Abstract

In the central nervous system, the dendritic tree of individual neurons normally extends beyond the borders of the nucleus or nucleus’ subdivision where its cell body locates. We refer to this as heterotopic dendritic distribution (Montero et al., Front Neural Circuits. 15:769342, 2021). This phenomenon has important implications for individual neurons afferent synaptic integration; insofar dendritic trees extending across different nuclei or subdivisions can receive differentiated input. A typical example of neurons exhibiting heterotopic dendrites is the substantia nigra pars compacta (SNc) neuron, whose dendritic domain can extend into the underlying substantia nigra pars reticulata (SNr). In this chapter, we describe three basic approaches to quantify dendritic extensions into adjacent nucleus using 3D reconstructions of previously labeled individual rodent SNc dopaminergic neurons. We used the software Neurolucida, which allows vector-based 3D reconstruction of both individual neurons and nuclei and offers various analytical tools. The first method involves the use of cyto- or chemo-architectonics to identify boundaries between subdivisions and marking, onto the dendrite being traced, the exact point where it crosses the border. The second method utilizes instead rendered 3D reconstructions of the relevant subdivisions (e.g., SNc or SNr) to identify dendritic border crossing, followed by computation of total dendritic length inside or outside the subdivision. We also propose a method based on MATLAB scripts to make the process of quantification more efficient. We finish discussing and listing the advantages and disadvantages of each approach.