Quantitative geometric three-dimensional reconstruction of neuronal architecture and mapping of labeled proteins from confocal image stacks

Abstract

Neuronal dendrites are amazingly complex structures which provide the scaffold for neuronal connectivity and information flow through circuits. On the one hand the projection area, surface, number, and density of branches determine which and how many other neurons can form synaptic connections with a neuron. On the other hand dendritic structure has profound effects on the computation of synaptic input. This chapter describes a tool kit to create three-dimensional geometric reconstructions of neuronal dendrites from confocal laser scanning image stacks. These tools allow for a comprehensive three-dimensional visualization of dendritic structure and provide quantitative measures of dendritic structure and branching topology which are readily available for statistical analysis. In addition, second and third channel image data can be mapped onto dendritic surface reconstructions to derive distribution estimates of putative synapses or other proteins in entire dendritic trees. These geometric dendrite reconstructions and protein localizations can be exported as multi-compartment models to the NEURON modeling environment such that structure-function relationships can be explored computationally and hypothesis formed for further experimental validation. © 2014 Springer Science+Business Media New York.