  Cellular neural circuit and networks consisting of interconnected neurons and
glia are ulti- mately responsible for the information processing associated
with information processing in the brain. While there are major efforts aimed
at mapping the structural and (electro)physiological connectivity of brain
networks, such as the White House BRAIN Initiative aimed at the devel- opment
of neurotechnologies capable of high density neural recordings, theoretical and
compu- tational methods for analyzing and making sense of all this data seem to
be further behind. Here, we propose and provide a summary of an approach for
calculating effective connectivity from experimental observations of neuronal
network activity. The proposed method operates on network-level data, makes use
of all relevant prior knowledge, such as dynamical models of individual cells
in the network and the physical structural connectivity of the network, and is
broadly applicable to large classes of biological and non-biological networks.
