Reconstructing Brain Regions: Challenges and Strategies

This lecture delves into the complexities of constructing network models for brain regions, focusing on the challenges faced when using atlases to reconstruct brain volumes. The instructor explains the difficulties in aligning image stacks, annotating layers, and dealing with noisy data. The discussion also touches on the importance of defining criteria for delineating anatomical areas and the implications of genetic atlases. Strategies such as parameter optimization, cloning, and jittering are explored to compensate for missing data and assumptions. The lecture emphasizes the need to make explicit the assumptions underlying models and the iterative process of refining them based on new data. Overall, the lecture highlights the interdisciplinary nature of modeling brain regions and the importance of understanding the interdependencies between data sets.