Brain Cytoarchitecture

Brain cytoarchitecture research focuses on mapping the detailed three-dimensional organization of cells within brain regions, aiming to understand the relationship between brain structure and function. Current efforts leverage deep learning, employing U-Net-like architectures and graph convolutional networks, to automatically segment and classify individual cells in histological images, often using Nissl staining. These advanced computational methods address challenges like image artifacts and the need for extensive manual annotation, enabling more efficient and accurate analysis of cell distributions and morphologies across species and brain regions. This improved understanding of cytoarchitecture has significant implications for comparative neuroanatomy, advancing our knowledge of brain development, evolution, and disease.