Summer School | Advanced tools for data analysis in neuroscience

Future event

Strasbourg, 12-21 Sept 2024

12 21 September 2024

Advanced tools for data analysis in neuroscience

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, fluorescence imaging or image series from human brain imaging.

There is no registration fees. Accommodation and lunches are also provided with no fees.

Travel is not covered.  

Target audience

Master and PhD students from the University of Strasbourg, French and European universities (including non EU).

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. 

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

FENS and IBRO-PERC provide 4 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




Thursday-Friday Sept 12th – Sept 13th.

  • 9-12:30; lunch; 2-6 PM

Introduction to Python programming: Conda environment, Python basics (Object, Types, list, arrays, loops, conditions, functions, classes), Python packages (e.g. Numpy, Pandas, Matplotlib…), Python with AI.


Monday Sept 16th

  • 8:30 AM: Welcome and course presentation
  • 9 - 12:30 AM: Fundamentals of spectral analysis 
  • 2 - 4 PM: Oscillations analyses - from the raw data to the characterization of oscillatory activity
  • 4:30 - 6 PM: What to do when you have to estimate a function? Non-parametric    regression techniques

Tuesday Sept 17th

  • 9 - 12:30 AM: Machine learning for dummies
  • 2 - 3:30 PM: Times series analysis, spike train statistics
  • 3:45 - 5 PM: Hands-on analyzing calcium imaging data
  • 5:30 - 7 PM: Introduction to AI in data analysis for neurosciences

Wednesday Sept 18th

  • 9-11 AM: Network tools, functional connectivity analyses graph theory
  • 11:30-12:30 PM: Neuronal circuits modelling microscale Part I
  • 2 - 4 PM: Neuronal circuits modelling microscale Part II
  • 4 - 6 PM Automated algorithms for movement analysis
  • 8-10 PM: Project selection, discussion

Thursday Sept 19th

  • 9 - 12:30 AM: Neuronal circuits modelling: macroscale
  • 2 - 8 PM:  Projects
  • Social evening at “la Petite France”

Friday Sept 20th

  • 9 - 12:30 AM: Projects
  • 2 - 6 PM: Projects
  • 7 - 8 PM: Reproducible science/Open Science

Saturday Sept 21th

  • 9 - 12 AM: Project presentations and debriefing



  • Claire Wyart, CNRS, INSERM, Paris Brain Institute, Paris, France
  • Jyotika Bahuguna, University of Strasbourg, France
  • Pascale Quilichini, INSERM, Aix-Marseille University, France
  • Demian Battaglia, USIAS, University of Strasbourg, France
  • 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, Stockholm, Sweden
  • Christophe Pouzat, IRMA, University of Strasbourg, France                   
  • Antoine Valera, CNRS, University of Strasbourg, France

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