Quantitative neuroanatomy and neuroinformatics.
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Biomedical subjects
Jaap van Pelt
Publications and source records attributed to Jaap van Pelt.
Branching rates and growth functions in the outgrowth of dendritic branching patterns.
The outgrowth of dendritic branching patterns proceeds by neurite elongation and branching. These actions are supported by growth cones, specialized dynamic structures at the tips of outgrowing neurites, in response to a multitude of intracellular and extracellular signals and mechanisms. Branching rates of growth cones and their temporal patterns thus reflect the extent and changes in these responses. The present study outlines a model framework to relate branching rates of individual growth cones with the growth rate of the entire dendritic tree. The branching rate of an individual growth cone is assumed to depend on the total number of growth cones at any given moment (representing competition between growth cones), on its position along the dendrite, and on a baseline component representing all other factors. Four different strategies are discussed for determining quantitatively these components from experimental data. The methods are applied in the analysis of dendritic trees of Wistar rat multipolar non-pyramidal neurons, quantitatively reconstructed at several developmental stages (Parnavelas J G and Uylings H B M 1980 Brain Res. 193 373-82, Uylings H B M, Parnavelas J G, Walg H and Veltman W A M 1980 Mikroskopie 37 220-4). It is shown that the baseline branching rate is a rapidly decreasing function of time, indicating the largest baseline drive for branching in the early days of outgrowth.
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The effect of dendritic topology on firing patterns in model neurons.
Neuronal firing patterns are influenced by both membrane properties and dendritic morphology. Distinguishing two sources of morphological variability-metrics and topology-we investigate the extent to which model neurons that have the same metrical and membrane properties can still produce different firing patterns as a result of differences in dendritic topology. Within a set of dendritic trees that have the same number of terminal segments and the same total dendritic length, we show that firing frequency strongly correlates with topology as expressed by the mean dendritic path length. The effect of dendritic topology on firing frequency is bigger for trees with equal segment diameters than for trees whose segment diameters obey Rall's 3/2 power law. If active dendritic channels are present, dendritic topology influences not only firing frequency but also type of firing (regular, bursting).
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A shape analysis framework for neuromorphometry.
This paper addresses in an integrated and systematic fashion the relatively overlooked but increasingly important issue of measuring and characterizing the geometrical properties of nerve cells and structures, an area often called neuromorphology. After discussing the main motivation for such an endeavour, a comprehensive mathematical framework for characterizing neural shapes, capable of expressing variations over time, is presented and used to underline the main issues in neuromorphology. Three particularly powerful and versatile families of neuromorphological approaches, including differential measures, symmetry axes/skeletons, and complexity, are presented and their respective potentials for applications in neuroscience are identified. Examples of applications of such measures are provided based on experimental investigations related to automated dendrogram extraction, mental retardation characterization, and axon growth analysis.
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Analysis of tubular structures in three-dimensional confocal images.
Knowledge about the relationship between morphology and the function of neurons is an important instrument in understanding the role that neurons play in information processing in the brain. In paricular, the diameter and length of segments in dendritic arborization are considered to be crucial morphological features. Consequently, accurate detection of morphological features such as centre line position and diameter is a prerequisite to establish this relationship. Accurate detection of neuron morphology from confocal microscope images is hampered by the low signal to noise ratio of the images and the properties of the microscope point spread function (PSF). The size and the anisotropy of the PSF causes feature detection to be biased and orientation dependent. We deal with these problems by utilizing Gaussian image derivatives for feature detection. Gaussian kernels provide for image derivative estimates with low noise sensitivity. Features of interest such as centre line positions and diameter in a tubular neuronal segment of a dendritic tree can be detected by calculating and subsequently utilizing Gaussian image derivatives. For diameter measurement the microscope PSF is incorporated into the derivative calculation. Results on real and simulated confocal images reveal that centre line position and diameter can be estimated accurately and are bias free even under realistic imaging conditions.
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Measures for quantifying dendritic arborizations.
Topological and metrical measures are reviewed, which describe whole dendritic trees and variables within trees. These measures are applied to differentiate and classify groups of neurons. They are also of importance for simulation or reconstruction of neuronal trees in view of functional computational characteristics.
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