Laureline Logiaco

Postdoctoral Researcher

I am generally interested in investigating how the interactions between neurons organized in a network can shape useful dynamics or activity patterns for downstream targets, or allow memory storage. These phenomena are key for our understanding of the mechanisms by which the brain gives rise to animals' adapted behaviors. In order to investigate these questions, I use techniques ranging from model-guided statistical analysis of neuronal data to the mathematical analysis of the dynamics of neuronal networks. So far, my main projects have been revolving around testing different memory and decision making models for cognitive control, and developing theories for the mechanisms of motor pattern generation in the basal ganglia-thalamus-cortical loop. From the theory side, these projects involved moving between different levels of abstraction, from a mean-field theory in a population of heterogeneous non-linear spiking adapting neurons to the analysis of high-dimensional dynamics in simpler rate networks.