5 resultados para Topological analysis
em Université de Lausanne, Switzerland
Resumo:
The action of various DNA topoisomerases frequently results in characteristic changes in DNA topology. Important information for understanding mechanistic details of action of these topoisomerases can be provided by investigating the knot types resulting from topoisomerase action on circular DNA forming a particular knot type. Depending on the topological bias of a given topoisomerase reaction, one observes different subsets of knotted products. To establish the character of topological bias, one needs to be aware of all possible topological outcomes of intersegmental passages occurring within a given knot type. However, it is not trivial to systematically enumerate topological outcomes of strand passage from a given knot type. We present here a 3D visualization software (TopoICE-X in KnotPlot) that incorporates topological analysis methods in order to visualize, for example, knots that can be obtained from a given knot by one intersegmental passage. The software has several other options for the topological analysis of mechanisms of action of various topoisomerases.
Resumo:
Patients with Temporal Lobe Epilepsy (TLE) suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor MR Imaging, volumetric and functional MRI studies. Diffusion Spectrum Imaging (DSI) is a diffusion imaging technique with high angular resolution for improving the mapping of white matter pathways. In this study, we used DSI, connectivity matrices and topological measures to investigate how the alteration in structural connectivity influences whole brain structural networks. Eleven patients with right-sided TLE and hippocampal sclerosis and 18 controls underwent our DSI protocol at 3T. The cortical and subcortical grey matters were parcellated into 86 regions of interest and the connectivity between every region pair was estimated using global tractography and a connectivity matrix (the adjacency matrix of the structural network). We then compared the networks of patients and controls using topological measures. In patients, we found a higher characteristic path length and a lower clustering coefficient compared to controls. Local measures at node level of the clustering and efficiency showed a significant difference after a multiple comparison correction (Bonferroni). These significant nodes were located within as well outside the temporal lobe, and the localisation of most of them was consistent with regions known to be part of epileptic networks in TLE. Our results show altered connectivity patterns that are concordant with the mapping of functional epileptic networks in patients with TLE. Further studies are needed to establish the relevance of these findings for the propagation of epileptic activity, cognitive deficits in medial TLE and outcome of epilepsy surgery in individual patients.
Resumo:
In this study we investigated the effect of medial temporal lobe epilepsy (MTLE) on the global characteristics of brain connectivity estimated by topological measures. We used DSI (Diffusion Spectrum Imaging) to construct a connectivity matrix where the nodes represents the anatomical ROIs and the edges are the connections between any pair of ROIs weighted by the mean GFA/FA values. A significant difference was found between the patient group vs control group in characteristic path length, clustering coefficient and small-worldness. This suggests that the MTLE network is less efficient compared to the network of the control group.
Resumo:
Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.
Resumo:
ABSTRACT Adult neuronal plasticity is a term that corresponds to a set of biological mechanisms allowing a neuronal circuit to respond and adapt to modifications of the received inputs. Mystacial whiskers of the mouse are the starting point of a major sensory pathway that provides the animal with information from its immediate environment. Through whisking, information is gathered that allows the animal to orientate itself and to recognize objects. This sensory system is crucial for nocturnal behaviour during which vision is not of much use. Sensory information of the whiskers are sent via brainstem and thalamus to the primary somatosensory area (S1) of the cerebral cortex in a strictly topological manner. Cell bodies in the layer N of S 1 are arranged in ring forming structures called barrels. As such, each barrel corresponds to the cortical representation in layer IV of a single whisker follicle. This histological feature allows to identify with uttermost precision the part of the cortex devoted to a given whisker and to study modifications induced by different experimental conditions. The condition used in the studies of my thesis is the passive stimulation of one whisker in the adult mouse for a period of 24 hours. It is performed by glueing a piece of metal on one whisker and placing the awake animal in a cage surrounded by an electromagnetic coil that generates magnetic field burst inducing whisker movement at a given frequency during 24 hours. I analysed the ultrastructure of the barrel corresponding the stimulated whisker using serial sections electron microscopy and computer-based three-dimensional reconstructions; analysis of neighbouring, unstimulated barrels as well as those from unstimulated mice served as control. The following elements were structurally analyzed: the spiny dendrites, the axons of excitatory as well as inhibitory cells, their connections via synapses and the astrocytic processes. The density of synapses and spines is upregulated in a barrel corresponding to a stimulated whisker. This upregulation is absent in the BDNF heterozygote mice, indicating that a certain level of activity-dependent released BDNF is required for synaptogenesis in the adult cerebral cortex. Synpaptogenesis is correlated with a modification of the astrocytes that place themselves in closer vicinity of the excitatory synapses on spines. Biochemical analysis revealed that the astrocytes upregulate the expression of transporters by which they internalise glutamate, the neurotransmitter responsible for the excitatory response of cortical neurons. In the final part of my thesis, I show that synaptogenesis in the stimulated barrel is due to the increase in the size of excitatory axonal boutons that become more frequently multisynaptic, whereas the inhibitory axons do not change their morphology but form more synapses with spines apposed to them. Taken together, my thesis demonstrates that all the cellular elements present in the neuronal tissue of the adult brain contribute to activity-dependent cortical plasticity and form part of a mechanism by which the animal responds to a modified sensory experience. Throughout life, the neuronal circuit keeps the faculty to adapt its function. These adaptations are partially transitory but some aspects remain and could be the structural basis of a memory trace in the cortical circuit. RESUME La plasticité neuronale chez l'adulte désigne un ensemble de mécanismes biologiques qui permettent aux circuits neuronaux de répondre et de s'adapter aux modifications des stimulations reçues. Les vibrisses des souris sont un système crucial fournissant des informations sensorielles au sujet de l'environnement de l'animal. L'information sensorielle collectée par les vibrisses est envoyée via le tronc cérébral et le thalamus à l'aire sensorielle primaire (S 1) du cortex cérébral en respectant strictement la somatotopie. Les corps cellulaires dans la couche IV de S 1 sont organisés en anneaux délimitant des structures nommées tonneaux. Chaque tonneau reçoit l'information d'une seule vibrisse et l'arrangement des tonneaux dans le cortex correspond à l'arrangement des vibrisses sur le museau de la souris. Cette particularité histologique permet de sélectionner avec certitude la partie du cortex dévolue à une vibrisse et de l'étudier dans diverses conditions. Le paradigme expérimental utilisé dans cette thèse est la stimulation passive d'une seule vibrisse durant 24 heures. Pour ce faire, un petit morceau de métal est collé sur une vibrisse et la souris est placée dans une cage entourée d'une bobine électromagnétique générant un champ qui fait vibrer le morceau de métal durant 24 heures. Nous analysons l'ultrastructure du cortex cérébral à l'aide de la microscopie électronique et des coupes sériées permettant la reconstruction tridimensionnelle à l'aide de logiciels informatiques. Nous observons les modifications des structures présentes : les dendrites épineuses, les axones des cellules excitatrices et inhibitrices, leurs connections par des synapses et les astrocytes. Le nombre de synapses et d'épines est augmenté dans un tonneau correspondant à une vibrisse stimulée 24 heures. Basé sur cela, nous montrons dans ces travaux que cette réponse n'est pas observée dans des souris hétérozygotes BDNF+/-. Cette neurotrophine sécrétée en fonction de l'activité neuronale est donc nécessaire pour la synaptogenèse. La synaptogenèse est accompagnée d'une modification des astrocytes qui se rapprochent des synapses excitatrices au niveau des épines dendritiques. Ils expriment également plus de transporteurs chargés d'internaliser le glutamate, le neurotransmetteur responsable de la réponse excitatrice des neurones. Nous montrons aussi que les axones excitateurs deviennent plus larges et forment plus de boutons multi-synaptiques à la suite de la stimulation tandis que les axones inhibiteurs ne changent pas de morphologie mais forment plus de synapses avec des épines apposées à leur membrane. Tous les éléments analysés dans le cerveau adulte ont maintenu la capacité de réagir aux modifications de l'activité neuronale et répondent aux modifications de l'activité permettant une constante adaptation à de nouveaux environnements durant la vie. Les circuits neuronaux gardent la capacité de créer de nouvelles synapses. Ces adaptations peuvent être des réponses transitoires aux stimuli mais peuvent aussi laisser une trace mnésique dans les circuits.