Multivariate statistical analysis of Golgi stained neurons.
The multivariate statistical analysis provides a useful method to study neuronal populations. It allows both the objective classification of neuronal types and the study of the morphological variation within a neuronal population. We report a particular example of the use of these techniques on a Golgi study of a complex telencephalic structure, the reptilian anterior dorsal ventricular ridge (aDVR). We present a R-mode factor analysis and a cluster analysis on the results of the factor analysis. Sixteen original variables were chosen for the study in order to obtain the greatest information about the cell body, the dendritic field and the location of 96 Golgi-stained cells. Six factors were obtained after the R-mode factor analysis, the interpretation of which was clear in five of them. This contributed to explain the morphological variation of the neuronal types within the aDVR. The cluster analysis classified the 96 cells into eight groups. Some groups could be ascribed to specific regions of the aDVR.
Andreu
M J
MJ
Department of Cell Biology, University of Málaga, Spain.
Dávila
J C
JC
Real
M A
MA
Guirado
S
S
D000818:Animals; D001369:Axons / Q000648:ultrastructure; D002552:Cerebral Ventricles / Q000166:cytology / Q000648:ultrastructure*; D016000:Cluster Analysis; D004396:Coloring Agents; D003712:Dendrites / Q000648:ultrastructure; D005260:Female; D008116:Lizards / Q000033:anatomy & histology*; D008297:Male; D015999:Multivariate Analysis; D009474:Neurons / Q000648:ultrastructure*
D004396:Coloring Agents