Marwan Muhammad Ahmed Abdellah

Marwan Abdellah, a self-motivated engineer born in Cairo, Egypt in 1987. He received his B.Sc. and M.Sc. degrees in Biomedical Engieering with distinction with honor from the Systems & Biomedical Engineering Department (SBME), Faculty of Engineering at Cairo University in 2009 and 2012 respectively. After graduation, he worked as a Research Engineer at IBE Technologies's R&D Department in a 4D ultrasound machines project. Then he moved to work as an Associate Software Engineer at the Biomedical Department in Symbyo Technologies. Afterwards, he joined the Multimedia Laboratory in the Swiss Federal Institute of Technology, Lausanne (EPFL) to conduct a research on H.264 & Reconfigurable Video Coding. Currently, he is working as a Scentific Visualization Engineer in the Blue Brain Project led by Prof. Henery Markram in the Brain Mind Institute at the Swiss Federal Institute of Technology, Lausanne (EPFL). Along with his professional career, Abdellah worked as an instructor at NILES (National Institute of Laser Enhanced Science) in Cairo University. He taught two courses in the areas of Computer Graphics and High Performance Computing. He focused in his M.Sc. thesis research on implementing high performance volume rendering techniques for large scale medical data on heterogeneous platforms. He succeeded in constructing a high performance Fourier Volume Render running entirely on CUDA-enable GPUs. Among his research intersets are High Perfromance Computing, Heterogenous Comuting, Visualization, Scalable Rendering, Computer Graphics & Modelling, Medical Image Processing, Video Processing & Reconfigurable Video Coding, Abdellah has been awarded a graphics card from NVIDIA during attending a workshop in High Performance Computing at the Intenational Center of Theoritical Physics (ICTP) in Trieste, Italy. His graduation project was honored by ITIDA and Egyptian Ministres of Telecommunications & Higher Education during a celebration organized by ITIDA in March 2010.

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Neurone

thumb|537x537px|Schéma complet d’un neurone. Un neurone, ou une cellule nerveuse, est une cellule excitable constituant l'unité fonctionnelle de la base du système nerveux. Les neurones assurent la

Primary somatosensory cortex

In neuroanatomy, the primary somatosensory cortex is located in the postcentral gyrus of the brain's parietal lobe, and is part of the somatosensory system. It was initially defined from surface sti

Somesthésie

La somesthésie (dite aussi sensibilité du corps) constitue un des systèmes sensoriels de l'organisme. La somesthésie désigne un ensemble de différentes sensations (pression, chaleur, douleur…) qui pr

Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep

Marwan Muhammad Ahmed Abdellah, Oren Amsalem, Marine Laure Bertschy, Grigori Chevtchenko, Benoît Jean-Albert Coste, Jean-Denis Georges Emile Courcol, András Ecker, Cyrille Pierre Henri Favreau, Adrien Christian Fleury, Michael Emiel Gevaert, Jayakrishnan Harikrishnavilas Raveendran Nair, Joni Henrikki Herttuainen, Sean Lewis Hill, Elisabetta Iavarone, Genrich Ivaska, Anna-Kristin Kaufmann, Samuel Claude Kerrien, James Gonzalo King, Pramod Shivaji Kumbhar, Polina Litvak, Patrycja Lurie, Ioannis Magkanaris, Henry Markram, Vignayanandam Ravindernath Muddapu, Rodrigo de Campos Perin, Fabien Petitjean, Michael Reimann, Nadir Roman Guerrero, Ying Shi, Liviu Soltuzu, Mohameth François Sy, Mustafa Anil Tuncel, Alexander Désiré Ulbrich, Werner Alfons Hilda Van Geit, Matthias Wolf

2023

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Meshing of Spiny Neuronal Morphologies using Union Operators

Marwan Muhammad Ahmed Abdellah, Alessandro Enrico Foni, Juan José García Cantero, Nadir Roman Guerrero, Felix Schürmann

Neurons are characterized by thin and long interleaving arborizations in which creating accurate mesh models of their cellular membranes is challenging. While union operators are central for CAD/CAM modeling and computer graphics applications, their applicability to neuronal mesh generation has not been explored. In this work, we present the results of exploring the effectiveness of using union operators to generate high fidelity surface meshes of spiny neurons from their morphological traces. To improve the visual realism of the resulting models, a plausible shape of the cell body is also realized with implicit surfaces (metaballs). The algorithm is implemented in Blender based on its Python API and is integrated into NeuroMorphoVis, a neuroscience-specific framework for visualization and analysis of neuronal morphologies. Our method is applied to a dataset consisting of more than 600 neurons representing 60 morphological types reconstructed from the neocortex of a juvenile rat. The performance of our implementation is quantitatively analyzed, and the results are qualitatively compared to previous implementation. The resulting meshes are applicable in multiple contexts including visualization and analysis of full compartmental simulations and generation of high quality multimedia content for scientific visualization and visual computing (Figure 1). Computer Graphics Marwan Abdellah, Juan José García Cantero, Alessandro Foni, Nadir Román Guerrero, Elvis Boci, and Felix Schürmann

The Eurographics Association2022

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Voltage-sensitive dye imaging (VSDI) is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but with effective resolution limits that confound interpretation. To address this limitation, we developed an in silico model of VSDI in a biologically faithful digital reconstruction of rodent neocortical microcircuitry. Using this model, we extend previous experimental observations regarding the cellular origins of VSDI, finding that the signal is driven primarily by neurons in layers 2/3 and 5, and that VSDI measurements do not capture individual spikes. Furthermore, we test the capacity of VSD image sequences to discriminate between afferent thalamic inputs at various spatial locations to estimate a lower bound on the functional resolution of VSDI. Our approach underscores the power of a bottom-up computational approach for relating scales of cortical processing. Voltage-sensitive dye imaging (VSDI) is a powerful technique for measuring membrane potential dynamics of neurons but the effective resolution is limited. Here, the authors developed an in silico model of VSDI to probe activity in a biologically detailed reconstruction of rodent neocortical microcircuits.

NATURE RESEARCH2021

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