Acquisition and Analysis of Neuronal Data
Integrated lecture and tutorials
Dates, Lecturers, and Location
Dates and Rooms:
Lecture: Fridays from 09:15 to 10:45 in the lecture hall 102 (Haus 6)
Tutorials: Fridays from 11:00 (st!) to 12:30 in the computer pool of Haus 2
Part 1: Richard Kempter
Part 2: Benjamin Blankertz, Carmen Vidaurre
Bernstein Center for Computational Neurosciences Berlin, Haus 6 (lecture) and Haus 2 (tutorials), Philippstr. 13
Further Information on the web page of the BCCN-B.
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 (spike statistics, neural coding, theory of point processes, linear systems theory, correlation analysis, spike-triggered average, reverse correlation, STRF, neural decoding, signal detection theory, infomation theory, signal-to-noise ratio analysis) - see here for details on the first part.
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.
Required background knowledge: 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 points in the exercises (5 ECTS) must be obtained.
To obtain the full 5 ECTS for the tutorial, every student has to complete an additional small project (2 ECTS). Topics will be distributed in May 2011. More information can be obtained here.
The final oral exam on the module "Acquisition and Analysis of Neuronal Data" will take place on September 20th, 2011.
Lecture #07: Script | Exercises: Sheet; Appendix; Material | Solution: Script
Lecture #08: Script | Exercises: Sheet; Appendix; Data; Paper | Solution: Script; XVal; LDA
Lecture #09: Script | Exercises: Sheet; Data; Matlab function | Solution: Script; BiserialCC
Lecture #10: Script | Exercises: Sheet; Data | Solution: Script; CSP
Lecture #12: Script part 1 Script part 2
Part 2 (EEG)
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. pdf url
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 url
Treder MS, Blankertz B, (C)overt attention and visual speller design in an ERP-based brain-computer interface. Behav Brain Funct, 6:28, 2010. url
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
Key AP, Dove GO, Maguire MJ. Linking brainwaves to the brain: an ERP primer. Dev Neuropsychol. 2005;27(2):183-215. pdf
Pfurtscheller G, Lopes da Silva FH. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol, 110(11):1842-1857, Nov 1999. 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
Dornhege G, Millán J del R, Hinterberger T, McFarland DJ, Müller KR, editors. Toward Brain-Computer Interfacing. MIT Press, Cambridge, MA, 2007.