1. Modulverzeichnis (MTS)
  2. Module
  3. Modulbeschreibung anzeigen

Brain-Computer Interfacing

Display language
To modulepage Generate PDF

#40362 / #3

SS 2016 - WS 2016/17

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

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.

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 501WiSeNo information4
Current Topics in Brain-Computer InterfacingSEM3435 L 502WiSeNo information2

Workload and Credit Points

Brain-Computer Interfacing (IV):

Workload descriptionMultiplierHoursTotal
Präsenzzeit15.04.0h60.0h
Vor-/Nachbereitung15.08.0h120.0h
180.0h(~6 LP)

Current Topics in Brain-Computer Interfacing (SEM):

Workload descriptionMultiplierHoursTotal
Präsenzzeit15.02.0h30.0h
Vor-/Nachbereitung15.04.0h60.0h
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-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. --- --- 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.

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. --- --- 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.

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

No information

Language

English

Test elements

NamePoints/WeightCategorieDuration/Extent
(Ergebnisprüfung): 10 Assignments / Hausaufgaben (Übungszettel) à 1.5 Punkte15No informationNo information
(Ergebnisprüfung): Talk in the seminar / Vortrag zum Seminar25No informationNo information
(Punktuelle Leistungsabfrage): 2 written exams / schriftliche Tests à 30 Punkte60No informationNo information

Grading scale

No information

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 eight 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. --- --- 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. * Seminarvortrag: An einem Blocktermin halten die Teilnehmenden Vorträge über ein zugeteiltes Thema aktueller Brain-Computer Interface Forschung. * Schriftliche Tests: Jeweils zum ersten und zum zweiten Teil der Vorlesung gibt es einen schriftlichen Test.

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

This module is not limited to a number of students.

Registration Procedures

Registration is not required, but an email stating the interest to participate in the lecture is welcome for the planning of resources: Sekr. MAR 4-3: Imke Weitkamp <imke.weitkamp@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 ISIS2 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
This module is not used in any degree program.

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

Miscellaneous

No information