dr. F. Stella (Federico)

As a theoretical neuroscientist I have been studying the computational and mathematical properties of networks of interacting neurons and their ability to store and encode specific types of information. My research has focused on circuits implicated in the process of learning and in the management of memories over different temporal periods.
I combine statistical analysis of experimental datasets of different nature (behavioral, single-unit electrophysiological recordings, imaging) with mathematical modeling of neural networks at the system level. My approach to theoretical neuroscience aims at bringing together methods derived from statistical mechanics, the physics of many-body interacting systems, machine learning techniques and numerical simulations of large-scale network dynamics. I have a particular interest in collective phenomena and on population dynamics emerging from interactions across multiple spatial and temporal scales.
Currently my work can be organized in two main (and highly interrelated) areas of interest:
i) Study of the role of sleep and of offline reactivations in the processing of episodic memories and in memory consolidation. Role of cortico-hippocampal exchange of information and of spontaneous propagation of activity across distributed cortical networks in the formation of knowledge structures. Of particular interest is the analysis of the statistical properties of reactivated neural patterns.
ii) Study of spatial representations in the hippocampal area and neighbouring cortices (place- grid- and sea-direction cells), of their interactions and of their dependance on experience.
I am also involved in other projects related to application of machine learning to neuroscience and the development of brain-machine interfaces and closed-loop stimulation protocols. At the moment I am actively part of multiple collaborative networks, in the NL, France, Norway and Austria among the others.
My work has been supported by the MSCA and by the HBP.

• Natural Computing & Neurotechnology

• Neuronal Networks of Memory