A fast and accurate procedure for deriving the Sholl profile in quantitative studies of neuronal morphology.
The growth and elaboration of neural processes underpins the establishment of neural architecture during development and is a key facet of neural plasticity throughout life. Sholl analysis is a valuable and widely used method for quantifying the extent and complexity of neural processes in the vicinity of the neuronal soma, such as the dendritic arbors of individual neurons in vivo and neuritic arbors of individual neurons in vitro. It consists of tracing a series of concentric rings with regular radial increments centred in the neuronal soma and counting the number X(i) of processes intersecting each ring. This is a laborious and time-consuming procedure that consequently can only be applied to relatively small numbers of neurons. We propose a simpler and accurate method for deriving exactly the same information based only on the relative position, with respect to the cell soma, of the bifurcation (B(i)) and terminal points (T(i)) of processes. By means of the iterative equation X(i)=X(i-1)+B(i)-T(i,) it is possible to automatically reconstruct the complete pattern of intersections between neurites and the concentric rings. We compared our method with the conventional Sholl analysis and found that our simplified procedure is approximately five times faster permitting numerically larger samples to be analyzed. We further tested the sensitivity of our method of analysis by looking at the effect of preventing NF-kappaB signaling on BDNF-dependent neuritic growth in sensory neurons.
Gutierrez
Humberto
H
School of Biosciences, Cardiff University, Museum Avenue, P.O. Box 911, Cardiff CF10 3US, Wales, United Kingdom. gutierrezh@cf.ac.uk
Davies
Alun M
AM
D000818:Animals; D000831:Animals, Newborn; D048429:Cell Size; D002478:Cells, Cultured; D003627:Data Interpretation, Statistical; D003712:Dendrites / Q000502:physiology* / Q000648:ultrastructure; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology* / Q000502:physiology*; D009620:Nodose Ganglion / Q000166:cytology