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ABSTRACT: Dentate nucleus (nucleus dentatus) is the most distant of the cerebellar nuclei and the major system for information transfer in the cerebellum. So far, dendritic branches of four different kinds of large neurons of dentate nucleus, have been considered mainly qualitatively with no quantification of their morphological features. The aim of the study was to test the qualitative hypothesis that the human dentate nucleus is composed of various types of the large neurons by quantitative analysis of their dendritic branching patterns.
Series of horizontal sections of the dentate nuclei were taken from 15 adult human brains, free of diagnosed neurological disorders. The 189 Golgi-impregnated images of large neurons were recorded by a digital camera connected to a light microscope. Dendritic branching patterns of digitized neuronal images were analyzed by modified Sholl and fractal analyses.
The number of intersections (N(m)), critical radius (r(c)) and fractal dimension (D) of dendritic branching pattern for four types of the large neurons were calculated, statistically evaluated and analyzed. The results show that there is a significant difference between four neuronal types in one morphometric parameter at least.
The present study is the first attempt to analyze quantitatively the dendritic branching pattern of neurons from the dentate nucleus in the human. The hypothesis that the four types of the large neurons exist in this part of human cerebellum is successfully supported.
Vojnosanitetski pregled. Military-medical and pharmaceutical review 09/2010; 67(9):712-6. · 0.18 Impact Factor
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ABSTRACT: The dentate nucleus represents the most lateral of the four cerebellar nuclei that serve as a major relay centres for fibres coming from the cerebellar cortex. Although many relevant findings regarding to the three-dimensional structure, the neuronal morphology and the cytoarchitectural development of the dentate nucleus have been presented so far, very little quantitative information has been collected to further explain several types of large neurons in the dentate nucleus. In this study we quantified the morphology of the large dentate neurons in the adult human taking, into account seven morphometric parameters that describe the main properties of the cell soma, the dendritic field and the dendritic branching pattern. Since the lateral cerebellar nucleus in the cat and other lower mammals is homologous to the dentate nucleus in primates and man, we have classified our sample of large neurons in accordance with the shape of the cell body, the dendritic arborization and their location within the dentate nucleus. By performing the appropriate statistical analysis, we have proved that our sample of human dentate neurons can be classified into four distinct types. In that sense, our quantitative analysis verifies the validity of previous qualitative conclusions concerning the large neurons in the developing human dentate nucleus. Furthermore, the present study represents the first attempt to perform a quantitative analysis and cell classification of the large projection neurons in the adult human dentate nucleus.
Neuroscience Letters 10/2009; 468(1):59-63. · 2.11 Impact Factor
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ABSTRACT: The measurement of the area of a shapeless plane region is one of the basic problems in traditional calculus. In order to calculate the 'true' area of such a region, we have superimposed a net of identical squares on this region, counted the squares containing at least one point of the region, and calculated the sum of the areas of said squares. This sum represents an approximation of the region's area. By mathematical modelling and computational techniques we have investigated the law governing the decrease of these areas with the decrease of the length of the square's side. In theory, the prediction of the 'true' area could then be performed if the side of the net's squares tend to zero. Of course, the accuracy of the calculated area strongly depends on the computational potential and the statistical possibilities. Several morphometric parameters are currently in use for the quantitative analysis of the morphology of neuronal cell images. The cell image area has not yet been used and evaluated as a classification parameter - but it has the potential to be chosen over some other alternatives due to the high mathematical accuracy at which it is defined. By adopting mathematical modelling and computational techniques we show that this parameter can lead to successful distinction between 2 types of morphologically very similar cells (large boundary neuron and large asymmetrical neuron) in the dentate nucleus of the rhesus monkey (Macaca mulatta), while some other parameters failed to achieve positive results.
Journal of neuroscience methods 07/2009; 182(2):272-8. · 2.30 Impact Factor
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ABSTRACT: Type I retinal ganglion cells in the rat have been classified into several groups based on the cell body size and dendritic morphology. Considerable overlap and heterogeneity within groups have been reported, which is especially obvious for the morphology of the dendritic tree. For that purpose, we analysed quantitatively the dendritic morphology of the alpha and delta rat retinal ganglion cells, using parameters which provide information on the dendritic field size, shape of the dendritic tree and dendritic branching complexity. We show that the alpha and delta cells have significantly different dendritic field sizes. Taking into account the level of stratification of the dendritic tree, we found a difference in the properties of the dendritic morphology between alpha inner and alpha outer cells, while the opposite result was obtained for the delta inner and delta outer delta cells. In this study we also call attention to the relationship between morphological parameters and retinal eccentricity. The significance of our quantitative results in terms of present alpha and delta rat retinal ganglion cell classification is discussed.
Journal of Theoretical Biology 04/2009; 259(1):142-50. · 2.21 Impact Factor
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ABSTRACT: The deep nuclei of the cerebellar cortex have not yet received adequate exploratory attention. An exception is represented by the pioneering work of Chan-Palay, published in 1977, on the dentate nucleus morphology. She has classified each individual cell in the dentatus of the monkey into one of six types. Although fractal analysis is presently the most prominent quantitative method for morphometric neuronal studies, no article referring to applications of this method to the analysis of cell types of the dentate nucleus has so far been published. In the present study we apply fractal analysis to this unsolved problem and calculate the fractal dimension for each dendritic arbour of a neuron. We will hereby prove that by application of fractal analysis to the dendritic arbours of these cells whilst ignoring other neuronal attributes allows for clear discrimination of only three cell types.
Neuroscience Letters 10/2007; 425(1):23-7. · 2.11 Impact Factor
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ABSTRACT: Images of Golgi-impregnated neurons from laminae I to VI in the dorsal horn of the cat spinal cord were subjected to the linear Sholl analysis of concentric circles to support Rexed's hypothesis on the laminar organization of spinal gray matter in mammals. Since Rexed's determination of the laminae is based upon size, location, and grouping of cell bodies, neglecting one of the principal morphologic attributes of the neuron-the dendritic tree, the purpose of the present study was to evaluate Rexed's hypothesis testing the structure of dendritic arborization patterns of neurons. The differences in the complexity of dendritic trees between the groups of neurons from different laminae were evaluated by nonparametric statistics. Data obtained using Sholl's method is not always subjected to complete statistical analysis. The problem becomes particularly apparent in the quantitative examination of dendritic structures. Our aim was also to perform a careful analysis of our data for normality, in order to choose the appropriate statistical method for data processing. In the linear Sholl analysis, it is important to properly represent and interpret the frequency functions. The objective of this study was also to investigate the problems of determining the frequency functions, plotting the corresponding lines of regression, and measuring the degree of fluctuation of experimental data points around these lines. The main result of our testing is a confirmation of Rexed's laminar scheme: we have proved that there are 6 out of 10 possible pairs of samples where one member significantly differs from the other, i.e. one lamina is significantly distinguishable from the other.
Neuroscience Letters 04/2007; 414(3):286-90. · 2.11 Impact Factor
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ABSTRACT: Although the Sholl analysis is a quantitative method for morphometric neuronal studies and its application provides many benefits to neurobiology since it is obvious, common and meaningful, there are many unresolved theoretical issues that need to be addressed. Nevertheless, it can be practiced without much background or sophistication. The two different methods of the Sholl analysis--log-log and semi-log--have been applied previously without a clear basis as to what to use. To make an adequate choice of the method, one should try and accept that one which gives a better result. We consider that some of the underlying principles, assumptions and limitations for the Sholl analysis can be found in basic mathematics. In order to compare the results of applications of the semi-log and log-log methods to the same neuron, we introduce the concept of determination ratio as the ratio of the coefficient of determination for the semi-log method and that for the log-log method. If the semi-log method is better as related to the log-log method, the value of this parameter is larger than 1. Having in mind that dendrites exhibit enormously diverse forms, we point out that the semi-log Sholl method is more frequently utilizable in practice. Only the neurons, whose dendritic trees have one or a few sparsely ramified dendrites being much longer than the rest ones, could be successfully and exactly analysed using the log-log method. We also compare the Sholl analysis with fractal analysis for the characterization of neuronal arborization patterns and found that between the Sholl and fractal analysis exist various and important analogies.
Journal of Theoretical Biology 04/2007; 245(1):130-40. · 2.21 Impact Factor
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ABSTRACT: The drawings of Golgi-impregnated neurons from laminae I to VI in dorsal horn of the cat spinal cord were analysed morphometrically with a modified Sholl method of concentric circles. In order to advance the Sholl analysis of neuronal dendritic arborization patterns, we developed a new method of data presentation using polynomial regression and defining three parameters: the critical value of the circle radius (which defines the place of a possible circle intersecting maximum number of dendrites), the maximum number of dendritic intersections with the circles (counted for consecutive circles placed starting at the cell body to the border of the dendritic tree), and the mean value of the fitted polynomial function (which describes an average property concerning numbers of branches of dendritic tree over the whole region occupied by the dendritic arbor). For that purpose we also used the Sholl regression coefficient as well as the Schoenen ramification index. As an illustration of our model, we demonstrate that proposed modification of the Sholl method can successfully discriminate neuronal populations among different laminae of the cat spinal cord.
Journal of Neuroscience Methods 01/2007; 158(2):212-8. · 1.98 Impact Factor
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ABSTRACT: Skeletonized images of Golgi impregnated neurons from the human, monkey, cat and rat dorsal horns were subjected to fractal analysis. These neurons have sparse branching of dendrite arbors. It is noticed that, in certain neuronal samples, some authors report that scaling range of experimentally declared fractals is extremely limited and spanned approximately between 0.5 and 2.0 decades. In order to retain our hypothesis that neurons with dendrites of uncomplicated shapes can be considered fractal over three decades of scale, we conducted four procedures: (i) we used the box-counting method, (ii) we scaled the box sizes as a power of 2, (iii) we chose the coefficient of correlation, measuring the "goodness of fit" of experimental data points to regression straight line, to be equal to or larger than 0.995, and (iv) we pointed out that all the neurons analyzed have a single fractal dimension measuring a global fractality showing no linear regions. As a control, we used some cerebellar Purkinje cells whose dendrite trees show much more complex structure and profuseness of branching. Since, generally, the neuronal structure is among the most complex of all cellular morphologies, we believe that supporting this hypothesis we advance the neuroscience and fractal theory.
Neuroscience Letters 05/2006; 396(3):172-6. · 2.11 Impact Factor
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ABSTRACT: Images of Golgi impregnated neurons from different laminae of the human and rat dorsal horns were subjected to a quantitative analysis to support the Rexed's laminar scheme in mammals. Four methods of fractal analysis were performed in the proceedings: box-counting, mass-radius, cumulative intersection, and vectorized intersection. The results show that the box-counting method is more precise than the other fractal methods performed, and offers support for the conclusion that fractal analysis can successfully discriminate the neuron populations among different laminae. The analysis supports the concept of Rexed's cytoarchitectonic lamination of the dorsal horn.
Journal of Neuroscience Methods 09/2005; 146(2):198-204. · 1.98 Impact Factor
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ABSTRACT: The main goal of morphometric analysis of neuronal images, except for getting information about their geometry and dendritic branching patterns, is their classification based on laminar organization. The majority of contemporary techniques for image analysis are based on the application of fractal theory, which has some limitations on results analysis. For that reasons, the new, mostly nonfractal techniques for image analysis had been designed in the past few years. This study shows the analysis of morphometry of the human spinal cord neurons from the marginal (lamina I) and substantia gelatinosa (laminae I-II). For the analysis of neuron images two techniques of morphometric analysis were used: box-counting method as a mainly used technique for fractal analysis, and circle-counting method as a newly designed technique for measuring the length of dendrites. The use of these methods for neurons of the mentioned regions of human spinal cord showed that circle-counting method had given more accurate results than fractal analysis method. When the proposed method was used for the analysis of neuronal images, it was possible to classify neurons according to their laminar position.
Vojnosanitetski pregled. Military-medical and pharmaceutical review 03/2005; 62(2):125-31. · 0.18 Impact Factor
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Vojnosanitetski pregled. Military-medical and pharmaceutical review 60(4):479-85. · 0.18 Impact Factor
