Neuronal morphology data bases: morphological noise and assesment of data quality.

For technical, instrumental and operator-related reasons, three-dimensional reconstructions of neurons obtained from intracellularly stained neuronal pieces scattered in serial sections are blurred by some morphological noise. This noise may strongly invalidate conclusions drawn from models built using the three-dimensional reconstructions and it must be taken into account when retrieving digitized neurons from available databases. We analyse the main generating sources of the noise and its consequences for the 'quality' of the data. We provide tools for detecting and evaluating the noise in any database providing sufficient information is given in the database. We propose a unified format for submitting data and a new neuron viewer/editor to analyse the digitized neurons with our tools.