Acquisition and Analysis of Neuronal Data

Integrated lecture and tutorials

Dates, Lecturers, and Location

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 (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.

Course Certificates

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 individual student has to complete an additional small programming project, see below.

The final oral exam on the module "Acquisition and Analysis of Neuronal Data" will take place in the week from October 4 to October 8, 2010.

Material

• Lecture #07: Script | Sheet; Appendix | Material | Solution: script, part II

• Lecture #08: Script | Sheet | Material | Solution: script

• Lecture #09: Script | Sheet | Material | Solution: script, part II

• Lecture #10: Script | Sheet | Material

Projects

To obtain the full 5 ECTS for the tutorial, every individual student has to complete an additional small programming project.

Project topics will be distributed at the end of the lecture series, and every student should work on her/his topic in the lecture-free time (July/August/September 2010). Written reports should be turned in via E-mail in September 2010 for evaluation.

Reports must be turned in at least 14 days before the registration to the oral exam on the module "Acquisition and Analysis of Neuronal Data", which will take place at the beginning of October 2010. A positively evaluated report is a prerequisite for registration to the oral exam! Please consider that corrections might become necessary, and the corrected report needs to be evaluated again before the registration to the oral exam.

Students are required to turn in a short written report, that is, a self-contained description of results. The report should comprise a single PDF file including a short Introduction, a Results/Discussion section, labeled Figures with caption, and the program code as an attachment. Guidelines for Writing a Scientific Report might be helpful.

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