Analysis of complex spatio-temporal neural data.

When we build and simulate models of developing networks in mammalian brains, we see many kinds of complex behaviors. These behaviors correspond to the activities of large numbers of neurons spread across space and occurring along time. How can we develop an understanding of these patterns of activity and use that to understand neural behavior? How can we identify structured patterns — in space, in time, and varying in both — in and among enormous quantities of background activity that has no "meaning"? How can we visualize neural activity in space and time when the spatial density is huge and the lengths of time are enormous (relative to the time it takes a neuron to do something)? These are the kinds of questions we are trying to answer.