Large neuroscience datasets have been produced that characterize the properties of individual neurons and their connections, and neural activity during behavior. Even with this wealth of data, mechanistic understanding of how function arises from the brain is still extremely limited. How do different brain areas work together to represent the world that is perceived? How are communications among different areas -- which depend on stimuli in the environment and the state of the observer -- implemented by a circuit which is fixed? This project will integrate vast datasets into a set of models which will be probed to address mechanistic questions involving multi-area interactions such as these. More specifically, a set of models which are similar in nature will be constructed. This set will start simple, but gradually simplifying assumptions about model parameters will be replaced by optimizations based on dynamical and functional data. The models will be used to test the hypotheses that: 1. The cell-type specific patterns of connectivity between areas are important in determining temporal responses to simple stimuli and observed frequency-specific inter-area interactions. 2. The functional specificity of inter-areal connections is important in determining the responses and inter-area communication in response to complex stimuli. 3. Variations in single-cell properties explain arousal-related changes in visual responses and oscillations. This project combines the unique exper