What you see, think, and do is determined by the electrical activity of cells in your brain. These cells are called neurons. Some neurons have electrical activity that is externally determined by the environment, such as neurons in the eye that sense light. However, most neuronal activity is internally generated by neuron-to-neuron signals sent and received at anatomical communication sites called synapses. Understanding how the brain works therefore amounts to discovering how neuronal activity is generated by the brain’s immense number of synaptic connections. For decades neuroscientists have tried to do this using mathematical models called neural networks, but a lack of experimental data has left it unclear whether these models are accurate enough. This Multilateral Research Project combines mathematical modeling, neuronal activity measurements, and synapse-resolution neuroanatomy to build and test biologically realistic neural network models of visual functions. The project capitalizes on recent experimental breakthroughs to build testable models and benchmark a general theoretical framework for modeling the brain and making experimental predictions. It will produce advanced theoretical methods, better annotated datasets, and new experiments that will be freely shared with the scientific community and published in publicly accessible forms. The project heralds a new era of neural networks research, and the research team will help other scientists enter this exciting new f