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| || <|2> '''Dates and Rooms:''' || Lecture: Fridays from 10:00 to 11:30 am in the lecture hall 102 || | || <(^|2> '''Dates and Rooms:''' || Lecture: Fridays from 10:00 to 11:30 am in the lecture hall 102 || |
Acquisition and Analysis of Neuronal Data
Integrated lecture and tutorials
Dates, Lecturers, and Location
<(^|2> 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 |
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Lecturers (part 1): |
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Lecturers (part 2): |
Benjamin Blankertz, Carmen Vidaurre |
|| Location: || Bernstein Center for Computational Neurosciences Berlin,
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)
P. Dayan and L.F. Abbott (2001) Theoretical Neuroscience. MIT Press, Cambridge, Massachusetts.