Introduction to brain-computer musical interfaces

Course Information
TitleΕισαγωγή στις διεπαφές εγκεφάλου-υπολογιστή με εφαρμογές στη μουσική / Introduction to brain-computer musical interfaces
FacultyFine Arts
SchoolMusic Studies
Cycle / Level1st / Undergraduate
Teaching PeriodWinter/Spring
Course ID600013930

Programme of Study: PPS Tmīmatos Mousikṓn Spoudṓn (2017-sīmera)

Registered students: 4
OrientationAttendance TypeSemesterYearECTS
Musicology / Music EducationElective Courses846
Music CompositionElective Courses846

Class Information
Academic Year2017 – 2018
Class PeriodSpring
Instructors from Other Categories
Weekly Hours4
Total Hours52
Class ID
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Learning Outcomes
The course will introduce students to basic Neuroscience chapters and theory/applications practice of Brain Computer Music Interfacing as it has appeared in international academic literature. It will focus on the feasibility and efficiency of extracting critical information from brain activity using modern available tools and the design and implementation of inter-connected music synthesis and sound production modules. At the final stage, students will work in groups to implement an affiliated project exploiting such tools with available EEG devices and incorporating the control of music performance and/or sound production elements. At the end of the course, students should: - understand the basics of Neuroscience and Brain Computer Interface technologies - understand the basics of Data Networking and TCP/IP - be able to work with popular open-source programming tools for the electronic arts - be familiar with Interdisciplinary Research concepts - be able to read and assess scholar academic papers, prepare and perform oral presentations - be able to work in groups to implement music-related projects which require both technical and artistic competencies and assess the artistic and functional challenges - be able to work with source code management repositories (Github) to release their open source code examples - be able to present their projects in the course weblog (selected projects).
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work in teams
  • Work in an international context
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Respect natural environment
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
The idea of blending brain interactions with music is not new. In 1965, A. Lucier composed the first musical piece “Music for Solo Performer” coupling EEG electrodes with percussion instruments. Despite these early promising steps, until recently EEG brainwave monitoring was mostly associated with clinical routine, where trained experts operated expensive devices. Similarly, the application of Brain-Computer Interfaces has mainly been confined to neuroprosthetics and to build communication and control channels for physically impaired people. Nowadays, recent advances in medical sensors have made the recording of human brain activity feasible for non medical experts. Commercial portable neuroimaging devices have entered the market at affordable prices, and favor the exploration of novel applications in the naturalistic environment more than ever before (here is an example of our latest research that drew the attention of digital business news . At the same time, data communication protocols and open source technologies are in a mature state to empower the continuously growing field of brain-oriented applications and services. In the scope of this course, the anticipated added value lies in the exploitation of newly born forms of brain-controlled real time interactions within elements of musical performance such as music phrasing and music expression. The main goal is to introduce the feasible use of modern Brain-Computer Interface technologies and facilitate the exploration of novel kinds of personalized and collective neurofeedback experience of musicians and/or audience. The course will provide the means to perform the control and altering of sound and music properties such as frequency response, tone, tempo and dynamics using modern motor control concepts and mental performance metrics (e.g. meditation and attention states). Most importantly, it will provide students with the ability to assess the functional and aesthetic value of modern BCI technologies in performing arts. The course is addressed to undergraduate students of the school of Music Studies, Faculty of Fine Arts and will integrate training modules from a) Neuroscience and Brain-Computer Interfaces b) Data Network Technologies and TCP/IP and c) open source visual interactive programming tools for the electronic and new media arts.
Educational Material Types
  • Slide presentations
  • Video lectures
  • Multimedia
  • Interactive excersises
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Course Organization
Laboratory Work150.5
Reading Assigment351.2
Student Assessment
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Performance / Staging (Summative)
  • Labortatory Assignment (Formative)
Additional bibliography for study
1. Brain-Computer Interfacing: An Introduction, Rajesh P. N. Rao (Author), Cambridge University Press; 1 edition (September 30, 2013), ISBN: 0521769418 2. Guide to Brain-Computer Music Interfacing, Eduardo Reck Miranda (Editor), Julien Castet (Editor), Springer; 2014 edition,ΙSBN: 1447165837 3. An Introduction to the Event-Related Potential Technique (MIT Press) second Edition, Steven J. Luck (Author), ISBN-10: 0262525852
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