Êtes-vous un étudiant de l'EPFL à la recherche d'un projet de semestre?
Travaillez avec nous sur des projets en science des données et en visualisation, et déployez votre projet sous forme d'application sur Graph Search.
To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possible, and to turn the model into a useful framework for making predictions based on the principles governing the nature of neural cells. In such a context, the access to existing neural models and data outstandingly facilitates the work of computational neuroscientists and fosters its novelty, as the scientific community grows wider and neural models progressively increase in type, size, and number. Nonetheless, even when accessibility is guaranteed, data and models are rarely reused since it is difficult to retrieve, extract and/or understand relevant information and scientists are often required to download and modify individual files, perform neural data analysis, optimize model parameters, and run simulations, on their own and with their own resources. While focusing on the construction of biophysically and morphologically accurate models of hippocampal cells, we have created an online resource, the Build section of the Hippocampus Hub -a scientific portal for research on the hippocampus- that gathers data and models from different online open repositories and allows their collection as the first step of a single cell model building workflow. Interoperability of tools and data is the key feature of the work we are presenting. Through a simple click-and-collect procedure, like filling the shopping cart of an online store, researchers can intuitively select the files of interest (i.e., electrophysiological recordings, neural morphology, and model components), and get started with the construction of a data-driven hippocampal neuron model. Such a workflow importantly includes a model optimization process, which leverages high performance computing resources transparently granted to the users, and a framework for running simulations of the optimized model, both available through the EBRAINS Hodgkin-Huxley Neuron Builder online tool.
Mahmut Selman Sakar, Lorenzo Francesco John Noseda
Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi
Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Srikanth Ramaswamy, Michael Reimann, Werner Alfons Hilda Van Geit, James Gonzalo King, Marwan Muhammad Ahmed Abdellah, Lida Kanari, Pramod Shivaji Kumbhar, Alexis Arnaudon, Ying Shi, Jean-Denis Georges Emile Courcol, Armando Romani, András Ecker, Michael Emiel Gevaert, Michele Migliore, Cyrille Pierre Henri Favreau, Vishal Sood, Cristina Colangelo, Mohameth François Sy, Judit Planas Carbonell, Szabolcs Kali, Genrich Ivaska, Carmen Alina Lupascu, Elvis Boci, Alberto Antonietti, Fabien Petitjean, Julian Martin Budd, Elisabetta Giacalone, Davide Bella, Mustafa Kerem Kurban, Pranav Rai, Juan Bautista Hernando Vieites, Huanxiang Lu, Liesbeth Maria L Vanherpe, Joni Henrikki Herttuainen, Rosanna Migliore, Anna-Kristin Kaufmann, Juan Luis Riquelme Roman, Sàra Sàray, Audrey Mercer, Thomas Brice Delemontex, Nadir Roman Guerrero