Lecture
This lecture focuses on assembling the building blocks of in silico neuroscience networks, including ion channels, morphologies, single cell models, connections, and synapses. The process involves creating single cell models, defining space, and populating it with neurons. Different approaches like arbitrary volumes, atlas-based volumes, and simplified volumes are discussed, highlighting the challenges and advantages of each method. The lecture also covers the modeling of specific microcircuits, such as the Rat CA1 microcircuit and SSCX microcircuit. Various techniques for cell positioning, respecting neurite targeting, and dealing with sparse data are explored. The importance of assumptions, data sparseness, and strategies for reconstructing brain regions are emphasized.