Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Pharmacology, Cellular and Molecular." Includes bibliographical references (p. 145-171).

Thesis (Ph. D.)--Florida State University, 2005. / Advisor: Dr. Chalres C. Ouimet, Florida State University, College of Arts and Sciences, Dept. of Psychology. Title and description from dissertation home page (viewed Sept. 19, 2005). Document formatted into pages; contains x, 83 pages. Includes bibliographical references.

Thèse (M.Sc.)--Université Laval, 2002. / Bibliogr.: f. [62]-78. Publié aussi en version électronique.

Its known that the age-related decline in cognitive facilities is not due to the loss of neurons but more subtle changes in specific areas of the brain. Structural and morphological changes in cellular alignment in the minicolumns correlate with increased prevalence of neurological diseases and in aging. In the rhesus monkey, cognitive decline is similar to what humans experience in aging. In the monkey prefrontal cortex, Brodmann area 46, an important region for executive functioning, cognitive decline correlates with changes in cellular alignment or “columnar strength” as studies by Cruz et al., (2009). Using the density maps method in Area 46, the ventral bank was identified to be the most susceptible to structural changes. Minicolumns, are defined by the cellular alignment of neurons in the cortex and some believe that the dendritic bundles of neurons in the cortex is also considered an integral part of the columns. The functional role of apical dendrites, is not well understood, however, given the that repeated organized bundles transverse through the laminae could be further support for their inclusion in minicolumns with possible functional importance. If structural changes such as loss of columnar strength (neuronal displacement) that correlates with cognitive aging, it is possible that the dendritic organization may also be affected in this area. In this thesis, it is hypothesized that the dendritic bundles in this area could also be related to the cognitive deficits associated with normal aging. Using double- fluorescence labeling for dendrites (MAP-2) and neurons (Neu-N), 3D confocal reconstructions of the dorsal and ventral banks of Area 46 were used to investigate structural/morphological changes in the dendritic bundles in young and old rhesus monkeys. While cortical thickness and apical dendritic length between both banks did not change, we found a significant increase in inter-bundle spacing at layer 6A in the older monkeys in the ventral bank. Inter-bundle spacing for bundles in layer 5 was measured and showed that the young consistently have smaller inter-bundle spacing. Future studies with larger sample size will also investigate whether changes in dendritic bundles and their organization also correlate with age-related cognitive deficits.

A neuron’s function depends critically on the shape, size, and territory of its dendritic field. We have only recently begun to understand how diverse dendritic arbors are built and how the morphology and territory of these arbors support diverse neural functions. In this thesis, I use the Drosophila larval peripheral nervous system (PNS) as a model for studying these questions, as these neurons are very amenable to genetic manipulation and in vivo imaging. First, I examined the relationship between dendritic fields and sensory activity in the proprioceptive neurons of the body wall. In collaboration with Elizabeth Hillman’s lab, we used a high-speed volumetric microscopy technique, Swept Confocally Aligned Planar Excitation (SCAPE) microscopy, to simultaneously image the dendrite deformation dynamics and sensory activity of body wall neurons in crawling Drosophila larvae. We imaged a set of proprioceptive neurons with diverse dendrite morphologies and territories, revealing that each neuron subtype responds in sequence during crawling. These activities could conceivably provide a continuum of position encoding during locomotion. Activity timing is related to the dynamics of each neuron’s dendritic arbors, suggesting arbor shape and targeting endow each proprioceptor with a specific role in monitoring body wall deformation. Furthermore, our results provide new insights into the body-wide activity dynamics of the proprioceptive system, which will inform models of sensory feedback during locomotion. To investigate how dendritic arbors are built to support sensory function, I focused on proprioceptive (class I) and touch-sensing (class II-III) dendritic arborization (da) neurons. Proprioceptive and touch-sensing dendrite territories tend to target non-overlapping, neighboring, areas of the body wall. How is territory coverage specified during development, and how does this coverage support a specific sensory function? Ablation studies indicate that repulsive interactions between heterotypic dendrites are not required for territory patterning. Instead, dendrite boundaries correlate with Anterior (A)-Posterior (P) compartment boundaries in the underlying epidermal substrate: proprioceptive class I dendrites target the P compartment, while touch-sensing dendrites tend to avoid that region. I found that genetic expansion of the P compartment leads to expansion of class I proprioceptive dendrites, suggesting compartmentalized epidermal cues instruct dendrite targeting. Furthermore, SCAPE imaging revealed that the P compartment coincides with a major body wall fold that occurs during crawling. These results support a model in which dendrite targeting by compartment cues reliably tunes neurons for predictable stimuli on the body wall: proprioceptive dendrites target areas that bend predictably during crawling, while touch-sensing dendrites could be avoiding those areas to be tuned for external mechanosensory stimuli. To investigate the molecular identity of the substrate cues guiding the compartmental organization of dendrites, I tested candidate cues and sought new potential cues. I first tested cues that are known to be expressed in a compartmental fashion (Hedgehog and EGFR pathways). Interestingly, the overall dendrite territory footprint of class I proprioceptive cells is unaffected by known compartment cues. To reveal new candidates, I performed cell sorting and RNA sequencing. I identified 290 cell surface and secreted molecules with differential expression in the A and P compartments. I provide initial findings from a knockdown and misexpression screen testing the role of these candidates for class I and class III territory patterning. Taken together, these results provide new insights into how dendritic fields are patterned to support proper neural function.

京都大学 / 0048 / 新制・課程博士 / 博士(生命科学) / 甲第21401号 / 生博第402号 / 新制||生||53(附属図書館) / 京都大学大学院生命科学研究科統合生命科学専攻 / (主査)教授 見学 美根子, 教授 上村 匡, 教授 渡邊 直樹 / 学位規則第4条第1項該当 / Doctor of Philosophy in Life Sciences / Kyoto University / DFAM

The objective of the completed research was to characterize the morphology of individual neurons within monolayer networks of fetal mouse spinal tissue via intraperikaryal injections of horseradish peroxidase (HRP). Thirty labelled neurons were reconstructed via camera lucida drawings and morphometrically analyzed.

This document only includes an excerpt of the corresponding thesis or dissertation. To request a digital scan of the full text, please contact the Ruth Lilly Medical Library's Interlibrary Loan Department (rlmlill@iu.edu).

Les neurones biologiques communiquent par le biais d’impulsions électriques, appelées spikes, et les fonctions cérébrales émergent notamment de la coordination entre les réceptions et émissions de ces spikes. Par ailleurs, il est largement admis que la fonction de chaque neurone dépend de sa morphologie. Les dendrites conditionnent l’intégration spatio-temporelle des spikes reçus et influent sur les temps d’occurrence des spikes émis. Elles sont donc fondamentales pour l’étude in silico des mécanismes de coordination, et en particulier pour l’étude des assemblées de neurones. Les modèles de neurones existants prenant en compte les dendrites, sont généralement des modèles mathématiques détaillés, souvent à base d’équations différentielles, dont la simulation nécessite des ressources de calculs importantes. De plus, leur complexité intrinsèque rend difficile l’analyse et les preuves sur ces modèles. Dans cette thèse, nous proposons un modèle de neurone intégrant des dendrites d’une manière abstraite. Dans l’objectif d’ouvrir la porte aux méthodes formelles, nous établissons une définition rigoureuse du cadre de modélisation et mettons en évidence des propriétés algébriques remarquables de l’intégration dendritique. Nous avons notamment démontré qu’il est possible de réduire la structure d’un neurone en préservant sa fonction d’entrée/sortie. Nous avons ainsi révélé des classes d’équivalence dont nous savons déterminer un représentant canonique. En s’appuyant sur la théorie des catégories et par des morphismes de neurones judicieusement définis, nous avons ensuite analysé plus finement ces classes d’équivalence. Un résultat surprenant découle de ces propriétés : un simple ajout de délais dans les modèles informatiques de neurones permet de prendre en compte une intégration dendritique abstraite, sans représenter explicitement la structure arborescente des dendrites. À la racine de l’arborescence dendritique, la modélisation du soma contient inévitablement une équation différentielle lorsque l’on souhaite préserver l’essence du fonctionnement biologique. Ceci impose de combiner une vision analytique avec la vision algébrique. Néanmoins, grâce à une étape préalable de discrétisation temporelle, nous avons également implémenté un neurone complet en Lustre qui est un langage formel autorisant des preuves par model checking. Globalement, nous apportons dans cette thèse un premier pas encourageant vers une formalisation complète des neurones, avec des propriétés remarquables sur l’intégration dendritique. / Biological neurons communicate by means of electrical impulses, called spikes. Brain functions emerge notably from reception and emission coordination between those spikes. Furthermore, it is widely accepted that the function of each neuron depends on its morphology. In particular, dendrites perform the spatio-temporal integration of received spikes and affect the occurrence of emitted spikes. Dendrites are therefore fundamental for in silico studies of coordination mechanisms, and especially for the study of so-called neuron assemblies. Most of existing neuron models taking into account dendrites are detailed mathematical models, usually based on differential equations, whose simulations require significant computing resources. Moreover, their intrinsic complexity makes difficult the analysis and proofs on such models. In this thesis, we propose an abstract neuron model integrating dendrites. In order to pave the way to formal methods, we establish a rigorous definition of the modeling framework and highlight remarkable algebraic properties of dendritic integration. In particular, we have demonstrated that it is possible to reduce a neuron structure while preserving its input/output function. We have thus revealed equivalence classes with a canonical representative. Based on category theory and thanks to properly defined neuron morphisms, we then analyzed these equivalence classes in more details. A surprising result derives from these properties: simply adding delays in neuron computational models is sufficient to represent an abstract dendritic integration, without explicit tree structure representation of dendrites. At the root of the dendritic tree, soma modeling inevitably contains a differential equation in order to preserve the biological functioning essence. This requires combining an analytical vision with the algebraic vision. Nevertheless, thanks to a preliminary step of temporal discretization, we have also implemented a complete neuron in Lustre which is a formal language allowing proofs by model checking. All in all, we bring in this thesis an encouraging first step towards a complete neuron formalization, with remarkable properties on dendritic integration.

Activity-dependent and synapse-specific translation of mRNAs is required for long-term changes in synaptic strength (or efficacy). However, many of the components mediating repression, transport and activation of mRNAs are unknown. Translational control in neurons is a highly conserved process and mediated by a ribonuclear particle (RNP). This study shows that RNPs in Drosophila neurons are similar not only to mammalian neuronal RNA granules but also to yeast P-bodies, cytoplasmic foci involved in translational repression and RNA decay. The evolutionarily conserved proteins Me31b and Trailer Hitch localize to RNA granules. Me31b and Trailer Hitch are required for normal dendritic growth. Mutations in Me31b and Trailer Hitch suppress phenotypes resulting from overexpression of Fragile X Mental Retardation protein, suggesting that both proteins may act as translational repressors. In addition, this study reports the identification of novel translational repressors in neurons. Using the overexpression phenotype of Fragile X Mental Retardation protein in a candidate-based genetic screen, I identified dominant suppressor mutations in five genes, including Doubletime/Discs Overgrown, Orb2/CPEB, PolyA Binding Protein, Rm62/Dmp68 and SmD3. Like Me31b and Trailer Hitch, all five proteins localize to neuronal RNPs. Overexpression of each proteins affects dendritic branching of sensory neurons in Drosophila. Identification and further characterization of these novel RNP granule components and dFMR1-interacting proteins may provide further insights into the mechanisms controlling translational in dendrites.