A key goal of computational neuroscience is to build mathematical models linking single-neuron activity to systems-level activity.
The guest has taken some bold steps in this direction by developing and exploring a multi-area model for the macaque visual cortex, and later also a model for the human cortex, using millions of simplified spiking neuron models.
We discuss the many design choices, the challenge of running the models, and what has been learned so far.
