Branching angles of pyramidal cell dendrites follow common geometrical design principles in different cortical areas

Unraveling pyramidal cell structure is crucial to understanding cortical circuit computations. Although it is well known that pyramidal cell branching structure differs in the various cortical areas, the principles that determine the geometric shapes of these cells are not fully understood. Here we analyzed and modeled with a von Mises distribution the branching angles in 3D reconstructed basal dendritic arbors of hundreds of intracellularly injected cortical pyramidal cells in seven different cortical regions of the frontal, parietal, and occipital cortex of the mouse. We found that, despite the differences in the structure of the pyramidal cells in these distinct functional and cytoarchitectonic cortical areas, there are common design principles that govern the geometry of dendritic branching angles of pyramidal cells in all cortical areas.

Dyrk1A Influences Neuronal Morphogenesis Through Regulation of Cytoskeletal Dynamics in Mammalian Cortical Neurons

Down syndrome (DS) is the most frequent genetic cause of mental retardation. Cognitive dysfunction in these patients is correlated with reduced dendritic branching and complexity, along with fewer spines of abnormal shape that characterize the cortical neuronal profile of DS. DS phenotypes are caused by the disruptive effect of specific trisomic genes. Here, we report that overexpression of dual-specificity tyrosine phosphorylation-regulated kinase 1A, DYRK1A, is sufficient to produce the dendritic alterations observed in DS patients. Engineered changes in Dyrk1A gene dosage in vivo strongly alter the postnatal dendritic arborization processes with a similar progression than in humans. In cultured mammalian cortical neurons, we determined a reduction of neurite outgrowth and synaptogenesis. The mechanism underlying neurite dysgenesia involves changes in the dynamic reorganization of the cytoskeleton.

The effects of cocaine self-administration on dendritic spine density in the rat hippocampus are dependent on genetic background

Chronic exposure to cocaine induces modifications to neurons in the brain regions involved in addiction. Hence, we evaluated cocaine-induced changes in the hippocampal CA1 field in Fischer 344 (F344) and Lewis (LEW) rats, 2 strains that have been widely used to study genetic predisposition to drug addiction, by combining intracellular Lucifer yellow injection with confocal microscopy reconstruction of labeled neurons. Specifically, we examined the effects of cocaine self-administration on the structure, size, and branching complexity of the apical dendrites of CA1 pyramidal neurons. In addition, we quantified spine density in the collaterals of the apical dendritic arbors of these neurons. We found differences between these strains in several morphological parameters. For example, CA1 apical dendrites were more branched and complex in LEW than in F344 rats, while the spine density in the collateral dendrites of the apical dendritic arbors was greater in F344 rats. Interestingly, cocaine self-administration in LEW rats augmented the spine density, an effect that was not observed in the F344 strain. These results reveal significant structural differences in CA1 pyramidal cells between these strains and indicate that cocaine self-administration has a distinct effect on neuron morphology in the hippocampus of rats with different genetic backgrounds.

Volume Haptics and Dendritic Spine Editing

Esta tesis se ha desarrollado en el contexto del proyecto Cajal Blue Brain, una iniciativa europea dedicada al estudio del cerebro. Uno de los objetivos de esta iniciativa es desarrollar nuevos métodos y nuevas tecnologías que simplifiquen el análisis de datos en el campo neurocientífico. El presente trabajo se ha centrado en diseñar herramientas que combinen información proveniente de distintos canales sensoriales con el fin de acelerar la interacción y análisis de imágenes neurocientíficas. En concreto se estudiará la posibilidad de combinar información visual con información háptica. Las espinas dendríticas son pequeñas protuberancias que recubren la superficie dendrítica de muchas neuronas del cerebro. A día de hoy, se cree que tienen un papel clave en la transmisión de señales neuronales. Motivo por el cual, el interés por parte de la comunidad científica por estas estructuras ha ido en aumento a medida que las técnicas de adquisición de imágenes mejoraban hasta alcanzar una calidad suficiente para analizar dichas estructuras. A menudo, los neurocientíficos utilizan técnicas de microscopía con luz para obtener los datos que les permitan analizar estructuras neuronales tales como neuronas, dendritas y espinas dendríticas. A pesar de que estas técnicas ofrezcan ciertas ventajas frente a su equivalente electrónico, las técnicas basadas en luz permiten una menor resolución. En particular, estructuras pequeñas como las espinas dendríticas pueden capturarse de forma incorrecta en las imágenes obtenidas, impidiendo su análisis. En este trabajo, se presenta una nueva técnica, que permite editar imágenes volumétricas, mediante un dispositivo háptico, con el fin de reconstruir de los cuellos de las espinas dendríticas. Con este objetivo, en un primer momento se desarrolló un algoritmo que proporciona retroalimentación háptica en datos volumétricos, completando la información que provine del canal visual. Dicho algoritmo de renderizado háptico permite a los usuarios tocar y percibir una isosuperficie en el volumen de datos. El algoritmo asegura un renderizado robusto y eficiente. Se utiliza un método basado en las técnicas de “marching tetrahedra” para la extracción local de una isosuperficie continua, lineal y definida por intervalos. La robustez deriva tanto de una etapa de detección de colisiones continua de la isosuperficie extraída, como del uso de técnicas eficientes de renderizado basadas en un proxy puntual. El método de “marching tetrahedra” propuesto garantiza que la topología de la isosuperficie extraída coincida con la topología de una isosuperficie equivalente determinada utilizando una interpolación trilineal. Además, con el objetivo de mejorar la coherencia entre la información háptica y la información visual, el algoritmo de renderizado háptico calcula un segundo proxy en la isosuperficie pintada en la pantalla. En este trabajo se demuestra experimentalmente las mejoras en, primero, la etapa de extracción de isosuperficie, segundo, la robustez a la hora de mantener el proxy en la isosuperficie deseada y finalmente la eficiencia del algoritmo. En segundo lugar, a partir del algoritmo de renderizado háptico propuesto, se desarrolló un procedimiento, en cuatro etapas, para la reconstrucción de espinas dendríticas. Este procedimiento, se puede integrar en los cauces de segmentación automática y semiautomática existentes como una etapa de pre-proceso previa. El procedimiento está diseñando para que tanto la navegación como el proceso de edición en sí mismo estén controlados utilizando un dispositivo háptico. Se han diseñado dos experimentos para evaluar esta técnica. El primero evalúa la aportación de la retroalimentación háptica y el segundo se centra en evaluar la idoneidad del uso de un háptico como dispositivo de entrada. En ambos casos, los resultados demuestran que nuestro procedimiento mejora la precisión de la reconstrucción. En este trabajo se describen también dos casos de uso de nuestro procedimiento en el ámbito de la neurociencia: el primero aplicado a neuronas situadas en la corteza cerebral humana y el segundo aplicado a espinas dendríticas situadas a lo largo de neuronas piramidales de la corteza del cerebro de una rata. Por último, presentamos el programa, Neuro Haptic Editor, desarrollado a lo largo de esta tesis junto con los diferentes algoritmos ya mencionados. ABSTRACT This thesis took place within the Cajal Blue Brain project, a European initiative dedicated to the study of the brain. One of the main goals of this project is the development of new methods and technologies simplifying data analysis in neuroscience. This thesis focused on the development of tools combining information originating from distinct sensory channels with the aim of accelerating both the interaction with neuroscience images and their analysis. In concrete terms, the objective is to study the possibility of combining visual information with haptic information. Dendritic spines are thin protrusions that cover the dendritic surface of numerous neurons in the brain and whose function seems to play a key role in neural circuits. The interest of the neuroscience community toward those structures kept increasing as and when acquisition methods improved, eventually to the point that the produced datasets enabled their analysis. Quite often, neuroscientists use light microscopy techniques to produce the dataset that will allow them to analyse neuronal structures such as neurons, dendrites and dendritic spines. While offering some advantages compared to their electronic counterpart, light microscopy techniques achieve lower resolutions. Particularly, small structures such as dendritic spines might suffer from a very low level of fluorescence in the final dataset, preventing further analysis. This thesis introduces a new technique enabling the edition of volumetric datasets in order to recreate dendritic spine necks using a haptic device. In order to fulfil this objective, we first presented an algorithm to provide haptic feedback directly from volumetric datasets, as an aid to regular visualization. The haptic rendering algorithm lets users perceive isosurfaces in volumetric datasets, and it relies on several design features that ensure a robust and efficient rendering. A marching tetrahedra approach enables the dynamic extraction of a piecewise linear continuous isosurface. Robustness is derived using a Continuous Collision Detection step coupled with acknowledged proxy-based rendering methods over the extracted isosurface. The introduced marching tetrahedra approach guarantees that the extracted isosurface will match the topology of an equivalent isosurface computed using trilinear interpolation. The proposed haptic rendering algorithm improves the coherence between haptic and visual cues computing a second proxy on the isosurface displayed on screen. Three experiments demonstrate the improvements on the isosurface extraction stage as well as the robustness and the efficiency of the complete algorithm. We then introduce our four-steps procedure for the complete reconstruction of dendritic spines. Based on our haptic rendering algorithm, this procedure is intended to work as an image processing stage before the automatic segmentation step giving the final representation of the dendritic spines. The procedure is designed to allow both the navigation and the volume image editing to be carried out using a haptic device. We evaluated our procedure through two experiments. The first experiment concerns the benefits of the force feedback and the second checks the suitability of the use of a haptic device as input. In both cases, the results shows that the procedure improves the editing accuracy. We also report two concrete cases where our procedure was employed in the neuroscience field, the first one concerning dendritic spines in the human cortex, the second one referring to an ongoing experiment studying dendritic spines along dendrites of mouse cortical pyramidal neurons. Finally, we present the software program, Neuro Haptic Editor, that was built along the development of the different algorithms implemented during this thesis, and used by neuroscientists to use our procedure.