The overall goal of this project is to provide a framework for the complete and compact description of dendritic morphology. The central idea is to define algorithms that extract statistical measures from experimental microscopic reconstructions and use these distributions to stochastically generate virtual neurons. If the synthetic neurons ate statistically indistinguishable from the real counterparts, the algorithms and their parameters constitute ac acceptable and complete description. If the algorithmic parameters correspond to simple physical observables (e.g. branch diameter and length) the description is intuitively accessible and may provide insights as to the mechanistic and developmental processes that lead to mature dendritic morphology. The goal of this continuing research proposal is to add system-level and subcellular-level anatomical and biophysical components to the morphological description, and to expand, improve, and distribute the experimental data, models, and the simulation and analysis of software tools.
