Mathematical and computational analyses of plastic spiking recurrent networks
The complex processing and behavioural capabilities of the brain are directly linked to the fact that neurons exhibit rich collective network dynamics. This dynamics emerges from the highly enmeshed and recurrent, yet structured, connectivity between neurons. Yet, it is poorly understood how the topology and connectivity of the network relate to the emerging dynamics. In this project, we will develop novel theoretical and computational approaches for neuroscience involving a tight interaction between state-of-the-art mathematical tools (graph theory, dynamical systems, stochastic processes, dimensionality reduction) in close connection with relevant data, models, and computer simulations of plastic neural networks.