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| * ''Part 2:'' 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 [[http://itb.biologie.hu-berlin.de/~kempter/Teaching/2012-SS-AAND/index.html|here]] for details on the first part. | * ''Part 2:'' 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 [[http://itb.biologie.hu-berlin.de/~kempter/Teaching/2013-SS-AAND/index.html|here]] for details on the second part. |
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| To obtain the full 5 ECTS for the tutorial, every student has to complete an additional small project (2 ECTS). The tasks of the project in AAND will be distributed in the lecture on July 6th and put on this web page. The tasks will be similar to the exercises (EEG data analysis with Matlab) and solutions have to be submitted until October 1st. The idea is to have small groups of two or three students who work together on the tasks. Each group will receive a different task. | To obtain the full 5 ECTS for the tutorial, every student has to complete an additional small project (2 ECTS). The tasks of the project will be distributed by Richard Kempter. |
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| The data for the final oral exam on the module "Acquisition and Analysis of Neuronal Data" will be announced here. | The final oral exam of the module "Acquisition and Analysis of Neuronal Data will be in September or October 2013. The exact date will be announced later. |
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| will be provided here. | * Lecture #01: [[http://doc.ml.tu-berlin.de/bbci/SS13_IL_AAND/AAND2013_lecture01_handout.pdf|Handout]] | [[http://doc.ml.tu-berlin.de/bbci/SS13_IL_AAND/AAND2013_sheet01.pdf|Sheet]]; [[http://doc.ml.tu-berlin.de/bbci/SS13_IL_AAND/AAND2013_sheet01_appendix.pdf|Appendix]] | [[http://doc.ml.tu-berlin.de/bbci/SS13_IL_AAND/AAND2013_sheet01_material.zip|Material]] (matlab code and data sets) |
Integrated lecture and tutorials ''Acquisition and Analysis of Neuronal Data''
Dates, Lecturers, and Location
Module |
Part of the Master Program Computation Neuroscience |
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 |
|
Lecturers: |
Part 1: Benjamin Blankertz |
Part 2: Richard Kempter |
|
Location: |
Bernstein Center for Computational Neurosciences Berlin, Haus 6 (lecture) and Haus 2 (tutorials), Philippstr. 13 |
TU University calendar: |
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: Statistical analysis of electroencephalogram (EEG) data, e.g., investigation of event-related potentials (ERPs) and event-related desynchronization (ERD); spatial filters; classification, adaptive classifiers.
Part 2: 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 second part.
Required background knowledge: Basic knowledge in Neurobiology and Mathematics at the level of the first year of the Master Program in Computational Neuroscience.
Course Certificates
To obtain course certificates, at least 75% of the points in the exercises (5 ECTS) must be attained.
To obtain the full 5 ECTS for the tutorial, every student has to complete an additional small project (2 ECTS). The tasks of the project will be distributed by Richard Kempter.
The final oral exam of the module "Acquisition and Analysis of Neuronal Data will be in September or October 2013. The exact date will be announced later.
Material
Background material
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.
Wolpaw JR, Wolpaw EW, editors. Brain-Computer Interfaces: Principles and Practice. Oxford University Press, 2012. ISBN-13: 978-0195388855.