<p>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. <br>
This meeting will to bring together researchers in mathematical and the