Talk 1 Speaker Konstantinos Mavreas (FACTAS) Title The secrets of the Moon rocks, a basic idea of remanent magnetization and how to approximate it with rational analysis Abstract Ferromagnetic materials (like iron) have ”memory”! This is in the form of natural remanent magnetization. Paleomagnetic studies, take advantage of that ”memory”…
Talk 1 Speaker Walid Djema (BIOCORE) Title Understanding some biological phenomena from control and mathematical biology standpoints: analysis aspects of cell population dynamics and optimisation of stains selection in photobioreactors. Abstract In the first part of this talk, we introduce some interesting biological mechanisms, like hematopoiesis, which is the process…
Probing retinal function with a multi-layered simulator
Our brain can recreate images from interpreting a stream of information emitted by one million parallel channels in the retina. This ability is partly due to the astonishing functional and anatomical diversity of the retinal ganglion cells (RGCs), each interpreting a different feature of the visual scene. In addition, RGCs “speak” to each other during complex tasks (especially motion handling), via amacrine cells (ACs - lateral connectivity). To decipher their role, we study an experimental setting that allows us to switch on or off RGCs and/or ACs using the drug CNO. This may not only impact the RGCs individual response but also their concerted activity to different stimuli, thus allowing us to understand how they contribute to the encoding of complex visual scenes. However, it is difficult to distinguish on pure experimental grounds the effect of CNO when both cell types are excited or inhibited, as these cells “antagonise” each other. Contrarily, numerical simulation can afford it. Here, we propose a novel simulation platform that can reflect normal and impaired retinal function (from single-cell to large-scale level). It is able to handle different visual processing circuits and allows us to visualise responses to visual scenes (movies). In addition, the platform allows simulation of retinal responses where we can silence or excite cell subclasses with CNO.
Selma Souihel (BIOVISION)
Title Anticipation in the retina and the primary visual cortex : towards an integrated retino-cortical model for motion processing
The retina is able to perform complex tasks and general feature extraction, allowing the visual cortex to process visual stimuli with more efficiency. With regards to motion processing, an interesting and useful task performed by the retina is anticipation and trajectory extrapolation. The first contribution of our work lies in the development of a generalized 2D model of the retina with three layers of ganglion cells : Fast OFF cells with gain control accounting for anticipation, direction selective cells connected via gap junctions, and Y-cells connected through amacrine cells, accounting for motion extrapolation. The second contribution is the use of the output of our retina model as an input to a mean field model of the primary visual cortex to reproduce motion anticipation as observed in VSDI recordings of V1 . We present results of the integrated retino-cortical model for motion processing, and study how anticipation and extrapolation depend on stimuli parameters such as speed, shape and trajectory. Through the integrated retina-cortical model we emphasize the mechanisms defining motion anticipation, due to the cooperation of gain control and lateral connectivity at the level of the retina and lateral connectivity in the cortex.
Location: Euler Violet room of Inria Sophia Antipolis - Méditerranée
Anne-Laure Simonelli (EUR DS4H)
Graduate School & Research : Digital Systems 4 Humans
Digital Systems for Humans (DS4H) is the first graduate school of research at Université Côte d'Azur and the only one in France with digital sciences as focus.
It is a multidisciplinary research and educational program centered on how the digital revolution does impact various disciplines such as computer sciences, electronics, economy and law. Within DS4H, Master and PhD students conceive and build tomorrow’s digital systems ; they explore the links between humans and the digital world.
DS4H gathers 12 partner laboratories and benefits from a close connection with the local innovation and business sphere. Its fully modular training program (including minors, in-lab immersion, and interdisciplinary group projects) provides graduates with highly-sought skills both in the industrial and research worlds.
Ashish Bhole (CASTOR)
Title Fluctuation splitting Riemann solver for a non-conservative modeling of shear shallow water flow
In this work, we propose a fluctuation splitting finite volume scheme for a non-conservative modeling of shear shallow water flow (SSWF). This model was originally proposed by Teshukov (2007) and was extended to include modeling of friction by Gavrilyuk et al. (2018). The directional splitting scheme proposed by Gavrilyuk et al. (2018) is tricky to apply on unstructured grids. Our scheme is based on the physical splitting in which we separate the characteristic waves of the model to form two different hyperbolic sub-systems. The fluctuations associated with each sub-systems are computed by developing Riemann solvers for these sub-systems in a local coordinate system. These fluctuations enables us to develop a Godunov-type scheme that can be easily applied on mixed/unstructured grids. While the equation of energy conservation is solved along with the SSWF model in Gavrilyuk et al. (2018), in this work we solve only SSWF model equations.
We develop a cell-centered finite volume code to validate the proposed scheme with the help of some numerical tests. As expected, the scheme shows first order convergence. The numerical simulation of 1D roll waves shows a good agreement with the experimental results. The numerical simulations of 2D roll waves show similar transverse wave structures as observed by Gavrilyuk et al. (2018).