Moses - Brain-Computer Interfacing

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum SS 2018 - WiSe 2020/21. Die Version für das aktuelle Semester (SoSe 2024) finden Sie hier: Modulbeschreibung des SoSe 2024

Module / Version:
#40362 / #5

Validity:
SS 2018 - WiSe 2020/21

Default display language:
English

Module title:
Brain-Computer Interfacing

Credits:
9

Responsible person:
Blankertz, Benjamin

Grading:
benotet

Type of exam:
Portfolioprüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Softwaretechnik und Theoretische Informatik

Area of expertise:
34355200 FG S-Professur Neurotechnologie

Prüfungsausschuss:
No information

Kontakt

Office:
MAR 4-3

Contact person:
Miklody, Daniel

E-mail address:
benjamin.blankertz@tu-berlin.de

Website:

http://wiki.ml.tu-berlin.de/wiki/NT/Courses

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 in data analysis of physiological signals.

Content

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 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

Module Components

Pflichtteil:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Brain-Computer Interfacing	IV	3435 L 501	WiSe	No information	4
Current Topics in Brain-Computer Interfacing	SEM	3435 L 502	WiSe	No information	2

Workload and Credit Points

Brain-Computer Interfacing (IV):

Workload description	Multiplier	Hours	Total
Bearbeitung der Übungsaufgaben	10.0	6.0h	60.0h
Präsenzzeit	15.0	4.0h	60.0h
Vor-/Nachbereitung	15.0	2.0h	30.0h
Vorbereitung für die Prüfungen	2.0	15.0h	30.0h
			180.0h(~6 LP)

Current Topics in Brain-Computer Interfacing (SEM):

Workload description	Multiplier	Hours	Total
Attendance	3.0	5.0h	15.0h
Pre/post-processing	1.0	75.0h	75.0h
			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-centered, 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.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

* Mandatory: 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.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte pro Element

Language

English

Test elements

Name	Weight	Categorie	Duration/Extent
(Ergebnisprüfung): 10 Assignments / Hausaufgaben (Übungszettel)	15	practical	jeweils 6h
(Ergebnisprüfung): Talk in the seminar / Vortrag zum Seminar	25	oral	30 min
(Punktuelle Leistungsabfrage): 2 written exams / schriftliche Tests	60	written	jeweils 60 min

Grading scale

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl	1.0	1.3	1.7	2.0	2.3	2.7	3.0	3.3	3.7	4.0
100.0pt	95.0pt	90.0pt	85.0pt	80.0pt	75.0pt	70.0pt	65.0pt	60.0pt	55.0pt	50.0pt

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)

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:
Wintersemester.

Maximum Number of Participants

The maximum capacity of students is 50.

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 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

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

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

	Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
This module is not used in any degree program.

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

Miscellaneous

No information

Brain-Computer Interfacing