Advertisement

Acta Biologica Hungarica

, Volume 53, Issue 1–2, pp 177–186 | Cite as

Branching-Pattern Analysis of the Dendritic Arborization in the Thalamic Nuclei of the Rat Brain

  • Cs. Szigeti
  • Z. Fülöp
  • K. GulyaEmail author
Article

Abstract

We investigated the dendritic patterns of rapid Golgi-impregnated, highly similar multipolar neurons from two functionally different thalamic regions of the rat brain: two dorsal nuclei (the nucleus laterodorsalis thalami, pars dorsomedialis and the nucleus laterodorsalis thalami, pars ventrolateralis), and two ventral nuclei (the nucleus ventrolateralis thalami and the nucleus ventromedialis thalami). The analysis involved conventional morphometric parameters (height and size) and a new parameter derived from graph theory, the relative imbalance (RI), derived from the branching patterns of the dendrites, which permits quantitative characterization of the dendritic arborization of a neuron. On this basis, neurons can be grouped into three fundamentally different types: type A, or highly-polarized (imbalanced) neurons (RI values close to 1); type B, or medium-polarized neurons (RI values around 0.5); and type C, or balanced neurons with low polarization (RI values close to 0). The orientations of the dendritic arbor, and thus the receptive fields, of the dorsal and ventral thalamic neurons, were mutually perpendicular. The H and S values indicated that the neurons in the dorsal and ventral thalamic nuclei differed significantly. However, their RI values demonstrated that they were similar neurons of type B. Our data reveal that 1) the dendritic arbor cannot be reliably characterized purely on the basis of height and size, and 2) RI is a valuable morphometric parameter that identifies the true nature of the dendritic arborization.

Keywords

Dendritic arborization Golgi impregnation morphometry rat relative imbalance thalamus 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cesar, R. M. Jr., Costa, L., da F. (1999) Computer-vision-based extraction of neural dendrograms. J. Neurosci. Meth. 93, 121–131.CrossRefGoogle Scholar
  2. 2.
    Grimaldi, R. P. (1994) Discrete and Combinatorial Mathematics. An Applied Introduction. Addison-Wesley Publ. Co.Google Scholar
  3. 3.
    Jones, E. G. (1985) The Thalamus. Plenum Press, New York.CrossRefGoogle Scholar
  4. 4.
    Knuth, D. E. (1988) The Art of Computer Programming. Vol. 1. Addison-Wesley Publ. Co.Google Scholar
  5. 5.
    Leontovich, T. A. (1975) Quantitative analysis and classification of subcortical forebrain neurons. In: Santini, M. (ed.), Golgi Centennial Symposium. Proceedings. Raven Press, New York, pp. 101–122.Google Scholar
  6. 6.
    Mainen, Z. F., Sejnowski, T. J. (1996) Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382, 363–366.CrossRefGoogle Scholar
  7. 7.
    Paxinos, G., Watson, C. (1986) The Rat Brain in Stereotaxic Coordinates. Academic Press, San Diego.Google Scholar
  8. 8.
    Percheron, G. (1979a) Quantitative analysis of dendritic branching. I. Simple formulae for the quantitative analysis of dendritic branching. Neurosci. Lett. 14, 287–293.CrossRefGoogle Scholar
  9. 9.
    Percheron, G. (1979b) Quantitative analysis of dendritic branching. II. Fundamental dendritic numbers as a tool for the study of neuronal groups. Neurosci. Lett. 14, 295–302.CrossRefGoogle Scholar
  10. 10.
    Price, J. L. (1995) Thalamus. In: Paxinos G. (ed.), The Rat Nervous System. 2nd ed. Academic Press, San Diego, pp. 629–648.Google Scholar
  11. 11.
    Ventimiglia, R., Jones, B. E., Moller, A. (1995) A quantitative method for morphometric analysis in neuronal cell culture: unbiased estimation of neuron area and number of branch points. J. Neurosci. Meth. 57, 63–66.CrossRefGoogle Scholar
  12. 12.
    Williams, R. S., Matthysse, S. (1983) Morphometric analysis of granule cell dendrites in the mouse dentate gyrus. J. Comp. Neurol. 215, 154–164.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest 2002

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of Zoology and Cell BiologyUniversity of SzegedSzegedHungary
  2. 2.Department of Computer ScienceUniversity of SzegedSzegedHungary

Personalised recommendations