The brain forms a large recurrent spiking neural network with extremely high connectivity making time-dependent mean-field approaches valuable tools to translate the microscopic level of single-neuron dynamics to the mesoscopic or macroscopic level. In recent years, experimental data as well as simulation studies have highlighted the importance of low-dimensional macroscopic dynamics in large recurrent spiking networks. On the theory side, the notion of low-rank connectivity has shifted into the focus of interest.
This one-week course runs in two phases:
Phase 1 (starts Monday November 2 at 13h30, ) is a worskhop over 2.5 days will to bring together researchers in mathematical and theoretical neuroscience who address the above topics from different perspectives.
Phase 2 are tutorial and discussions (Thursday and Friday)
The location is the Bernoulli Center EPFL.
The main course page is:
https://www.epfl.ch/labs/lcn/dynamics-in-brain-inspired-neural-networks-2-6-november-2026/
- Professor: Wulfram Gerstner
