Brain Networks in Learning

The primary visual cortex of the mouse is an ideal model system in which we can study network restructuring duringlearning, due to the well-described functional properties of its neurons, the existence of a robust learning paradigm, and the feasibility of recording large populations of neurons.

Here we aim to identify functional groupsof cortical neurons based on the robust estimation of their correlations and observe the topological re-structuring ofthe network they form.

We will build comprehensive Bayesian multi-level models that respect the multidimensionalstructure of the data for estimation and interpretation of our results. We hypothesize that we will observe major re-structuring of functional cortical sub-networks upon learning.