Lab Meeting by Raul Palma

First, I will talk about the project I've done in the first part of my Ph.D.:  Since functions such as memory formation, attention, and learning seem to relate to the synchronization of neuronal networks, a better understanding of the conditions for synchronization in the brains is desirable. With this motivation in mind, we applied the Master Stability Function formalism to study the linear stability of synchronized states in networks of Izhikevich neurons.
In the second part of my seminar, I'll present the projects I'm involved with here at UPC, where I am working on recovering the connectivity of neuronal networks from the observed dynamics of neuronal activity. To do so, we use the Kalman filter technique, a well-established method used for data assimilation and parameter estimation in many fields of science and technology. We show that the KF can infer the parameters of the Izhikevich model, and the connectivity of neuronal network.