- BSc ThesisA Multidisciplinary Analysis of the Link between Structure and Function in Biological Neural NetworksMoalla, SkanderApr 2020
In recent applications of algebraic topology to explore and analyze digital reconstructions of neocortical microcircuitry developed at the Blue Brain Project, researchers have been able to quantify the structural complexity of a neural network and its activity. Those results suggest a correlation between the structural complexity and the functional complexity of a neural network. In this report, we first provide an overview of the multidisciplinary approach one has to adopt to study such a correlation. Incidentally, we build the simple framework of choice: an implementation of a simple yet very efficient neuron model using Brian — a user-friendly python simulator for spiking neurons. Then, we focus on the topological structures suspected to drive this correlation, namely, directed cliques of neurons and build a network where this correlation can be measured and analyzed using tools from information theory. In particular, we look at the evolution of mutual information between pairs of neurons within cliques and break this measure down using the partial information decomposition. The results of our analysis suggest that when subject to a stimulus, high dimensional cliques transform the information coming from the stimulus to generate new information reflecting their high degree of organization.