Neurone miroir | EPFL Graph Search

vignette|Diagramme illustrant la problématique d'une personne amputée d'un bras, qui est remplacé par une image en miroir : le cerveau reçoit une image artificielle du membre fantôme et met en jeu les neurones miroirs. Les neurones miroirs sont une catégorie de neurones du cerveau qui présentent une activité aussi bien lorsqu'un individu exécute une action que lorsqu'il observe un autre individu (en particulier de son espèce) exécuter la même action, ou même lorsqu'il imagine une telle action, d'où le terme miroir. Ils sont connus pour être à l'origine du bâillement. Il existe également des neurones échos. En neurosciences cognitives, les neurones miroirs joueraient un rôle dans la cognition sociale, notamment dans l'apprentissage par imitation, mais aussi dans les processus affectifs, tels que l'empathie. Le professeur Ramachandran les appelle neurones empathiques. Les neurones miroirs sont considérés comme une découverte majeure en neurosciences. Si, pour certains chercheurs, ils c

Shedding of neurexin 3 beta ectodomain by ADAM10 releases a soluble fragment that affects the development of newborn neurons

Erika Myrna Borcel Novoa, Mitko Dimitrov, Patrick Fraering, Marine Krzisch, Magda Maria Palczynska, Giorgio Ulrich

Neurexins are transmembrane synaptic cell adhesion molecules involved in the development and maturation of neuronal synapses. In the present study, we report that Nrxn3 beta is processed by the metalloproteases ADAM10, ADAM17, and by the intramembrane-cleaving protease.-secretase, producing secreted neurexin3 beta (sNrxn3 beta) and a single intracellular domain (Nrxn3 beta-ICD). We further completed the full characterization of the sites at which Nrxn3 beta is processed by these proteases. Supporting the physiological relevance of the Nrxn3 beta processing, we demonstrate in vivo a significant effect of the secreted shedding product sNrxn3 beta on the morphological development of adult newborn neurons in the mouse hippocampus. We show that sNrxn3 beta produced by the cells of the dentate gyrus increases the spine density of newborn neurons whereas sNrxn3 beta produced by the newborn neuron itself affects the number of its mossy fiber terminal extensions. These results support a pivotal role of sNrxn3 beta in plasticity and network remodeling during neuronal development.

Nature Publishing Group2016

Data-driven whole mouse brain modeling for multi-scale simulations

Dimitri Bruno Marie Rodarie

In this thesis, we present a data-driven iterative pipeline to generate, simulate and validate point-neuron models of the whole mouse brain. The ultimate goal is to replicate close loop experiments with a virtual body in a virtual world. This pipeline was origi-nally created by a PhD student of the Blue Brain Project and this pioneer work has yielded the first versions of the model and their simulations. My objective is to refine, extend and consolidate the previous version of the workflow and in particular to extend the repertoire of neuron types by integrating and consolidating available literature data.The pipeline has four main parts. First, we define a pair of reference atlases to create a spatial reference for every dataset that we want to integrate. Second, we create a cell atlas with estimates of the number and density of the major cell types in each brain region. Then, we build a connectivity atlas that describes the connections of each neuron of the mouse brain and their properties. Finally, we assign point-neuron parameters to each of the neuron types, and synaptic parameters to each of the connection types of our model to obtain a point-neuron network of the mouse brain. This network can be simulated to perform mouse brain experi-ments in-silico.In this thesis, we evaluate the quality of the different reference atlases, released by the Allen Institute for Brain Science and pro-vide methods to mitigate the impact of artifacts in the original images. We further extend the cell atlas with density estimates of more inhibitory neuron types. To do so, we introduce a new method to combine estimates of inhibitory neuron counts from the literature into a consistent framework. We also estimate inhibitory neuron density in regions where no literature data are avai-lable, using collected literature estimates and gene expression data from in situ hybridization image stacks. Our approach can be further extended to other cell types and provides a resource to build more detailed circuits of the mouse brain. Next, we refine the connectivity atlas, including literature findings on short-range connectivity. Additionally, we construct a database to store data collected on neuron types point-neuron parameters and synaptic parameters. With the results of the previous steps, we generate a new version of the whole mouse brain point-neuron network. We tested this new model against its previous version using three benchmark experiments. We explore the possibility to embed and connect detailed circuit reconstructions of the mouse brain to our point neuron model and co-simulate them. Finally, we constrain a 3D skeleton model of the mouse with joint constraints from the literature and attach muscle to its bones to create a musculoskeletal model of the mouse body that can be simulated in close-loop with our model to reproduce motor control experiments.

EPFL2022

Data-driven whole mouse brain modeling for multi-scale simulations

Dimitri Bruno Marie Rodarie

EPFL2022