Forschung

Summer Term 2018 / Neural Inf Process


 Download: WEEK PLAN (compulsory courses) // WEEK PLAN (elective courses) // EXAM SCHEDULE

Course title

Neural Data Analysis

Lecturer
Berens, Ecker
Credits
4.00
Course content / topics

Objective
In recent years our experimental methods to record brain activity have been revolutionized. As the complexity of the data acquired by neurophysiologists increases, neural data analysis becomes ever more important: The complex multidimensional signals recorded with multielectrode arrays or two-photon imaging can no longer be interpreted by eye, but mathematical and statistical techniques are needed.

In this practical course we will cover a selection of topics related to the analysis of different kinds of neural data: basic descriptive and inferential statistics, time series analysis, spike triggered average/covariance, spike sorting, dimensionality reduction techniques and information theory. The focus will be on hands-on experience in data analysis.

Lecture Schedule

Please notice: the TUTORIAL to this lecture will take place on thu 3-5 pm

Learning targets
In this course students will acquire the techniques necessary to analyze multidimensional discrete (spike trains) and continuous (cellular voltage/calcium signals, LFP, EEG, etc.) neural signals. In the computer exercises and the homework assignments, they will acquire hands-on knowledge and learn to deal with the difficulties of applying those techniques to real data.

Prerequisites
Programming skills (Matlab/Python)
Basic mathematical skills (vector algebra, probability theory)

Suggested reading
Emery N Brown, Robert E Kass, und Partha P Mitra, „Multiple neural spike train data analysis: state-of-the-art and future challenges“, Nat Neurosci 7, Nr. 5 (Mai 2004): 456-461.
Robert E. Kass, Valérie Ventura, und Emery N. Brown, „Statistical Issues in the Analysis of Neuronal Data“, Journal of Neurophysiology 94, Nr. 1 (Juli 1, 2005): 8 -25.
Liam Paninski’s course ‘Statistical analysis of neural data’ www.stat.columbia.edu/~liam/teaching/neurostat-spr11/ (we will cover only a few of these topics)
Dayan and Abbott: Theoretical Neuroscience. MIT Press.
Rieke, Warland, Ruyter van Stevenik and Bialek: Spikes – Exploring the neural code. MIT Press.

Day, time & location

Tue 9-11 am, GTC Lecture Hall (Start: April 17, 2018)