Differences between revisions 1 and 2
Revision 1 as of 2010-02-09 09:57:32
Size: 3945
Comment:
Revision 2 as of 2010-02-09 09:58:19
Size: 3847
Comment:
Deletions are marked like this. Additions are marked like this.
Line 20: Line 20:
     [[http://itb.biologie.hu-berlin.de/~kempter/Teaching/2009_SS/index.html|details on part 1]]

Acquisition and Analysis of Neuronal Data

Integrated lecture and tutorials

Dates, Lecturers, and Location

Dates and Rooms:

Lecture: Fridays from 10:00 to 11:30 am in the lecture hall 102

Tutorials: Fridays from 12:30 to 14:00 pm in rooms 115 and/or 215

Lecturers:

Part 1: Richard Kempter

Part 2: Benjamin Blankertz, Carmen Vidaurre

Location:

Bernstein Center for Computational Neurosciences Berlin, Haus 6, Philippstr. 13

Further Information on the web page of the BCCN-B.

Topics

This part of the module "Acquisition and Analysis of Neural Data" of the Master Program in Computational Neuroscience provides knowledge on statistical analyses of neural data:

  • Part 1: Analysis of Spike Trains (Introduction to Linear Systems Theory, Introduction to Point Process Theory, Autoregressive Models for Neural Spike Trains, Correlation Analysis of Neural Spike Trains)

  • Part 2: Statistical analysis of electroencephalogram (EEG) data, e.g., investigation of event-related potentials (ERPs) and event-related desynchronization (ERD); spatial filters; classification, adaptive classifiers.

Requirements

Requirements: Basic knowledge in Neurobiology and Mathematics at the level of the first year of the Masters Program in Computational Neuroscience.

To obtain course certificates, at least 75% of the lectures (2 ECTS) must be attended, and at least 75% of the points in the exercises (5 ECTS) must be obtained.

Material

will be provided along with the lecture.

Background material

Part 1 (spike trains)

  • P. Dayan and L.F. Abbott (2001) Theoretical Neuroscience. MIT Press, Cambridge, Massachusetts. Online

Part 2 (EEG)

  • Dornhege G, Millán J del R, Hinterberger T, McFarland DJ, Müller KR, editors. Toward Brain-Computer Interfacing. MIT Press, Cambridge, MA, 2007.

  • Pfurtscheller G, Lopes da Silva FH. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol, 110(11):1842-1857, Nov 1999. pdf

  • Key AP, Dove GO, Maguire MJ. Linking brainwaves to the brain: an ERP primer. Dev Neuropsychol. 2005;27(2):183-215. pdf

  • Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clin. Neurophysiol., 113:767-791, 2002. pdf

  • Parra LC, Spence CD, Gerson AD, Sajda P. Recipes for the linear analysis of EEG. NeuroImage, 28(2):326-341, 2005. pdf

  • Parra LC, Christoforou C, Gerson AD, Dyrholm M, Luo A, Wagner M, Philastides M, Sajda P. Spatiotemporal Linear Decoding of Brain State. IEEE Signal Proc Magazine, 25(1): 107-115, 2008. pdf

  • Blankertz B, Tomioka R, Lemm S, Kawanabe M, Müller KR. Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Proc Magazine, 25(1):41-56, 2008. pdf

IDA Wiki: Main/SS10_AnalysisOfNeuronalData (last edited 2011-06-02 22:47:07 by BenjaminBlankertz)