Abstract
Digital reconstruction of neuronal arborizations is an important step in the quantitative investigation of cellular neuroanatomy. In this process, neurites imaged by microscopy are semi-manually traced through the use of specialized computer software and represented as binary trees of branching cylinders (or truncated cones). Such form of the reconstruction files is efficient and parsimonious, and allows extensive morphometric analysis as well as the implementation of biophysical models of electrophysiology. Here, we describe Neuron_Morpho, a plugin for the popular Java application ImageJ that mediates the digital reconstruction of neurons from image stacks. Both the executable and code of Neuron_Morpho are freely distributed (www.maths.soton.ac.uk/staff/D’Alessandro/morpho or www.krasnow.gmu.edu/L-Neuron), and are compatible with all major computer platforms (including Windows, Mac, and Linux). We tested Neuron_Morpho by reconstructing two neurons from each of the two preparations representing different brain areas (hippocampus and cerebellum), neuritic type (pyramidal cell dendrites and olivar axonal projection terminals), and labeling method (rapid Golgi impregnation and anterograde dextran amine), and quantitatively comparing the resulting morphologies to those of the same cells reconstructed with the standard commercial system, Neurolucida. None of the numerous morphometric measures that were analyzed displayed any significant or systematic difference between the two reconstructing systems.
Similar content being viewed by others
References
Ascoli, G. A., Krichmar, J. L., Nasuto, S. J., and Senft, S. L. (2001) Generation, description and storage of dendritic morphology data. Philos. Trans. R. Soc. Lond. B Biol. Sci. 356 (1412), 1131–1145.
Bailer, W. (2003) Writing ImageJ Plugins-A Tutorial, Upper Austria University of Applied Sciences, Department of Media Technology and Design, Hagenberg, Austria. http://mtd.fh-hagenberg.at/depot/imaging/imagej.
Bower, J. M. and Beeman, D. (1998) The book of GENESIS: exploring realistic neural models with the GEneral NEural SImulation System, 2nd ed., Springer-Verlag, New York.
Cannon, R. C., Turner, D. A., Pyapali, G. K., and Wheal, H. V. (1998) An on-line archive of reconstructed hippocampal neurons. J. Neurosci. Methods 84 (1–2), 49–54.
Capowski, J. J. (1985) Computer techniques in neuroanatomy, Plenum, New York.
Cathala, L., Brickley, S., Cull-Candy, S., and Farrant, M. (2003) Maturation of EPSCs and intrinsic membrane properties enhances precision at a cerebellar synapse. J. Neurosci. 23 (14), 6074–6085.
Davison, A. P., Morse, T. M., Migliore, M., Shepherd, G. M., and Hines, M. L. (2004) Semi-automated population of an online database of neuronal models (ModelDB) with citation information, using PubMed for validation. Neuroinformatics 2 (3), 327–332.
Desmond, N. L., Heydenreich, M. S., and Levy, W. B. (1990) Quantitative characterization of the hippocampal CA1 pyramidal cell dendritic field in stratum moleculare. Anat. Rec. 226, 26A.
Desmond, N. L. and Levy, W. B. (1982) A quantitative anatomical study of the granule cell dendritic fields of the rat dentate gyrus using a novel probabilistic method. J. Comp. Neurol. 212 (2), 131–145.
Duan, H., Wearne, S. L., Morrison, J. H., and Hof, P. R. (2002) Quantitative analysis of the dendritic morphology of corticocortical projection neurons in the macaque monkey association cortex. Neuroscience 114 (2), 349–359.
Glaser, J. R. and Glaser, E. M. (1990) Neuron imaging with Neurolucida-a PC-based system for image combining microscopy. Comput. Med. Imaging Graph. 14 (5), 307–317.
Gulyas, A. I., Megias, M., Emri, Z., and Freund, T. F. (1999) Total number and ratio of excitatory and inhibitory synapses converging onto single interneurons of different types in the CA1 area of the rat hippocampus. J. Neurosci. 19 (22), 10,082–10,097.
He, W., Hamilton, T. A., Cohen, A. R., et al. (2003) Automated three-dimensional tracing of neurons in confocal and brightfield images. Microsc. Microanal. 9 (4), 296–310.
Hines, M. L. and Carnevale, N. T. (2001) NEURON: a tool for neuroscientists. Neuroscientist 7 (2), 123–135.
Holmes, T. J., O’Connor, N. J. (2000) Blind deconvolution of 3D transmitted light brightfield micrographs. J. Microsc. 200 (Pt 2), 114–127.
Jaeger, D. (2001) Accurate reconstruction of neuronal morphology, in Computational neuroscience: realistic modeling for experimentalists, De Schutter, E., ed., Lewis Publishers, Boca Raton, FL, pp. 159–178.
Kaspirzhny, A. V., Gogan, P., Horcholle-Bossavit, G., and Tyc-Dumont, S. (2002) Neuronal morphology data bases: morphological noise and assessment of data quality. Network 13, 357–380.
Megias, M., Emri, Z., Freund, T. F., and Gulyas, A. I. (2001) Total number and distribution of inhibitory and excitatory synapses on hippocampal CA1 pyramidal cells. Neuroscience 102, 527–540.
Migliore, M., Morse, T. M., Davison, A. P., Marenco, L., Shepherd, G. M., and Hines, M. L. (2003) ModelDB: making models publicly accessible to support computational neuroscience. Neuroinformatics 1 (1), 135–139.
Niemeyer, P. and Knudsen, J. (2000) Learning Java, O’Reilly, Sebastopol, CA.
Rodriguez, A., Ehlenberger, D., Kelliher, K., et al. (2003) Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images. Methods 30 (1), 94–105.
Scorcioni, R. and Ascoli, G. A. (2001) Algorithmic extraction of morphological statistics from electronic archives of neuroanatomy. Lect. Notes Comput. Sci. 2084, 30–37.
Scorcioni, R., Lazarewicz, M. T., and Ascoli, G. A. (2004) Quantitative morphometry of hippocampal pyramidal cells: differences between anatomical classes and reconstructing laboratories. J. Comp. Neurol. 473 (2), 177–193.
Schmitt, S., Evers, J. F., Duch, C., Scholz, M., and Obermayer, K. (2004) New methods for the computer-assisted 3-D reconstruction of neurons from confocal image stacks. NeuroImage 23 (4), 1283–1298.
Sugihara, I., Wu, H., and Shinoda, Y. (1999) Morphology of single olivocerebellar axons labeled with biotinylated dextran amine in the rat. J. Comp. Neurol. 414 (2), 131–148.
Szilagyi, T. and De Schutter, E. (2004) Effects of variability in anatomical reconstruction techniques on models of synaptic integrationby dendrites: a comparison of three Internet archives. Eur. J. Neurosci. 19 (5), 1257–1266.
Turner, D. A., Cannon, R. C., and Ascoli, G. A. (2002) Web-based neuronal archives: neuronal morphometric and electrotonic analysis, in Neuroscience databases-a practical guide, Kotter, R., ed., Elsevier, Amsterdam, pp. 81–98.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Brown, K.M., Donohue, D.E., D’Alessandro, G. et al. A cross-platform freeware tool for digital reconstruction of neuronal arborizations from image stacks. Neuroinform 3, 343–359 (2005). https://doi.org/10.1385/NI:3:4:343
Issue Date:
DOI: https://doi.org/10.1385/NI:3:4:343