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Alexander Radbruch - One of the best experts on this subject based on the ideXlab platform.

Nebojsa T Milosevic - One of the best experts on this subject based on the ideXlab platform.

  • classification of adult human Dentate Nucleus border neurons artificial neural networks and multidimensional approach
    Journal of Theoretical Biology, 2016
    Co-Authors: Ivan Grbatinic, Nebojsa T Milosevic
    Abstract:

    Abstract Aims Primary aim in this study is to investigate whether external and internal border neurons of adult human Dentate Nucleus express the same neuromorphological features or belong to a different morphological types i.e. whether can be classified not only by way of their topology as external and internal, but also based on their morphological features or in addition to their topology also by way of their morphology. Secondary aim is to determine and compare various methodologies in order to perform the first aim in a more accurate and efficient manner. Material and Methods Blocks of tissue were cut out from the adult human cerebellum and stained according to the Kopsch-Bubenaite method. Border neurons of the Dentate Nucleus were investigated and digitized under the light microscope and processed thereafter. Seventeen parameters quantifying various aspects of neuron morphology are then measured. They can be categorized as shape, magnitude, complexity, length and branching parameters. Analyzes used are neural networks, separate unifactor, cluster, principal component, discriminant and correlation–comparison analysis. Results The external and internal border neurons differ significantly in six of the seventeen parameters investigated, mainly concerning dendritic ramification patterns, overall shape of dendritic tree and dendritic length. All six methodological approaches are in accordance showing slight clustering of data. Classification is based on six parameters: neuron (field) area, dendritic (field) area, total dendrite length, and position of maximal dendritic arborization density. Cluster analysis shows two data clusters. Separate unifactor analysis demonstrates inter–cluster differences with statistical significance (p Conclusion Border neurons from adult human Dentate Nucleus can be divided to external and internal according to its topology and based on neuromorphological computational parameters. This has potentially significant neurofunctional implications but further studies are needed to elucidate that. Multimethodological approach is shown as the best for finding the solution closest to reality. The possible functional meaning of these morphological differences for cerebellar network structure and function are discussed.

  • neurons from the adult human Dentate Nucleus neural networks in the neuron classification
    Journal of Theoretical Biology, 2015
    Co-Authors: Ivan Grbatinic, Dusica L Maric, Nebojsa T Milosevic
    Abstract:

    Abstract Objectives Topological (central vs. border neuron type) and morphological classification of adult human Dentate Nucleus neurons according to their quantified histomorphological properties using neural networks on real and virtual neuron samples. Results In the real sample 53.1% and 14.1% of central and border neurons, respectively, are classified correctly with total of 32.8% of misclassified neurons. The most important result present 62.2% of misclassified neurons in border neurons group which is even greater than number of correctly classified neurons (37.8%) in that group, showing obvious failure of network to classify neurons correctly based on computational parameters used in our study. On the virtual sample 97.3% of misclassified neurons in border neurons group which is much greater than number of correctly classified neurons (2.7%) in that group, again confirms obvious failure of network to classify neurons correctly. Statistical analysis shows that there is no statistically significant difference in between central and border neurons for each measured parameter (p>0.05). Total of 96.74% neurons are morphologically classified correctly by neural networks and each one belongs to one of the four histomorphological types: (a) neurons with small soma and short dendrites, (b) neurons with small soma and long dendrites, (c) neuron with large soma and short dendrites, (d) neurons with large soma and long dendrites. Statistical analysis supports these results (p Conclusion Human Dentate Nucleus neurons can be classified in four neuron types according to their quantitative histomorphological properties. These neuron types consist of two neuron sets, small and large ones with respect to their perykarions with subtypes differing in dendrite length i.e. neurons with short vs. long dendrites. Besides confirmation of neuron classification on small and large ones, already shown in literature, we found two new subtypes i.e. neurons with small soma and long dendrites and with large soma and short dendrites. These neurons are most probably equally distributed throughout the Dentate Nucleus as no significant difference in their topological distribution is observed.

  • mathematical model of neuronal morphology prenatal development of the human Dentate Nucleus
    BioMed Research International, 2014
    Co-Authors: Katarina Rajkovic, Dusan Ristanovic, Goran Bacic, Nebojsa T Milosevic
    Abstract:

    The aim of the study was to quantify the morphological changes of the human Dentate Nucleus during prenatal development using mathematical models that take into account main morphometric parameters. The camera lucida drawings of Golgi impregnated neurons taken from human fetuses of gestational ages ranging from 14 to 41 weeks were analyzed. Four morphometric parameters, the size of the neuron, the dendritic complexity, maximum dendritic density, and the position of maximum density, were obtained using the modified Scholl method and fractal analysis. Their increase during the entire prenatal development can be adequately fitted with a simple exponential. The three parameters describing the evolution of branching complexity of the dendritic arbor positively correlated with the increase of the size of neurons, but with different rate constants, showing that the complex development of the dendritic arbor is complete during the prenatal period. The findings of the present study are in accordance with previous crude qualitative data on prenatal development of the human Dentate Nucleus, but provide much greater amount of fine details. The mathematical model developed here provides a sound foundation enabling further studies on natal development or analyzing neurological disorders during prenatal development.

  • morphology and classification of large neurons in the adult human Dentate Nucleus a qualitative and quantitative analysis of 2d images
    Neuroscience Research, 2010
    Co-Authors: Dusan Ristanovic, Nebojsa T Milosevic, Dusica L Maric, Bratislav D Stefanovic, Katarina Rajkovic
    Abstract:

    The Dentate Nucleus represents the most lateral of the four cerebellar nuclei that serve as major relay centres for fibres coming from the cerebellar cortex. Although many relevant findings regarding to the structure, neuronal morphology and cytoarchitectural development of the Dentate Nucleus have been presented so far, very little quantitative information has been collected on the types of large neurons in the human Dentate Nucleus. In the present study we qualitatively analyze our sample of large neurons according to their morphology and topology, and classify these cells into four types. Then, we quantify the morphology of such cell types taking into account seven morphometric parameters which describe the main properties of the cell soma, dendritic field and dendrite arborization. By performing appropriate statistics we prove out our classification of the large Dentate neurons in the adult human. To the best of our knowledge, this study represents the first attempt of quantitative analysis of morphology and classification of the large neurons in the adult human Dentate Nucleus.

  • morphology and cell classification of large neurons in the adult human Dentate Nucleus a quantitative study
    Neuroscience Letters, 2010
    Co-Authors: Nebojsa T Milosevic, Dusan Ristanovic, Dusica L Maric, Katarina Rajkovic
    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 arborisation 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.

Katarina Rajkovic - One of the best experts on this subject based on the ideXlab platform.

  • mathematical model of neuronal morphology prenatal development of the human Dentate Nucleus
    BioMed Research International, 2014
    Co-Authors: Katarina Rajkovic, Dusan Ristanovic, Goran Bacic, Nebojsa T Milosevic
    Abstract:

    The aim of the study was to quantify the morphological changes of the human Dentate Nucleus during prenatal development using mathematical models that take into account main morphometric parameters. The camera lucida drawings of Golgi impregnated neurons taken from human fetuses of gestational ages ranging from 14 to 41 weeks were analyzed. Four morphometric parameters, the size of the neuron, the dendritic complexity, maximum dendritic density, and the position of maximum density, were obtained using the modified Scholl method and fractal analysis. Their increase during the entire prenatal development can be adequately fitted with a simple exponential. The three parameters describing the evolution of branching complexity of the dendritic arbor positively correlated with the increase of the size of neurons, but with different rate constants, showing that the complex development of the dendritic arbor is complete during the prenatal period. The findings of the present study are in accordance with previous crude qualitative data on prenatal development of the human Dentate Nucleus, but provide much greater amount of fine details. The mathematical model developed here provides a sound foundation enabling further studies on natal development or analyzing neurological disorders during prenatal development.

  • Neurons of the Human Dentate Nucleus: Box-Count Method in the Quantitative Analysis of Cell Morphology
    2013 19th International Conference on Control Systems and Computer Science, 2013
    Co-Authors: Dusica L Maric, Neboja T. Miloevic, Herbert F. Jelinek, Katarina Rajkovic
    Abstract:

    The morphology of neurons from the human Dentate Nucleus was analyzed estimating the size and shape of the dendritic field, shape of the neuron, space-filling property and the degree of dendrite aberrations. Among them, the last three morphological properties were investigated using the most popular technique of fractal analysis: the box-count method. The box dimensions of binary images and dendritic field area were statistically investigated in order to test whether the binary box dimension can quantify the size of the neuron. The same analysis was carried out using the box dimension of outline images and image circularity. The parameters, presented in this study have proved to be a useful means for quantifying the morphology of Dentate neurons as they provide a robust means of differentiating between neuron subtypes in the Dentate Nucleus. The findings of the present study are in accordance with previous qualitative data.

  • morphology and classification of large neurons in the adult human Dentate Nucleus a qualitative and quantitative analysis of 2d images
    Neuroscience Research, 2010
    Co-Authors: Dusan Ristanovic, Nebojsa T Milosevic, Dusica L Maric, Bratislav D Stefanovic, Katarina Rajkovic
    Abstract:

    The Dentate Nucleus represents the most lateral of the four cerebellar nuclei that serve as major relay centres for fibres coming from the cerebellar cortex. Although many relevant findings regarding to the structure, neuronal morphology and cytoarchitectural development of the Dentate Nucleus have been presented so far, very little quantitative information has been collected on the types of large neurons in the human Dentate Nucleus. In the present study we qualitatively analyze our sample of large neurons according to their morphology and topology, and classify these cells into four types. Then, we quantify the morphology of such cell types taking into account seven morphometric parameters which describe the main properties of the cell soma, dendritic field and dendrite arborization. By performing appropriate statistics we prove out our classification of the large Dentate neurons in the adult human. To the best of our knowledge, this study represents the first attempt of quantitative analysis of morphology and classification of the large neurons in the adult human Dentate Nucleus.

  • morphology and cell classification of large neurons in the adult human Dentate Nucleus a quantitative study
    Neuroscience Letters, 2010
    Co-Authors: Nebojsa T Milosevic, Dusan Ristanovic, Dusica L Maric, Katarina Rajkovic
    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 arborisation 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.

  • application of fractal analysis to neuronal dendritic arborisation patterns of the monkey Dentate Nucleus
    Neuroscience Letters, 2007
    Co-Authors: Nebojsa T Milosevic, Dusan Ristanovic, Katarina Rajkovic, Radmila Gudovic, Dusica L Maric
    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.

Ulrike Dydak - One of the best experts on this subject based on the ideXlab platform.

  • in vivo Dentate Nucleus gamma aminobutyric acid concentration in essential tremor vs controls
    The Cerebellum, 2018
    Co-Authors: Elan D Louis, Nora Hernandez, Jonathan P Dyke, Ruoyun E, Ulrike Dydak
    Abstract:

    Despite its high prevalence, essential tremor (ET) is among the most poorly understood neurological diseases. The presence and extent of Purkinje cell (PC) loss in ET is the subject of controversy. PCs are a major storehouse of central nervous system gamma-aminobutyric acid (GABA), releasing GABA at the level of the Dentate Nucleus. It is therefore conceivable that cerebellar Dentate Nucleus GABA concentration could be an in vivo marker of PC number. We used in vivo 1H magnetic resonance spectroscopy (MRS) to quantify GABA concentrations in two cerebellar volumes of interest, left and right, which included the Dentate Nucleus, comparing 45 ET cases to 35 age-matched controls. 1H MRS was performed using a 3.0-T Siemens Tim Trio scanner. The MEGA-PRESS J-editing sequence was used for GABA detection in two cerebellar volumes of interest (left and right) that included the Dentate Nucleus. The two groups did not differ with respect to our primary outcome of GABA concentration (given in institutional units). For the right Dentate Nucleus, [GABA] in ET cases = 2.01 ± 0.45 and [GABA] in controls = 1.86 ± 0.53, p = 0.17. For the left Dentate Nucleus, [GABA] in ET cases = 1.68 ± 0.49 and [GABA] controls = 1.80 ± 0.53, p = 0.33. The controls had similar Dentate Nucleus [GABA] in the right vs. left Dentate Nucleus (p = 0.52); however, in ET cases, the value on the right was considerably higher than that on the left (p = 0.001). We did not detect a reduction in Dentate Nucleus GABA concentration in ET cases vs. controls. One interpretation of the finding is that it does not support the existence of PC loss in ET; however, an alternative interpretation is the observed pattern could be due to the effects of terminal sprouting in ET (i.e., collateral sprouting from surviving PCs making up for the loss of GABA-ergic terminals from PC degeneration). Further research is needed.

Dusica L Maric - One of the best experts on this subject based on the ideXlab platform.

  • neurons from the adult human Dentate Nucleus neural networks in the neuron classification
    Journal of Theoretical Biology, 2015
    Co-Authors: Ivan Grbatinic, Dusica L Maric, Nebojsa T Milosevic
    Abstract:

    Abstract Objectives Topological (central vs. border neuron type) and morphological classification of adult human Dentate Nucleus neurons according to their quantified histomorphological properties using neural networks on real and virtual neuron samples. Results In the real sample 53.1% and 14.1% of central and border neurons, respectively, are classified correctly with total of 32.8% of misclassified neurons. The most important result present 62.2% of misclassified neurons in border neurons group which is even greater than number of correctly classified neurons (37.8%) in that group, showing obvious failure of network to classify neurons correctly based on computational parameters used in our study. On the virtual sample 97.3% of misclassified neurons in border neurons group which is much greater than number of correctly classified neurons (2.7%) in that group, again confirms obvious failure of network to classify neurons correctly. Statistical analysis shows that there is no statistically significant difference in between central and border neurons for each measured parameter (p>0.05). Total of 96.74% neurons are morphologically classified correctly by neural networks and each one belongs to one of the four histomorphological types: (a) neurons with small soma and short dendrites, (b) neurons with small soma and long dendrites, (c) neuron with large soma and short dendrites, (d) neurons with large soma and long dendrites. Statistical analysis supports these results (p Conclusion Human Dentate Nucleus neurons can be classified in four neuron types according to their quantitative histomorphological properties. These neuron types consist of two neuron sets, small and large ones with respect to their perykarions with subtypes differing in dendrite length i.e. neurons with short vs. long dendrites. Besides confirmation of neuron classification on small and large ones, already shown in literature, we found two new subtypes i.e. neurons with small soma and long dendrites and with large soma and short dendrites. These neurons are most probably equally distributed throughout the Dentate Nucleus as no significant difference in their topological distribution is observed.

  • Neurons of the Human Dentate Nucleus: Box-Count Method in the Quantitative Analysis of Cell Morphology
    2013 19th International Conference on Control Systems and Computer Science, 2013
    Co-Authors: Dusica L Maric, Neboja T. Miloevic, Herbert F. Jelinek, Katarina Rajkovic
    Abstract:

    The morphology of neurons from the human Dentate Nucleus was analyzed estimating the size and shape of the dendritic field, shape of the neuron, space-filling property and the degree of dendrite aberrations. Among them, the last three morphological properties were investigated using the most popular technique of fractal analysis: the box-count method. The box dimensions of binary images and dendritic field area were statistically investigated in order to test whether the binary box dimension can quantify the size of the neuron. The same analysis was carried out using the box dimension of outline images and image circularity. The parameters, presented in this study have proved to be a useful means for quantifying the morphology of Dentate neurons as they provide a robust means of differentiating between neuron subtypes in the Dentate Nucleus. The findings of the present study are in accordance with previous qualitative data.

  • morphology and classification of large neurons in the adult human Dentate Nucleus a qualitative and quantitative analysis of 2d images
    Neuroscience Research, 2010
    Co-Authors: Dusan Ristanovic, Nebojsa T Milosevic, Dusica L Maric, Bratislav D Stefanovic, Katarina Rajkovic
    Abstract:

    The Dentate Nucleus represents the most lateral of the four cerebellar nuclei that serve as major relay centres for fibres coming from the cerebellar cortex. Although many relevant findings regarding to the structure, neuronal morphology and cytoarchitectural development of the Dentate Nucleus have been presented so far, very little quantitative information has been collected on the types of large neurons in the human Dentate Nucleus. In the present study we qualitatively analyze our sample of large neurons according to their morphology and topology, and classify these cells into four types. Then, we quantify the morphology of such cell types taking into account seven morphometric parameters which describe the main properties of the cell soma, dendritic field and dendrite arborization. By performing appropriate statistics we prove out our classification of the large Dentate neurons in the adult human. To the best of our knowledge, this study represents the first attempt of quantitative analysis of morphology and classification of the large neurons in the adult human Dentate Nucleus.

  • morphology and cell classification of large neurons in the adult human Dentate Nucleus a quantitative study
    Neuroscience Letters, 2010
    Co-Authors: Nebojsa T Milosevic, Dusan Ristanovic, Dusica L Maric, Katarina Rajkovic
    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 arborisation 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.

  • application of fractal analysis to neuronal dendritic arborisation patterns of the monkey Dentate Nucleus
    Neuroscience Letters, 2007
    Co-Authors: Nebojsa T Milosevic, Dusan Ristanovic, Katarina Rajkovic, Radmila Gudovic, Dusica L Maric
    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.