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#40362 / #7

WiSe 2021/22 - SoSe 2022

English

Brain-Computer Interfacing

9

Blankertz, Benjamin

benotet

Portfolioprüfung

Zugehörigkeit


Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34355200 FG S-Professur Neurotechnologie

No information

Kontakt


MAR 4-3

Miklody, Daniel

benjamin.blankertz@tu-berlin.de

PORD-Nr.ModultitelLPBenotungPrüfungsformPNr. (POS)Modulprüfung PORDModulprüfung PNr.
29007

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 NameTypeNumberCycleLanguageSWSVZ
Brain-Computer InterfacingIV3435 L 501WSNo information4
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
Präsenzzeit15.04.0h60.0h
Vor-/Nachbereitung15.02.0h30.0h
Vorbereitung für die Prüfungen2.015.0h30.0h

Current Topics in Brain-Computer Interfacing (SEM):

Workload descriptionMultiplierHoursTotal
90.0h(~3 LP)
Attendance3.05.0h15.0h
Pre/post-processing1.075.0h75.0h
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:

No information

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 points per element

Language

English

Test elements

NameWeightCategorieDuration/Extent
(Deliverable assessment / Ergebnisprüfung): 10 Assignments / Hausaufgaben (Übungszettel)15practicaljeweils 6h
(Deliverable assessment / Ergebnisprüfung): Talk in the seminar / Vortrag zum Seminar25oral30 min
(Examination / Punktuelle Leistungsabfrage): 2 written exams / schriftliche Tests60writtenjeweils 60 min

Grading scale

1.01.31.72.02.32.73.03.33.74.0
95.090.085.080.075.070.065.060.055.050.0

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 60 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 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.

 

Literature

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
Biomedizinische Technik (M. Sc.)25WiSe 2021/22WiSe 2022/23

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

Miscellaneous

No information