ANDA 2020 - G-Node Advanced Neural Data Analysis Course/ postponed

Techniques to record neuronal data from populations of neurons are rapidly improving. Simultaneous recordings from hundreds of channels are possible while animals perform complex behavioral tasks. The analysis of such massive and complex data becomes increasingly challenging. This advanced course aims at providing deeper training in state-of-the-art analysis approaches in systems neuroscience.

The course is addressed to excellent master and PhD students and young researchers who are interested in learning advanced techniques in data analytics and in getting hands-on experience in the analysis of electrophysiological data. Internationally renowned researchers will give lectures on statistical data analysis and data mining methods with accompanying exercises. Students will define and perform their own analyses on provided data to solve a challenge.

Participants are required to have a strong interest in data analysis, a background in a mathematical or related field, knowledge of algebra, matrix operations, and statistics, and need to have solid programming experiences (preferably in Python).

Date and Venue
April 14 - 30, 2020
Haus Overbach, Juelich-Barmen, Germany

Faculty   

Topics covered
Single neuron properties and statistics · Stochastic processes · Surrogate methods · Detection of spatio-temporal patterns · Unitary Events · Statistical analysis of massively parallel spike data · Higher-order correlation analyses · Elephant toolbox · Spike-LFP relationship · Population coding · State space analysis · Machine learning · Data mining · Research data management, reproducibility, data sharing

Requirements
Applicants should be familiar with linear algebra, probability, differential and integral calculus and experienced using Python or Matlab. Preparatory reading material will be provided. Students should bring their own laptops and should be able to install software on their system. Students that do not have a suitable laptop should indicate this immediately after acceptance to the course.

Course Fee
A course fee of 1000 Euros will be charged to cover costs for accommodation and meals. Limited financial support may be available for students that otherwise would not be able to attend, which is to be indicated in the application.

Housing
Accommodation in 2-bed rooms for students will be provided at the course site.

How to apply

Deadlines
Deadline for application is November 15, 2019.

For further information see here

Organizers

• Sonja Grün, Jülich Research Center and RWTH Aachen Univ, Germany
• Martin Nawrot, University of Cologne, Germany
• Thomas Wachtler, G-Node, Ludwig-Maximillians-Universität München, Germany