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Iazzetta, Fernando. "The Politics of Computer Music." In Simpósio Brasileiro de Computação Musical. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbcm.2019.10464.

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When a set of objects, actions, and procedures begin to coalesce and gain some coherence, they become perceived as a new, cohesive field. This may be related to the emergence of a new discipline, a new craft, or a new technological configuration. As this new field shows some coherence and unity, we tend to overlook the conditions that gave rise to it. These conditions become "naturalized" as if they were inherent in that field. From this point on, we do not wonder anymore to what extent the contingencies (formal, social, economic, technological, aesthetic, religious) that gave rise to that field have been crucial to its constitution. When it comes to computer music we are comfortably used to its applied perspective: tools, logical models, and algorithms are created to solve problems without questioning the (non-computational) origin of these problems or the directions taken by the solutions we give to them. The idea of computing as a set of abstract machines often hides the various aspects of the sonic cultures that are at play when we develop tools and models in computer music. The way we connect the development of computer tools with the contingencies and contexts in which these tools are used is what I call the politics of computer music. This connection is often overshadowed in the development of computer music. However, I would like to argue that this connection is behind everything we do in terms of computer music to the point that it often guides the research, development, and results within the field.
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Liu, Jie, and Liang Liang. "The Application of Computer Music Technology in Music Education." In 2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC). IEEE, 2021. http://dx.doi.org/10.1109/ipec51340.2021.9421234.

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Reports on the topic "Computer music"

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Möllenkamp, Andreas. Paradigms of Music Software Development. Staatliches Institut für Musikforschung, December 2014. http://dx.doi.org/10.25366/2022.99.

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On the way to a more comprehensive and integrative historiography of music software, this paper proposes a survey of the main paradigms of music software development from the 1950s to the present. Concentrating on applications for music composition, production and performance, the analysis focusses on the concept and design of the human-computer-interaction as well as the implicit user.
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Kiv, Arnold E., Vladyslav V. Bilous, Dmytro M. Bodnenko, Dmytro V. Horbatovskyi, Oksana S. Lytvyn, and Volodymyr V. Proshkin. The development and use of mobile app AR Physics in physics teaching at the university. [б. в.], July 2021. http://dx.doi.org/10.31812/123456789/4629.

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This paper outlines the importance of using Augmented Reality (AR) in physics education at the university as a valuable tool for visualization and increasing the attention and motivation of students to study, solving educational problems related to future professional activities, improving the interaction of teachers and students. Provided an analysis of the types of AR technology and software for developing AR apps. The sequences of actions for developing the mobile application AR Physics in the study of topics: “Direct electronic current”, “Fundamentals of the theory of electronic circuits”. The software tools for mobile application development (Android Studio, SDK, NDK, Google Sceneform, 3Ds MAX, Core Animation, Asset Media Recorder, Ashampoo Music Studio, Google Translate Plugin) are described. The bank of 3D models of elements of electrical circuits (sources of current, consumers, measuring devices, conductors) is created. Because of the students’ and teachers’ surveys, the advantages and disadvantages of using AR in the teaching process are discussed. Mann-Whitney U-test proved the effectiveness of the use of AR for laboratory works in physics by students majoring in “Mathematics”, “Computer Science”, and “Cybersecurity”.
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Raychev, Nikolay. Can human thoughts be encoded, decoded and manipulated to achieve symbiosis of the brain and the machine. Web of Open Science, October 2020. http://dx.doi.org/10.37686/nsrl.v1i2.76.

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This article discusses the current state of neurointerface technologies, not limited to deep electrode approaches. There are new heuristic ideas for creating a fast and broadband channel from the brain to artificial intelligence. One of the ideas is not to decipher the natural codes of nerve cells, but to create conditions for the development of a new language for communication between the human brain and artificial intelligence tools. Theoretically, this is possible if the brain "feels" that by changing the activity of nerve cells that communicate with the computer, it is possible to "achieve" the necessary actions for the body in the external environment, for example, to take a cup of coffee or turn on your favorite music. At the same time, an artificial neural network that analyzes the flow of nerve impulses must also be directed at the brain, trying to guess the body's needs at the moment with a minimum number of movements. The most important obstacle to further progress is the problem of biocompatibility, which has not yet been resolved. This is even more important than the number of electrodes and the power of the processors on the chip. When you insert a foreign object into your brain, it tries to isolate itself from it. This is a multidisciplinary topic not only for doctors and psychophysiologists, but also for engineers, programmers, mathematicians. Of course, the problem is complex and it will be possible to overcome it only with joint efforts.
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