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||<(|2> '''Lecturers''' || Part 1: [[http://itb.biologie.hu-berlin.de/~kempter/|Richard Kempter]] || ||<(|2> '''Lecturers:''' || Part 1: [[http://itb.biologie.hu-berlin.de/~kempter/|Richard Kempter]] ||
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   *    * Guido Dornhege, José del R. Millán, Thilo Hinterberger, Dennis McFarland, and Klaus-Robert Müller, editors. Toward Brain-Computer Interfacing. MIT Press, Cambridge, MA, 2007.
   * Gert Pfurtscheller and F. H. Lopes da Silva. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol, 110(11):1842-1857, Nov 1999.
   * Key AP, Dove GO, Maguire MJ. Linking brainwaves to the brain: an ERP primer. Dev Neuropsychol. 2005;27(2):183-215.
   * Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, and Theresa M. Vaughan. Brain-computer interfaces for communication and control. Clin. Neurophysiol., 113:767-791, 2002.
   * Lucas C. Parra, Clay D. Spence, Adam D. Gerson, and Paul Sajda. Recipes for the linear analysis of EEG. NeuroImage, 28(2):326-341, 2005.
   * Benjamin Blankertz, Ryota Tomioka, Steven Lemm, Motoaki Kawanabe, and Klaus-Robert Müller. Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Proc Magazine, 25(1):41-56, 2008.

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.

Background material

Part 1 (spike trains)

Part 2 (EEG)

  • Guido Dornhege, José del R. Millán, Thilo Hinterberger, Dennis McFarland, and Klaus-Robert Müller, editors. Toward Brain-Computer Interfacing. MIT Press, Cambridge, MA, 2007.

  • Gert Pfurtscheller and F. H. Lopes da Silva. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol, 110(11):1842-1857, Nov 1999.
  • Key AP, Dove GO, Maguire MJ. Linking brainwaves to the brain: an ERP primer. Dev Neuropsychol. 2005;27(2):183-215.

  • Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, and Theresa M. Vaughan. Brain-computer interfaces for communication and control. Clin. Neurophysiol., 113:767-791, 2002.

  • Lucas C. Parra, Clay D. Spence, Adam D. Gerson, and Paul Sajda. Recipes for the linear analysis of EEG. NeuroImage, 28(2):326-341, 2005.

  • Benjamin Blankertz, Ryota Tomioka, Steven Lemm, Motoaki Kawanabe, and Klaus-Robert Müller. Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Proc Magazine, 25(1):41-56, 2008.

IDA Wiki: Main/SS09_AnalysisOfNeuronalData (last edited 2010-05-28 10:02:17 by BenjaminBlankertz)