Context: Neuronal networks generate large-scale activity patterns that support cognitive function. However, understanding how the anatomical and physiological properties of the network shape network activity and function is still a major challenge. Working memory is defined as the ability to temporarily store and manipulate behaviourally relevant information. The objective of our project is to elucidate how synaptic properties give rise to population activity patterns in working memory, which could reveal fundamental principles linking synaptic physiology and network computation. The project relies on a hybrid approach combining neuronal recordings and theoretical modelling. M2 project: The intern will work on the construction of predictive neuronal network models constrained by available experimental evidence both from the existing scientific literature and from the dataset collected by the project experimental partner. He/she will work exclusively at the interface between models and large-scale data analysis, without participating in animal handling. Depending on the student’s interests, the project can emphasize modelling or data analysis.