The notion of histogram of forces : a new way to represent the relative position of 2D-objects

The assessment of the directional spatial relations (such as "to the right of", "to the south of" . . .) between 2D-objects relies generally on the computation of a histogram of angles, which is supposed to provide a reasonably good representation o f the relative position of an object with regard to another . In this paper, we introduce the notion of histogram of forces . It generalize s and supersedes the one of histogram of angles . The objects are handled as longitudinal sections (1D-entities) . It is thus possibl e to benefit in full by the power of integral calculus and to ensure a rapid processing of raster data as well as of vector data unde r explicit consideration of both angular and metric information .L'évaluation des relations spatiales directionnelles (telles que « à droite de », « au sud de » ...) entre objets 2D repose généralement sur la constitution d'un histogramme d'angles. Un tel histogramme est supposé constituer une bonne représentation de la position relative d'un objet par rapport à un autre. Dans cet article, nous introduisons la notion d'histogramme de forces. Elle généralise et supplante celle d'histogramme d'angles. La manipulation des objets (entités de dimension 2) est ramenée à celle de leurs sections longitudinales (entités de dimension 1), non pas à celle de points. Il est ainsi possible de bénéficier de la puissance du calcul intégral et d'assurer un traitement incomparablement plus rapide aussi bien de données rasters que vecteurs, tout en tenant compte explicitement aussi bien de l'information angulaire que de l'information métrique

Computational model combined with in vitro experiments to analyse mechanotransduction during mesenchymal stem cell adhesion.

The shape that stem cells reach at the end of adhesion process influences their differentiation. Rearrangement of cytoskeleton and modification of intracellular tension may activate mechanotransduction pathways controlling cell commitment. In the present study, the mechanical signals involved in cell adhesion were computed in in vitro stem cells of different shapes using a single cell model, the so-called Cytoskeleton Divided Medium (CDM) model. In the CDM model, the filamentous cytoskeleton and nucleoskeleton networks were represented as a mechanical system of multiple tensile and compressive interactions between the nodes of a divided medium. The results showed that intracellular tonus, focal adhesion forces as well as nuclear deformation increased with cell spreading. The cell model was also implemented to simulate the adhesion process of a cell that spreads on protein-coated substrate by emitting filopodia and creating new distant focal adhesion points. As a result, the cell model predicted cytoskeleton reorganisation and reinforcement during cell spreading. The present model quantitatively computed the evolution of certain elements of mechanotransduction and may be a powerful tool for understanding cell mechanobiology and designing biomaterials with specific surface properties to control cell adhesion and differentiation

Brain network modules of meaningful and meaningless objects

Network modularity is a key feature for efficient information processing in the human brain. This information processing is however dynamic and networks can reconfigure at very short time period, few hundreds of millisecond. This requires neuroimaging techniques with sufficient time resolution. Here we use the dense electroencephalography, EEG, source connectivity methods to identify cortical networks with excellent time resolution, in the order of millisecond. We identify functional networks during picture naming task. Two categories of visual stimuli were presented, meaningful (tools, animals) and meaningless (scrambled) objects. In this paper, we report the reconfiguration of brain network modularity for meaningful and meaningless objects. Results showed mainly that networks of meaningful objects were more modular than those of meaningless objects. Networks of the ventral visual pathway were activated in both cases. However a strong occipitotemporal functional connectivity appeared for meaningful object but not for meaningless object. We believe that this approach will give new insights into the dynamic behavior of the brain networks during fast information processing.Comment: The 3rd Middle East Conference on Biomedical Engineering (MECBME'16

Mesure de l'excitation et de l'inhibition dans le tissu neuronal en épilepsie par identification d'un modèle dynamique non linéaire d'activité EEG

Le problème posé est d'identifier un modèle réaliste physiologiquement pour interpréter les signaux EEG rencontrés en épilepsie. Ce modèle présente des non-linéarités, et son identification peut être envisagée suivant différentes approches. Celle qui est présentée passe par la minimisation d'une distance dans un espace de descripteurs, au moyen d'un algorithme évolutionnaire. Des résultats en simulation et sur signaux réels montrent que les valeurs identifiées permettent effectivement de dégager et d'interpréter certaines évolutions caractéristiques en début des crises