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#40362 / #4

SS 2017 - WS 2017/18


Brain-Computer Interfacing


Blankertz, Benjamin




Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34355200 FG S-Professur Neurotechnologie

No information


MAR 4-3

Miklody, Daniel


PORD-Nr.ModultitelLPBenotungPrüfungsformPNr. (POS)Modulprüfung PORDModulprüfung PNr.

Learning Outcomes

Students know the essential concepts of Brain-Computer Interfacing (BCI). They are capable of applying methods of biomedical signal processing and single-trial classification to neural data. They can provide an interpretation of the outcome of their analysis in a statistical as well as in a neurophysiological manner. They have deeper knowledge about special topics of BCI research, either in data analysis of physiological signals with respect to a technical/ physical background.


IL: Approaches to Brain-Computer Interfacing (BCI); Event-related potentials (ERPs); Spatial filters; Multivariate analysis of brain signals; Single-trial classification of spatio-temporal features; Regularized discriminant analysis (RDA); The linear model (forward and backward) of EEG; Interpretation of spatial patterns and filters; Modulation of spontaneous brain rhythms; Event-related synchronization and desynchronization (ERS, ERD); Common spatial pattern (CSP) Analysis; Classification of spatio-spectral features; Signal decomposistion methods; Supervised and unsupervised methods of adaptation in the classification of EEG; Experimental design Additionally to the IL, participants either take part in the seminar (SE) or in practical sessions (PR). There is also a larger version of the modul, which is called "Brain-Computer Interfacing (extended)" which encompasses the SE and the PR and has 12 LP, and as well a small version called "Brain-Computer Interfacing (bassic)" with 6 LP which consists of the IL only. SE: Examplary topics: Neural correlates of attention in free viewing, Predictors of BCI Performance, Co-adaptive Systems, Control by Spatial Attention; Hybrid BCIs, Multimodal BCIs PR: In the practical session, the technological and physical basics of Brain-Computer Interfacing will be elaborated. It covers the path from the (electrical) activity of single neurons via the volume conduction of the human head and the instrumentation to the computer.

Module Components


All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Brain-Computer InterfacingIV3435 L 501WSNo information4

Elective part (SEM or PR):

1 from the following courses must be completed.

Course NameTypeNumberCycleLanguageSWSVZ
Brain-Computer Interfacing - from neurons to dataPR3435 L 9106SSNo information2
Current Topics in Brain-Computer InterfacingSEM3435 L 502WSNo information2

Workload and Credit Points

Brain-Computer Interfacing (IV):

Workload descriptionMultiplierHoursTotal
180.0h(~6 LP)
Bearbeitung der Übungsaufgaben10.06.0h60.0h
Vorbereitung für die Prüfungen2.015.0h30.0h

Brain-Computer Interfacing - from neurons to data (PR):

Workload descriptionMultiplierHoursTotal
90.0h(~3 LP)
Bearbeitung der Übungsaufgaben5.06.0h30.0h

Current Topics in Brain-Computer Interfacing (SEM):

Workload descriptionMultiplierHoursTotal
90.0h(~3 LP)
The Workload of the module sums up to 270.0 Hours. Therefore the module contains 9 Credits.

Description of Teaching and Learning Methods

The integrated lecture (IL) consists of a lecture (mainly teacher-centred, with some period of group work) and assignments. The latter require independently solving programming exercises and working on complex tasks under guidance of a tutor. Talks in the seminar (SE) are developed independently with the guidance of a tutor. They are presented and discussed at one or two days in the second half of the semester. The practical session (PR) consist of a lecture and a closely connected exercise session in a weekly exchange. In the exercises, the content of the lecture will be elaborated and they will be graded. --- --- Die integrierte Lehrveranstaltung besteht aus einem Vorlesungsteil (Frontalunterricht vor allen Teilnehmern zur Vermittlung des Stoffes) und einem Anteil praktischer Arbeit. Letztere besteht aus dem selbstständigen Bearbeiten von Übungsaufgaben und der Bearbeitung einer komplexeren Fragestellung unter Anleitung eines Assistenten. Die Seminarvorträge werden unter Anleitung eines Betreuers erarbeitet und in einem Blockseminar in der zweiten Hälfte des Semesters präsentiert und diskutiert. Das Prkatikum besteht aus einer Vorlesung und einer Übung im wöchentlichen Wechsel, wobei der Inhalt der Vorlesung in der eng verknüpften Übung erarbeitet wird. Die Übung wird bewertet.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

* Required: programming skills; background in mathematics, in particular linear algebra and probability theory. * Helpful, but not obligatory: Basic knowledge in signal processing and machine learning. For the practical session basic knowledge in electrostatics and electronics are of advantage. --- --- Programmierkenntnisse, gute Grundlagen in Mathematik, insbesondere Lineare Algebra und Wahrscheinlichkeitstheorie. Grundlagen der Signalverarbeitung und des maschinellen Lernens sind ratsam, jedoch bei solidem theoretischen Vorwissen und Fähigkeiten nicht zwingend erforderlich. Für das Praktikum sind Grundlagen in Elektrostatik und Elektronik vorteilhaft.

Mandatory requirements for the module test application:

No information

Module completion



Type of exam

Portfolio examination

Type of portfolio examination

100 points per element



Test elements

(Ergebnisprüfung): 5 Assignments in the PR / Hausaufgaben im PR25practicaljeweils 6h
(Ergebnisprüfung): 10 Assignments / Hausaufgaben (Übungszettel)15practicaljeweils 6h
(Ergebnisprüfung): Talk in the seminar / Vortrag zum Seminar25oral30 min
(Punktuelle Leistungsabfrage): 2 written exams / schriftliche Tests60writtenjeweils 45 min

Grading scale

Test description (Module completion)

The grade is determined according to § 47 (2) AllgStuPO with the grading system 2 of faculty IV. * Exercises: Concurrent to the lecture, there will be a tutorial in which ten assignment sheets have to be solved. These are devoted to practical EEG analysis (programming). * Written exams: In the first half and in the second half of the lecture, there will a written test of about 45 minutes. * Seminar talk: Presentation of a research topic (orally with slides) * Practical session: As part of the practical sessions, five assignment sheets have to be solved. --- --- Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt. * Übungsaufgaben: Zur Ergebnisprüfung gibt es begleitend zu der Vorlesung zehn Übungszettel in denen praktische Aufgaben zur EEG Analyse gelöst werden müssen. * Schriftliche Tests: Jeweils zum ersten und zum zweiten Teil der Vorlesung gibt es einen schriftlichen Test. * Seminarvortrag: An zwei Blockterminen halten die Teilnehmenden Vorträge über ein zugeteiltes Thema aktueller Brain-Computer Interface Forschung. * Praktikum: Zur Ergebnisprüfung gibt es in dem Praktikum fünf Übungszettel.

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Winter- und Sommersemester.

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

Registration is not required, but stating the interest to participate in the lecture is welcome for the planning of resources. * Either email to Sekr. MAR 4-3: Imke Weitkamp <imke.weitkamp@tu-berlin.de> * or register in the respective courses in the information system at https://isis.tu-berlin.de/

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable


Electronical lecture notes

Availability:  available
Additional information:
Skripte in elektronischer Form werden jeweils nach der Vorlesung auf ISIS zur Verfügung gestellt.



Recommended literature
Blankertz B, Lemm S, Treder MS, Haufe S, Müller KR, Single-trial analysis and classification of ERP components - a tutorial, Neuroimage, 56:814-825, 2011.
Blankertz B, Tomioka R, Lemm S, Kawanabe M, Müller KR, Optimizing Spatial Filters for Robust EEG Single-Trial Analysis, IEEE Signal Process Mag, 25(1):41-56, 2008.
Dornhege G, R. Millán J d, Hinterberger T, McFarland D, Müller K (eds), Toward Brain-Computer Interfacing, MIT Press, 2007.
Parra LC, Spence CD, Gerson AD, Sajda P. Recipes for the Linear Analysis of EEG, Neuroimage, 28(2):326-341, 2005.

Assigned Degree Programs

This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
This module is not used in any degree program.

Students of other degrees can participate in this module without capacity testing.


No information