Lecture + Tutorial, Summer 2017
Computational Neuroscience:
Acquisition and Analysis of Neural Data
Richard Kempter, Benjamin Blankertz
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Lecture + Tutorial, Summer 2017Computational Neuroscience:
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Lecture:
Richard Kempter,
Benjamin Blankertz
Tutorial on spike trains:
Paula Kuokkanen and Jens Kremkow
Tutorial on EEG data:
Benjamin Blankertz and coworkers
Date: From 21-April-2017 to 21-July-2017.
Location: Lectures and tutorials take place at the Bernstein Center for Computational Neuroscience Berlin.
Times:
Lectures (2 SWS, 2 ECTS): Fridays from 09:15 am to 10:45 am, Lecture Hall
102, Haus 6
Tutorials (2 SWS, 5 ECTS): Fridays from 11:00 am to 12:30 pm, Lecture Hall / Computer Pool, Haus 2
Target Group: Students of Computational Neuroscience, Medical Neuroscience, Biology, Biophysics, Physics, Mathematics, and Computer Science.
Requirements: Basic knowledge in Neurobiology and Mathematics at the level of the first year of the Masters Program in Computational Neuroscience.
Topics: This course is the second part of the module
''Acquisition and Analysis of Neural Data'' of the
Master Program in Computational Neuroscience, and this second part
focuses on statistical analyses
of neural data:
(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, information theory, signal-to-noise ratio analysis). This Moodle Course provides details on the tutorials.
(2) Statistical analysis of electroencephalogram (EEG) data, e.g., forward calculation; investigation of event-related potentials (ERPs) and event-related desynchronization (ERD); spatial filters; classification.
| (01) | 21.04. | The firing rate (Richard Kempter, RK) |
| (02) | 28.04. | Spike-train statistics: spike-triggered average and reverse correlation (RK) |
| (03) | 05.05. | Correlation functions and the neural code (RK) |
| (04) | 12.05. | Neural encoding (RK) |
| (05) | 19.05. | Neural decoding (RK) |
| 26.05. | - no lecture - | |
| (06) | 02.06. | Information theory (RK) |
| 09.06. | - no lecture - | |
| (07) | 16.06. | Overview BCI; Characterization of Gaussian Distributions (Benjamin Blankertz, BB) |
| (08) | 23.06. | ERP-based BCIs; Spatio-Temporal Features; LDA (BB) |
| (09) | 30.06. | Shrinkage of the Empirical Covariance Matrix (BB) |
| (10) | 07.07. | Linear Model of EEG; Spatial Patterns and Spatial Filters (BB) |
| (11) | 14.07. | Modulations of Brian Rhythms; Common Spatial Pattern Analysis (BB) |
| (12) | 21.07. | Adaptive Classification (supervised and unsupervised) (BB) |
Course Certificates: To obtain a course certificate, at least 75% of the points in the weekly exercises must be obtained. This 75% rule applies to each of the two blocks in the summer term separately. Thus, 75% must be achieved on average over all assignments in the part on the "Analysis of spike trains" and, separately, in the part on the "Statistical analysis of EEG". Participants via the Master module MB-B12 (HU Berlin, Biology) need to obtain only 50%, which accounts for the lower number of 3 ECTS points for the Computer Practical.
Exam: The final oral exam on the module "Acquisition and Analysis of Neuronal Data" will take place on 10-October-2017 (and, if necessary, also in the afternoon of 09-October-2017).
Background material for the analysis of spike trains:
P. Dayan and L.F. Abbott (2001)
Theoretical Neuroscience.
MIT Press, Cambridge, Massachusetts.