A new connectivity toolbox to infer topological features of in-vitro neural networks

A detailed analysis of functional connectivity of in vitro neural networks, as well as the possibility to understand the interplay between topology, structure, function and dynamics, is very important for better understanding how the nervous system represents and stores the information. Thus, we developed an informatics toolbox to infer functional connectivity in in-vitro neuronal networks. To prove the validity of the software tool and to verify its performances, we used it to estimate topological metrics on mature hippocampal assemblies coupled to Micro-Electrode Arrays (MEAs).