• neuroscience
• complex systems
• nonlinear dynamics
• time series analysis
• nerual networks
• neural models
• calcium signals

My thesis is part of a larger multidisciplinary research project that aims to study the evolution of biological networks of in vitro neural cells and to investigate how it can be altered by the administration of certain drugs. This work was carried out in collaboration with the Bio@SNS laboratory and with the institute of biophysics of the CNR of Pisa and it can be summarized in two main activities:

1) The study of biological calcium signals using linear and non linear techniques. In this way we search for criteria and statistics discriminating different regimes of activity depending on the administered drugs. We focus on the study of the interaction between time series associated to different neurons (using for example correlation measures, mutual information and symbolic
transfer entropy) and on the complexity analysis of the single time series (using measures such as permutation entropy and global node entropy).

2) The use of nonlinear dynamics to study neural models looking for a compromise between biological fidelity and computational complexity. Then we let the single nerual models interact within a network connecting them with suitable synaptic models and diversifying between populations of pyramidal neurons and of interneurons. In this way we aim to reproduce experimental calcium signals and to match it with the electrophysiological activity.