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Interdisciplinary tutorials in neurosciences (TINS)

Master in Life Sciences, ENS
BIO_M2_E15 | TINS - Interdisciplinary tutorials in neurosciences
Year and Semester : M2 | S1
Where : Biology department, ENS
Duration : 1st semester
Maximum class size : 14 students

—2024-2025 planning to come—


Mariano Casado, Biology department, ENS
Boris Barbour, Biology department, ENS




Computational Neuroscience | Theoretical Neuroscience | Modeling | Data Analysis in Neurophysiology.

Course prerequisites

Students should be motivated by interdisciplinary approaches in Neuroscience and be capable of benefiting from both theoretical and experimental aspects of Neuroscience research.
Programming skills are very often needed. Precise programming requirements may be announced for each topic.

Course objectives and description

Aims : In depth study of a research topic related to neuronal networks, based on modeling, data mining, development of data analysis tools, computational neurophysiology... done under the close supervision of both a theoretician and an experimental researchers.
Themes : Understanding the brain will require the development of effective abstractions and simplifications of its complexity. Research in this field is active at the interface between theoretical and experimental neuroscience.
This module offers insight into such interdisciplinary research in a tutorial setting with active theoretical and experimental neuroscientists.
Organisation : Discussion with mentors, supervised bibliographical analysis (necessary but not sufficient), possible data mining and analysis, and modeling.


A minimum of 60 h personal work, from October to January, punctuated with several meetings with the supervisors to assess the progress of the project.


Written report (to be produced by early January), oral presentation mid-January.

Course material

To be provided by mentors.

Teaching team

Mariano CASADO, Biology department, ENS
Boris BARBOUR Biology department, ENS
Vincent HAKIM, Physics department, ENS
Jonas RANFT Biology department, ENS

Suggested readings in relation with the module content