|
Size: 2388
Comment:
|
Size: 2387
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 7: | Line 7: |
| || <|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
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 |
|
Lecturers (part 1): |
|
Lecturers (part 2): |
Benjamin Blankertz, Carmen Vidaurre |
Location: |
Bernstein Center for Computational Neurosciences Berlin, Haus 6, Philippstr. 13 |
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.