Courses '09

1st G-Node Winter Course in Neural Data Analysis

 The G-Node Winter Course in Neural Data Analysis is planned on a yearly basis. This 1st course gives hands-on experience with neural data analysis for PhD students and young postdocs. Participants with either theoretical or experimental background are equally invited.

Participants may have a theoretical  background with interest in analyzing biological (or simulated) data or they may come from an experimental background, interested in new ways of analyzing their data .

We will focus on two types of data. (1) In intracellular patch clamp recordings from slice preparations synaptic events (PSCs and PSPs) will be analyzed with respect to quantal size and reliability. (2) In extracellular cortical single and multi unit recordings from awake monkeys we study time-resolved firing rates and spike train variability as well as tuning and correlations.

All participants must have ample programming skills in Matlab. Most analysis tools have to be programmed by the individual participant, under the guidance of tutors. Participants should show interest in model-driven analyses and be open to theoretical approaches to data analysis. Likewise, they should show interest in the practical analysis of real biological data.

Credits (4 ECTS) are granted to PhD students where applicable. Acceptance of credits is subject to the rules of the respective graduate program. Agreements exist with PhD Programs of the Bernstein Centers for Computational Neuroscience Berlin and Freiburg.

Faculty

• Clemens Boucsein · ALU Freiburg
• Alex Loebel · LMU Munich
• Martin Nawrot · FU Berlin
• Thomas Wachtler · PU Marburg / G-Node Munich

Registration

All places for this course are filled. Please do not apply for participation anymore.

Total number of participants : 15
We restrict the number of participants from one work group to a max. of 2
We will fill up places according to registration date, i.e.  first come - first serve

For registration please send Email to Martin Nawrot including

• full institutional address (with phone number)
• your current status (PhD student, Postdoc, stipend)
• a brief description of your programming skills and experience with Matlab
• you may add why you are interested in this course and a short description of your project work and particular interests in type of data analysis (this is not mandatory)

Contact

Martin Nawrot