Sponsored by FENS/IBRO-PERC and ITI-Neurostra

Research discoveries are increasingly dependent on the development of new tools and technologies, as well as on the ability to process, manage and analyze the large amounts of data collected with these tools.

In this summer school, we will focus on several aspects of data preparation and analysis, as well as on the use of simulation and modeling tools capable of generating predictions. These tools will be applied to different data acquisition techniques such as electrophysiological recordings (e.g. EEG, intra or extracellular recordings) or image series from brain imaging (e.g. MRI).

There is no registration fee.

Target audience:

Master and PhD students from the University of Strasbourg and other French and foreign universities are welcome to apply.

Priority will be given to students enrolled in a basic or medical neuroscience program, but students from other specialties will be able to participate as long as places are available.

Students are encouraged to come with their own dataset.

During the school (Sep. 4-9th), accomodation and lunches (but not travel) will be offered to non-Strasbourg students.

Note: Pre-school: Introduction to Python programming (Only for beginners)

FENS and IBRO-PERC provide 5 stipends of 750 EUR for Master and/or PhD students based in Europe interested in attending this course.Through these stipends FENS and IBRO-PERC aim to encourage and promote international experience of students; hence, students that are currently residing or studying in France are not eligible for a FENS and IBRO-PERC stipend for this course.

How to apply:

Send your CV and a letter of recommendation to philippe.isope at unistra.fr

Application deadline: May 15, 2023.

Pre-school Aug 31st – Sept 1^{st, 2023}

Thursday-Friday August 31st – Sept 1^st.

Pre-school: Introduction to Python programming (Only for beginners)

Summer School Sept 4-9, 2023

Monday 4th

● Session 1: Fundamentals of spectral analysis
● Session 2: Oscillations analyses using MATLAB: from the raw data to the characterization of oscillatory activity

Tuesday 5th

● Session 3: Machine learning for dummies
● Session 4: Hands-on analyzing calcium imaging data
● Session 5: Network tools, functional connectivity analyses graph theory
● Evening lecture
 
Wednesday 6th

● Session 6: Times series analysis, spike train statistics

● Session 7: Introduction to neuronal models

● Project selection and discussion

● Evening lecture

Thursday 7th

● Session 8: Neuronal circuits modelling: microscale

● Session 9: Neuronal circuits modelling: macroscale

● Project

Friday 8th

● Project

Saturday 9^th (Morning only)

● Project presentation and debriefing

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Faculty:

Demian Battaglia, USIAS, University of Strasbourg, France

Jyotika Bahuguna, Carnegie Mellon University, Pittsburgh, USA

Romain Goutagny, CNRS, University of Strasbourg, France

Axel Hutt, INRIA, Strasbourg, France

Philippe Isope, CNRS, University of Strasbourg, France

Arvind Kumar, KTH Royal Institute of Technology, Sweden

Christophe Pouzat, CNRS, University of Strasbourg, France

Pascale Quilichini, INSERM, Aix-Marseille University, France

Antoine Valera, CNRS, University of Strasbourg, France

Strasbourg, France

Preschool: Introduction to Python programming - Aug. 31 - Sept. 1, 2023

Summer School: Advanced tools for data analysis in Neuroscience - Sept. 4-9, 2023